Projek.ipynb

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      "name": "Projek_JST.ipynb",
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      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/abuwildanm/Leaf-Classification/blob/master/Projek.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "metadata": {
        "id": "InPGdX60NOex",
        "colab_type": "text"
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      "cell_type": "markdown",
      "source": [
        "# Projek JST\n",
        "# Leaf Classification with Learning Vector Quantization\n",
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "CkklT9Wf4fDo",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Nama Anggota Kelompok\n",
        "1. Abu Wildan Mucholladin\n",
        "2. Avisena Abdillah Alwi\n",
        "3. Ghaly Rizqi Mauludin\n",
        "4. Febriana Ranta Lidya"
      ]
    },
    {
      "metadata": {
        "id": "EEJcaJcqNYwD",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Prepare the Data"
      ]
    },
    {
      "metadata": {
        "id": "JRCzGzlENyQ_",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Import Library Standard\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Import Library Sklearn\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import PowerTransformer\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "t1Z-JTbOONPH",
        "colab_type": "code",
        "outputId": "cbd45179-8789-4127-8448-0bc2f7db72c8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 244
        }
      },
      "cell_type": "code",
      "source": [
        "# Read Dataset\n",
        "dataset = pd.read_csv('swedish-leaf.csv')\n",
        "dataset.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>roundness</th>\n",
              "      <th>perimeter_ratio_to_diameter</th>\n",
              "      <th>compactness</th>\n",
              "      <th>eccentricity</th>\n",
              "      <th>aspect_ratio</th>\n",
              "      <th>rectangularity</th>\n",
              "      <th>narrow_factor</th>\n",
              "      <th>perimeter_ratio_major_minor</th>\n",
              "      <th>hu_1</th>\n",
              "      <th>hu_2</th>\n",
              "      <th>...</th>\n",
              "      <th>skewness_G</th>\n",
              "      <th>skewness_B</th>\n",
              "      <th>kurtosis_R</th>\n",
              "      <th>kurtosis_G</th>\n",
              "      <th>kurtosis_B</th>\n",
              "      <th>contrast</th>\n",
              "      <th>correlation</th>\n",
              "      <th>energy</th>\n",
              "      <th>homogeneity</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.36884</td>\n",
              "      <td>3.5331</td>\n",
              "      <td>5.8370</td>\n",
              "      <td>0.82170</td>\n",
              "      <td>1.7546</td>\n",
              "      <td>0.77832</td>\n",
              "      <td>1.1003</td>\n",
              "      <td>2.4763</td>\n",
              "      <td>0.18666</td>\n",
              "      <td>0.009050</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.519140</td>\n",
              "      <td>1.49320</td>\n",
              "      <td>4.2487</td>\n",
              "      <td>4.5371</td>\n",
              "      <td>4.4354</td>\n",
              "      <td>0.13121</td>\n",
              "      <td>0.98877</td>\n",
              "      <td>0.23375</td>\n",
              "      <td>0.93751</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.38151</td>\n",
              "      <td>3.4243</td>\n",
              "      <td>5.7392</td>\n",
              "      <td>0.82174</td>\n",
              "      <td>1.7548</td>\n",
              "      <td>0.77691</td>\n",
              "      <td>1.1152</td>\n",
              "      <td>2.4325</td>\n",
              "      <td>0.18701</td>\n",
              "      <td>0.009087</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.001791</td>\n",
              "      <td>0.53622</td>\n",
              "      <td>3.6658</td>\n",
              "      <td>3.7257</td>\n",
              "      <td>2.3236</td>\n",
              "      <td>0.13221</td>\n",
              "      <td>0.98827</td>\n",
              "      <td>0.23445</td>\n",
              "      <td>0.93722</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.40996</td>\n",
              "      <td>3.4313</td>\n",
              "      <td>5.5365</td>\n",
              "      <td>0.79911</td>\n",
              "      <td>1.6634</td>\n",
              "      <td>0.77352</td>\n",
              "      <td>1.1003</td>\n",
              "      <td>2.3579</td>\n",
              "      <td>0.18297</td>\n",
              "      <td>0.007366</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.199190</td>\n",
              "      <td>0.84646</td>\n",
              "      <td>3.3483</td>\n",
              "      <td>3.4704</td>\n",
              "      <td>2.6509</td>\n",
              "      <td>0.13279</td>\n",
              "      <td>0.98817</td>\n",
              "      <td>0.22993</td>\n",
              "      <td>0.93672</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.39323</td>\n",
              "      <td>3.4399</td>\n",
              "      <td>5.6530</td>\n",
              "      <td>0.82015</td>\n",
              "      <td>1.7478</td>\n",
              "      <td>0.77444</td>\n",
              "      <td>1.0939</td>\n",
              "      <td>2.3935</td>\n",
              "      <td>0.18723</td>\n",
              "      <td>0.009002</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.227690</td>\n",
              "      <td>0.78302</td>\n",
              "      <td>3.6617</td>\n",
              "      <td>3.8209</td>\n",
              "      <td>2.5256</td>\n",
              "      <td>0.12910</td>\n",
              "      <td>0.98867</td>\n",
              "      <td>0.23076</td>\n",
              "      <td>0.93856</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.47409</td>\n",
              "      <td>3.3010</td>\n",
              "      <td>5.1485</td>\n",
              "      <td>0.77141</td>\n",
              "      <td>1.5715</td>\n",
              "      <td>0.78131</td>\n",
              "      <td>1.0997</td>\n",
              "      <td>2.2185</td>\n",
              "      <td>0.17661</td>\n",
              "      <td>0.005596</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.231780</td>\n",
              "      <td>0.69847</td>\n",
              "      <td>4.5870</td>\n",
              "      <td>4.9923</td>\n",
              "      <td>2.7346</td>\n",
              "      <td>0.12452</td>\n",
              "      <td>0.98688</td>\n",
              "      <td>0.26982</td>\n",
              "      <td>0.94075</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 32 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   roundness  perimeter_ratio_to_diameter  compactness  eccentricity  \\\n",
              "0    0.36884                       3.5331       5.8370       0.82170   \n",
              "1    0.38151                       3.4243       5.7392       0.82174   \n",
              "2    0.40996                       3.4313       5.5365       0.79911   \n",
              "3    0.39323                       3.4399       5.6530       0.82015   \n",
              "4    0.47409                       3.3010       5.1485       0.77141   \n",
              "\n",
              "   aspect_ratio  rectangularity  narrow_factor  perimeter_ratio_major_minor  \\\n",
              "0        1.7546         0.77832         1.1003                       2.4763   \n",
              "1        1.7548         0.77691         1.1152                       2.4325   \n",
              "2        1.6634         0.77352         1.1003                       2.3579   \n",
              "3        1.7478         0.77444         1.0939                       2.3935   \n",
              "4        1.5715         0.78131         1.0997                       2.2185   \n",
              "\n",
              "      hu_1      hu_2  ...  skewness_G  skewness_B  kurtosis_R  kurtosis_G  \\\n",
              "0  0.18666  0.009050  ...   -0.519140     1.49320      4.2487      4.5371   \n",
              "1  0.18701  0.009087  ...   -0.001791     0.53622      3.6658      3.7257   \n",
              "2  0.18297  0.007366  ...   -0.199190     0.84646      3.3483      3.4704   \n",
              "3  0.18723  0.009002  ...   -0.227690     0.78302      3.6617      3.8209   \n",
              "4  0.17661  0.005596  ...   -0.231780     0.69847      4.5870      4.9923   \n",
              "\n",
              "   kurtosis_B  contrast  correlation   energy  homogeneity  class  \n",
              "0      4.4354   0.13121      0.98877  0.23375      0.93751      1  \n",
              "1      2.3236   0.13221      0.98827  0.23445      0.93722      1  \n",
              "2      2.6509   0.13279      0.98817  0.22993      0.93672      1  \n",
              "3      2.5256   0.12910      0.98867  0.23076      0.93856      1  \n",
              "4      2.7346   0.12452      0.98688  0.26982      0.94075      1  \n",
              "\n",
              "[5 rows x 32 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 719
        }
      ]
    },
    {
      "metadata": {
        "id": "zWBpOl23OtMH",
        "colab_type": "code",
        "outputId": "97ee4106-5da0-4e9c-9154-a95d88572f87",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Ukuran Dataset\n",
        "print('Ukuran dataset:', dataset.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Ukuran dataset: (975, 32)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "l9_OnaplCPEP",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "data = dataset.iloc[:, :-1]\n",
        "label = dataset['class']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "SkjfvzEknBd4",
        "colab_type": "code",
        "outputId": "aa35182a-5253-47e7-aa10-27aff9d0ad07",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1171
        }
      },
      "cell_type": "code",
      "source": [
        "data.hist(figsize=(20,20));"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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mFluWylbkypB0PFmLJAYGBhgaGupW2C1Zu3Zt6WKqpVtxzpm+rqPrG9iq/jqr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\n",
            "text/plain": [
              "<Figure size 1440x1440 with 36 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "B6Ox1GWzDX4P",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Setelah dilihat histogram masing-masing fitur, terlihat bahwa terdapat beberapa fitur yang distribusinya masih belum mendekati distribusi normal"
      ]
    },
    {
      "metadata": {
        "id": "LRWy4U8mWb-E",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Check Skewness"
      ]
    },
    {
      "metadata": {
        "id": "uhhqOp5ZLubi",
        "colab_type": "code",
        "outputId": "4817cdff-e886-4739-b9fa-71cc19606526",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 554
        }
      },
      "cell_type": "code",
      "source": [
        "# Check Skewness\n",
        "print('Skewness:')\n",
        "for column in data:\n",
        "  print(column, ':', data[column].skew())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Skewness:\n",
            "roundness : -0.01763487371266934\n",
            "perimeter_ratio_to_diameter : 0.7740462725199914\n",
            "compactness : 0.8622724665987933\n",
            "eccentricity : -0.6651077891043039\n",
            "aspect_ratio : 2.81596754776404\n",
            "rectangularity : -1.9934744684694414\n",
            "narrow_factor : 0.3722701506064889\n",
            "perimeter_ratio_major_minor : 1.354135362190747\n",
            "hu_1 : 3.02545204844238\n",
            "hu_2 : 3.274692290439898\n",
            "hu_3 : 12.567854970619335\n",
            "hu_4 : 5.00532608558966\n",
            "hu_5 : -15.122510807614521\n",
            "hu_6 : 3.8609810033396834\n",
            "hu7 : 20.341204463740002\n",
            "mean_R : 0.020221330207309474\n",
            "mean_G : 0.153347999617765\n",
            "mean_B : 0.9273826312410595\n",
            "std_R : 0.46529068342519797\n",
            "std_G : 0.24803265184597448\n",
            "std_B : -0.1838231350801374\n",
            "skewness_R : 0.7970526367031292\n",
            "skewness_G : 0.7895108146100074\n",
            "skewness_B : 2.8637926268066862\n",
            "kurtosis_R : 1.431315683185697\n",
            "kurtosis_G : 0.9248361376002053\n",
            "kurtosis_B : 6.768752434439314\n",
            "contrast : 0.9314004640576299\n",
            "correlation : -1.2510091443780396\n",
            "energy : 0.5666640224067242\n",
            "homogeneity : -0.7344777424539618\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "rYPSl4I-EtpZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Skewness adalah derajat ketidaksimetrisan suatu distribusi. Jika kurva frekuensi suatu distribusi memiliki ekor yang lebih memanjang ke kanan (dilihat dari meannya) maka dikatakan menceng kanan (positif) dan jika sebaliknya maka menceng kiri (negatif). Secara perhitungan, skewness adalah momen ketiga terhadap mean. Distribusi normal (dan distribusi simetris lainnya, misalnya distribusi t atau Cauchy) memiliki skewness 0 (nol). <br>\n",
        "\n",
        "![](https://cdn-images-1.medium.com/max/1600/1*nj-Ch3AUFmkd0JUSOW_bTQ.jpeg)\n",
        "\n",
        "<br>Terlihat beberapa fitur di atas memiliki nilai skewness yang tinggi sehingga fitur tersebut sangat menyimpang jauh dari distribusi normal"
      ]
    },
    {
      "metadata": {
        "id": "5ODAEoFeWgP6",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Atribute Correlation"
      ]
    },
    {
      "metadata": {
        "id": "aRKnaoPqFilG",
        "colab_type": "code",
        "outputId": "a96ae52f-b030-4220-b620-a1bc81f5e3eb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1294
        }
      },
      "cell_type": "code",
      "source": [
        "# Uji korelasi atribut\n",
        "f, ax = plt.subplots(figsize=(20, 20))\n",
        "corr = data.corr()\n",
        "hm = sns.heatmap(round(corr,2), annot=True, ax=ax, cmap=\"coolwarm\", fmt='.2f', linewidths=.05)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5ZXRW2QYzf9Mupo8YiKW5Gd8P60tpD1ciY+Lo/90cGlWvgp2NVYF5vR2mO88O/f4Aj++E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\nwEufMhjaiFyxoigNx9Gq+s4BvRVFydb/Oxs1uigP2AKkKYryiBBiPhC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W3IYAL1cjuZLy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\nT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RBDY1O6vfYNjm5l6zywfgJpidEM+XAvAIc3TCEl/g4AedlpGJtZ89rU3eXqDIq4x7d/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OXHsXdwJiGu6I1VaQ7t3ca4Qe+xZd0y+gzSf/4kxEVj7/BMzGIqsPSJjX5CbHQEteo20Zs2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\nzrLwC6Pv47i85XuJyOfPWPDbXkLuB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zJh3nKSUlK44HOT9bv+ZPuSWTwOfc6y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\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4QbeGoTg7ORIk9yZY4cP5O7bf1VYzmWClL0GKh5rhxF64bmXj6epc8u+8Ql3JJZWQyCss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\n0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oUC1/ZdyD9rvu5E3uljOAUZ1/Gyq+GOvToAfVoySBJ2xeun2QfWwSGwLgUXrUddtKgb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noHxqzbi1qW6de8Lp7uClYdOUfdiq60r1edHWeuEHTnMabGRthaWjBnoDYPzKX7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\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4XdnW1JVtx44dc/tT/vru1KkTQQX6WX6u3nlIRTfn3LlIl+YNOX72ip5Mk1rVsciZi9Tx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\nB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KZl5IWdh45TvWLZ1N8/O2+inFi6Lsg0n1XLsfvURdN8lipGnpTfrLxvYe4/1PKpoJCY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\nnoR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njh/lXsxdvlrxHVcuX+TLxQuZu2BJCbuvlixg3Pg3CApuxIfvTyHq+FFat1UcPYmJ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TOB+yn9As4CzrddbcZXX+6jmLNd9oUuu1tGREea/iwPY/v6ipm/Bdal9PtrpZjUxThj+CRd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\nAAAAMGuPGKfdWN5ZRHkAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x1440 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "ibphEy4NJzr5",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Uji Pearson Product Moment adalah salah satu dari beberapa jenis uji korelasi yang digunakan untuk mengetahui derajat keeratan hubungan 2 variabel yang berskala interval atau rasio, di mana dengan uji ini akan mengembalikan nilai koefisien korelasi yang nilainya berkisar antara -1, 0 dan 1. Nilai -1 artinya terdapat korelasi negatif yang sempurna, 0 artinya tidak ada korelasi dan nilai 1 berarti ada korelasi positif yang sempurna.\n",
        "\n",
        "Rentang dari koefisien korelasi yang berkisar antara -1, 0 dan 1 tersebut dapat disimpulkan bahwa apabila semakin mendekati nilai 1 atau -1 maka hubungan makin erat, sedangkan jika semakin mendekati 0 maka hubungan semakin lemah. <br><br>\n",
        "\n",
        "**Koefisien Korelasi Pearson Product Moment**<br>\n",
        "![](https://i2.wp.com/www.statistikian.com/wp-content/uploads/blogger/-ziyIYtPwW3U/U0jNjkwBZKI/AAAAAAAACik/bREUN-MTd1c/s1600/pearson%2Btabel%2Bkoefisien.JPG?zoom=1.25&resize=400%2C72)\n",
        "<br><br>\n",
        "![](https://i0.wp.com/www.smartstat.info/images/stories/statistik/korelasi/korelasi-scatter.png)\n",
        "<br><br>\n",
        "\n",
        "Berdasarkan tabel di atas, dapat kami jelaskan tentang nilai koefisien korelasi uji pearson product moment dan makna keeratannya dalam sebuah analisis statistik atau analisis data. Berikut penjelasannya:\n",
        "\n",
        "1. Nilai koefisien 0 = Tidak ada hubungan sama sekali (jarang terjadi),\n",
        "2. Nilai koefisien 1 = Hubungan sempurna (jarang terjadi),\n",
        "3. Nilai koefisien > 0 sd < 0,2 = Hubungan sangat rendah atau sangat lemah,\n",
        "4. Nilai koefisien 0,2 sd < 0,4 = Hubungan rendah atau lemah,\n",
        "5. Nilai koefisien 0,4 sd < 0,6 = Hubungan cukup besar atau cukup kuat,\n",
        "6. Nilai koefisien 0,6 sd < 0,8 = Hubungan besar atau kuat,\n",
        "7. Nilai koefisien 0,8 sd < 1 = Hubungan sangat besar atau sangat kuat.\n",
        "8. Nilai negatif berarti menentukan arah hubungan, misal: koefisien korelasi antara penghasilan dan berat badan bernilai -0,5. Artinya semakin tinggi nilai penghasilan seseorang maka semakin rendah berat badannya dengan besarnya keeratan hubungan sebesar 0,5 atau cukup kuat (lihat tabel di atas)."
      ]
    },
    {
      "metadata": {
        "id": "jTDW6wOaNmFP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Preprocessing"
      ]
    },
    {
      "metadata": {
        "id": "Vu7wUOt9CLN2",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Count Missing Value"
      ]
    },
    {
      "metadata": {
        "id": "cITNslIrS-QU",
        "colab_type": "code",
        "outputId": "e815cb6f-cc2c-46cc-93d6-2fc19212b5fa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 588
        }
      },
      "cell_type": "code",
      "source": [
        "print('The number of missing value on dataset:')\n",
        "dataset.isna().sum()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The number of missing value on dataset:\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "roundness                      0\n",
              "perimeter_ratio_to_diameter    0\n",
              "compactness                    0\n",
              "eccentricity                   0\n",
              "aspect_ratio                   0\n",
              "rectangularity                 0\n",
              "narrow_factor                  0\n",
              "perimeter_ratio_major_minor    0\n",
              "hu_1                           0\n",
              "hu_2                           0\n",
              "hu_3                           0\n",
              "hu_4                           0\n",
              "hu_5                           0\n",
              "hu_6                           0\n",
              "hu7                            0\n",
              "mean_R                         0\n",
              "mean_G                         0\n",
              "mean_B                         0\n",
              "std_R                          0\n",
              "std_G                          0\n",
              "std_B                          0\n",
              "skewness_R                     0\n",
              "skewness_G                     0\n",
              "skewness_B                     0\n",
              "kurtosis_R                     0\n",
              "kurtosis_G                     0\n",
              "kurtosis_B                     0\n",
              "contrast                       0\n",
              "correlation                    0\n",
              "energy                         0\n",
              "homogeneity                    0\n",
              "class                          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 725
        }
      ]
    },
    {
      "metadata": {
        "id": "tFn4glW1KuXz",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### View Distribution of Value"
      ]
    },
    {
      "metadata": {
        "id": "O_ZGhqGuGo_f",
        "colab_type": "code",
        "outputId": "1c59364a-6395-4112-e2dc-f067ed9c5bfa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 32239
        }
      },
      "cell_type": "code",
      "source": [
        "for column in data:\n",
        "  print(column, ':')\n",
        "  print(data[column].value_counts())\n",
        "  print('\\n')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "roundness :\n",
            "0.71574    2\n",
            "0.80745    2\n",
            "0.30118    2\n",
            "0.76394    2\n",
            "0.65866    2\n",
            "0.49706    2\n",
            "0.82114    2\n",
            "0.39527    2\n",
            "0.54891    2\n",
            "0.61181    1\n",
            "0.59301    1\n",
            "0.43928    1\n",
            "0.59103    1\n",
            "0.28060    1\n",
            "0.28936    1\n",
            "0.61436    1\n",
            "0.67951    1\n",
            "0.28261    1\n",
            "0.58665    1\n",
            "0.31072    1\n",
            "0.55455    1\n",
            "0.58644    1\n",
            "0.41743    1\n",
            "0.39569    1\n",
            "0.42245    1\n",
            "0.62445    1\n",
            "0.58868    1\n",
            "0.55588    1\n",
            "0.29096    1\n",
            "0.69186    1\n",
            "          ..\n",
            "0.22844    1\n",
            "0.32583    1\n",
            "0.65433    1\n",
            "0.73776    1\n",
            "0.28638    1\n",
            "0.47833    1\n",
            "0.40622    1\n",
            "0.35807    1\n",
            "0.50217    1\n",
            "0.58608    1\n",
            "0.72816    1\n",
            "0.37294    1\n",
            "0.39972    1\n",
            "0.29374    1\n",
            "0.54375    1\n",
            "0.27145    1\n",
            "0.71588    1\n",
            "0.64857    1\n",
            "0.41846    1\n",
            "0.49982    1\n",
            "0.63514    1\n",
            "0.28830    1\n",
            "0.40996    1\n",
            "0.53808    1\n",
            "0.29661    1\n",
            "0.45385    1\n",
            "0.42974    1\n",
            "0.27349    1\n",
            "0.62390    1\n",
            "0.65946    1\n",
            "Name: roundness, Length: 966, dtype: int64\n",
            "\n",
            "\n",
            "perimeter_ratio_to_diameter :\n",
            "3.3587    4\n",
            "3.3010    3\n",
            "3.1055    2\n",
            "3.2558    2\n",
            "2.7849    2\n",
            "2.9996    2\n",
            "4.6016    2\n",
            "3.2295    2\n",
            "3.3027    2\n",
            "3.4708    2\n",
            "3.6260    2\n",
            "3.3258    2\n",
            "3.0201    2\n",
            "3.5310    2\n",
            "2.1132    2\n",
            "3.1682    2\n",
            "3.2520    2\n",
            "3.2047    2\n",
            "3.2694    2\n",
            "3.0557    2\n",
            "3.4423    2\n",
            "2.1215    2\n",
            "3.3600    2\n",
            "3.2902    2\n",
            "2.8947    2\n",
            "3.2508    2\n",
            "2.5573    2\n",
            "3.4313    2\n",
            "3.0653    2\n",
            "3.4679    2\n",
            "         ..\n",
            "2.1005    1\n",
            "3.3526    1\n",
            "2.8859    1\n",
            "3.3877    1\n",
            "3.3625    1\n",
            "3.0861    1\n",
            "3.1635    1\n",
            "2.6857    1\n",
            "4.0713    1\n",
            "3.4395    1\n",
            "2.1312    1\n",
            "2.8637    1\n",
            "2.1274    1\n",
            "4.3729    1\n",
            "2.7796    1\n",
            "4.7750    1\n",
            "2.7303    1\n",
            "4.1134    1\n",
            "2.7494    1\n",
            "3.1886    1\n",
            "2.1239    1\n",
            "3.5449    1\n",
            "4.6753    1\n",
            "2.6641    1\n",
            "3.2688    1\n",
            "3.1207    1\n",
            "3.2628    1\n",
            "2.7823    1\n",
            "3.0411    1\n",
            "3.4563    1\n",
            "Name: perimeter_ratio_to_diameter, Length: 937, dtype: int64\n",
            "\n",
            "\n",
            "compactness :\n",
            "6.4594    2\n",
            "4.1901    2\n",
            "3.9450    2\n",
            "3.9120    2\n",
            "4.3133    2\n",
            "4.4212    2\n",
            "5.6384    2\n",
            "4.8154    2\n",
            "5.5273    2\n",
            "4.1780    2\n",
            "4.3679    2\n",
            "5.6199    2\n",
            "4.7847    2\n",
            "4.0558    2\n",
            "4.2013    1\n",
            "6.9101    1\n",
            "6.1423    1\n",
            "5.9827    1\n",
            "4.4816    1\n",
            "4.1102    1\n",
            "4.8986    1\n",
            "6.5269    1\n",
            "4.6926    1\n",
            "4.2613    1\n",
            "6.1313    1\n",
            "4.7848    1\n",
            "4.5781    1\n",
            "4.2625    1\n",
            "4.9875    1\n",
            "5.1657    1\n",
            "         ..\n",
            "3.9786    1\n",
            "6.8146    1\n",
            "4.8664    1\n",
            "6.4438    1\n",
            "6.9044    1\n",
            "4.3910    1\n",
            "4.1432    1\n",
            "5.5472    1\n",
            "4.7152    1\n",
            "7.5084    1\n",
            "4.2306    1\n",
            "4.6880    1\n",
            "4.9256    1\n",
            "4.7421    1\n",
            "4.5226    1\n",
            "5.5048    1\n",
            "5.0946    1\n",
            "6.0592    1\n",
            "7.3375    1\n",
            "5.2250    1\n",
            "6.6920    1\n",
            "7.0318    1\n",
            "4.0231    1\n",
            "6.0647    1\n",
            "7.1853    1\n",
            "5.1204    1\n",
            "4.5503    1\n",
            "5.3247    1\n",
            "6.9841    1\n",
            "6.8125    1\n",
            "Name: compactness, Length: 961, dtype: int64\n",
            "\n",
            "\n",
            "eccentricity :\n",
            "0.815690    2\n",
            "0.260480    2\n",
            "0.843250    2\n",
            "0.460490    2\n",
            "0.984520    2\n",
            "0.578120    2\n",
            "0.854290    2\n",
            "0.857870    2\n",
            "0.741400    2\n",
            "0.854320    2\n",
            "0.753690    2\n",
            "0.239110    2\n",
            "0.766500    2\n",
            "0.984380    2\n",
            "0.615920    2\n",
            "0.831150    2\n",
            "0.843130    2\n",
            "0.982790    2\n",
            "0.841760    2\n",
            "0.820150    2\n",
            "0.832160    1\n",
            "0.988260    1\n",
            "0.354710    1\n",
            "0.802890    1\n",
            "0.792130    1\n",
            "0.713810    1\n",
            "0.432910    1\n",
            "0.669820    1\n",
            "0.857320    1\n",
            "0.880650    1\n",
            "           ..\n",
            "0.893240    1\n",
            "0.845790    1\n",
            "0.800260    1\n",
            "0.152110    1\n",
            "0.980390    1\n",
            "0.610040    1\n",
            "0.531490    1\n",
            "0.983710    1\n",
            "0.454620    1\n",
            "0.766480    1\n",
            "0.512970    1\n",
            "0.828320    1\n",
            "0.836450    1\n",
            "0.374690    1\n",
            "0.831700    1\n",
            "0.723890    1\n",
            "0.443710    1\n",
            "0.708850    1\n",
            "0.877780    1\n",
            "0.568890    1\n",
            "0.083513    1\n",
            "0.279300    1\n",
            "0.789200    1\n",
            "0.717790    1\n",
            "0.853720    1\n",
            "0.239200    1\n",
            "0.219120    1\n",
            "0.746030    1\n",
            "0.165210    1\n",
            "0.552870    1\n",
            "Name: eccentricity, Length: 955, dtype: int64\n",
            "\n",
            "\n",
            "aspect_ratio :\n",
            "1.5570    3\n",
            "1.0299    3\n",
            "1.7653    2\n",
            "5.7056    2\n",
            "1.1001    2\n",
            "1.8604    2\n",
            "1.0249    2\n",
            "1.0403    2\n",
            "1.7854    2\n",
            "1.1265    2\n",
            "1.7744    2\n",
            "1.9240    2\n",
            "1.3294    2\n",
            "1.0779    2\n",
            "1.0960    2\n",
            "1.7478    2\n",
            "1.7984    2\n",
            "1.9837    2\n",
            "1.0630    2\n",
            "1.2256    2\n",
            "1.0878    2\n",
            "1.2693    2\n",
            "1.0358    2\n",
            "1.9668    2\n",
            "1.0326    2\n",
            "1.3956    2\n",
            "1.8524    2\n",
            "1.0653    2\n",
            "1.9460    2\n",
            "1.5215    2\n",
            "         ..\n",
            "1.1168    1\n",
            "2.0652    1\n",
            "1.2242    1\n",
            "1.2758    1\n",
            "1.0318    1\n",
            "5.0749    1\n",
            "1.0994    1\n",
            "1.5256    1\n",
            "1.5012    1\n",
            "1.4523    1\n",
            "1.1625    1\n",
            "1.2750    1\n",
            "2.0960    1\n",
            "1.7286    1\n",
            "1.1464    1\n",
            "1.2283    1\n",
            "1.2731    1\n",
            "1.7546    1\n",
            "1.2391    1\n",
            "1.5926    1\n",
            "1.6532    1\n",
            "1.2009    1\n",
            "1.8189    1\n",
            "1.8599    1\n",
            "1.8018    1\n",
            "1.0507    1\n",
            "1.5029    1\n",
            "5.3634    1\n",
            "1.9592    1\n",
            "2.2500    1\n",
            "Name: aspect_ratio, Length: 936, dtype: int64\n",
            "\n",
            "\n",
            "rectangularity :\n",
            "0.77839    3\n",
            "0.78023    3\n",
            "0.77609    3\n",
            "0.77542    3\n",
            "0.77868    3\n",
            "0.77567    3\n",
            "0.77545    3\n",
            "0.77148    3\n",
            "0.77735    3\n",
            "0.77902    3\n",
            "0.77941    3\n",
            "0.77937    3\n",
            "0.77465    3\n",
            "0.77030    3\n",
            "0.77557    3\n",
            "0.76904    3\n",
            "0.77470    2\n",
            "0.77995    2\n",
            "0.77276    2\n",
            "0.77647    2\n",
            "0.77519    2\n",
            "0.74955    2\n",
            "0.77801    2\n",
            "0.77969    2\n",
            "0.67624    2\n",
            "0.77883    2\n",
            "0.77202    2\n",
            "0.78096    2\n",
            "0.77784    2\n",
            "0.77530    2\n",
            "          ..\n",
            "0.74222    1\n",
            "0.75778    1\n",
            "0.76241    1\n",
            "0.77846    1\n",
            "0.69029    1\n",
            "0.76854    1\n",
            "0.77732    1\n",
            "0.71803    1\n",
            "0.77159    1\n",
            "0.76410    1\n",
            "0.67609    1\n",
            "0.76099    1\n",
            "0.78178    1\n",
            "0.76552    1\n",
            "0.76880    1\n",
            "0.73165    1\n",
            "0.76835    1\n",
            "0.78015    1\n",
            "0.75957    1\n",
            "0.71947    1\n",
            "0.72898    1\n",
            "0.72806    1\n",
            "0.77194    1\n",
            "0.72608    1\n",
            "0.77791    1\n",
            "0.77968    1\n",
            "0.77430    1\n",
            "0.77415    1\n",
            "0.77090    1\n",
            "0.69748    1\n",
            "Name: rectangularity, Length: 846, dtype: int64\n",
            "\n",
            "\n",
            "narrow_factor :\n",
            "1.0868    5\n",
            "1.1176    4\n",
            "1.1144    4\n",
            "1.1179    4\n",
            "1.1856    4\n",
            "1.1229    4\n",
            "1.1778    4\n",
            "1.1131    4\n",
            "1.1126    4\n",
            "1.1227    4\n",
            "1.1027    4\n",
            "1.2113    3\n",
            "1.0957    3\n",
            "1.0848    3\n",
            "1.1155    3\n",
            "1.0996    3\n",
            "1.1726    3\n",
            "1.0960    3\n",
            "1.1068    3\n",
            "1.1756    3\n",
            "1.0984    3\n",
            "1.1421    3\n",
            "1.0379    3\n",
            "1.1024    3\n",
            "1.0962    3\n",
            "1.1119    3\n",
            "1.1256    3\n",
            "1.1082    3\n",
            "1.1157    3\n",
            "1.1066    3\n",
            "         ..\n",
            "1.2137    1\n",
            "1.2049    1\n",
            "1.1536    1\n",
            "1.0736    1\n",
            "1.1175    1\n",
            "1.2115    1\n",
            "1.0724    1\n",
            "1.1388    1\n",
            "1.0869    1\n",
            "1.0745    1\n",
            "1.1310    1\n",
            "1.2155    1\n",
            "1.0485    1\n",
            "1.1908    1\n",
            "1.1226    1\n",
            "1.1107    1\n",
            "1.1243    1\n",
            "1.1882    1\n",
            "1.1158    1\n",
            "1.1342    1\n",
            "1.1274    1\n",
            "1.1354    1\n",
            "1.1090    1\n",
            "1.1471    1\n",
            "1.1694    1\n",
            "1.1749    1\n",
            "1.1919    1\n",
            "1.2178    1\n",
            "1.0318    1\n",
            "1.1875    1\n",
            "Name: narrow_factor, Length: 727, dtype: int64\n",
            "\n",
            "\n",
            "perimeter_ratio_major_minor :\n",
            "2.2441    2\n",
            "2.0868    2\n",
            "2.0013    2\n",
            "2.3031    2\n",
            "1.7314    2\n",
            "1.8899    2\n",
            "3.0682    2\n",
            "2.2882    2\n",
            "1.7484    2\n",
            "1.9294    2\n",
            "1.8768    2\n",
            "2.0298    2\n",
            "2.2848    2\n",
            "2.0622    2\n",
            "1.8607    2\n",
            "2.3412    2\n",
            "1.7919    2\n",
            "1.8431    2\n",
            "1.9718    2\n",
            "2.0672    2\n",
            "2.2386    2\n",
            "1.7411    2\n",
            "1.9767    2\n",
            "2.0887    2\n",
            "1.9871    2\n",
            "2.1930    2\n",
            "2.4346    2\n",
            "1.9946    2\n",
            "2.2185    2\n",
            "2.3641    2\n",
            "         ..\n",
            "1.7865    1\n",
            "2.3920    1\n",
            "2.5182    1\n",
            "2.0176    1\n",
            "3.1642    1\n",
            "2.0033    1\n",
            "1.9523    1\n",
            "2.3625    1\n",
            "3.5960    1\n",
            "2.2034    1\n",
            "3.1053    1\n",
            "2.2511    1\n",
            "1.9682    1\n",
            "3.2282    1\n",
            "2.2949    1\n",
            "2.4314    1\n",
            "3.0268    1\n",
            "2.0188    1\n",
            "1.9041    1\n",
            "1.8007    1\n",
            "1.9971    1\n",
            "1.8967    1\n",
            "2.5092    1\n",
            "1.9633    1\n",
            "1.9117    1\n",
            "2.4222    1\n",
            "1.9397    1\n",
            "2.5652    1\n",
            "1.8280    1\n",
            "1.9375    1\n",
            "Name: perimeter_ratio_major_minor, Length: 925, dtype: int64\n",
            "\n",
            "\n",
            "hu_1 :\n",
            "0.17468    3\n",
            "0.16523    3\n",
            "0.16132    3\n",
            "0.16627    3\n",
            "0.16715    3\n",
            "0.16719    3\n",
            "0.17377    3\n",
            "0.16048    2\n",
            "0.16181    2\n",
            "0.16617    2\n",
            "0.16471    2\n",
            "0.20689    2\n",
            "0.17997    2\n",
            "0.18900    2\n",
            "0.18498    2\n",
            "0.16846    2\n",
            "0.17277    2\n",
            "0.16554    2\n",
            "0.17485    2\n",
            "0.16820    2\n",
            "0.16024    2\n",
            "0.18784    2\n",
            "0.16518    2\n",
            "0.16395    2\n",
            "0.17922    2\n",
            "0.17768    2\n",
            "0.16555    2\n",
            "0.18017    2\n",
            "0.17457    2\n",
            "0.18578    2\n",
            "          ..\n",
            "0.18548    1\n",
            "0.17611    1\n",
            "0.19941    1\n",
            "0.16426    1\n",
            "0.17010    1\n",
            "0.21133    1\n",
            "0.16478    1\n",
            "0.18928    1\n",
            "0.53317    1\n",
            "0.19155    1\n",
            "0.19820    1\n",
            "0.17373    1\n",
            "0.22993    1\n",
            "0.16827    1\n",
            "0.16577    1\n",
            "0.17239    1\n",
            "0.20846    1\n",
            "0.16647    1\n",
            "0.16367    1\n",
            "0.23894    1\n",
            "0.20602    1\n",
            "0.16596    1\n",
            "0.19348    1\n",
            "0.20160    1\n",
            "0.16696    1\n",
            "0.19449    1\n",
            "0.22077    1\n",
            "0.16511    1\n",
            "0.21774    1\n",
            "0.17012    1\n",
            "Name: hu_1, Length: 889, dtype: int64\n",
            "\n",
            "\n",
            "hu_2 :\n",
            "0.000008    5\n",
            "0.000017    4\n",
            "0.000171    3\n",
            "0.000051    3\n",
            "0.000022    3\n",
            "0.000183    3\n",
            "0.000028    3\n",
            "0.000105    3\n",
            "0.000098    3\n",
            "0.000370    2\n",
            "0.000004    2\n",
            "0.001101    2\n",
            "0.000103    2\n",
            "0.000005    2\n",
            "0.000050    2\n",
            "0.011384    2\n",
            "0.000137    2\n",
            "0.000032    2\n",
            "0.000010    2\n",
            "0.000358    2\n",
            "0.000109    2\n",
            "0.000772    2\n",
            "0.000692    2\n",
            "0.000993    2\n",
            "0.002462    2\n",
            "0.000079    2\n",
            "0.000164    2\n",
            "0.000238    2\n",
            "0.000656    2\n",
            "0.003891    2\n",
            "           ..\n",
            "0.010588    1\n",
            "0.008117    1\n",
            "0.007384    1\n",
            "0.005748    1\n",
            "0.000559    1\n",
            "0.000181    1\n",
            "0.003243    1\n",
            "0.005983    1\n",
            "0.001270    1\n",
            "0.012898    1\n",
            "0.001838    1\n",
            "0.011758    1\n",
            "0.001334    1\n",
            "0.001705    1\n",
            "0.195610    1\n",
            "0.004577    1\n",
            "0.007742    1\n",
            "0.005114    1\n",
            "0.004889    1\n",
            "0.000552    1\n",
            "0.009775    1\n",
            "0.000290    1\n",
            "0.006640    1\n",
            "0.000021    1\n",
            "0.200450    1\n",
            "0.002528    1\n",
            "0.009002    1\n",
            "0.005272    1\n",
            "0.000119    1\n",
            "0.002452    1\n",
            "Name: hu_2, Length: 903, dtype: int64\n",
            "\n",
            "\n",
            "hu_3 :\n",
            "0.000004    22\n",
            "0.000003    18\n",
            "0.000001    15\n",
            "0.000002    15\n",
            "0.000010    12\n",
            "0.000000    12\n",
            "0.000013    12\n",
            "0.000005    12\n",
            "0.000012    11\n",
            "0.000068     9\n",
            "0.000021     9\n",
            "0.000025     9\n",
            "0.000016     9\n",
            "0.000007     8\n",
            "0.000029     8\n",
            "0.000011     8\n",
            "0.000009     8\n",
            "0.000071     8\n",
            "0.000017     8\n",
            "0.000006     8\n",
            "0.000042     7\n",
            "0.000067     7\n",
            "0.000018     7\n",
            "0.000048     7\n",
            "0.000047     6\n",
            "0.000032     6\n",
            "0.000074     6\n",
            "0.000027     6\n",
            "0.000008     6\n",
            "0.000028     6\n",
            "            ..\n",
            "0.000154     1\n",
            "0.000782     1\n",
            "0.001213     1\n",
            "0.000488     1\n",
            "0.001309     1\n",
            "0.000828     1\n",
            "0.000635     1\n",
            "0.000401     1\n",
            "0.000857     1\n",
            "0.001824     1\n",
            "0.000987     1\n",
            "0.001595     1\n",
            "0.000136     1\n",
            "0.001135     1\n",
            "0.001291     1\n",
            "0.002953     1\n",
            "0.001382     1\n",
            "0.000261     1\n",
            "0.000321     1\n",
            "0.001707     1\n",
            "0.000264     1\n",
            "0.001024     1\n",
            "0.000440     1\n",
            "0.000469     1\n",
            "0.000409     1\n",
            "0.000379     1\n",
            "0.000092     1\n",
            "0.000381     1\n",
            "0.000433     1\n",
            "0.000272     1\n",
            "Name: hu_3, Length: 450, dtype: int64\n",
            "\n",
            "\n",
            "hu_4 :\n",
            "0.000000    258\n",
            "0.000001    163\n",
            "0.000002     79\n",
            "0.000003     52\n",
            "0.000004     35\n",
            "0.000005     32\n",
            "0.000006     26\n",
            "0.000007     20\n",
            "0.000009     16\n",
            "0.000008     15\n",
            "0.000012     12\n",
            "0.000010     11\n",
            "0.000011     11\n",
            "0.000017      8\n",
            "0.000014      8\n",
            "0.000019      7\n",
            "0.000018      7\n",
            "0.000015      6\n",
            "0.000016      6\n",
            "0.000013      6\n",
            "0.000025      4\n",
            "0.000022      4\n",
            "0.000026      4\n",
            "0.000021      4\n",
            "0.000047      3\n",
            "0.000033      3\n",
            "0.000090      3\n",
            "0.000023      3\n",
            "0.000661      3\n",
            "0.000029      2\n",
            "           ... \n",
            "0.001154      1\n",
            "0.001551      1\n",
            "0.000101      1\n",
            "0.000241      1\n",
            "0.000322      1\n",
            "0.000130      1\n",
            "0.000034      1\n",
            "0.001676      1\n",
            "0.000174      1\n",
            "0.000915      1\n",
            "0.001869      1\n",
            "0.000077      1\n",
            "0.000282      1\n",
            "0.000640      1\n",
            "0.003395      1\n",
            "0.000509      1\n",
            "0.001622      1\n",
            "0.002145      1\n",
            "0.001857      1\n",
            "0.001004      1\n",
            "0.000425      1\n",
            "0.000184      1\n",
            "0.000124      1\n",
            "0.000305      1\n",
            "0.000645      1\n",
            "0.000099      1\n",
            "0.000152      1\n",
            "0.001818      1\n",
            "0.000020      1\n",
            "0.000341      1\n",
            "Name: hu_4, Length: 175, dtype: int64\n",
            "\n",
            "\n",
            "hu_5 :\n",
            " 0.000000    918\n",
            " 0.000001     24\n",
            " 0.000002     13\n",
            " 0.000004      5\n",
            " 0.000005      3\n",
            "-0.000005      2\n",
            " 0.000009      2\n",
            "-0.000001      2\n",
            " 0.000010      2\n",
            "-0.000044      1\n",
            " 0.000016      1\n",
            " 0.000007      1\n",
            " 0.000008      1\n",
            "Name: hu_5, dtype: int64\n",
            "\n",
            "\n",
            "hu_6 :\n",
            " 0.000000    672\n",
            " 0.000001     92\n",
            " 0.000002     40\n",
            " 0.000003     11\n",
            " 0.000005      8\n",
            " 0.000004      7\n",
            " 0.000015      6\n",
            " 0.000049      4\n",
            " 0.000014      3\n",
            " 0.000020      3\n",
            " 0.000008      3\n",
            " 0.000019      3\n",
            " 0.000009      3\n",
            " 0.000024      2\n",
            " 0.000031      2\n",
            " 0.000023      2\n",
            " 0.000044      2\n",
            " 0.000365      2\n",
            " 0.000078      2\n",
            " 0.000377      2\n",
            " 0.000308      2\n",
            " 0.000063      2\n",
            " 0.000035      2\n",
            "-0.000001      2\n",
            " 0.000012      2\n",
            " 0.000322      2\n",
            " 0.000006      2\n",
            " 0.000233      2\n",
            " 0.000027      2\n",
            " 0.000030      2\n",
            "            ... \n",
            " 0.000013      1\n",
            " 0.000287      1\n",
            " 0.000029      1\n",
            " 0.000142      1\n",
            " 0.000847      1\n",
            " 0.000345      1\n",
            " 0.000227      1\n",
            " 0.000515      1\n",
            " 0.000103      1\n",
            " 0.000041      1\n",
            " 0.000017      1\n",
            " 0.000117      1\n",
            " 0.000037      1\n",
            " 0.000016      1\n",
            " 0.000079      1\n",
            " 0.000416      1\n",
            " 0.000623      1\n",
            " 0.000034      1\n",
            "-0.000246      1\n",
            " 0.000068      1\n",
            " 0.000970      1\n",
            " 0.000964      1\n",
            " 0.000335      1\n",
            " 0.000202      1\n",
            " 0.000334      1\n",
            " 0.001388      1\n",
            " 0.000200      1\n",
            "-0.000118      1\n",
            " 0.000040      1\n",
            " 0.000036      1\n",
            "Name: hu_6, Length: 116, dtype: int64\n",
            "\n",
            "\n",
            "hu7 :\n",
            " 0.000000    957\n",
            "-0.000001      3\n",
            " 0.000001      3\n",
            " 0.000004      2\n",
            " 0.000003      2\n",
            "-0.000003      2\n",
            "-0.000008      1\n",
            " 0.000008      1\n",
            " 0.000028      1\n",
            "-0.000004      1\n",
            " 0.000007      1\n",
            " 0.000002      1\n",
            "Name: hu7, dtype: int64\n",
            "\n",
            "\n",
            "mean_R :\n",
            "60.584    2\n",
            "72.473    2\n",
            "66.516    2\n",
            "49.320    2\n",
            "76.540    2\n",
            "65.197    2\n",
            "67.176    2\n",
            "86.370    2\n",
            "66.381    2\n",
            "79.015    2\n",
            "69.725    2\n",
            "61.115    2\n",
            "68.637    2\n",
            "70.015    2\n",
            "73.743    2\n",
            "70.426    2\n",
            "69.580    2\n",
            "69.585    2\n",
            "77.638    2\n",
            "72.839    2\n",
            "63.338    2\n",
            "70.342    2\n",
            "66.479    2\n",
            "61.697    2\n",
            "71.455    2\n",
            "55.017    2\n",
            "66.042    2\n",
            "65.040    2\n",
            "70.906    1\n",
            "78.111    1\n",
            "         ..\n",
            "72.377    1\n",
            "69.611    1\n",
            "55.540    1\n",
            "79.139    1\n",
            "67.640    1\n",
            "79.182    1\n",
            "53.122    1\n",
            "63.024    1\n",
            "70.441    1\n",
            "70.362    1\n",
            "78.385    1\n",
            "60.226    1\n",
            "62.690    1\n",
            "66.486    1\n",
            "77.492    1\n",
            "78.445    1\n",
            "60.550    1\n",
            "76.845    1\n",
            "79.817    1\n",
            "69.051    1\n",
            "74.706    1\n",
            "67.575    1\n",
            "66.935    1\n",
            "72.615    1\n",
            "65.683    1\n",
            "62.084    1\n",
            "72.620    1\n",
            "57.257    1\n",
            "64.549    1\n",
            "73.750    1\n",
            "Name: mean_R, Length: 947, dtype: int64\n",
            "\n",
            "\n",
            "mean_G :\n",
            "87.646    2\n",
            "57.472    2\n",
            "68.768    2\n",
            "62.586    2\n",
            "65.486    2\n",
            "60.047    2\n",
            "60.806    2\n",
            "62.601    2\n",
            "46.789    2\n",
            "62.083    2\n",
            "43.792    2\n",
            "63.030    2\n",
            "72.178    2\n",
            "59.764    2\n",
            "92.464    1\n",
            "67.808    1\n",
            "48.133    1\n",
            "57.216    1\n",
            "65.437    1\n",
            "67.228    1\n",
            "68.769    1\n",
            "50.439    1\n",
            "64.052    1\n",
            "47.587    1\n",
            "65.118    1\n",
            "59.319    1\n",
            "39.225    1\n",
            "73.043    1\n",
            "63.433    1\n",
            "60.797    1\n",
            "         ..\n",
            "45.746    1\n",
            "60.708    1\n",
            "75.380    1\n",
            "63.741    1\n",
            "85.302    1\n",
            "68.623    1\n",
            "83.060    1\n",
            "85.631    1\n",
            "59.219    1\n",
            "47.816    1\n",
            "72.369    1\n",
            "65.279    1\n",
            "84.622    1\n",
            "58.430    1\n",
            "61.378    1\n",
            "73.788    1\n",
            "77.420    1\n",
            "56.837    1\n",
            "92.521    1\n",
            "81.479    1\n",
            "61.993    1\n",
            "61.320    1\n",
            "43.977    1\n",
            "69.906    1\n",
            "52.201    1\n",
            "80.441    1\n",
            "61.194    1\n",
            "56.509    1\n",
            "59.504    1\n",
            "80.000    1\n",
            "Name: mean_G, Length: 961, dtype: int64\n",
            "\n",
            "\n",
            "mean_B :\n",
            "5.82310     2\n",
            "24.22700    2\n",
            "16.39700    2\n",
            "3.08700     2\n",
            "3.87760     2\n",
            "21.76600    2\n",
            "5.78080     2\n",
            "6.13880     2\n",
            "21.90200    2\n",
            "3.49780     1\n",
            "23.96700    1\n",
            "22.00700    1\n",
            "28.78200    1\n",
            "13.68300    1\n",
            "0.27458     1\n",
            "0.53326     1\n",
            "6.95350     1\n",
            "25.66600    1\n",
            "12.05600    1\n",
            "23.97100    1\n",
            "1.48750     1\n",
            "23.61600    1\n",
            "12.72500    1\n",
            "18.40300    1\n",
            "1.05870     1\n",
            "40.41700    1\n",
            "3.53180     1\n",
            "5.05020     1\n",
            "3.37950     1\n",
            "10.14000    1\n",
            "           ..\n",
            "18.14500    1\n",
            "0.74456     1\n",
            "6.49790     1\n",
            "15.56800    1\n",
            "20.75600    1\n",
            "15.03200    1\n",
            "21.01200    1\n",
            "0.13962     1\n",
            "0.29049     1\n",
            "11.86500    1\n",
            "15.62600    1\n",
            "23.01600    1\n",
            "21.35400    1\n",
            "5.10240     1\n",
            "22.37300    1\n",
            "23.22500    1\n",
            "2.59480     1\n",
            "46.30000    1\n",
            "4.56700     1\n",
            "4.53180     1\n",
            "3.92160     1\n",
            "2.31480     1\n",
            "2.74890     1\n",
            "6.60510     1\n",
            "15.81800    1\n",
            "1.71760     1\n",
            "7.69970     1\n",
            "4.23410     1\n",
            "4.78760     1\n",
            "23.37500    1\n",
            "Name: mean_B, Length: 966, dtype: int64\n",
            "\n",
            "\n",
            "std_R :\n",
            "17.853    3\n",
            "16.676    3\n",
            "16.276    2\n",
            "23.658    2\n",
            "16.978    2\n",
            "13.003    2\n",
            "14.570    2\n",
            "17.743    2\n",
            "16.800    2\n",
            "16.472    2\n",
            "12.989    2\n",
            "15.092    2\n",
            "17.623    2\n",
            "16.764    2\n",
            "15.693    2\n",
            "16.439    2\n",
            "15.627    2\n",
            "17.158    2\n",
            "17.817    2\n",
            "12.246    2\n",
            "16.596    2\n",
            "15.432    2\n",
            "14.488    2\n",
            "18.755    2\n",
            "18.053    2\n",
            "16.673    2\n",
            "17.405    2\n",
            "14.951    2\n",
            "17.499    2\n",
            "18.225    2\n",
            "         ..\n",
            "12.074    1\n",
            "17.442    1\n",
            "16.268    1\n",
            "17.650    1\n",
            "12.580    1\n",
            "18.243    1\n",
            "15.103    1\n",
            "12.872    1\n",
            "17.561    1\n",
            "17.715    1\n",
            "16.689    1\n",
            "18.083    1\n",
            "12.097    1\n",
            "17.911    1\n",
            "15.468    1\n",
            "15.385    1\n",
            "18.430    1\n",
            "15.675    1\n",
            "19.606    1\n",
            "23.684    1\n",
            "26.252    1\n",
            "18.345    1\n",
            "16.854    1\n",
            "15.997    1\n",
            "18.511    1\n",
            "17.525    1\n",
            "16.775    1\n",
            "16.025    1\n",
            "15.883    1\n",
            "17.625    1\n",
            "Name: std_R, Length: 932, dtype: int64\n",
            "\n",
            "\n",
            "std_G :\n",
            "19.670    3\n",
            "14.799    3\n",
            "16.203    2\n",
            "18.201    2\n",
            "18.887    2\n",
            "17.570    2\n",
            "16.004    2\n",
            "17.811    2\n",
            "20.842    2\n",
            "17.005    2\n",
            "18.209    2\n",
            "16.730    2\n",
            "17.557    2\n",
            "17.181    2\n",
            "17.341    2\n",
            "14.271    2\n",
            "16.983    2\n",
            "17.897    2\n",
            "19.453    2\n",
            "19.833    2\n",
            "21.059    2\n",
            "19.921    2\n",
            "18.136    2\n",
            "16.829    2\n",
            "17.654    2\n",
            "17.575    2\n",
            "17.771    2\n",
            "18.928    2\n",
            "19.095    2\n",
            "18.817    2\n",
            "         ..\n",
            "19.413    1\n",
            "19.891    1\n",
            "15.634    1\n",
            "18.689    1\n",
            "19.808    1\n",
            "19.083    1\n",
            "18.355    1\n",
            "14.718    1\n",
            "14.385    1\n",
            "17.410    1\n",
            "16.167    1\n",
            "17.284    1\n",
            "15.128    1\n",
            "14.657    1\n",
            "14.006    1\n",
            "20.260    1\n",
            "19.059    1\n",
            "13.575    1\n",
            "19.501    1\n",
            "19.252    1\n",
            "19.345    1\n",
            "13.927    1\n",
            "20.400    1\n",
            "21.373    1\n",
            "21.141    1\n",
            "19.275    1\n",
            "18.025    1\n",
            "22.766    1\n",
            "18.850    1\n",
            "17.750    1\n",
            "Name: std_G, Length: 922, dtype: int64\n",
            "\n",
            "\n",
            "std_B :\n",
            "14.1980    2\n",
            "22.3780    2\n",
            "20.1610    2\n",
            "14.0390    2\n",
            "13.6800    2\n",
            "10.9520    2\n",
            "19.7160    2\n",
            "15.7520    2\n",
            "22.5640    2\n",
            "20.6350    2\n",
            "14.2850    2\n",
            "11.7030    2\n",
            "11.2110    2\n",
            "16.4060    2\n",
            "14.6190    2\n",
            "20.4440    2\n",
            "10.9410    1\n",
            "9.5422     1\n",
            "26.9280    1\n",
            "12.4330    1\n",
            "8.6228     1\n",
            "9.5862     1\n",
            "20.0300    1\n",
            "9.1434     1\n",
            "18.8370    1\n",
            "5.3777     1\n",
            "16.1320    1\n",
            "11.6850    1\n",
            "23.1400    1\n",
            "11.4340    1\n",
            "          ..\n",
            "4.0713     1\n",
            "6.8662     1\n",
            "4.6468     1\n",
            "13.5880    1\n",
            "24.1860    1\n",
            "15.1350    1\n",
            "18.4100    1\n",
            "9.6699     1\n",
            "10.0540    1\n",
            "21.7560    1\n",
            "13.0320    1\n",
            "10.9510    1\n",
            "10.1540    1\n",
            "24.9730    1\n",
            "14.8760    1\n",
            "14.5080    1\n",
            "13.1770    1\n",
            "12.1220    1\n",
            "8.1423     1\n",
            "18.5610    1\n",
            "16.1000    1\n",
            "22.4000    1\n",
            "6.9057     1\n",
            "8.0669     1\n",
            "24.6300    1\n",
            "19.2800    1\n",
            "19.7340    1\n",
            "10.7780    1\n",
            "7.2028     1\n",
            "21.5000    1\n",
            "Name: std_B, Length: 959, dtype: int64\n",
            "\n",
            "\n",
            "skewness_R :\n",
            " 0.523150    2\n",
            " 0.329950    2\n",
            " 0.030064    2\n",
            " 1.822800    2\n",
            " 1.766600    2\n",
            " 1.114200    2\n",
            " 0.660420    2\n",
            " 0.279760    2\n",
            " 1.304700    2\n",
            " 0.167900    1\n",
            " 0.069219    1\n",
            " 0.854270    1\n",
            " 0.952620    1\n",
            " 0.290660    1\n",
            " 0.699300    1\n",
            "-0.009465    1\n",
            " 0.728790    1\n",
            " 0.843440    1\n",
            " 0.125680    1\n",
            " 0.597280    1\n",
            "-0.411570    1\n",
            " 0.455690    1\n",
            " 0.112040    1\n",
            " 0.103590    1\n",
            "-0.075094    1\n",
            " 0.462480    1\n",
            " 1.512500    1\n",
            "-0.244650    1\n",
            " 0.435580    1\n",
            " 0.069359    1\n",
            "            ..\n",
            "-0.165630    1\n",
            " 1.570300    1\n",
            " 0.345480    1\n",
            " 0.168370    1\n",
            "-0.019610    1\n",
            " 0.895340    1\n",
            "-0.018480    1\n",
            " 0.298890    1\n",
            "-0.394620    1\n",
            " 0.204840    1\n",
            " 0.449130    1\n",
            " 1.913600    1\n",
            " 0.156620    1\n",
            " 0.473170    1\n",
            "-0.227710    1\n",
            " 0.307130    1\n",
            " 0.706250    1\n",
            " 0.279240    1\n",
            "-0.119670    1\n",
            " 0.619000    1\n",
            " 1.156900    1\n",
            " 0.451820    1\n",
            " 0.125540    1\n",
            " 0.864120    1\n",
            " 0.313050    1\n",
            " 0.626550    1\n",
            " 0.000961    1\n",
            " 1.025600    1\n",
            " 0.264520    1\n",
            " 0.056381    1\n",
            "Name: skewness_R, Length: 966, dtype: int64\n",
            "\n",
            "\n",
            "skewness_G :\n",
            " 1.249300    2\n",
            " 0.765130    2\n",
            " 1.248900    2\n",
            "-0.037599    1\n",
            " 1.311800    1\n",
            "-0.019894    1\n",
            " 0.075000    1\n",
            " 0.350020    1\n",
            " 0.052447    1\n",
            "-0.054718    1\n",
            " 0.176560    1\n",
            " 0.309390    1\n",
            " 0.062775    1\n",
            "-0.431650    1\n",
            " 1.482500    1\n",
            " 0.105310    1\n",
            " 1.148000    1\n",
            " 0.068422    1\n",
            " 0.357610    1\n",
            " 0.418710    1\n",
            "-0.027504    1\n",
            " 0.103400    1\n",
            " 0.394180    1\n",
            " 0.119910    1\n",
            " 0.018265    1\n",
            " 0.281710    1\n",
            " 0.039005    1\n",
            " 0.226520    1\n",
            "-0.075956    1\n",
            "-0.090248    1\n",
            "            ..\n",
            " 0.328390    1\n",
            "-0.028036    1\n",
            " 0.130910    1\n",
            "-0.070187    1\n",
            " 0.224070    1\n",
            "-0.571160    1\n",
            "-0.391220    1\n",
            "-0.856130    1\n",
            " 0.479670    1\n",
            "-0.018535    1\n",
            "-0.221950    1\n",
            " 0.049698    1\n",
            " 0.465220    1\n",
            "-0.034016    1\n",
            " 0.102770    1\n",
            " 0.169200    1\n",
            "-0.018904    1\n",
            " 0.231140    1\n",
            " 0.365570    1\n",
            " 0.051356    1\n",
            "-0.062622    1\n",
            " 0.733800    1\n",
            " 0.304270    1\n",
            " 0.016028    1\n",
            "-0.110450    1\n",
            "-0.066518    1\n",
            "-0.377780    1\n",
            " 0.416380    1\n",
            " 0.364870    1\n",
            "-0.684290    1\n",
            "Name: skewness_G, Length: 972, dtype: int64\n",
            "\n",
            "\n",
            "skewness_B :\n",
            "1.98560     2\n",
            "2.70340     2\n",
            "4.04430     2\n",
            "2.82260     2\n",
            "0.68700     2\n",
            "3.08940     2\n",
            "3.56490     2\n",
            "5.13140     1\n",
            "0.81324     1\n",
            "0.10959     1\n",
            "6.80120     1\n",
            "6.80450     1\n",
            "0.62058     1\n",
            "3.11300     1\n",
            "5.53510     1\n",
            "5.39990     1\n",
            "0.68883     1\n",
            "3.66190     1\n",
            "1.16970     1\n",
            "1.51690     1\n",
            "7.51560     1\n",
            "1.30000     1\n",
            "0.42170     1\n",
            "3.78180     1\n",
            "8.87280     1\n",
            "30.51300    1\n",
            "1.20500     1\n",
            "1.25230     1\n",
            "8.13380     1\n",
            "9.86360     1\n",
            "           ..\n",
            "3.30640     1\n",
            "6.13430     1\n",
            "15.62600    1\n",
            "9.27540     1\n",
            "1.73120     1\n",
            "4.54810     1\n",
            "0.85066     1\n",
            "3.50630     1\n",
            "1.33640     1\n",
            "2.95220     1\n",
            "0.81794     1\n",
            "1.27810     1\n",
            "1.51180     1\n",
            "0.30356     1\n",
            "0.27825     1\n",
            "17.01600    1\n",
            "2.24770     1\n",
            "15.92700    1\n",
            "1.77560     1\n",
            "0.99468     1\n",
            "0.26207     1\n",
            "2.84210     1\n",
            "13.17500    1\n",
            "0.79375     1\n",
            "2.91780     1\n",
            "0.29094     1\n",
            "3.50110     1\n",
            "4.18530     1\n",
            "12.86700    1\n",
            "1.93750     1\n",
            "Name: skewness_B, Length: 968, dtype: int64\n",
            "\n",
            "\n",
            "kurtosis_R :\n",
            "7.4050     2\n",
            "4.7342     2\n",
            "10.2680    2\n",
            "8.7216     2\n",
            "6.9479     2\n",
            "5.0510     2\n",
            "5.7451     2\n",
            "5.0095     2\n",
            "5.4281     2\n",
            "4.0637     2\n",
            "4.5460     2\n",
            "5.5156     1\n",
            "4.1601     1\n",
            "8.3438     1\n",
            "5.2262     1\n",
            "4.0209     1\n",
            "4.2876     1\n",
            "4.9880     1\n",
            "6.4624     1\n",
            "5.3814     1\n",
            "5.6795     1\n",
            "3.3223     1\n",
            "4.1623     1\n",
            "4.7181     1\n",
            "4.1146     1\n",
            "3.9696     1\n",
            "4.5738     1\n",
            "3.6506     1\n",
            "6.7780     1\n",
            "6.7625     1\n",
            "          ..\n",
            "4.0670     1\n",
            "4.0618     1\n",
            "6.3843     1\n",
            "5.0888     1\n",
            "5.2695     1\n",
            "8.3079     1\n",
            "4.3894     1\n",
            "8.1242     1\n",
            "3.4889     1\n",
            "4.4575     1\n",
            "5.0437     1\n",
            "4.4239     1\n",
            "4.6562     1\n",
            "5.2513     1\n",
            "5.4688     1\n",
            "4.2002     1\n",
            "11.9500    1\n",
            "5.2373     1\n",
            "3.7766     1\n",
            "3.8511     1\n",
            "6.9706     1\n",
            "4.7794     1\n",
            "5.9703     1\n",
            "6.2374     1\n",
            "5.3454     1\n",
            "4.4652     1\n",
            "6.9181     1\n",
            "5.4774     1\n",
            "8.0863     1\n",
            "3.6875     1\n",
            "Name: kurtosis_R, Length: 964, dtype: int64\n",
            "\n",
            "\n",
            "kurtosis_G :\n",
            "4.1210    2\n",
            "4.5284    2\n",
            "5.8543    2\n",
            "6.7368    2\n",
            "4.4943    2\n",
            "4.3777    2\n",
            "4.2132    2\n",
            "5.3670    2\n",
            "3.4374    2\n",
            "7.1522    2\n",
            "5.5331    2\n",
            "4.0670    2\n",
            "4.3553    2\n",
            "3.0487    2\n",
            "4.6425    2\n",
            "4.1801    2\n",
            "6.2600    2\n",
            "4.5221    2\n",
            "4.4947    2\n",
            "5.8369    1\n",
            "3.7484    1\n",
            "4.2489    1\n",
            "4.5323    1\n",
            "3.7626    1\n",
            "3.5045    1\n",
            "6.3200    1\n",
            "4.1342    1\n",
            "4.9348    1\n",
            "4.6681    1\n",
            "3.5256    1\n",
            "         ..\n",
            "3.1189    1\n",
            "3.8584    1\n",
            "5.1902    1\n",
            "4.8494    1\n",
            "3.2613    1\n",
            "4.9750    1\n",
            "5.0670    1\n",
            "4.0943    1\n",
            "5.5307    1\n",
            "4.1576    1\n",
            "5.7478    1\n",
            "5.9253    1\n",
            "5.9281    1\n",
            "4.7341    1\n",
            "4.6390    1\n",
            "4.6164    1\n",
            "5.5256    1\n",
            "6.4396    1\n",
            "6.2311    1\n",
            "4.0741    1\n",
            "4.5509    1\n",
            "5.6434    1\n",
            "4.3532    1\n",
            "6.7718    1\n",
            "4.9463    1\n",
            "3.8783    1\n",
            "3.8655    1\n",
            "4.6637    1\n",
            "6.3275    1\n",
            "4.2768    1\n",
            "Name: kurtosis_G, Length: 956, dtype: int64\n",
            "\n",
            "\n",
            "kurtosis_B :\n",
            "12.3290     3\n",
            "8.5133      2\n",
            "7.8686      2\n",
            "3.1471      2\n",
            "19.5480     2\n",
            "305.0700    1\n",
            "5.2833      1\n",
            "31.4930     1\n",
            "63.3600     1\n",
            "6.5986      1\n",
            "11.9360     1\n",
            "12.5540     1\n",
            "4.2262      1\n",
            "129.0200    1\n",
            "5.9219      1\n",
            "3.1438      1\n",
            "571.7500    1\n",
            "13.0450     1\n",
            "17.7920     1\n",
            "7.9760      1\n",
            "288.2000    1\n",
            "3.6619      1\n",
            "22.6730     1\n",
            "2.5256      1\n",
            "33.0250     1\n",
            "10.8060     1\n",
            "21.4300     1\n",
            "22.4670     1\n",
            "12.7750     1\n",
            "86.5500     1\n",
            "           ..\n",
            "3.8000      1\n",
            "3.7825      1\n",
            "31.7700     1\n",
            "2.9373      1\n",
            "34.4860     1\n",
            "649.7200    1\n",
            "2.3430      1\n",
            "6.6116      1\n",
            "26.7150     1\n",
            "9.5254      1\n",
            "4.9248      1\n",
            "3.4464      1\n",
            "61.7730     1\n",
            "67.0210     1\n",
            "25.9360     1\n",
            "102.6400    1\n",
            "8.6125      1\n",
            "3.0351      1\n",
            "469.7800    1\n",
            "372.7300    1\n",
            "2.6420      1\n",
            "4.9535      1\n",
            "22.9020     1\n",
            "2.7111      1\n",
            "3.1986      1\n",
            "5.0506      1\n",
            "13.0140     1\n",
            "5.6171      1\n",
            "2.3637      1\n",
            "163.0000    1\n",
            "Name: kurtosis_B, Length: 969, dtype: int64\n",
            "\n",
            "\n",
            "contrast :\n",
            "0.185280    2\n",
            "0.165800    2\n",
            "0.243540    2\n",
            "0.144520    2\n",
            "0.144130    2\n",
            "0.172310    2\n",
            "0.131210    2\n",
            "0.140150    2\n",
            "0.132420    2\n",
            "0.134330    2\n",
            "0.114590    2\n",
            "0.130450    2\n",
            "0.151080    2\n",
            "0.148250    2\n",
            "0.176000    2\n",
            "0.186250    2\n",
            "0.149880    2\n",
            "0.131890    2\n",
            "0.160920    2\n",
            "0.149920    2\n",
            "0.160410    2\n",
            "0.150660    2\n",
            "0.139130    2\n",
            "0.206340    2\n",
            "0.115200    2\n",
            "0.131630    2\n",
            "0.128820    2\n",
            "0.137580    2\n",
            "0.147580    2\n",
            "0.163650    2\n",
            "           ..\n",
            "0.142740    1\n",
            "0.122220    1\n",
            "0.134130    1\n",
            "0.157770    1\n",
            "0.284740    1\n",
            "0.163270    1\n",
            "0.311280    1\n",
            "0.159450    1\n",
            "0.163510    1\n",
            "0.080808    1\n",
            "0.287500    1\n",
            "0.134380    1\n",
            "0.129900    1\n",
            "0.286600    1\n",
            "0.154330    1\n",
            "0.189420    1\n",
            "0.133160    1\n",
            "0.304400    1\n",
            "0.238490    1\n",
            "0.138770    1\n",
            "0.230200    1\n",
            "0.215580    1\n",
            "0.132450    1\n",
            "0.172450    1\n",
            "0.168650    1\n",
            "0.134290    1\n",
            "0.161670    1\n",
            "0.154630    1\n",
            "0.114230    1\n",
            "0.163260    1\n",
            "Name: contrast, Length: 942, dtype: int64\n",
            "\n",
            "\n",
            "correlation :\n",
            "0.98869    6\n",
            "0.98788    5\n",
            "0.98834    4\n",
            "0.98983    4\n",
            "0.98888    4\n",
            "0.98908    4\n",
            "0.98758    4\n",
            "0.98857    4\n",
            "0.98877    4\n",
            "0.99090    4\n",
            "0.98543    4\n",
            "0.98232    4\n",
            "0.98974    4\n",
            "0.99113    4\n",
            "0.98803    3\n",
            "0.98500    3\n",
            "0.98973    3\n",
            "0.99063    3\n",
            "0.98946    3\n",
            "0.98901    3\n",
            "0.99122    3\n",
            "0.99030    3\n",
            "0.98915    3\n",
            "0.98835    3\n",
            "0.98982    3\n",
            "0.98505    3\n",
            "0.98581    3\n",
            "0.99007    3\n",
            "0.98714    3\n",
            "0.98840    3\n",
            "          ..\n",
            "0.99012    1\n",
            "0.98308    1\n",
            "0.98103    1\n",
            "0.99091    1\n",
            "0.99148    1\n",
            "0.99112    1\n",
            "0.97565    1\n",
            "0.98393    1\n",
            "0.98709    1\n",
            "0.98180    1\n",
            "0.99134    1\n",
            "0.98822    1\n",
            "0.98629    1\n",
            "0.98424    1\n",
            "0.98397    1\n",
            "0.98704    1\n",
            "0.98619    1\n",
            "0.98072    1\n",
            "0.98917    1\n",
            "0.97817    1\n",
            "0.98452    1\n",
            "0.98832    1\n",
            "0.98029    1\n",
            "0.97987    1\n",
            "0.98648    1\n",
            "0.98733    1\n",
            "0.98593    1\n",
            "0.99172    1\n",
            "0.98027    1\n",
            "0.98649    1\n",
            "Name: correlation, Length: 683, dtype: int64\n",
            "\n",
            "\n",
            "energy :\n",
            "0.22516    3\n",
            "0.23162    2\n",
            "0.27204    2\n",
            "0.22371    2\n",
            "0.19767    2\n",
            "0.21892    2\n",
            "0.22418    2\n",
            "0.20751    2\n",
            "0.18194    2\n",
            "0.24322    2\n",
            "0.21961    2\n",
            "0.25678    2\n",
            "0.24750    2\n",
            "0.23257    2\n",
            "0.22817    2\n",
            "0.24093    2\n",
            "0.26361    2\n",
            "0.36820    2\n",
            "0.26547    2\n",
            "0.31600    2\n",
            "0.22957    2\n",
            "0.30267    2\n",
            "0.23076    2\n",
            "0.21971    2\n",
            "0.27455    2\n",
            "0.25060    2\n",
            "0.30335    2\n",
            "0.26553    2\n",
            "0.21395    2\n",
            "0.24622    2\n",
            "          ..\n",
            "0.23973    1\n",
            "0.33291    1\n",
            "0.27384    1\n",
            "0.26706    1\n",
            "0.24062    1\n",
            "0.25108    1\n",
            "0.29217    1\n",
            "0.26721    1\n",
            "0.39477    1\n",
            "0.25640    1\n",
            "0.21149    1\n",
            "0.27772    1\n",
            "0.22502    1\n",
            "0.15758    1\n",
            "0.21484    1\n",
            "0.29549    1\n",
            "0.31216    1\n",
            "0.24922    1\n",
            "0.21385    1\n",
            "0.20710    1\n",
            "0.33580    1\n",
            "0.34467    1\n",
            "0.21782    1\n",
            "0.27754    1\n",
            "0.34443    1\n",
            "0.24332    1\n",
            "0.21537    1\n",
            "0.22620    1\n",
            "0.26524    1\n",
            "0.24299    1\n",
            "Name: energy, Length: 941, dtype: int64\n",
            "\n",
            "\n",
            "homogeneity :\n",
            "0.93668    3\n",
            "0.92277    3\n",
            "0.93114    3\n",
            "0.94030    2\n",
            "0.93639    2\n",
            "0.94413    2\n",
            "0.93242    2\n",
            "0.93667    2\n",
            "0.92931    2\n",
            "0.94182    2\n",
            "0.93241    2\n",
            "0.91564    2\n",
            "0.93102    2\n",
            "0.92099    2\n",
            "0.93264    2\n",
            "0.93672    2\n",
            "0.91988    2\n",
            "0.93751    2\n",
            "0.93442    2\n",
            "0.91156    2\n",
            "0.90194    2\n",
            "0.92497    2\n",
            "0.93554    2\n",
            "0.94119    2\n",
            "0.94248    2\n",
            "0.90395    2\n",
            "0.93761    2\n",
            "0.91664    2\n",
            "0.91721    2\n",
            "0.94055    2\n",
            "          ..\n",
            "0.92555    1\n",
            "0.94188    1\n",
            "0.88920    1\n",
            "0.92784    1\n",
            "0.91651    1\n",
            "0.87213    1\n",
            "0.92611    1\n",
            "0.90631    1\n",
            "0.93315    1\n",
            "0.91814    1\n",
            "0.91566    1\n",
            "0.91905    1\n",
            "0.91727    1\n",
            "0.90359    1\n",
            "0.89319    1\n",
            "0.88212    1\n",
            "0.93942    1\n",
            "0.91194    1\n",
            "0.88268    1\n",
            "0.93889    1\n",
            "0.93093    1\n",
            "0.92124    1\n",
            "0.89883    1\n",
            "0.91485    1\n",
            "0.89484    1\n",
            "0.94433    1\n",
            "0.90770    1\n",
            "0.94244    1\n",
            "0.92397    1\n",
            "0.94071    1\n",
            "Name: homogeneity, Length: 909, dtype: int64\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "6b84_6u-Px9X",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Drop Feature"
      ]
    },
    {
      "metadata": {
        "id": "6adgaONGP2Vv",
        "colab_type": "code",
        "outputId": "4d7c649f-f11a-4a8b-e6f4-fedc67c5340c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 134
        }
      },
      "cell_type": "code",
      "source": [
        "feature_drop = ['hu_4', 'hu_5', 'hu_6', 'hu7']\n",
        "data = data.drop(columns=feature_drop)\n",
        "data.columns"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['roundness', 'perimeter_ratio_to_diameter', 'compactness',\n",
              "       'eccentricity', 'aspect_ratio', 'rectangularity', 'narrow_factor',\n",
              "       'perimeter_ratio_major_minor', 'hu_1', 'hu_2', 'hu_3', 'mean_R',\n",
              "       'mean_G', 'mean_B', 'std_R', 'std_G', 'std_B', 'skewness_R',\n",
              "       'skewness_G', 'skewness_B', 'kurtosis_R', 'kurtosis_G', 'kurtosis_B',\n",
              "       'contrast', 'correlation', 'energy', 'homogeneity'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 727
        }
      ]
    },
    {
      "metadata": {
        "id": "UrVG8KiNCr1e",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Normalization"
      ]
    },
    {
      "metadata": {
        "id": "2Xi_wFuNCoqy",
        "colab_type": "code",
        "outputId": "4912e304-c60b-402b-aa45-0ab5040a1f40",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1171
        }
      },
      "cell_type": "code",
      "source": [
        "# # Min-Max Normalization\n",
        "# # Min-Max = (x-min) / (max-min)\n",
        "# mms = MinMaxScaler()\n",
        "# result = mms.fit_transform(data)\n",
        "# data = pd.DataFrame(data=result, columns=data.columns)\n",
        "# data.hist(figsize=(20,20));\n",
        "\n",
        "# # Standard Normalization (Z-Score)\n",
        "# # Z = (x-mean) / (standard deviation)\n",
        "# ss = StandardScaler()\n",
        "# result = ss.fit_transform(data)\n",
        "# data = pd.DataFrame(data=result, columns=data.columns)\n",
        "# data.hist(figsize=(20,20));\n",
        "\n",
        "# Power Transform\n",
        "pt = PowerTransformer()\n",
        "result = pt.fit_transform(data)\n",
        "data = pd.DataFrame(data=result, columns=data.columns)\n",
        "data.hist(figsize=(20,20));"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Ok7x947Jt5mljXD6vcYmzanxiHYc4l5OnXmImSdIqqKqbqury9vFdwDXAPksssgE4p6p+\nWFXfADYDTx98pJIkSZpGI3GJmSRJ0yTJGuDJwOeAZwHHJnk58EVgY1XdTlN5dGnHYjeyQIVSkqOB\nowFmZmaYnZ0FYNu2bfc8nhSTtk2Ttj0wmdskSdK0sIJIkqRVlGQ34DzgDVV1Z5L3AW+l6ZforcBJ\nwCu7XV9VnQqcCrBu3bpav349ALOzs8w9nhSTtk2Ttj0wmdskSdK08BIzSZJWSZKdaSqHzq6qjwBU\n1S1VdXdV/Rh4P/deRrYV2Ldj8Ue3ZZIkSVLfWUEkSdIqSBLgNOCaqnpXR/leHbO9CLiqfXw+8JIk\nD07yWGA/4POrFa8kSZKmi5eYaVnWHHdBT8tv2XRonyKRBsPvuAboWcDLgCuTXNGWnQC8NMkBNJeY\nbQFeA1BVVyc5F/gKsB04pqruXvWodT+9/k6AvxXSjnSTZxvXbufIReYzxyR1o9d9+hkHjfYQ98tl\nBZEkSaugqj4DZIFJFy6xzNuAtw0sKEmSJKnlJWaSJEmSJElTzgoiSZIkSZKkKWcFkSRJkiRpLCTZ\nN8klSb6S5Ookr2/L90hyUZJr2/tHtOVJ8p4km5N8OclThrsF0uiygkiSJEmSNC62Axuran/gmcAx\nSfYHjgMurqr9gIvb5wAH04wEuh9wNPC+1Q9ZGg9WEEkTIMnpSW5NclVH2YlJtia5or0d0jHt+PYs\nyteSPH84UUuSJEnLU1U3VdXl7eO7gGuAfYANwJntbGcCL2wfbwDOqsalwO5J9lrlsKWx4Chm0mQ4\nAzgFOGte+bur6k87C9ozLC8BngDsDXwqyc84fLYkSZLGSZI1wJOBzwEzVXVTO+lmYKZ9vA9wQ8di\nN7ZlN3WUkeRomhZGzMzMMDs723Uc27ZtW9b8wzIuccLqxbpx7faelh+n97QbVhBJE6CqPt3uILux\nATinqn4IfCPJZuDpwGcHFJ4kSZLUV0l2A84D3lBVdya5Z1pVVZJazvqq6lTgVIB169bV+vXru152\ndnaW5cw/LOMSJ6xerEced0FPy59x0K5j8552w0vMpMl2bNsZ3+lzHfWx+FkUSZIkaeQl2Zmmcujs\nqvpIW3zL3KVj7f2tbflWYN+OxR/dlkmaxxZE0uR6H/BWoNr7k4BXLmcFvTS17TSKTS8Xi6nXZqa9\nbOc4vU/DNIoxSZKk1ZGmqdBpwDVV9a6OSecDRwCb2vuPdZQfm+Qc4BnAHR2XoknqYAWRNKGq6pa5\nx0neD3y8fdr1WZRemtp2GsXmrIvF1Gsz0y2H33+d3Rqn92mYRjEmSdJoWdPj/hxgy6ZD+xCJBuBZ\nwMuAK5Nc0ZadQFMxdG6So4DrgcPaaRcChwCbgR8Ar1jdcKXxscMKoiSnAy8Abq2qJ7ZlJwKvBr7d\nznZCVV3YTjseOAq4G3hdVX1iAHFL2oEke3WcHXkRMDfC2fnAB5O8i6aT6v2Azw8hREmaWmuOu4CN\na7evuFLaP66SplVVfQbIIpMPXGD+Ao4ZaFDShOimD6IzgIMWKH93VR3Q3uYqhzpHRzoIeG+SnfoV\nrKSFJfkQTSfTP5vkxvbMyTuTXJnky8Czgd8FqKqrgXOBrwD/ABzjCGaSJEGSfZNckuQrSa5O8vq2\nfI8kFyW5tr1/RFueJO9Jsrnt8+8pw90CSZJWboctiBwdSRp9VfXSBYpPW2L+twFvG1xEkiSNpe3A\nxqq6PMlDgcuSXAQcCVxcVZuSHAccB7wZOJimJe5+NH2bvK+9lyRp7PQyipmjI0mSJGliVNVNVXV5\n+/gu4BqaY9kNwJntbGcCL2wfbwDOqsalwO5zoyhJkjRuVtpJ9ciMjjQo4zRKzmrG2o8RnnxvJUnS\nqGtb0D8Z+Bww09Gv383ATPt4sZOj9xkhaVjHveN8HNPNMefMLr0fmy5lmO/dOH92ksbXiiqIRml0\npEEZp1FyVjPWfozw5HsrSZJGWZLdgPOAN1TVnc2o2o2qqiS1nPUN67h3nI9jujnm3Lh2OyddObhB\nmXsZmbRX4/zZSRpfK7rEbF7T2fmjI70kyYOTPBZHR5IkSdIYSbIzTeXQ2VX1kbb4lrnj3/b+1ra8\n65OjkiSNuh1WEDk6kiRJkqZBmqZCpwHXVNW7OiadDxzRPj4C+FhH+cvb0cyeCdzRcSmaJEljpZtR\nzBwdSZIkSdPgWcDLgCuTXNGWnQBsAs5tT5ReDxzWTrsQOATYDPwAeMXqhitJUv8M7qJdSZJ0jyT7\nAmfRdG5bwKlVdXKSPYAPA2uALcBhVXV725LhZJo/nz8AjpwbXUnSYFTVZ4AsMvnABeYv4JiBBiVJ\n0irpZZh7SZLUve3AxqraH3gmcEyS/YHjgIuraj/g4vY5wME0ffntRzP60ftWP2RJkiRNCyuIJEla\nBVV101wLoKq6C7iGZjjsDcCZ7WxnAi9sH28AzqrGpcDu8waJkCRJkvrGS8wkTYw1XQyJO2fj2u1d\nDaErDUKSNcCTgc8BMx2d2t5McwkaNJVHN3QsdmNbdp8OcJMcTdPCiJmZGWZnZwHYtm3bPY8nxahs\n08a12/uynpldVr6uUXgfFjIqn5EkSVo+K4gkSVpFSXajGUL7DVV1Z9PVUKOqKkktZ31VdSpwKsC6\ndetq/fr1QFOBMPd4UozKNvWrcnnj2u2cdOXKDsW2HL6+LzH026h8RpIkafmsIJoiy2ldIUnqvyQ7\n01QOnV1VH2mLb0myV1Xd1F5CdmtbvhXYt2PxR7dlkiRJUt/ZB5EkSaugHZXsNOCaqnpXx6TzgSPa\nx0cAH+sof3kazwTu6LgUTZIkSeorK4ikCZDk9CS3Jrmqo+xPknw1yZeTfDTJ7m35miT/muSK9vYX\nw4tcmirPAl4GPKcj/w4BNgHPS3It8Nz2OcCFwHXAZuD9wO8MIWZJkiRNCS8xkybDGcApwFkdZRcB\nx1fV9iTvAI4H3txO+3pVHbC6IUrTrao+A2SRyQcuMH8Bxww0KEmSJKllBZE0Aarq0+2oSJ1ln+x4\neinwG6sZk1amH32Fbdl0aB8ikSRJkjRNrCCSpsMrgQ93PH9skv8D3An8QVX980ILLTZ89nKt1rDH\nyxkuupfhpZfSy3Zu27aNjWvvHmoM843ikNWjGJMkSZI07qwgkiZckrcA24Gz26KbgJ+qqtuSPBX4\nuyRPqKo75y+72PDZy7Vawx4vZ+jpXoaXXkovQ0/Pzs5y0me+P9QY5hvFIatHMSZJkiRp3NlJtTTB\nkhwJvAA4vO3PhKr6YVXd1j6+DPg68DNDC1KSJEmSNHS2IJImVJKDgDcBv1JVP+gofxTw3aq6O8nj\ngP1oRkrShOi1HyP7MJIkSZKmjxVE0gRI8iFgPbBnkhuBP6QZtezBwEVJAC6tqtcC/y/wR0l+BPwY\neG1VfXcogUuSJEmSRsLYVBB5RlxaXFW9dIHi0xaZ9zzgvMFGNL16+a1qOs0em59lSZKkVZfkdJou\nFG6tqie2ZScCrwa+3c52QlVd2E47HjgKuBt4XVV9YtWDlsaEfRBJkiRJksbFGcBBC5S/u6oOaG9z\nlUP7Ay8BntAu894kO61apNKYsYJIkiRJkjQWqurTQLfdI2wAzmkHafkGsBl4+sCCk8acFUSSJEmS\npHF3bJIvJzk9ySPasn2AGzrmubEtk7QAO7uQJElTpdd+DSVJI+d9wFuBau9PAl65nBUkORo4GmBm\nZobZ2dmul922bduy5h+WcYkTVi/Wpg/QlRun97QbVhBJkiRJksZWVd0y9zjJ+4GPt0+3Avt2zPro\ntmyhdZwKnAqwbt26Wr9+fdevPzs7y3LmH5ZxiRNWL9YjezxpdMZBu47Ne9oNLzGTJEmSJI2tJHt1\nPH0RcFX7+HzgJUkenOSxwH7A51c7PmlcWEEkSZIk0QyfneTWJFd1lJ2YZGuSK9rbIR3Tjk+yOcnX\nkjx/OFFL0yXJh4DPAj+b5MYkRwHvTHJlki8DzwZ+F6CqrgbOBb4C/ANwTFXdPaTQpZHnJWZjZLE+\nEzau3d5z0zhJkiRxBnAKcNa88ndX1Z92FswbPntv4FNJfsY/n9JgVdVLFyg+bYn53wa8bXARSZNj\naiqIltsh5fxKly2bDu13SJIkSRohVfXpJGu6nP2e4bOBbySZGz77swMKT5KkgZqaCiJJkiRphY5N\n8nLgi8DGqrqdZqjsSzvmWXT47F5GR+rFMEfXuXLrHT0tv3HtjueZ2aX3EYiWMsyRiSZtZCRJ48EK\nIkmSJGlxPQ+f3cvoSL0Y5ohFq9H9wca12znpysH9ndly+PqBrXtHxmm0KUmTw06qJUmSpEVU1S1V\ndXdV/Rh4P81lZLCM4bMlSRoHVhBJE2KRkVf2SHJRkmvb+0e05UnynnbklS8necrwIpemg6MjSePJ\n4bMlSdPCCiJpcpwBHDSv7Djg4qraD7i4fQ5wMM2B7H40fSK8b5VilKbZGdw/R6EZHemA9nYh3G90\npIOA9ybZadUilaaUw2dLkqaZfRBJE2KRkVc2AOvbx2cCs8Cb2/KzqqqAS5PsnmSvqrppdaLVKOsc\n9XH+iI7dcNTHhTk6kjT6HD5bkjTNrCCSJttMR6XPzcBM+3gf4IaO+eZGXrlPBVG/Rl1ZrZE4ljOS\nyaBHPlmJSYlp0J/1BI7s0tPoSJIkSVI/dFVBlOR04AXArVX1xLZsD+DDwBpgC3BYVd2eJMDJwCHA\nD4Ajq+ry/ocuaTmqqpLUMpfpy6grqzUSx3Jaugx65JOVmJSYBj3qy4SN7NLz6EiLVeROYEVa37Zp\nVCpie6kUHtXPdhK/d5IkTYtuj/rPAE4Bzuoom+vbZFOS49rnb+a+fZs8g+bg9xn9CljSstwyd+lY\n28nmrW25I69II6Cqbpl7nOT9wMfbp13n6GIVuRNWkQb0b5tWY/jtbvRSKTzM4beXMonfO0mSpkVX\nRyX2bSKNrfOBI4BN7f3HOsqPTXIOTQXuHeao+mVNH/58T0s/RvP2j/NHR/pgkncBe+PoSJIkSffT\nj+NO3auXaxlWtW+T1W4OPr/Z9yg0l17sPRjFfksWMzs7O1bNz8cp1nbklfXAnkluBP6QpmLo3HYU\nluuBw9rZL6S5DHQzzaWgr1j1gKUps0iOrk9yAM0lZluA10AzOlKSudGRtuPoSJIkSRqwvnR2sRp9\nm6x2c/D5zb5HoSn3Yu/BKPZbspgth68fq+bn4xTrIiOvABy4wLwFHDPYiCR1cnQkSZIkjbJeahWm\nqm8TL5mQJEmSpkevx/8e+0saNw/oYdm5vk3g/n2bvDyNZ2LfJpIkSZIkSSOt22Hu7dtEkiRJkiRp\nQnU7ipl9m0iSJEmSJE2oXi4xkyRJkiRJ0gSwgkiSJEmSJGnKjcfY6BOiHyOhSZIkSZI07pb6f7xx\n7XaO9P/zqrMFkSRJkiRJ0pSzgkiSJEmSJGnKWUEkSZIkSZI05awgkiRJkiRJmnJWEEmSJEmSxkaS\n05PcmuSqjrI9klyU5Nr2/hFteZK8J8nmJF9O8pThRS6NNkcxkyZYkp8FPtxR9DjgvwG7A68Gvt2W\nn1BVF65yeJIkSdJKnAGcApzVUXYccHFVbUpyXPv8zcDBwH7t7RnA+9r7oep1hOstmw7tUyTSvawg\nkiZYVX0NOAAgyU7AVuCjwCuAd1fVnw4xPEmSNIJ6/eMqDVpVfTrJmnnFG4D17eMzgVmaCqINwFlV\nVcClSXZPsldV3bQ60UrjwwoiaXocCHy9qq5PMuxYJEk98MyzJN3PTEelz83ATPt4H+CGjvlubMvu\nU0GU5GjgaICZmRlmZ2e7fuFt27Yta36AjWu3L2v++Zb7erCyOAdpqfdgZpfe36PVMGrvaa+sIJKm\nx0uAD3U8PzbJy4EvAhur6vbhhCVJ0uhIcjrwAuDWqnpiW7YHzSXba4AtwGFVdXuaMy4nA4cAPwCO\nrKrLhxG3pHtVVSWpZS5zKnAqwLp162r9+vVdLzs7O8ty5gc4steK/sOX93qwsjgHaan3YOPa7Zx0\n5ehXV5xx0K4j9Z72avTfcUk9S/Ig4NeB49ui9wFvBaq9Pwl45QLLrfhMSqfVqllfzlmGUTwrYUz3\nWur7MmlnaiSNnDMY875NpCl1y9ylY0n2Am5ty7cC+3bM9+i2TNI8VhBJ0+Fg4PKqugVg7h4gyfuB\njy+0UC9nUjp1e7ai9z4Puv9JG8WzEsZ0r6XOio3a2S9Jk8W+TaSxdT5wBLCpvf9YR/mxSc6hqcC9\nwxztD/srmzwOcy9Nh5fScXlA4feSAAAgAElEQVRZe1ZlzouAq+63hCRJmrPcvk0kDVCSDwGfBX42\nyY1JjqKpGHpekmuB57bPAS4ErgM2A+8HfmcIIUtjYbROVUurYDk13RvXbr/ftbHj1rFnkl2B5wGv\n6Sh+Z5IDaC4x2zJvmiRJWsRK+jbp1yXby7XSS3JH7XLnxYzipdmdevmcvZx6aVX10kUmHbjAvAUc\nM9iIpMlgBZE04arq+8Aj55W9bEjhSFPNzm81KvpxWcC4nTDpUU99m/Trku3lWuklub12nrtaRvHS\n7E4r6UR4jpdTSxoGLzGTJGn1nAEcNK9srvPb/YCL2+dw385vj6bp/FbScMz1bQL379vk5Wk8E/s2\nkSSNMSuIJElaJVX1aeC784o30HR6S3v/wo7ys6pxKbD7vP7DJA2AfZtIkqbV6LbJlCRpOiy389v7\ntE5YrG+TSey/ol/bNCp9lox6/yk7stBnMQnfO/s2kSRNKyuIJEkaESvp/Haxvk0msf+Kfm3TqPSv\nMur9p+zIQv2rTOL3TpJG0Ur6kps/AM+U9SWnLniJmSRJw3XL3KVjK+n8VpIkSeoHK4gkSRouO7+V\nJEnS0I1vu2ZJksZM2/ntemDPJDcCf0jT2e25bUe41wOHtbNfSDPE/WaaYe5fseoBS5KkibWSy9Q0\n2awgkiRpldj5rSRJkkaVl5hJkiRJkiRNOSuIJEmSJEmSppyXmEmSJEmSJA1Br31Bbdl0aJ8isQWR\nJEmSJEnS1LOCSJIkSZIkacp5iZk0BZJsAe4C7ga2V9W6JHsAHwbWAFuAw6rq9mHFKEmS+mPucoWN\na7dzpMNYS5K6ZAsiaXo8u6oOqKp17fPjgIuraj/g4va5JEmSJGkK9VxBlGRLkiuTXJHki23ZHkku\nSnJte/+I3kOV1GcbgDPbx2cCLxxiLJIkSZKkIerXJWbPrqrvdDyfa5mwKclx7fM39+m1JC1fAZ9M\nUsBfVtWpwExV3dROvxmYmb9QkqOBowFmZmaYnZ1d0Ytv27atq2U3rt2+ovWvxMwuq/t63TCmey31\nfen2+yRJkiSpe4Pqg2gDsL59fCYwixVE0jD9UlVtTfITwEVJvto5saqqrTxiXvmpwKkA69atq/Xr\n16/oxWdnZ+lm2dXsJ2Hj2u2cdOVodcNmTPfacvj6Rad1+32SJEmS1L1+HPWvSsuE1T6DPYpn8hcz\nTrHOzs4O/ez/ct6rhd7bcWy5UFVb2/tbk3wUeDpwS5K9quqmJHsBtw41SEmSJEnS0PSjgmhVWias\n9ggMo3gmfzHjFOuWw9cP/ez/cr5LC723S7VsGEVJdgUeUFV3tY9/Ffgj4HzgCGBTe/+x4UUpSZIk\nSRqmnmsVbJmg5Vhz3AU9Dbm6ZdOhfY5oKswAH00CTc5/sKr+IckXgHOTHAVcDxw2xBglSZIkSUPU\nUwWRLROk0VdV1wFPWqD8NuDA1Y9IkiRJkjRqem1BZMsESZIkSZKkMddTBZEtEyRJkiRJoyLJFuAu\n4G5ge1WtS7IH8GFgDbAFOKyqbh9WjNKoesCwA5AkSZIkqY+eXVUHVNW69vlxwMVVtR9wcftc0jxW\nEEmSJEldSLIlyZVJrkjyxbZsjyQXJbm2vX/EsOOUdD8bgDPbx2cCLxxiLNLIGo+x0SVJkqTR8Oyq\n+k7H87mWCZuSHNc+f/NwQpMEFPDJJAX8ZVWdCsxU1U3t9Jtp+tK9jyRHA0cDzMzMMDs72/ULbtu2\nbVnzA2xcu31Z8/fDzC7Ded2VGJdYV/LZz9frdvb6+p2sIJIkaQTYZ4I0tjYA69vHZwKzWEEkDdMv\nVdXWJD8BXJTkq50Tq6rayiPmlZ8KnAqwbt26Wr9+fdcvODs7y3LmBzjyuAuWNX8/bFy7nZOuHI8q\ngHGJ9YyDdl32Zz9fr9+FLYf39vqdRv8dlyRpetgyQRptq94yYSXmzkaPyxn4lRr17evlc+5Hq4Rp\nVVVb2/tbk3wUeDpwS5K9quqmJHsBtw41SGlEWUEkSdLosmWCNFpWvWXCSsydjR6XM/ArNerb18tZ\n/ZW0SBEk2RV4QFXd1T7+VeCPgPOBI4BN7f3HhhelNLpG9xdVkqTp0teWCZN49nlum67cekdP69m4\ntk8B9WjUWz/syELfr0n83nWyZYI08maAjyaB5r/uB6vqH5J8ATg3yVHA9cBhQ4xRGllWEEmSNBr6\n2jJhEs8+z23TMPptGIRRb/2wIwu1jpjE790cWyZoudb08Fu1ce32e5qPqntVdR3wpAXKbwMOXP2I\nNOmu3HrHxByXgBVEkiSNBFsmSCPPlgmSpIlmBZEkSUNmywRp9NkyQVKnzhZiG9dun6hWJJpeDxh2\nAJIGJ8m+SS5J8pUkVyd5fVt+YpKtSa5ob4cMO1Zpys0An0nyJeDzwAVV9Q80FUPPS3It8Nz2uSRJ\nktR3tiCSJtt2YGNVXZ7kocBlSS5qp727qv50iLFJatkyQZIkScNmBZE0wdrRj25qH9+V5Bpgn+FG\nJUmaBAt1wLucyyy2bDq03yFJkqQeWEEkTYkka4AnA58DngUcm+TlwBdpWhndvsAyCw6fvZjFhp6e\n2QX+x9k77jplNYeeHsXhpY3pXkt91yZ9GG1JkiRpGKwgkqZAkt2A84A3VNWdSd4HvBWo9v4k4JXz\nl1ts+OzFLHbWeBSHcjam7gwrpoWGz54zycNoS5IkScNiJ9XShEuyM03l0NlV9RGAqrqlqu6uqh8D\n76cZTluSJEmSNKWsIJImWJIApwHXVNW7Osr36pjtRcBVqx2bJEmSJGl0jNa1DJL67VnAy4Ark1zR\nlp0AvDTJATSXmG0BXjOc8CRJkiRJo8AKImmCVdVngCww6cLVjkWSJEmSNLq8xEySJEmSJGnK2YJI\nkjRy1iwyIh40I6stNmLenC2bDu13SJIkSdJEswWRJEmSJEnSlLOCSJIkSZIkacpZQSRJkiRJkjTl\nrCCSJEmSJEmacnZSLUmSVs1SHZDvSDcdlEvSpOjl93KOgzZIWg5bEEmSJEmSJE05WxBJkiRJI6Qf\nLUckSVouWxBJkiRJkiRNOSuIJEmSJEmSppwVRJIkSZIkSVNuYH0QJTkIOBnYCfirqto0qNeStDLm\nqTT6Ri1P7RtFur9Ry1NJ92eeSjs2kBZESXYC/hw4GNgfeGmS/QfxWpJWxjyVRp95Ko0+81Qafeap\n1J1BtSB6OrC5qq4DSHIOsAH4yoBeT1PCM9d9ZZ5Ko888lUafeSqNPvNU6sKgKoj2AW7oeH4j8IwB\nvZaklTFPpdHX9zy1ol3qO/enGlm9/uZv2XRonyIZOvNU6sLA+iDakSRHA0e3T7cl+dqwYlnI62BP\n4DvDjqMb4xQrjFe8C8Wad+xwsccMKp7V1q88HcXP3Ji6M64xmafACH52vRrF72MvJm17YHnbZJ4O\n3iR+xzpN8vaNyraZp90Zlc9rR8YlThifWEchzn7m6aAqiLYC+3Y8f3Rbdo+qOhU4dUCv37MkX6yq\ndcOOoxvjFCuMV7zjFOsKrFqejuL7aEzdMaahW3GeTuL7NGnbNGnbA5O5TV0Y2ePeSf88Jnn7Jnnb\nhmSgeToun9e4xAnjE+u4xNmtQQ1z/wVgvySPTfIg4CXA+QN6LUkrY55Ko888lUafeSqNPvNU6sJA\nWhBV1fYkxwKfoBlG8PSqunoQryVpZcxTafSZp9LoM0+l0WeeSt0ZWB9EVXUhcOGg1r8KRvbytwWM\nU6wwXvGOU6zLtop5OorvozF1x5iGrIc8ncT3adK2adK2ByZzm3ZohI97J/3zmOTtm+RtG4oB5+m4\nfF7jEieMT6zjEmdXUlXDjkGSJEmSJElDNKg+iCRJkiRJkjQmrCBaRJIXJ7k6yY+TjGyv5EkOSvK1\nJJuTHDfseJaS5PQktya5atix7EiSfZNckuQr7ffg9cOOadwl+ZMkX03y5SQfTbL7CMQ0Enk+ink8\navlqTvYmycYklWTPYcfSi1H8HVmpUcz7lTI/R9sk5c2cScqf+cyn8TUuuTYqx7+LGZf8HrVj5X6x\ngmhxVwH/Efj0sANZTJKdgD8HDgb2B16aZP/hRrWkM4CDhh1El7YDG6tqf+CZwDEj/t6Og4uAJ1bV\nLwD/Fzh+yPHACOT5COfxGYxWvpqTK5RkX+BXgW8OO5Y+GMXfkWUb4bxfKfNztE1E3syZwPyZz3wa\nX+OSa0M//l3MmOX3GYzWsXJfWEG0iKq6pqq+Nuw4duDpwOaquq6q/h04B9gw5JgWVVWfBr477Di6\nUVU3VdXl7eO7gGuAfYYb1Xirqk9W1fb26aXAo4cZD4xMno9kHo9avpqTPXk38CZg7DsdHMXfkRUa\nybxfKfNztE1Q3syZqPyZz3waX+OSayNy/LuYscnvUTtW7hcriMbbPsANHc9vxB1I3yVZAzwZ+Nxw\nI5korwT+fthBjAjzeJnMye4l2QBsraovDTuWARjn35GJzXvzc+SNc97Mmdj8mc98GmuTkGvDMDX5\nPaoGNsz9OEjyKeAnF5j0lqr62GrHo9GTZDfgPOANVXXnsOMZdd3kVJK30DSfPntUYtL4MCfvb6nv\nOHACzeVlY2MUf0fUHfNzeMybyWM+jaZxyTWPf7VSU11BVFXPHXYMPdoK7Nvx/NFtmfogyc40O+az\nq+ojw45nHOwop5IcCbwAOLCqVuVylzHIc/O4S+bkwhb7jidZCzwW+FISaL5blyd5elXdvIohLsso\n/o4MwMTlvfk5XFOSN3MmLn/mM59G17jk2hgc/y5m4vN71HmJ2Xj7ArBfkscmeRDwEuD8Icc0EdL8\nmzoNuKaq3jXseCZBkoNo+kH59ar6wbDjGSHmcRfMyeWrqiur6ieqak1VraFppv2UUa4c2pEJ+h2Z\nqLw3P0fbBOXNnInKn/nMp/E1gbk2DBOd3+PACqJFJHlRkhuBXwQuSPKJYcc0X9sJ2rHAJ2g6sDu3\nqq4eblSLS/Ih4LPAzya5MclRw45pCc8CXgY8J8kV7e2QYQc15k4BHgpc1L6ffzHsgEYhz0c1j0cw\nX81JwQj+jqzEqOZ9D8zP0TYReTNnAvNnPvNpfI1Fro3C8e9ixim/R/BYuS8y/q1MJUmSJEmS1Atb\nEEmSJEmSJE05K4gkSZIkSZKmnBVEkiRJkiRJU84KIkmSJEmSpClnBZEkSZIkSdKUs4JIkiRJkiRp\nyllBJEmSJEmSNOWsIJIkSZIkSZpyVhBJkiRJkiRNOSuIJEmSJEmSppwVRJIkSZIkSVPOCiJJkiRJ\nkqQpZwWRpKmUZEuS5w47jmFIsi3J44YdhyRJkqTRYQWRJE2Zqtqtqq4DSHJGkv9v2DFJwzLNlcXS\nuDBPpdFnnk4GK4hEkgcOOwZJkiZBkmcnuSTJHUm2DDseSfeX5I1JrkpyV5JvJHnjsGOSdF9JfjfJ\ndUnuTPKtJO/2f+vgWUE04pLsneS8JN9ud2Cva8tPTHJukrPandvVSdbtaLmOZf82yQeS3AkcmWSX\nJGcmuT3JNUnelOTGdv43JjlvXlzvSXLyKr0N0qAckOTL7R+5Dyd5CECSVyfZnOS7Sc5PsvfcAkkq\nye8kubbNvbcm+ekk/9LuwM5N8qCO+Zda168m+Vr7+u9N8k9JXtUx/ZVtPt6e5BNJHjMvjte2cXwv\nyZ8nyTKWfXySo4HDgTe1l539L/Nd6tn3gdMB/3BKoyvAy4FHAAcBxyZ5yXBDkjTP+cBTquphwBOB\nJwGvW3oR9coKohGW5AHA/wK+BOwDHAi8Icnz21l+HTgH2J0mgU7pcjmADcDftsueDfwhsAZ4HPA8\n4Lc75v0AcFCS3dv1PxB4CXBWXzdYWn2H0RwYPhb4BZrK0ucAb2+n7QVcT5NnnZ4PPBV4JvAm4FSa\nnNmXZgf2UoCl1pVkT5ocPB54JPA14D/MvUCSDcAJwH8EHgX8M/CheXG8AHhaG/thbVzdLktVnUqT\n/+9sLzv7Ncx3Taf7VRYnOTLJZzpnmqtcXWpFVfX5qvpr4LqBRixNn37m6Tur6vKq2l5VXwM+Bjxr\nkMFLU6Kfefr1qvre3CLAj4Ell1HvrCAabU8DHlVVf1RV/972GfJ+mj9rAJ+pqgur6m7gr2lqVbtZ\nDuCzVfV3VfXjqvpXmj+Xf1xVt1fVjcB75masqpuATwMvbosOAr5TVZcNZrOlVfOeqvpWVX2XplL1\nAJoWNae3B44/pKnA+cUkazqWe2dV3VlVVwNXAZ+squuq6g7g74Ent/Mtta5DgKur6iNVtZ0m527u\neI3XAm+vqmva6X9Ms9N9TMc8m6rqe1X1TeCSNv5ul12Q+a4pdb/K4qFGI2khA8nTtvXtLwNX92N9\n0pTra54m+a32ipfv0PzX/cteA9TSrCAabY8B9m4vH/leku/RtAqYaad3/pn8AfCQ9mz/jpYDuGHe\na+09r2z+9DO5t1XRb9NUSEnjbn4O7UaTC9fPFVbVNuA2mtZ4c27pePyvCzzfrX281Lruk3NVVcCN\nHet5DHByRw5/l+bsSWccC8Xf7bJLMd81bRaqLJY0WgaVpyfS/Cf6n31anzTN+pqnVfXB9hKznwH+\ngvsec2sArCAabTcA36iq3TtuD62qQ/qwXM1b5ibg0R3P9503/e+AX0jyRJrLWs5ewfZI4+BbNBUs\nACTZleYSsK19Xtd9cq49g9mZgzcAr5mXx7tU1b908brLWXb+bwGY75o+i1W2Shodfc/TJMfS9EV0\naNvSV1JvBrI/rapraVr5vbcf69PirCAabZ8H7kry5jSdSO+U5IlJnjaA5c4Fjk/yiCT7AMd2Tqyq\nf6PpL+WDwOfbS1qkSfQh4BVJDkjyYJrLsz5XVVv6vK4LgLVJXti2/DsG+MmOZf+CJiefAJDk4Ule\nTHeWs+wtNH2P3cN8l4Cms+n/Z+5Jkp9cYl5Jw7HiPE3ySuA44MC2ewVJg9Gv/ekDgZ/uS0RalBVE\nI6ztW+gFNE3zvkFz7eVfAQ8fwHJ/RHN5yzeAT9H8OZx/JuVMYC1ebqIJVlWfAv4rcB5NK5+f5r79\nd/VlXVX1HZp+ft5Jc9nZ/sAXafOuqj4KvAM4p732+irg4C5fdznLngbs316O9ncd5ea7pt2XgCe0\nFbwPobkMZYeSPKCdf+fmaR6SjpENJfXVSvP0cJqTNs9r++qUNDgrzdNXJfmJ9vH+NH15XjywKAVA\nmm4vpPtK8p+Bl1TVr3SU/RTwVeAnq+rOoQUnTaB29MEbgcOr6pIRiMd811RIsgV4VVuhS5ITgcdX\n1W8neQvwuzR9ix1PU2G6X1VtXmJ962k6je/0T1W1vu/BS1NiAHn6DZrLujtPhn6gql47mC2QJt8A\n8vR/0gzqshvwbeBvgP/atnTXgFhBJACS7EVzmclngf1oLn85par+rJ3+AOBdwMOq6pVDC1SaIEme\nD3yOZmf5RprLzB7Xjiw4zLjMd0mSJGnKPHDYAWhkPIhm2MDHAt8DzqHtBKztWPcWmtGYDhpWgNIE\n+kWafn4eBHwFeOEIVA6Z75IkSdIUsgWRJEnSMiS5mo4RCju8pqoc9U8aAeapNPrM09FjBZEkSasg\nyb7AWcAMUMCpVXVykj2ADwNrgC3AYVV1e5IAJ9Ncf/8D4MiqunwYsUuSJGnyjUQF0Z577llr1qwZ\ndhhL+v73v8+uu+467DAGZpK3b7W37bLLLvtOVT1q1V5wlfQ7Tyf1O+d2jYdh5Gnb19teVXV5kocC\nlwEvBI4EvltVm5IcBzyiqt6c5BDgv9BUED0DOLmqnrHUawx6fzpu3wPjHaxBxzst+9Nx+9znjGPc\nxtx/05Knc0b98+jWJGyH29C95eTpSPRBtGbNGr74xS8OO4wlzc7Osn79+mGHMTCTvH2rvW1Jrl+1\nF1tF/c7TSf3OuV3jYRh5WlU3ATe1j+9Kcg2wD7ABWN/OdiYwC7y5LT+rmjM5lybZPcle7XoWNOj9\n6bh9D4x3sAYd77TsT8ftc58zjnEbc/9NS57OGfXPo1uTsB1uQ/eWk6cjUUEkSdI0SbIGeDLNKHYz\nHZU+N9NcggZN5dENHYvd2Jbdp4IoydHA0QAzMzPMzs4OKmy2bds20PX3m/EO1rjFK0mSlmYFkSRJ\nqyjJbsB5wBuq6s6mq6FGVVWSZV37XVWnAqcCrFu3rgZ5JmrcztYZ72CNW7ySJGlpDxh2AJIkTYsk\nO9NUDp1dVR9pi29p+yea66fo1rZ8K7Bvx+KPbsskSZKkvrOCSJKkVdCOSnYacE1Vvatj0vnAEe3j\nI4CPdZS/PI1nAncs1f+QpP5JslOS/5Pk4+3zxyb5XJLNST6c5EFt+YPb55vb6WuGGbckSb2wgkiS\npNXxLOBlwHOSXNHeDgE2Ac9Lci3w3PY5wIXAdcBm4P3A7wwhZmlavR64puP5O4B3V9XjgduBo9ry\no4Db2/J3t/NJkjSW7INojKw57oKelt+y6dA+RSJpMVduvYMje8hV83RyVdVngCwy+cAF5i/gmIEG\ntQLuizTpkjwaOBR4G/B7beu/5wC/1c5yJnAi8D6a0QZPbMv/FjglSdr8XTHzTBp95qkmkRVEkiRJ\n0r3+DHgT8ND2+SOB71XV9vb53IiC0DHaYFVtT3JHO/93Ole41GiDC40Gt3HtdnqxGqPLjeModsYs\nSUuzgkiSJEkCkrwAuLWqLkuyvl/rXWq0wYVGg+ulJSrAlsPX73CeXo3jKHbGLElLs4JoiizVDHLj\n2u1dHYzYFFKSJE2wZwG/3vYP9hDgYcDJwO5JHti2IuocUXButMEbkzwQeDhw2+qHLUlS76wgkqQO\nvV5PvnFtnwKRJK26qjoeOB6gbUH0+1V1eJK/AX4DOIf7jzZ4BPDZdvo/9tr/kCRJw+IoZpIkSdLS\n3kzTYfVmmj6GTmvLTwMe2Zb/HnDckOKTJKlntiCSJEmS5qmqWWC2fXwd8PQF5vk34MWrGpgkSQOy\nwxZESfZNckmSryS5Osnr2/I9klyU5Nr2/hFteZK8J8nmJF9O8pRBb4Q07cxTSZIkSVIvurnEbDuw\nsar2B54JHJNkf5omtBdX1X7AxdzbpPZgYL/2djTwvr5HLWk+81SSJEmStGI7rCCqqpuq6vL28V3A\nNcA+wAbgzHa2M4EXto83AGdV41KaUR/26nvkku5hnkqSJEmSerGsPoiSrAGeDHwOmKmqm9pJNwMz\n7eN9gBs6FruxLbupo4wkR9O0XGBmZobZ2dnlRb7Ktm3bNvQYN67dPrB1z+zS3fqH/R6sxCh8dqtp\nXPJ0VD+XXvOs21xazCi+JzC6n5ckSZKk/ui6gijJbsB5wBuq6s4k90yrqkqyrCE9q+pU4FSAdevW\n1fr165ez+KqbnZ1l2DEe2ePw20vZuHY7J12546/DlsPXDyyGQRmFz261jFOejurn0muedZtLi7ry\n+z29PsCWTYf2vI75RvXzkiRJktQfXQ1zn2Rnmj+dZ1fVR9riW+YuSWnvb23LtwL7diz+6LZM0gCZ\np5IkSZKklepmFLMApwHXVNW7OiadDxzRPj4C+FhH+cvbUZKeCdzRcYmLpAEwTyVJkiRJvejmOohn\nAS8DrkxyRVt2ArAJODfJUcD1wGHttAuBQ4DNwA+AV/Q1YkkLMU8lSZIkSSu2wwqiqvoMkEUmH7jA\n/AUc02NckpbBPJUkSZIk9aKrPogkSZIkSZI0uawgkiRJkiRJmnJWEEmSJEmSJE05K4gkSZIkSZKm\nXDejmEn3WHPcBT0tv2XToX2KRJIkSdK0SfIQ4NPAg2n+z/5tVf1hkscC5wCPBC4DXlZV/57kwcBZ\nwFOB24DfrKotQwleGnG2IJIkSZIkjYsfAs+pqicBBwAHJXkm8A7g3VX1eOB24Kh2/qOA29vyd7fz\nSVqAFUSSJEmSpLFQjW3t053bWwHPAf62LT8TeGH7eEP7nHb6gUmySuFKY8UKIkmSJEnS2EiyU5Ir\ngFuBi4CvA9+rqu3tLDcC+7SP9wFuAGin30FzGZqkeeyDSJIkSZI0NqrqbuCAJLsDHwV+rtd1Jjka\nOBpgZmaG2dnZ+82zbdv/z97dR8tW13eef398iM1oOkgwJwh0rj1Be9DbQXMHzJhJn8SY8GDnxp6E\ngbZRlA5mBSa6crvj1aQbOzZrbieibWLCBAcamDYgK2rDUjqKNGeI06IizfAo7RWv471Brg+AXO0Y\nD37nj9oHi8M599Y59bR31fu11lmn6rd3VX33qfpW1fnt3+/7O/B4+46ty0/avhFr3f+k9B9HV3kM\n42EHkSRJkiSpc6rq4SQ3AT8FHJ7kac0ooWOAfc1u+4Bjgb1Jngb8EL1i1avv6xLgEoBt27bV4uLi\nkx5vaWmJlfazh12859VPvv9J6T+OrvIYxsMpZpIkSZKkTkjynGbkEEkOA14B3AvcBPxKs9trgWub\ny9c112m2/6eqqslFLHWHHUSSJE1AksuS7E9yV1/b25LsS3J783Nq37a3JNmd5L4kvzidqCVJap2j\ngJuS3AF8Brihqj4MvBn4rSS76dUYurTZ/1Lgh5v23wJ2TiFmqROcYiZJ0mRcDrwHuHJV+7uq6h39\nDUmOB84AXgg8F/h4kuc3NRckSZpbVXUH8OI12u8HTlyj/a+BX51AaFLnOYJIkqQJqKqbgW8MuPt2\n4Oqq+k5VfRHYzRpfeiVJkqRRsYNIkqTpOj/JHc0UtGc3bY8vydvoX65XkiRJGjmnmEmSND0XA28H\nqvl9EfD6jdzBIMvyjsqBAwfYsXW4WW6TXM61jcvHHozxSpKkabKDSJKkKamqB1cuJ3kv8OHm6sqS\nvCv6l+tdfR+HXJZ3VJaWlrjoE98a6j4muaxvG5ePPRjjnb4kfwu4GXgGve/Jf15VFyR5HnA1vcK3\nnwXOqqq/SfIMenXFfpLestn/a1XtmUrwkiQNySlmkiRNSZKj+q6+ClhZ4ew64Iwkz2j+MT0O+PSk\n45Pm0HeAn6uqnwBOAE5O8lLg39ArKP/jwEPAOc3+5wAPNe3vavaTJKmTHEEkSdIEJLkKWASOTLIX\nuABYTHICvSlme4A3AFWtXsUAACAASURBVFTV3UmuAe4BloHzZmUFsy07PzL0fezZddoIIpGerKoK\nONBcfXrzU8DPAf+4ab8CeBu9KaLbm8sAfw68J0ma+5EkqVPsIJIkaQKq6sw1mi89yP4XAheOLyJJ\na0nyVHrTyH4c+GPgC8DDVbXc7NJfNP7xgvJVtZzkEXrT0L626j7XrRW2Vi2nHVuXGcYkakN1sQaV\nMUvSwdlBJEmSJDWa0XonJDkc+BDw90Zwn+vWClurltPZQ460m0Stry7WoDJmSTo4axBJkiRJq1TV\nw8BNwE8BhydZObHaXzT+8YLyzfYfolesWpKkznEEkSRJc2SYGkC9aS9+ddDsSvIc4LtV9XCSw4BX\n0Cs8fRPwK/RWMnstcG1zk+ua659stv8n6w9JkrrqkCOIklyWZH+Su/ra3pZkX5Lbm59T+7a9Jcnu\nJPcl+cVxBS7p+8xTSZJG4ijgpiR3AJ8BbqiqDwNvBn4ryW56NYZW6oddCvxw0/5bwM4pxCxJ0kgM\nchrwcuA9wJWr2t9VVe/ob0hyPHAG8ELgucDHkzx/VlZekVrscsxTSZKGUlV3AC9eo/1+4MQ12v8a\n+NUJhCZJ0tgdcgRRVd0MfGPA+9sOXF1V36mqLwK7WePDVNJomaeSJEmSpGEMU0jg/CSvAW4FdlTV\nQ/SW+rylb5/+ZUCf4GDLfbZRG5aYHHbJ04NZOGy8979iGn/DNjx3U9TaPG3r8zJsHkwqlw5mHH/X\ntj5fkiRJkkZjsx1EFwNvB6r5fRHw+o3cwcGW+2yjNiwxOeySpwezY+syF905/sKjk1h2dbU2PHdT\n0uo8bevzMmyeTSqXDmYcedbW50uSJEnSaGxqmfuqerCqHquq7wHv5fvTUx5f6rPRvwyopAkyTyVJ\nkiRJg9pUB1GSo/quvgpYWTnpOuCMJM9I8jzgOODTw4UoaTPMU0mSJEnSoA45DyLJVcAicGSSvcAF\nwGKSE+hNXdkDvAGgqu5Ocg1wD7AMnOfKSNL4maeSJEmSpGEcsoOoqs5co/nSg+x/IXDhMEFJ2hjz\nVJIkSZI0jOlWUpUkSZqwLUMWo9+z67QRRSJJktQedhBJkqROGbSDZ8fW5bGuACpJkjRLNlWkWpIk\nSZIkSbPDDiJJkiRJkqQ5ZweRJEmSJEnSnLODSJIkSZIkac7ZQSRJkiRJkjTn7CCSJEmSJEmac3YQ\nSZIkSZIkzbmnTTuAebJl50emHYIkSZIkSdKTOIJIkiRJktQJSY5NclOSe5LcneSNTfsRSW5I8vnm\n97Ob9iT5wyS7k9yR5CXTPQKpvewgkiRJkiR1xTKwo6qOB14KnJfkeGAncGNVHQfc2FwHOAU4rvk5\nF7h48iFL3WAHkSRJkiSpE6rqgaq6rbn8KHAvcDSwHbii2e0K4Jeby9uBK6vnFuDwJEdNOGypE6xB\nJGlmWOdLkiRpfiTZArwY+BSwUFUPNJu+Aiw0l48Gvtx3s71N2wNIegI7iCRJkiRJnZLkWcAHgDdV\n1TeTPL6tqipJbfD+zqU3BY2FhQWWlpaetM+BAwceb9+xdXmzoQOsef+T0n8cXeUxjIcdRJIkTUiS\ny4BXAvur6kVN2xHA+4EtwB7g9Kp6KL1vuu8GTgW+DZy9MqRekqR5luTp9DqH3ldVH2yaH0xyVFU9\n0Ewh29+07wOO7bv5MU3bE1TVJcAlANu2bavFxcUnPe7S0hIr7WcPOXJ9z6uffP+T0n8cXeUxjIc1\niCRJmpzLgZNXtVlUU5KkATUnUC4F7q2qd/Ztug54bXP5tcC1fe2vaVYzeynwSN9UNEl97CCSJGlC\nqupm4Burmi2qKUnS4F4GnAX8XJLbm59TgV3AK5J8Hvj55jrA9cD9wG7gvcBvTCFmqROcYiZJ0nQN\nVVRzkJoJ/YapmbBw2PA1FyZpXPGOq15AG2sRHEzX4h1EkmOBK+nlYQGXVNW7nQoqtUdVfQLIOptf\nvsb+BZw31qCkGWEHkSRJLbGZopqD1EzoN0zNhB1bl7nozu58dRhXvOOqG9HGWgQH07V4B7QM7Kiq\n25L8IPDZJDcAZ9ObCroryU56U0HfzBOngp5EbyroSVOJXJKkITnFTJKk6XpwZerYZopqShqdqnpg\nZQRQVT0K3Etv5J5TQSVJM687pwElSZpNK0U1d/HkoprnJ7ma3ogEi2pKE5RkC/Bi4FOMcSroWlP1\nurB8dhenGBqzJB2cHUSSJE1IkquAReDIJHuBC+h1DF2T5BzgS8Dpze7X06trsptebZPXTTxgaU4l\neRa9JbTfVFXf7JUa6hn1VNC1pup1YfnsLk4xNGa1yZZh83zXaSOKRPq+gTqIklwGvBLYX1Uvatos\n1ie1iHkqtV9VnbnOJotqSi2R5On0OofeV1UfbJofTHJUVT3gVFBJ0qwatAbR5cDJq9p20ivWdxxw\nY3Mdnlis71x6xfokjd/lmKeSJG1acwLlUuDeqnpn36aVqaDw5Kmgr0nPS3EqqCSpwwYaQVRVNzfz\nsPttpzdMHnrF+pborebweLE+4JYkh6+ccRlFwJLWNgt5OuxQW0mShvQy4CzgziS3N21vxamgkqQ5\nMEwNorEV62ujURSIG7bg4DgtHDaZ+KbxPM95cb/W5uk4inK2waRy6WDG8Xqf8zySNCeq6hNA1tns\nVFBJ0kwbSZHqURfra6NRFIgbtuDgOO3YusxFd46/ZvkkiiauZnG/nrbl6TiKcrbBpHLpYMaRZ+aR\nJEmSNNsGrUG0lgebIn1YrE9qLfNUkiRJknRIw3QQWaxPaj/zVJIkSZJ0SIMuc38VvUK3RybZC1yA\nxfqkVjFPJUmSJEmbNegqZmeus8lifdqQYVep2rPrtBFFMnvMU0mSJEnSZg0zxUySJEmSJEkzwA4i\nSZIkSZKkOWcHkSRJkiRJ0pyzg0iSJEmSJGnODVSkWpIkSep3575HOHuIxSdceEKSpHZxBJEkSZIk\nSdKccwSRJEnSBmwZYtTMCkfPSJKktnEEkSRJkiRJ0pyzg0iSJEmSJGnO2UEkSZIkSZI05+wgkiRJ\nkiRJmnN2EEmSJEmSJM05O4gkSZIkSZLmnMvcS5IkSTNky86PDHX7PbtOG1EkkqQucQSRJEmSJEnS\nnHMEkSTNGM8cS5Kmzc8iSeoeRxBJkiRJkjojyWVJ9ie5q6/tiCQ3JPl88/vZTXuS/GGS3UnuSPKS\n6UUutZsdRJIkSZKkLrkcOHlV207gxqo6DrixuQ5wCnBc83MucPGEYpQ6xylmkiRJkqTOqKqbk2xZ\n1bwdWGwuXwEsAW9u2q+sqgJuSXJ4kqOq6oHJRDsew0zj3LF1mbN3fsSpnHoSO4jUKZt5I1x5A1zh\nG6GkNkqyB3gUeAxYrqptSY4A3g9sAfYAp1fVQ9OKUZKkFlvo6/T5CrDQXD4a+HLffnubtk53EEnj\nYAeRJEnt8bNV9bW+6yvD5Xcl2dlcf/N0QtMorXXCY/UJjYPxZMf4JLkMeCWwv6pe1LSt2VmbJMC7\ngVOBbwNnV9Vt04hb0vdVVSWpjdwmybn0pqCxsLDA0tLSk/Y5cODA4+07ti4PHee0LBzWi3+tY+yK\n/ueiq9p4DHYQSZLUXusNl5c0PpcD7wGu7Gtbr7O2v7bJSfRqm5w00WglrXhwZepYkqOA/U37PuDY\nvv2OadqeoKouAS4B2LZtWy0uLj7pAZaWllhpH7RDv412bF3mojufxp5XL047lE3rfy66qo3HYAeR\nJEntUMDHmjOef9p8UV1vuPzjBjnj2W+YM54rZxy7YpbjbcMZx2H/vm04hrVY22SwKf0bGfEmTch1\nwGuBXc3va/vaz09yNb0O3Ee6nqPSuAzdQWTNBKn9zFOpE366qvYl+RHghiSf69+43nD5Qc549hvm\nH7qVM45dMcvxtuGs7x+979qh/r5tOIYNsLaJ1CJJrqLXaXtkkr3ABfQ6hq5Jcg7wJeD0Zvfr6U0D\n3U1vKujrJh6w1BGj+tZkzQSp/cxTqcWqal/ze3+SDwEnsv5weUlTMuraJmvVoOjCyLdxj9Abxwiz\nNtb7OJQuxjwJVXXmOptevsa+BZw33oik2TCu02rWTJDazzyVWiLJM4GnVNWjzeVfAH6P9YfLS5qs\nsdU2WasGRRembo17hN44Rpi1sd7HoXQxZkndNYp39YnUTJi2UfTet/lsUNfqNGzE6mNr+2ttTFqX\np109Y3oos5BLh1q1Q2OxAHyotyASTwP+rKr+IslnWHu4vKTJsraJJGnmjaKDaCI1E6ZtFL33bT4b\n1LU6DRux+tg6VvNgVFqXp109Y3oos5BLa+WIZzDHq6ruB35ijfavs8ZweUnjY20TSdK8Gvq/mHmp\nmXDnvkdm4p9Xzad5yVNJkoZlbRNJ0rx6yjA3TvLMJD+4cplezYS7+P4wXLBmgjRV5qkkSZIk6VCG\nHUFkzQSp/cxTSZIkSdJBDdVBZM0Eqf3MU0mS1DVbhiztsGfXaSOKRJLGq03vd92upCpJkiRJWlOb\n/vGU1H5D1SCSJEmSJElS99lBJEmSJEmSNOfsIJIkSZIkSZpz1iCSNDIbmee+Y+syZw85L16SJEnS\ndFjjavbYQSRJkiRJ0pwZtoNHs8cpZpIkSZIkSXPOEUSSJEkd47B+SZI0ao4gkiRJkiRJmnN2EEmS\nJEmSJM05p5hJkiRJkiRt0DBTvtu4qrMjiCRJkiRJkuacI4gkSZIkSdJEtWH0jYs2PJEjiCRJkiRJ\nkuacI4gkSZLmzDBnbVfs2DqCQKQxWes1vtERB44skGbfKD4PZ8ncdBAN+8T7JUjSvBj2S7VfqCVJ\nkqTucYqZJEmSJEnSnLODSJIkSZIkac7NzRQzacWw0w2dPiNJkiRJmjWOIJIkSZIkSZpzjiCSJI3U\nKFaDcKSeJGnaHHUuad44gkiSJEmSJGnO2UEkSZIkSZI058Y2xSzJycC7gacC/2dV7Rrm/kYxZUHS\nE406TyWNnnkqtZ95KrWfeSod2lg6iJI8Ffhj4BXAXuAzSa6rqnvG8XiSNs48ldrPPJXazzzVeqxh\n1B7mqTSYcY0gOhHYXVX3AyS5GtgOmIBSe5inai2/VD/OPJXazzyV2s88lQaQqhr9nSa/ApxcVf+0\nuX4WcFJVnd+3z7nAuc3VFwD3jTyQ0ToS+Nq0gxijWT6+SR/bj1XVcyb4eJvSgjyd1decx9UN5unm\ndO11YLzjNe545yVPu/a8r+hi3MY8evOSpyva/nwMahaOw2MY3MB5OrVl7qvqEuCSaT3+RiW5taq2\nTTuOcZnl45vlYxu3cebprD4vHpcmbZKfp117HRjveHUt3mk6WJ529e/YxbiNWQczyOfprDwfs3Ac\nHsN4jGsVs33AsX3Xj2naJLWHeSq1n3kqtZ95KrWfeSoNYFwdRJ8BjkvyvCQ/AJwBXDemx5K0Oeap\n1H7mqdR+5qnUfuapNICxTDGrquUk5wMfpbeM4GVVdfc4HmuCOjMdbpNm+fhm+dg2rQV5OqvPi8el\nkWlBnq7WtdeB8Y5X1+IdixHkaVf/jl2M25jn1Ag/T2fl+ZiF4/AYxmAsRaolSZIkSZLUHeOaYiZJ\nkiRJkqSOsINIkiRJkiRpztlBtAFJ/iDJ55LckeRDSQ6fdkzDSnJykvuS7E6yc9rxjFKSY5PclOSe\nJHcneeO0Y9ITzVpOzWI+mUdaLcmvNq+F7yVp1dKs/bqUj0kuS7I/yV3TjmUQvi+MXlfyCrqVWyu6\nlmNgnrVZl/J1tS7m72pdzOfV2pzfdhBtzA3Ai6rq7wP/FXjLlOMZSpKnAn8MnAIcD5yZ5PjpRjVS\ny8COqjoeeClw3owd3yyYmZya4Xwyj7TaXcA/Am6ediDr6WA+Xg6cPO0gNsD3hdFrfV5BJ3NrxeV0\nK8fAPGuzTuTrah3O39Uup3v5vFpr89sOog2oqo9V1XJz9RbgmGnGMwInArur6v6q+hvgamD7lGMa\nmap6oKpuay4/CtwLHD3dqNRvxnJqJvPJPNJqVXVvVd037TgOoVP5WFU3A9+YdhyD8n1h9DqSV9Cx\n3FrRtRwD86zNOpSvq3Uyf1frYj6v1ub8toNo814P/MdpBzGko4Ev913fS0temKOWZAvwYuBT041E\nB9H1nJr5fDKP1CEzn49t4fvC3DG3psA804iYvy3Utvx+2rQDaJskHwd+dI1Nv1NV1zb7/A69YWHv\nm2Rs2pwkzwI+ALypqr457XjmjTk1G8yj+TJI3kq+L2yMeaXNMM+mw3zVJLQxv+0gWqWqfv5g25Oc\nDbwSeHlV1USCGp99wLF9149p2mZGkqfTS7r3VdUHpx3PPJqjnJrZfDKP5s+h8rYDZjYf28L3hY2b\ngbwCc2uizLPpmZF8Xc38bZG25rdTzDYgycnAbwO/VFXfnnY8I/AZ4Lgkz0vyA8AZwHVTjmlkkgS4\nFLi3qt457Xj0ZDOWUzOZT+aROmom87EtfF+Ya+bWhJhnGgPztyXanN92EG3Me4AfBG5IcnuS/2Pa\nAQ2jKQ58PvBReoWxrqmqu6cb1Ui9DDgL+Lnm+bo9yanTDkpPMDM5NcP5ZB7pCZK8Ksle4KeAjyT5\n6LRjWq1r+ZjkKuCTwAuS7E1yzrRjOgTfF0asC3kF3cutFR3MMTDPWqsr+bpaV/N3tY7m82qtze90\ne0aHJEmSJEmShuUIIkmSJEmSpDlnB5EkSZIkSdKcs4NIkiRJkiRpztlBJEmSJEmSNOfsIJIkSZIk\nSZpzdhBJkiRJkiTNOTuIJEmSJEmS5pwdRJIkSZIkSXPODiJJkiRJkqQ5ZweRJEmSJEnSnLODSJIk\nSZIkac7ZQSRJkiRJkjTn7CCagiR7kvz8tOPol+TuJIvTjkNqC/NUaj/zVJIkaXTsIOqwJItJ9o7i\nvqrqhVW1tMk4tiSpJAeanweT/EmSp48iNqnL2pKnTSw/kORfJrkvybeS7EvyH5P8wijik7qqLXm6\nxufpniQ7RxGXpI1JcnmSv2ly8dEkn03yD6Ydl6QnSrItyYeTPJTk4ST3JLkwybOnHVsX2UHUUUme\nNu0Y1nB4VT0L2Ar8FHDelOORpqqFefrnwHbgNcCzgecB7wZOm2ZQ0jS1ME/h+5+nvwL8iySvmHZA\n0pz6/SYX/zZwMfDBJE+dckySGkn+J2AJ+H+Av1dVhwMnA8vAT0wxtM6yg2jKkvwPSb6Y5MzmrOGP\n9227PMm/bi4vJtmb5M1JvgJcBfxH4Ll9Zxqfm+QZSf5tkr9qfv5tkmc093Fk07v6cJJvJPnLJE9p\ntj0+TD/JiUluTfLNZjTQOzdyTFW1H7gBOH4kfyRpymYhT5vbvQLYXlWfqqq/aX7+oqreOJY/nDRB\ns5Cnq1XVrcDdwAkj+SNJLdPkyz9Pckd6I1svTbKQ3ujWR5N8fGUUQJKXJvnPTd79v+mbypnkdUnu\nbW5zf5I39G1byfkdSfYneSDJ6zYSZ1UV8GfAEcDCaI5e6oaW5+nvA/+uqv73qnoQoKr+v6q6YJhR\n9/PMDqIpSvIS4KPA/1ZVVw1wkx+l98H0Y/RGAJwC/FVVPav5+Svgd4CX0vsy+RPAicDvNrffAewF\nnkPvw+2tQK3xOO8G3l1Vfxv474FrNnhczwV+EbhlI7eT2miG8vTngU9V1Uim0UhtMkN5uvq4Xgq8\nCNi9kdtJHfO/0DuB8XzgH9LrsH0rvfx6CvCbSY4GPgL8a3q5+8+ADyR5TnMf+4FX0hvp8zrgXc37\nwoofBX4IOBo4B/jjbGD6SXqjhl4DfBF4cHOHKXVa6/I0yTPpzVr5wIiOUdhBNE3/M3Ad8Jqq+vCA\nt/kecEFVfaeq/ts6+7wa+L2q2l9VXwX+FXBWs+27wFHAj1XVd6vqL5szIqt9F/jxJEdW1YGqGrSj\n52tJHgb2Ad+iN51F6rJZytMjga+sXElyRHN255Ekfz3gsUltNEt5uuJrSf4b8EngT4D/MODtpC76\no6p6sKr2AX9J72TGf6mqvwY+BLwY+CfA9VV1fVV9r6puAG4FTgWoqo9U1Req5/8GPkbvvWHFd+nl\n83er6nrgAPCCAWL7Z8132wPAvwX+RVU9NprDljqljXn6bHr9Gf3fb3+/+X77rSS/u/5NtR47iKbn\n14H/vMGhb19tkvBgngt8qe/6l5o2gD+gdxbyY82wvvUKX55Dr3f4c0k+k+SVA8Z3ZDPv87+jNw/0\nowPeTmqrWcrTr9P7hxaAqvpGk68/CTzjELeV2myW8nTFkcCz6I1UWgRc9EGzrH9Ezn9b4/qz6I32\n+9XmH7+Hm06bn6b5XEtySpJbmimfD9P7h/TIvvv5elUt913/dnO/h/KOvu+224A/SHLKBo9PmgVt\nzNOH6J3w6f9++9tNzn4IaGONwdazg2h6fh34O0ne1df2bXofQCt+dNVtVp+dXOts5V/RS84Vf6dp\no6oeraodVfV3gV8CfivJy1ffQVV9vqrOBH4E+DfAnzdD+AbSnI29HHhpkiMPsbvUZrOUpzcC/2OS\nYw6yj9RFs5Sn/bd9rKreCfw18BuD3EaaYV8G/q+qOrzv55lVtSu92mAfAN4BLDT/HF4PZFQP3ox4\nuIveCVAXdpDWNtE8rapvAZ8C/tEoglePHUTT8yi9Cus/k2RX03Y78I+TPDXJycChltJ8EPjhJD/U\n13YV8LtJntN0zvxL4N8DJHllkh9PEuAR4DF6va5PkOSfJHlOVX0PeLhpftJ+62neAM6iN9zv64Pe\nTmqhmcnTqvoYcBPwH5KclN6S90+nV2NF6rKZydN17AJ+O8nf2uDtpFny74F/mOQXm7z+W01R22OA\nH6A3EvarwHIzwucXRh1Akr9HbzTE3aO+b2lGTCNPfxt4fZKdSX4EoHm8543gvueSHURTVFUP0yv2\ndUqStwNvpFf062F6tQ8OWnOgqj5H7wvs/c0wvufSKwp2K3AHcCdwW9MGcBzwcXrzOT8J/ElV3bTG\nXZ8M3J3kAL0Cm2ccpEZDv4eb2zxIr2DYL61Tk0HqjBnL01cBH6b3Af4wvWKbr6ZXVF7qrBnL09U+\nQm8Y/a9t8HbSzKiqLwPb6RXF/Sq9kQr/HHhKVT0K/Ca9IvAPAf+YXl2yUfjt9FY2/Ba9ein/DvjT\nEd23NFOmkadV9Qng54CfAf5rM3XtL4Al4I+Gvf95FP9/lyRJkiRJmm+OIJIkSZIkSZpzh+wgSnJZ\nkv1J7upre1uSfUlub35O7dv2liS7k9yXxGkLMyLJq5shtqt/nIcttYR5KrWfeSq1R5K718nHV087\nNkk95ulkHXKKWZKfoTfH/sqqelHT9jbgQFW9Y9W+x9Obw38ivaVgPw48v6oeG33okiRJkiRJGoWn\nHWqHqro5yZYB7287cHVVfQf4YpLd9DqLPnmwGx155JG1ZcugDzEd3/rWt3jmMwde6X2quhLrrMb5\n2c9+9mtV9ZwxhjQV5un0zOpxwfSOzTydLF/D3TXN45vHPG3r68m4Nq6tsY06LvO0mzyGdpjUMWwk\nTw/ZQXQQ5yd5Db0VPnZU1UPA0cAtffvsbdoOasuWLdx6661DhDJ+S0tLLC4uTjuMgXQl1lmNM8mX\nxhfN9Jin0zOrxwXTOzbzdLJ8DXfXNI9vHvO0ra8n49q4tsY26rjM027yGNphUsewkTzdbAfRxcDb\ngWp+XwS8fiN3kORc4FyAhYUFlpaWNhnKZBw4cKD1Ma7oSqzGKUmSJElSO2yqg6iqHly5nOS9wIeb\nq/uAY/t2PaZpW+s+LgEuAdi2bVu1vfevSz2UXYnVOCVJkiRJaodNLXOf5Ki+q68CVlY4uw44I8kz\nkjwPOA749HAhSpIkSZIkaZwOOYIoyVXAInBkkr3ABcBikhPoTTHbA7wBoKruTnINcA+wDJznCmaS\nJEmSJEntNsgqZmeu0XzpQfa/ELhwmKAkSZIkSZI0OcOsYjZX7tz3CGfv/MhQ97Fn12kjikZSW23x\nfUJqPfNU0iCGea/YsXWZxdGFIs2kYXPs7J0f8TN5xDZVg0iSJG1MkmOT3JTkniR3J3lj035EkhuS\nfL75/eymPUn+MMnuJHckecl0j0CSJEmzzA4iSZImYxnYUVXHAy8FzktyPLATuLGqjgNubK4DnEJv\nsYfjgHOBiycfsiRJkuaFHUSSJE1AVT1QVbc1lx8F7gWOBrYDVzS7XQH8cnN5O3Bl9dwCHL5qFVFJ\nkiRpZKxBJEnShCXZArwY+BSwUFUPNJu+Aiw0l48Gvtx3s71N2wN9bSQ5l94IIxYWFlhaWhpX2Jt2\n4MCBVsW1Y+vyULf/o/dd+/jlhcOeeH1QW4/+oaFimJS2PXeSJGl85qaDaNiClDu2jigQSdJcS/Is\n4APAm6rqm0ke31ZVlaQ2cn9VdQlwCcC2bdtqcXFxhNGOxtLSEm2Ka9hFJ/rt2LrMRXdu/OvUnlcv\njiyGcWrbcydJSY4FrqR3QqWAS6rq3UneBvwa8NVm17dW1fXNbd4CnAM8BvxmVX104oFLHTA3HUSS\nJE1bkqfT6xx6X1V9sGl+MMlRVfVAM4Vsf9O+Dzi27+bHNG2SJM2zlZp+tyX5QeCzSW5otr2rqt7R\nv3NT7+8M4IXAc4GPJ3l+VT020ailDrCDSJKkCUhvqNClwL1V9c6+TdcBrwV2Nb+v7Ws/P8nVwEnA\nI31T0SSp1YYdvT/s0tXDPr7aq/ksfKC5/GiSlZp+69kOXF1V3wG+mGQ3cCLwybEHK3WMRaolSZqM\nlwFnAT+X5Pbm51R6HUOvSPJ54Oeb6wDXA/cDu4H3Ar8xhZglSWqtVTX9oHdi5Y4klyV5dtO2Xk0/\nSas4gkiSpAmoqk8AWWfzy9fYv4DzxhqUJEkdtUZNv4uBt9OrS/R24CLg9Ru4v4EWfZiF4v1tOYZh\nFo1YOKx3+zYcx2a15XnoZweRJEmSJKkz1qrpV1UP9m1/L/Dh5upANf0GXfRhFor3t+UYhlk0YmWR\niK4s+rCWtjwP/ZxiJkmSJEnqhPVq+jULPax4FXBXc/k64Iwkz0jyPOA44NOTilfqEkcQSZIkSZK6\nYqWm351Jbm/a7++wVgAAIABJREFU3gqcmeQEelPM9gBvAKiqu5NcA9xDbwW081zBTFqbHUSSJEkS\nkOQy4JXA/qp6UdP2B8A/BP4G+ALwuqp6uCmOey9wX3PzW6rq1ycetDRnDlLT7/qD3OZC4MKxBSXN\nCKeYSTMgybFJbkpyT5K7k7yxaT8iyQ1JPt/8fnbTniR/mGR3s9LDS6Z7BJIktcLlwMmr2m4AXlRV\nfx/4r8Bb+rZ9oapOaH7sHJIkddohRxB5JkXqhGVgR1XdluQHgc8muQE4G7ixqnYl2QnsBN4MnEJv\n/vVxwEnAxc1vTdmWNYr17di6vKEifnt2nTbKkCRpblTVzc332f62j/VdvQX4lUnGJEnSpAwyxexy\n4D3AlX1tNwBvqarlJP+G3pmUNzfbvlBVJ4w0SkkHVVUPAA80lx9Nci9wNLAdWGx2uwJYoper24Er\nm2W0b0lyeJKjmvuRJElrez3w/r7rz0vyX4BvAr9bVX+51o26vnz2ZuIaZvlqYKDHO1hcwz7+sBYO\nG+wYJq2trzFJ7XDIDiLPpEjd0uTri4FPAQt9nT5fARaay0cDX+672d6m7QkdRIN+oW2LNnzpGccX\n0oXDNna/0/4bbEQbnjNJGkSS36E3Yvd9TdMDwN+pqq8n+UngPyR5YVV9c/Vtu7589mbiGmb5amCg\npasPFtewjz+sHVuXOX1GnktJ82MURao3dSZF0ugleRbwAeBNVfXN3iqgPVVVSWoj9zfoF9q2aMOX\nnnF8Id2xdZmL7hz87XqQL9Vt0YbnTJIOJcnZ9EouvLwZfUtVfQf4TnP5s0m+ADwfuHVacUqSNIyh\nOoiGOZMy6ZEJw57V3+gZ/LVM6ix5V87IG+doJXk6vc6h91XVB5vmB1emjiU5CtjftO8Dju27+TFN\nmyRJ6pPkZOC3gX9QVd/ua38O8I2qeizJ36VX1+/+KYUpSdLQNt1BNOyZlEmPTBj2rP5Gz+CvZVJn\n9btyRt44Rye9oUKXAvdW1Tv7Nl0HvBbY1fy+tq/9/CRX0ytO/Yj1hyRJ8y7JVfRq9x2ZZC9wAb1a\nm88AbmhG5q4swvIzwO8l+S7wPeDXq+obUwlckqQR2FSPh2dSpNZ5GXAWcGeS25u2t9LrGLomyTnA\nl4DTm23XA6cCu4FvA6+bbLiSJLVPVZ25RvOl6+z7AXojdzUGa63qudpGV/mUJB3cIMvceyZFarmq\n+gSQdTa/fI39CzhvrEFJktY1yD+/B7Nn12kjikSSJKlnkFXMPJMiSZIkSRtgR7CkrnnKtAOQJEmS\nJEnSdNlBJEmSJEmSNOfsIJIkSZIkSZpzw63brg1xHrIkSZIkSWojRxBJkiRJkiTNOTuIJEmSJEmS\n5pwdRJIkSZIkSXPODiJJkiRJUickOTbJTUnuSXJ3kjc27UckuSHJ55vfz27ak+QPk+xOckeSl0z3\nCKT2soNIkiRJktQVy8COqjoeeClwXpLjgZ3AjVV1HHBjcx3gFOC45udc4OLJhyx1g6uYSZIkSZI6\noaoeAB5oLj+a5F7gaGA7sNjsdgWwBLy5ab+yqgq4JcnhSY5q7kcd50rho+UIIkmSJElS5yTZArwY\n+BSw0Nfp8xVgobl8NPDlvpvtbdokreIIIm2IPbSStDlJLgNeCeyvqhc1bW8Dfg34arPbW6vq+mbb\nW4BzgMeA36yqj048aEmSWirJs4APAG+qqm8meXxbVVWS2uD9nUtvChoLCwssLS2tud+BAwfW3dYV\nbTmGHVuXN33bhcOGu/2Kaf4d2vI89LODSJKkybgceA9w5ar2d1XVO/obmloKZwAvBJ4LfDzJ86vq\nsUkEKmm+rT4huGPrMmcPeZJQGqUkT6fXOfS+qvpg0/zgytSxJEcB+5v2fcCxfTc/pml7gqq6BLgE\nYNu2bbW4uLjmYy8tLbHetq5oyzEM876yY+syF905fHfGnlcvDn0fm9WW56GfHUSSJE1AVd3cDIUf\nxHbg6qr6DvDFJLuBE4FPjim8Thl2NKt0MOuM9jsCeD+wBdgDnF5VD6U3ZOHdwKnAt4Gzq+q2acQt\nzYsm7y4F7q2qd/Ztug54LbCr+X1tX/v5Sa4GTgIesf6QtDY7iCRJmq7zk7wGuJXeqiwP0auNcEvf\nPuvWSxh0SPw0jXoI9SiGlI/KqIa4b9Sknuc2Dn+fgMt58mi/ldWRdiXZ2Vx/M09cHekkeqsjnTTR\naKX58zLgLODOJLc3bW+l1zF0TZJzgC8BpzfbrqfXibubXkfu6yYbrtQdA3UQeSZFkqSxuBh4O1DN\n74uA12/kDgYdEj9Nox5C3aapLqMa4r5RkxoS38bh7+O2zmg/V0eSWqKqPgFknc0vX2P/As4ba1DS\njBj0G83leCZFkjrBYvLdUVUPrlxO8l7gw83VgeolSJqYja6OZAeRJKlzBuog8kzKbLBmgyS1y6rP\nx1cBdzWXrwP+LMk76RWpPg749BRClLTKPKyOtHra5LSmUh5KW+OC0cQ2jtdCW15jktppmDHRnkmR\nJGlASa6id2LlyCR7gQuAxSQn0Jtitgd4A0BV3Z3kGuAeYBk4zxXMpKmaq9WRVk/jnNZUykNpa1ww\nmtjGMZW0La8xSe00knfUcZ5JGZVhe/DbcIZi0L/RemcGph0/PPEYunIGoytxSmq3qjpzjeZLD7L/\nhcCF44tI0ga4OpIkaeYN00E0kTMpozJsQcs2nKEY9CzCemcG2lDUs/8YunIGowtxrlNI/m3ArwFf\nbXZ7a1Vd32x7C3AO8Bjwm1X10YkHLUlSC60z2q9TqyNZVkCStBnD9Hh4JmXCBv2w37F1uRWdQZqo\ny3lyIXmAd1XVO/obkhwPnAG8kF5tk48neb7TVyRJWne0H7g6kiRpxg26zH3nz6RIs2ydQvLr2Q5c\nXVXfAb6YZDdwIvDJMYUnSZIkacY4WnH2DLqKmWdSpG46P8lrgFuBHVX1EL2i8bf07bNSSF6SJEmS\nNKfaWfZf0ihcDLyd3upIbwcuAl6/kTuYdDH5YbWhoPg4isFPukj+JP+GbXjOJEmSJNlBpAnrH4a4\nmVpJe3adNuqQZlZVPbhyOcl7gQ83VwcqJN/cx0SLyQ+rDQXFx1H/a9JF8sexrO562vCcSZIkSYKn\nTDsASePRrC644lXAXc3l64AzkjwjyfOA44BPTzo+SZIkSVJ7OIJImgHrFJJfTHICvSlme4A3AFTV\n3UmuAe4BloHzXMFMkiRJkuabHUTSDFinkPylB9n/QuDC8UUkSZIkSeoSp5hJkiRJkiTNOTuIJEmS\nJEmS5pwdRJIkSZIkSXPODiJJkiRJkqQ5ZweRJEmSJKkTklyWZH+Su/ra3pZkX5Lbm59T+7a9Jcnu\nJPcl+cXpRC11gx1EkiRJkqSuuBw4eY32d1XVCc3P9QBJjgfOAF7Y3OZPkjx1YpFKHeMy95LUZ8vO\nj0w7BEmSJK2jqm5OsmXA3bcDV1fVd4AvJtkNnAh8ckzhSZ3mCCJJkiRJUtedn+SOZgras5u2o4Ev\n9+2zt2mTtAZHEEmSJEmSuuxi4O1ANb8vAl6/kTtIci5wLsDCwgJLS0tr7nfgwIF1t3XFqI5hx9bl\n4YPZpIXDRvP403wu2/hasoNIkiRJOogkLwDe39f0d4F/CRwO/Brw1ab9rSu1TyRNTlU9uHI5yXuB\nDzdX9wHH9u16TNO21n1cAlwCsG3btlpcXFzzsZaWllhvW1eM6hjOnmJphh1bl7nozuG7M/a8enH4\nYDapja+lTU8xS/KCvirxtyf5ZpI3HayCvCRJktQ1VXXfSvFb4CeBbwMfajY/qTCupMlKclTf1VcB\nKyucXQeckeQZSZ4HHAd8etLxSV2x6S63qroPOAGgqQS/j94H5evofVC+YyQRSpIkSe3xcuALVfWl\nJNOORZo7Sa4CFoEjk+wFLgAWk5xAb4rZHuANAFV1d5JrgHuAZeC8qnpsGnFLXTCqKWZ+UEqSJGke\nnAFc1Xf9/CSvAW4FdlTVQ6tvMOnaJqOuCzKqWh+j1ta4YDSxjaM2SRtrnmxUVZ25RvOlB9n/QuDC\n8UUkzY5RdRBt+INSkiRJ6pIkPwD8EvCWpmmgwriTrm0y6rogo6r1MWptjQtGE9s4aqO0seaJpPYY\n+h11sx+Ug55JGZVhe/DbfIZita7Eupk4p3HGYxbOtEgbsWXIfyz27DptRJFIUuucAty2UhD3IIVx\nJUnqnFF0uW/qg3LQMymjMuyZlDafoVitK7FuKs47vzX04270n1fPtEgalSSXAa8E9lfVi5q2I+it\njrSFXt2E06vqofTmbL8bOJVeQdyzq+q2acQt6XFn0jdqPslRVfVAc7W/MK4kqQM8MfpEo+hF8INS\nkqTBXA68B7iyr20ncGNV7Uqys7n+ZnonYI5rfk6iN0L3pIlGK+lxSZ4JvIKm+G3j99cqjDusYf9h\nkSRpM4bqIJrkB6UkSV1XVTcn2bKqeTu91VgArgCW6HUQbQeurKoCbkly+KqTMJImqKq+Bfzwqraz\nphSOJEkjN1QHkR+UkiQNbaGv0+crwEJz+Wjgy3377W3antBBNOmafpsx6lpubaqzN626f5N6nq3D\nJ0nS/Gh/oRpJkuZEVVWS2uBtJlrTbzNGXctt1Cs0DWNadf/GsbrRWqzDJ0nS/LCDSJKk6XpwZepY\nkqOA/U37PuDYvv2Oadoki2pKkqSRe8q0A5Akac5dB7y2ufxa4Nq+9tek56XAI9YfkiRJ0rjYQSTN\niCSXJdmf5K6+tiOS3JDk883vZzftSfKHSXYnuSPJS6YXuTQ/klwFfBJ4QZK9Sc4BdgGvSPJ54Oeb\n6wDXA/cDu4H3Ar8xhZAlSZI0J5xiJs2Oy3H5bKnVqurMdTa9fI19CzhvvBFJkiRJPY4gkmZEVd0M\nfGNV83Z6y2bT/P7lvvYrq+cW4PCm9okkSZIkaQ45gkiabTO/fHa/USzH3Kbls1dMaxntzdrIc+AS\n2pIkSVI72EEkzYlZXT673yiWY27T8tkrprWM9mZtZPltl9CWJEmS2sEpZtJse3Bl6pjLZ0uSJEmS\n1mMHkTTbXD5bkiRJknRI3ZmzIOmgmuWzF4Ejk+wFLqC3XPY1zVLaXwJOb3a/HjiV3vLZ3wZeN/GA\nJUmSJEmtYQeRNCNcPluSJEnzIMllwCuB/VX1oqbtCOD9wBZgD3B6VT2UJMC76Z0c/TZwdlXdNo24\npbZzipkkSZIkqUsuB05e1bYTuLGqjgNubK4DnAIc1/ycC1w8oRilzrGDSJIkSZLUGVV1M/CNVc3b\ngSuay1cAv9zXfmX13AIcvrKIi6Qn6swUsy0tXHpakiRJ8yPJHuBR4DFguaq2rTetZVoxSnNsoW/R\nla8AC83lo4Ev9+23t2lzgRZplaE7iPyglCRJ0hz52ar6Wt/1lWktu5LsbK6/eTqhSYJevc0ktZHb\nJDmX3hQ0FhYWWFpaWnO/AwcOrLutK0Z1DDu2Lg8fzCYtHDbdx18xzN+xja+lUY0g8oNSkiRJ82g7\nvVVEoTetZQm/90rT8GCSo6rqgWYK2f6mfR9wbN9+xzRtT1BVlwCXAGzbtq0WFxfXfJClpSXW29YV\nozqGs6c4y2fH1mUuunP6E6L2vHpx07dt42tpXH9RPyglSZI0awr4WDMy4U+bfyjXm9byuI2OTGjD\nWfF+bTlTv1pb44LRxDaOkQVtHLEwQtcBrwV2Nb+v7Ws/P8nVwEnAI305K6nPKDqINvVBKUmSJHXM\nT1fVviQ/AtyQ5HP9G9eb1rLRkQnTPCu/lracqV+trXHBaGIbZmTCeto4YmEzklxFb0DCkUn2AhfQ\n6xi6Jsk5wJeA05vdr6e3xP1uesvcv27iAUsdMYp31E19UA56JmXFtM8OtPkMxWpdiXVacW70rMmM\nn2mRJEkDqqp9ze/9ST4EnMj601okjUlVnbnOppevsW8B5403Imk2DN1BtNkPykHPpKyY9pmUNp+h\nWK0rsU4rzo2ejZmVMy2SJGnzkjwTeEpVPdpc/gXg91h/WoskSZ0y1H/nflCqi7ZssLNxx9blJ3RQ\n7tl12qhDkiRJ7bcAfCgJ9L5D/1lV/UWSz7D2tBZJkjpl2OEbflBKkqSBbbSTXmqLqrof+Ik12r/O\nGtNaJEmzb5jvNSsDEdo0AGGoDiI/KCVJkiRJkrrvKdMOQJIkSZIkSdNlB5EkSZIkSdKcs4NIkiRJ\nkiRpztlBJEmSJEmSNOeGXcVMkiRJkjRio1j1sU2rI0lqP0cQSZIkSZIkzTlHEEmS1AJJ9gCPAo8B\ny1W1LckRwPuBLcAe4PSqemhaMUqSpNkxilFqmi2OIJIkqT1+tqpOqKptzfWdwI1VdRxwY3NdkiRJ\nGjk7iCRJaq/twBXN5SuAX55iLJIkSZphTjGT5sC8TF25c98jnO1QWXVXAR9LUsCfVtUlwEJVPdBs\n/wqwsPpGSc4FzgVYWFhgaWlpQuEO7sCBA4/HtWPr8nSDGbGFw7p5TIO+TvqfO0mSNNvsIJLmx89W\n1df6rq9MXdmVZGdz/c3TCU0S8NNVtS/JjwA3JPlc/8aqqqbziFXtlwCXAGzbtq0WFxcnEuxGLC0t\nsRLXrHXi7ti6zEV3du/r1J5XLw60X/9zJ0mSZptTzKT55dQVqUWqal/zez/wIeBE4MEkRwE0v/dP\nL0JJkiTNsu6d8pK0GTM7daVfV6d6HErXjmsjrxOnr/QkeSbwlKp6tLn8C8DvAdcBrwV2Nb+vnV6U\nkiRJmmV2EEnzYWanrvT7o/dd28mpHofStSksg05dAaev9FkAPpQEep/Nf1ZVf5HkM8A1Sc4BvgSc\nPsUYJUlqvXmpvSmNQ3f+45C0af1TV5I8YepKVT3g1BVpuqrqfuAn1mj/OvDyyUckSVKnWXtT2oRN\ndxAlORa4kt5ZzwIuqap3J3kb8GvAV5td31pV1w8bqKTNceqKJm3LBooQ79i6vGbR4j27ThtlSJJW\nGTRP18tRmK889Xuv1HnbgcXm8hXAEnYQSU8yzAiiZWBHVd2W5AeBzya5odn2rqp6x/DhSRoBp65I\nkjQcv/dK3bGp2puShuggahLsgebyo0nuBY4eVWCSRsOpK5IkDcfvvVKnbKr25qCLs8zCAhsrx9Cl\nRVBW69oiLmtZOYY2vZ5GUoMoyRbgxcCngJcB5yd5DXArvbMtTyoAttHVkab95HfpBdiVWLsaZ5sS\nWJIkTdY4v/e29Z+2tn5na2tc0J7YVr/WZqFz41A2W3tz0MVZZmGBjZVjWG8KcRd0bRGXtawcw0YW\neBm3of+iSZ4FfAB4U1V9M8nFwNvpDe17O3AR8PrVt9vo6kjTfvF26QXYlVi7GmebEliSJE3OuL/3\ntvWftrZ+Z2trXNCe2FZ/b52Fzo2DsfamNJyh3rWSPJ3eh+T7quqDAFX1YN/29wIfHipCSZIkacr8\n3it1grU3pSEMs4pZgEuBe6vqnX3tR/UVAHsVcNdwIUqSJEnT4/deqRusvSkNZ5gRRC8DzgLuTHJ7\n0/ZW4MwkJ9AbarsHeMNQEUqSJEnT5fdeSdLMG2YVs08AWWPT9ZsPR5IkSWoXv/dKkubB9CunSZKk\nztiyieK5O7Yut67oriRJkp7oKdMOQJIkSZIkSdPlCCJJkiRJmkGrR31udETnnl2njTokSS3mCCJJ\nkiRJkqQ5ZweRJEmSJEnSnLODSJIkSZIkac7ZQSRJkiRJkjTnLFItSZIkSVKHrC5AvhEbLVau+WEH\nkaTWGOaDDmDH1hEFIkmSJElzxilmkiRJkiRJc84OIkmSJEmSpDlnB5EkSZIkSdKcswaRJEmSNmzY\nunF7dp02okgkSequNn2e2kEkSWqdNn1QSpIkSfPAKWaSJEmSJElzbmwdRElOTnJfkt1Jdo7rcSRt\nnnkqtZ95KrWfeSq1n3kqHdpYppgleSrwx8ArgL3AZ5JcV1X3jOPxJG2ceSq13zjydNjpe5KeyM9T\nqf3MU2kw46pBdCKwu6ruB0hyNbAdMAGl9hh5nvqPpzRyfp5K7WeeSu1nnkoDSFWN/k6TXwFOrqp/\n2lw/Czipqs7v2+dc4Nzm6guA+0YeyGgdCXxt2kEMqCuxzmqcP1ZVzxlXMKNinnbKrB4XTO/YzNPJ\n8jXcXdM8vnnM07a+noxr49oa26jjMk+7yWNoh0kdw8B5OrVVzKrqEuCSaT3+RiW5taq2TTuOQXQl\nVuNsP/O0HWb1uGC2j21SupCns/w8z/Kxwewf36QMmqdt/Xsb18a1Nba2xtUGXc/TjfAY2qGNxzCu\nItX7gGP7rh/TtElqD/NUaj/zVGo/81RqP/NUGsC4Oog+AxyX5HlJfgA4A7huTI8laXPMU6n9zFOp\n/cxTqf3MU2kAY5liVlXLSc4HPgo8Fbisqu4ex2NNUKuH76/SlViNc4rM006Z1eOC2T62oc1Qns7y\n8zzLxwazf3xDG3GetvXvbVwb19bY2hrXWM1Jnm6Ex9AOrTuGsRSpliRJkiRJUneMa4qZJEmSJEmS\nOsIOIkmSJEmSpDlnB9EGJPnVJHcn+V6SVi1HB5Dk5CT3JdmdZOe041lPksuS7E9y17RjWU+SY5Pc\nlOSe5jl/47Rj0qEl+YMkn0tyR5IPJTl82jENqyt5vVHm2PwxP7vFHJ2etuZK274HtzH/2vod13we\nnyQ7klSSI6cdy0a19b1mEG3M/41oc07aQbQxdwH/CLh52oGsluSpwB8DpwDHA2cmOX66Ua3rcuDk\naQdxCMvAjqo6HngpcF6L/576vhuAF1XV/8/encfLVdf3H3+92RHQQMErJNFYRVowFm0ELLZeRWW1\nwVYRatmkoi1UramK6K+mIjVtBVxQFIQGlC0VKRSjssgFaQUEyiIgEiGYxJDInoCigc/vj+93yMlk\n7r1z7yznzMz7+Xjcx52zzufMmc+cM9/5Lq8CfgZ8vOR4WtJjeT1RzrHB4/zsLc7R8lQ1VypzH1zh\n/JtPNe9xnc8dIGk68FbgF2XHMklV/awZU4XzfyIqm5MuIJqAiLg7Iu4pO45R7AYsioj7IuK3wAXA\n7JJjaigirgUeKTuOsUTE8oi4JT9eBdwNTC03KhtPRFweEWvy5PXAtDLjaYOeyeuJco4NHudnb3GO\nlqequVKx++BK5l9V73Gdzx1zCvBRoCdHfarqZ00TKpn/E1HlnHQBUf+YCiwpTC+lIm+yXidpBvBq\n4IZyI7EJeg/w3bKDaNFA5LVzbCA5P3uIc7RU/ZArnTAw+dduzuf2kDQbWBYRt5UdS5v00mdNX+V/\n1XJyo7IDqBpJVwIvarDoExFxSbfjsXJJ2hK4CPhQRDxRdjzWXI5K+gSp6ua53YzNJs451l+cn/3H\nOdoZVc0V3wf3N+fzxIyVD8DxpOZllVbVzxpLqpiTLiCqExFvLjuGSVoGTC9MT8vzbJIkbUxK2HMj\n4ttlx2PJeDkq6QjgAGCviOjJKr8FfZ3XzrH+4/zsn/wE52gnVTVXeug+uO/zr92czxM3Wj5Imgm8\nFLhNEqT33y2SdouIB7sY4riq+lnTor7I/6rmpJuY9Y8fAztKeqmkTYCDgUtLjqlnKX3anwncHREn\nlx2PNUfSPqS24H8eEU+VHU8b9G1eO8cGj/OztzhHy9OHudIJfZ1/7eZ8bq+IuCMiXhgRMyJiBqmJ\n02uqVjg0nh7+rOn5/K9yTrqAaAIkvV3SUuB1wHckfb/smGpyB2PHAt8ndXK1ICLuLDeqxiSdD/wI\n2EnSUklHlR1TA3sChwJvknRr/tuv7KBsXKcCWwFX5HP21bIDakUv5fUkOMcGj/OztzhHy1PJXKnS\nfXBV86/C97jOZ2ukkp8146lq/k9QZXNSvVOTzMzMzMzMzMzMOsE1iMzMzMzMzMzMBpwLiMzMzMzM\nzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzM\nzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwL\niMzMzMzMzMzMBpwLiMzMzGxcku6UNFx2HGWQtFrS75cdB4CkF+d4Niw5ju9KOrzMGKwx52o1crVI\n0gxJIWmjPO38MZsESYslvbmF7Sv5GVElLiAyM+sRkjaX9N+SHpf0n2XHY4MlInaJiJF271fSEZKu\na/d+J0vSiKS/Kc6LiC0j4r6yYiqKiF/keJ4pOY59I+LsMmOwxpyrk8/Vbh1jWfnT6DUzG08u3Hx5\n2XG0Q/EzQtJ8SZ8pO6aqcQGRNS0n0W9zyesjkq6Q9Adlx2U2QN4BDAG/FxHvnOxOqnaTb9VW+8W7\nqiYSX9WPpdN64fh7Icaqqvpr51ztfWXXXLTJG/ScGvTjnwgXENlE/VtEbAlMBZYBZ5Ycj1nXKdlg\nvHkd8BLgZxGxpsPPMyZfZHtHror9cUl3SXpU0n9I2iwvO0DSrZIek/S/kl5Vt93HJN0OPClpo2K1\nbklzJf2npG9KWiXpDkmvyM+1UtISSW8t7O8Fks6UtFzSMkmfkbShpD8Evgq8Lv/48Fhef1NJn5P0\nC0krJH1V0uZ52bCkpTm+B4H/GOP411tX0taSLpP0q/yaXCZpWl7/ROBPgVNzPKfm+c/9epqP5Zy8\n/QOSPjle7udC2f+RdEp+ve+T9Cd5/pL8mh1eWH9/Sf8n6Ym8fG5hWX1TlR0kXZp/uFkk6b2FdedK\n+lY+T08AR4wR40TP6XM1EfJxXJfP2aOS7pe0b2HdtsTYz5yr5efqGMc4mZzfML8uD0m6D9i/bnkx\nf14m6QeSHs7rnytpSt05/oik2yU9mc/PkFIztVWSrpS0dWH9PfL75DFJtyk3NxzjNfsDpR99H5F0\nj6SDCvuaL+k0SQslPQm8cazjtmpp8PnwYkkX5ffy/ZI+UFh3Q0nHS/p5fl/dLGm6pGvzKrfl9827\nxsrNvK8RSScoXfdWSbpc0raF5YflXHpY0v/Tup9Z69TqqX02jHJ8u0n6UX6vL5d0qqRNCstD0jGS\n7gXuLcyorN3wAAAgAElEQVR7uaSjgXcDH83H9d85zy6qe44vSvpCC6eh90SE/yr0BywGPgLcDjxJ\nKoAZAr4LrAKuBLbO6+4B/C/wGHAbMFzYz5HA3Xmb+4D3FZYNA0uBOcBKYDlwZBOxzQc+U5jeD3iy\n7NfMf/6byF/OsX/MOfY4cCGwGbA1cBnwK+DR/HhaYbsR4ETgf4BfAy8fZd4OwKXAI8Ai4L15+83y\nOtvm6U8Aa4Dn5+kTgM+PEfc/A78FfgesBo4CXgb8AHgYeAg4F5hS2GY68O18TA8DpwJ/CPwGeCbv\n57G87guAc/K6DwCfBDbIy47Ix3hK3s9n2nEu/Ne19/tP8nthm3wePwO8On/+7w5sCBye1920sN2t\nebvNC/PenB/Pze+jvYGN8nvn/vy+3hh4L3B/IY6Lga8BWwAvBG4kX5fy++u6urhPyXm0DbAV8N/A\nZ/Oy4Zw7/wpsWotvlONfb13g94C/BJ6X9/2fwH8VthkB/qZuPwG8PD8+B7gkbzsD+Blw1Djn4Ygc\nx5H59f4M8Avgyzmut5Ku11sW4p5J+iHvVcAK4MC8bEaOZ6M8fS3wFdJnzK6kHH5T4Tz9Djgw72us\n12qi5/S51ykf3+/yOhsCfwv8ElA7Y+znP5yr661Leblaf4yT2c/7gZ8WzufVrJu3z8VOund4Sz7u\n7Uj58vnCvhYD15O+D0zN74db8ntjM9J9wKfyulNJ1+n9SPn0ljy9XaPXLJ/nJaTPpo3yPh8Cds7L\n55PulfbM+9us7FzxX/N/rPv5sAVwM/BPwCbA75O+I+6d1/0IcAewEyDgj0g11tfJqzzdTG7+HHhF\nzuURYF5etjPp/vP1OY7Pka4Btc+s+az7fXMYWFp3TLV1/5j0fXijnJt3Ax8qrBvAFTkHN68/lgbP\ntT3p+/eUPL1Rzrc/LvtcdvV9U3YA/qs7IU1eBJq4AOxP+vIo4A3AU8Br8rJh0kX406Sbg/3y8q3H\nie25JMofMt8Abiv7NfOf/ybyl3PsRlJBzjb5YvL+Ji92vwB2yReMjUeZN9YXoWuBv8yPLyddPPct\nLHv7OLHPBb5ZmB71ppL0ReI20s37Fjme1+dlRzCBG2DWfrn9+3ycA/kFrhf/8vv9/YXp/fL77jTg\nhLp17wHeUNjuPQ32VfzSeUVh2dtIN3wb5umtSDdhU0jXs6eL7xvgEODqRu9H0nXrSeBlhXmvI3+J\nJV3DfksTX1SaWTfn6aOF6RFG+dKZ8+q35C9Pedn7gJFx4jgCuLcwPTPvc6gw72Fg11G2/zxwSn48\nI2+7Eemm/xlgq8K6nwXmF87TtU2+V5o+p/WvUz6+RYVtn5fXfVE7Y+znP5yr465L93K1eIyT3c8P\n6s7nWxmlgKjBtgcC/1d3Pt9dmL4IOK0w/ffk+xXgY8A36vb3feDwRs8LvAv4Yd36X2NtgdN84Jyy\n88N/k/srfj6QCpl/Ubf848B/5Mf3ALNH2c86BUQNljfKzU8Wpv8O+F5+/E/A+YVlz8s5NuECogZx\nfAi4uC7uN412LPXPled9l7U/7h4A3FX2eez2n5sJVNOXImIFgKQfAisj4v/y9MXAXsBfAwsjYmHe\n5gpJN5FuKM6OiO8U9neNpMtJ1UpvyfN+B3w6UlOVhZJWk0qMrx8ntn+UdCzwfFItg9ktHqtZGb4Y\nEb8EkPTfpC9lXyXddJHnn0j6xa9ofkTcWVhnnXmSppN+Zds/In4D3Crp68BhpJvFa4A3SLqEVCvg\ns3n6auC1pAKepkXEIlItJYBfSTqZVIAMsBupEOwjsbZJWsN+h5T6FDg4vw6rgFWSTgIOZW0z0l9G\nxJfy41KbuNmELSk8foD0vngJcLikvy8s2yQva7RdIysKj38NPBRrO07+df6/Zd7nxsDynDOQftgY\nbf/bkW4Yby6sL9IXtZpf5RxrxjrrSnoeqeB0H1LNQYCtJG0Y43f8vG0+lgcK8x4g/WgznvrXi9q1\nvjBvyxzj7sA84JWk87IpqdC63g7AIzlvi/HMKkyPdx7HinG0c/pYg20frD2IiKfyuduSVPjezhj7\nmXO1Grnajv3swPrnsyFJQ8AXSPfpW5Fe80frVqs/hw0/O0jvl3dKelth+casfz9DYf3dlZvTZRuR\nfgSucX72ttr5ewmwQ9253hD4YX48nVQoPa4mc/PBwiZPsfY9uk5u5OvFw00eS30crwBOJl1Pnkd6\n795ct9pE379nk2rBnkH6vv2NsVfvP+6DqJqauQjULgCP1f5IVfW2B5C0r6Trc3vix0gFR9sW9vNw\nrNuPSTFxx/K5iJhC+gXz16RCJbNes95FS9LzJH0tt4l+glRYM0XrdsjY6CJTnDfal7XajeQ1pF9C\nXkOqxnsFqYbfHqRf3yd0gVTqg+ACpX4ingC+ydo8nw48EM31V9TMDbBvEHvX9MLjF5Oa/iwBToyI\nKYW/50XE+YV1o03Pv4RUK2HbwnM9PyJ2GeV5HiJdX3YprP+CSP3fTSa2+nXnkK5du0fE84E/y/M1\nyvr1sf2OdA2ueTGpT752Oo/UbGd6RLyA1C+KGqz3S2AbSVuNEU+7zuNk9UKMVeFcXVcZudroGCez\nn+Wsfz5H8y/5eWfm4/xrGud7M5aQahAV3y9bRMS8vLz++JYA19Stv2VE/G1hHednb6udvyWk2n3F\nc71VROxXWP6yJvc5Xm6OZTlQ7K+o1py05klSYU/Ni8bY12mkppw75jiObxDDWO/fRsv+C3iVpFeS\nahCdO8b2fckFRL1r1AuApE1JNSE+R6q+PgVYyOQvNuuJiF8AHwS+kBPbrNc1c7FrdCEpzhvvi9D/\n5ud4O+mG7K68fD9S4dFEjXVTuQR4sRp3KD2ZG2DfIPauYyRNk7QNqd+RC0m/jL1f0u5KtlDqGHmr\nsXc1cRGxnNSk8iRJz5e0gVKnrG/Iq6wAptU6loyIZ3N8p0h6IYCkqZL2blNIW5G+1D6WX5NP1S1f\nQeqbodGxPAMsAE6UtJWklwAfJhXOttNWpMLm30jaDfirUeJZQvpc+aykzZQ6Lz6qA/FMWi/EWCHO\n1XWVkav1xzjZ/SwAPpDP59bAcWOsuxWp2d/jkqaS+oKZrG8Cb5O0t1Knw5spdfJb+0Je/5pdBrxC\n0qGSNs5/r1XqsNv6y42kGuIfk7R5fn+8UtJr8/KvAydI2jF/1rxKUq3gpv59M15ujuVbpPfon+Q8\nm8u699q3AvtJ2kbSi0jNxkazFfAEsFppZO2/HWPdRtb7DMm1GL9F+qHmxvydd6C4gKh3jXUBqFVH\n/xWwRmkkkbeOtbPJiIgrSF+Ij273vs1K0MrFDhj/i1BEPEWq+noMawuE/pfUB9JkCojGuqm8kfQr\nzbz8hWIzSXvmZe26AbbecB7pS999pOrjn4mIm0id055KasqwiM6OHnUY6dp0V36+b5FrvJKaX94J\nPCjpoTzvYzmm63PtuCtpX43Vz5M6zXyI1Kz6e3XLvwC8Q2lkli822P7vSb9w3kdqtnkecFabYqv5\nO+DTklaR+mtYMMa6h5Bq9f6S1MHwpyLiyjbH06peiLEKnKvrKiNXGx3jZPZzBqnvn9tI3Tt8e4x1\n/5lUs/hx4DvjrDumfB8ym1ST4lekH4s+wtrvfOu8ZrnG81tJzcx/SaphXeso3PpIvtc7gNRf0P2k\nvPo6aZASSE21FpA+g54gdTFQqwQwFzhbqdXKQYyfm2PFcScppy4g3aeuJvW5+3Re5RukvFmcY7lw\njN39I+kHlFWknBtr3UbOBHbOx/Vfhflnk/oKHLjmZbB2dAmrCEmLSZ3HXZmnv0lqejI3T/8NcHBE\nvFmpj4J/I72BnyF9IfzbiPiFpGNIN5WbkkaU2Djv55NKw11+MyKmjfa8o8Q2n9RJ2CcL895F+kD5\n/Yh4erRtzaqiQY7NJXVo+VHSTd8s0k3SSaRmHRtHxBpJI6S8+XphX43mTcvb/Qnp5vrfc/9GteWf\nJf0aMiUinlbq0+tLwIvq+iNpFPtcUsd6f52ndyF1Lr0T6Qb9G8A/1HJb0ouBL5L6NQjgvIj4QC4Y\nupjUmeizEbFt/oXzS6SRbn5DutB+JiKelXREfs1e38xrbNXRzGe79RZJv0/qRH7j8E1c33Cumtkg\nklTr127HiLi/7Hjgufvnn5LuzZ8oO55ucwGRmZlZn/KXzv4j6c9JI5o121eE9QDnqlnzlAYFOYc0\n8l4Ap0fEF3IN8AtJNRYXAwdFxKOSRKo9VRu5+YiIuKXRvq3zlDpRv4rUtOwk0ghrr6nCjx6SNiBV\nfnh+RLyn7HjK4CZmZmZm1rMkHS9pdYO/73Y5jq+OEsdXx9+66ef4MHA6Y/dnMtb23x0lxuPbFaPZ\naPotV7uR8zaqNcCciNiZNNDHMZJ2Jn02XhURO5IKIGqflfsCO+a/o0mdG1t5ZpNq6/+SdE4Orkjh\n0Bak5nVvYRJdTfQL1yCydUi6k3U7qq15X0QMXC/uvULSZqRRtzYlDfH4rYj4lKSXktr4/h6p75tD\nI+K3Sh2ZnwP8MfAw8K6IWFxK8LYO56CZmZlZ8yRdQuqn61RgOCKWS9oeGImInSR9LT8+P69/T229\n8qI2q6ZGo9vYACsMZWq95WngTRGxWtLGwHX5F7kPk5oiXJB/0TqK9KvJUcCjEfFySQeTOiR8V1nB\n21rOQTMzM7PmSJoBvBq4gTR6c63Q50FSEzSAqaQOu2uW5nkuIDKrU4kCom233TZmzJhRynM/+eST\nbLHFFqU8dyf4eMp38803PxQR23XzOXO1zNV5cuP8F8CbWDs88tmkUQhOI1XtnJvnfws4VZLGqt5Z\nZp4W9eJ7YiL6/figGsdYRp52QyfztArnzXE0VpVY2h2H87SxqpzvThuU44TePtYy8zR3cHwR8KGI\neCJ1NZREREiaUFMZSUeTR2fefPPN/3j69OnrrfPss8+ywQa92UtLr8beq3FDdWL/2c9+1nSeVqKA\naMaMGdx0002lPPfIyAjDw8OlPHcn+HjKJ+mBkp53Q1IzspcDXyYNkftYRKzJq9R+LYHCLyl5hK7H\nSc3QHqrb53MXyqGhIT73uc91+jDGtXr1arbccsuyw+iYfj8+qMYxvvGNbywlTzutk9fTqnweO471\nVSWWdsdR1vW001rN06qc704blOOE3j7WEu97NyYVDp0bEd/Os1dI2r7QxGxlnr8MKJb2TMvz1hER\np5P6eWPWrFnRKE97+Vz1auy9GjdUJ/aJ5GklCojMrHUR8Qywq6QppCHM/6AN+1znQlmFD7iqfNB2\nSr8fHwzGMZqZmVln5FHJzgTujoiTC4suBQ4H5uX/lxTmHyvpAtKIWY+7/yGzxlxAZNZnIuIxSVcD\nrwOmSNoo1yIq/lpS+yVlqaSNgBeQOqs2MzMzM6uyPYFDgTsk3ZrnHU8qGFog6SjgAeCgvGwhaYj7\nRaRh7o/sbrhmvcMFRGZ9QNJ2wO9y4dDmpOEZ/xW4GngHaSSz+l9SDgd+lJf/oArDS5qZmZmZjSUi\nrgM0yuK9GqwfwDEdDcqsT7iAyKw/bA+cnfsh2gBYEBGXSboLuEDSZ4D/I1XHJf//hqRFwCPAwWUE\nbWZmZmZmZtXgAiKzPhARt5OG+Kyffx+wW4P5vwHe2YXQzMzMzMzMrAe4gKiHzDjuO+OuM2fmGo4Y\nZb3F8/Zvd0hmVqeZPB3L/H16c5hbM5uYVj8rfE23fnfHssdHvadthnPEzJrh6/G6Nig7ADMzMzMz\nMzMzK5cLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzMzMzMzMzMBpwLiMzM\nzMzMzMzMBpwLiMzMzMzMzMzMBtxGZQdgZmZm1k0zjvtOS9svnrd/myIxMzMzqw7XIDIzMzMzAyRt\nJulGSbdJulPSP+f5L5V0g6RFki6UtEmev2meXpSXzygzfjMzs1a4gMjMzMzMLHkaeFNE/BGwK7CP\npD2AfwVOiYiXA48CR+X1jwIezfNPyeuZmZn1JBcQmZmZmZkBkazOkxvnvwDeBHwrzz8bODA/np2n\nycv3kqQuhWtmZtZW7oPIzMzMekqrfQiZjUXShsDNwMuBLwM/Bx6LiDV5laXA1Px4KrAEICLWSHoc\n+D3gobp9Hg0cDTA0NMTIyMik41u9enVL2/eKoc1hzsw14684il56jQblnJr1o7HuSebMXMMRTdyz\nVKlvQxcQDZB23FBX6c1rZmZm1m4R8Qywq6QpwMXAH7Rhn6cDpwPMmjUrhoeHJ72vkZERWtm+V3zp\n3Es46Y7Jf1VZ/O7h9gXTYYNyTs2s+sZtYiZpuqSrJd2VO+v7YJ6/jaQrJN2b/2+d50vSF3NnfbdL\nek2nD8LMzMzMrJ0i4jHgauB1wBRJtdKKacCy/HgZMB0gL38B8HCXQzUzM2uLZvogWgPMiYidgT2A\nYyTtDBwHXBUROwJX5WmAfYEd89/RwGltj9rM1jFGQe5cScsk3Zr/9its8/FckHuPpL3Li97MzKwa\nJG2Xaw4haXPgLcDdpIKid+TVDgcuyY8vzdPk5T+IiOhexGZmZu0zbr3NiFgOLM+PV0m6m9TeejYw\nnFc7GxgBPpbnn5MvjtdLmiJp+7wfM+uMWkHuLZK2Am6WdEVedkpEfK64ci7kPRjYBdgBuFLSK3K1\nejMzs0G1PXB27odoA2BBRFwm6S7gAkmfAf4PODOvfybwDUmLgEdI11YzM7OeNKGGvZJmAK8GbgCG\nCoU+DwJD+fFznfVltY781ikgamdnfa3opU7hmumor9UO/cbT7deql85PmcYoyB3NbOCCiHgauD/f\n2O4G/KjjwZqZmVVURNxOutetn38f6TpZP/83wDu7EJqZmVnHNV1AJGlL4CLgQxHxRHEEz4gISROq\nTtvOzvpa0UudwjXTA/qcmWta6tBvPN3u8K+Xzk9V1BXk7gkcK+kw4CZSLaNHSYVH1xc2K47IUtxX\nJQpyi6peaNhqAW3Vj68dBuEYG5F0FnAAsDIiXpnnzQXeC/wqr3Z8RCzMyz4OHAU8A3wgIr7f9aDN\nzMzMbGA0VZIgaWNS4dC5EfHtPHtFremYpO2BlXn+c531ZcWO/MysgxoU5J4GnABE/n8S8J5m91eV\ngtyiqhcaNlOQO5b5+2xR6eNrh6qfww6aD5wKnFM3381AzczMzKx0zYxiJlL76rsj4uTComKnfPWd\n9R2WRzPbA3jc/Q+ZdV6jgtyIWBERz0TEs8AZrK0e74Jcsy6LiGtJfZQ047lmoBFxP1BrBmpmZmZm\n1hHN1CDaEzgUuEPSrXne8cA8YIGko4AHgIPysoXAfqSb2aeAI9sasZmtZ7SC3LoO4t8O/CQ/vhQ4\nT9LJpNoJOwI3djFkM1tr0s1AoXtNQavSNHD16tXMmVluRaqRkZGWX49Wm6MWn7tK56YKcZiZmdnk\nNDOK2XWARlm8V4P1AzimxbjMbGJGK8g9RNKupCZmi4H3AUTEnZIWAHeRRkA7xk1XzErRUjNQ6F5T\n0Ko0DRwZGeGk654sNYbF7x5u+fVotTlqsU/AKp2bKsRhZmZmk9O53oxtPTNavBk0G80YBbkLx9jm\nRODEjgVlZuOKiBW1x5LOAC7Lk24GamZmZmZdNW4fRGZmZtYZeZCHmvpmoAdL2lTSS3EzUDMzMzPr\nMNcgMjMz6wJJ5wPDwLaSlgKfAobdDNTMzMzMqsAFRGZmZl0QEYc0mH3mGOu7GaiZmVkdSWcBBwAr\nI+KVed5c4L3Ar/Jqx0fEwrzs48BRwDPAByLi+10P2qxHuImZmZmZmZmZ9Yr5wD4N5p8SEbvmv1rh\n0M7AwcAueZuvSNqwa5Ga9RgXEJmZmZmZmVlPiIhrgUeaXH02cEFEPB0R9wOLgN06FpxZj3MTMzMz\nMzMzM+t1x0o6DLgJmBMRjwJTgesL6yzN89Yj6WjgaIChoSFGRkbWW2f16tUN5/eCXo2903HPmbmm\nY/se2ry5/VfpvLiAyMzMzMwMkDQdOAcYInUef3pEfMH9m5hV3mnACaS8PQE4CXjPRHYQEacDpwPM\nmjUrhoeH11tnZGSERvN7Qa/G3um4jzjuOx3b95yZazjpjvGLXBa/e7hjMUyUC4jMzMzMzJI1pJoH\nt0jaCrhZ0hV52SkR8bniynX9m+wAXCnpFR510Ky7ImJF7bGkM4DL8uQyYHph1Wl5npk14D6IzMzM\nzMyAiFgeEbfkx6uAuxmlOUrm/k3MKkDS9oXJtwM/yY8vBQ6WtKmklwI7Ajd2Oz6zXuEaRGZmZmZm\ndSTNAF4N3ADsSQv9mzTTt0mzerUfkYlqtu+O0fTSazQo57RdJJ0PDAPbSloKfAoYlrQrqYnZYuB9\nABFxp6QFwF2kGoLHuIaf2ehcQGRmZmZmViBpS+Ai4EMR8YSklvo3aaZvk2b1aj8iE/Wlcy9pqu+O\n0VSpT4/xDMo5bZeIOKTB7DPHWP9E4MTORWTWP9zEzMzMzMwsk7QxqXDo3Ij4NqT+TSLimYh4FjiD\ntc3I3L+JmZn1DdcgMjMzM5uAGcd9hzkz13R05BMrhySRaiLcHREnF+ZvHxHL82R9/ybnSTqZ1Em1\n+zcxM7Oe5QIiMzMzM7NkT+BQ4A5Jt+Z5xwOHuH8TMzPrdy4gMjMzMzMDIuI6QA0WLRxjG/dvYmZm\nfcF9EJn1AUnTJV0t6S5Jd0r6YJ6/jaQrJN2b/2+d50vSFyUtknS7pNeUewRmZmZmZmZWJhcQmfWH\nNaQhd3cG9gCOkbQzcBxwVUTsCFyVpwH2JfWTsCNp2N3Tuh+ymZmZmZmZVYULiMz6QEQsj4hb8uNV\nwN3AVGA2cHZe7WzgwPx4NnBOJNcDUyRt3+WwzczMzMzMrCLcB5FZn5E0A3g1cAMwVBh15UFgKD+e\nCiwpbLY0z1temIeko0k1jBgaGmJkZKRTYTdt9erVlYhjNHNmrmlp+6ofXzsMwjGamZmZmfUaFxCZ\n9RFJWwIXAR+KiCfSaL1JRISkmMj+IuJ04HSAWbNmxfDwcBujnZyRkRGqEMdoWh32ev4+W1T6+Nqh\n6ufQzMzMzHrDjBbvvW1d4zYxk3SWpJWSflKYN1fSMkm35r/9Css+nju+vUfS3p0K3MzWJWljUuHQ\nuRHx7Tx7Ra3pWP6/Ms9fBkwvbD4tzzMzMzMzM7MB1EwfRPOBfRrMPyUids1/CwFyp7gHA7vkbb4i\nacN2BWtmjSlVFToTuDsiTi4suhQ4PD8+HLikMP+wPJrZHsDjhaZoZmZmZmZmNmDGbWIWEdfmPk2a\nMRu4ICKeBu6XtAjYDfjRpCM0s2bsCRwK3CHp1jzveGAesEDSUcADwEF52UJgP2AR8BRwZHfDNTMz\nMzMzsypppQ+iYyUdBtxEGl77UVInt9cX1ql1fLueqnR+283OUlvtvLYZQ5t39nm6fZ7cmW1zIuI6\nQKMs3qvB+gEc09GgzMzMzMzMrGdMtoDoNOAEIPL/k4D3TGQHVen8tpudpbbaeW0z5sxcw0l3dK7v\n8cXvHu7YvhtxZ7ZmZmZmZmZmnddMH0TriYgVEfFMRDwLnEFqRgbu+NbMzMzMzMzMrOdMqqqJpO0L\nHdq+HaiNcHYpcJ6kk4EdgB2BG1uO0sxsQNyx7PGWaxsunrd/m6IxMzMzM7NB0cww9+eTOpneSdLS\n3Nntv0m6Q9LtwBuBfwCIiDuBBcBdwPeAYyLimY5Fb2ZmZmbWJpKmS7pa0l2S7pT0wTx/G0lXSLo3\n/986z5ekL0paJOl2Sa8p9wjMzMwmr5lRzA5pMPvMMdY/ETixlaDMzMzMzEqwhjT4yi2StgJulnQF\ncARwVUTMk3QccBzwMWBfUo35HYHdSf107l5K5GZmZi2aVB9EZmZmZmb9JiKWR8Qt+fEq4G7SiLyz\ngbPzamcDB+bHs4FzIrkemCJp+y6HbWZm1hadG+7KzMzMzKxHSZoBvBq4ARgq9L/5IDCUH08FlhQ2\nW5rnLS/MQ9LRwNEAQ0NDjIyMTDqu1atXt7R9rxjaPI3OO1m99BoNyjk1s+pzAZGZmZmZWYGkLYGL\ngA9FxBOSnlsWESEpJrK/iDgdOB1g1qxZMTw8POnYRkZGaGX7XvGlcy/hpDsm/1Vl8buH2xdMhw3K\nOTWz6nMBkZmZmZlZJmljUuHQuRHx7Tx7RW0U39yEbGWevwyYXth8Wp5nZn1uhkedtT7kPojMzMy6\nRNJZklZK+klhnkdHMqsIpapCZwJ3R8TJhUWXAofnx4cDlxTmH5bzdQ/g8UJTNDMzs57iAiIzM7Pu\nmQ/sUzfvONLoSDsCV+VpWHd0pKNJoyOZWWftCRwKvEnSrflvP2Ae8BZJ9wJvztMAC4H7gEXAGcDf\nlRCzmZlZW7iJmZmZWZdExLW549ui2cBwfnw2MEIaPvu50ZGA6yVNqTVx6U60ZoMnIq4DNMrivRqs\nH8AxHQ3KzMysS1xAZGZmVq7KjI40lnaNsnPHssdb2j6NbNRyGC1rdYSlVhXPRVVGQKpKHGZmZjY5\nLiAyMzOriLJHRxpLu0bZOaLFTj3nzFzT0shG7VJ2HMURmqoyAlJV4jAzM7PJcR9EZmZm5VqRR0XC\noyOZmZmNz4M+mHWGC4jM+sAoF8m5kpbVdbJZW/bxfJG8R9Le5URtZplHRzIzM5uY+XjQB7O2cwGR\nWX+Yz/oXSYBTImLX/LcQQNLOwMHALnmbr0jasGuRmg0wSecDPwJ2krRU0lF4dCQzM7MJiYhrgUfq\nZs8mDfZA/n9gYf45kVwPTKnV3DWzdZXfiN/MWjbKyEijmQ1cEBFPA/dLWgTsRvrSamYdFBGHjLLI\noyOZmZm1puODPhQ74291oIJud+rfqwMJjBd3mQNGjKfZAS2qdF5cQGTW346VdBhwEzAnIh4lXRCv\nL6xTu0iup1ujI01E1S9urV6k2jEyUpVfH6j+OTQzM7Pe1qlBH4qd8bc66EJxsIFu6NWBBMaLu9Xz\n0EnNDmjR7ffCWFxAZBMyo9UPwnn7tykSa8JpwAlA5P8nAe+ZyA66NTrSRFT94laFEZqqdJFppOrn\n0BEUNXkAACAASURBVMzMzHrSCknbR8RyD/pgNjkuIGpSqwUjZt0WEStqjyWdAVyWJ32RNDMzM7N+\nUxv0YR7rD/pwrKQLgN3xoA9mo3IBkVmfqv2CkiffDtRGOLsUOE/SycAOpBEdbiwhRDMzM+tTrf64\nOmdmmwKxvpQHfRgGtpW0FPgUqWBoQR4A4gHgoLz6QmA/0qAPTwFHdj1gsx7hAiKzPjDKRXJY0q6k\nJmaLgfcBRMSdkhYAdwFrgGMi4pky4jYzMzMzmygP+mDWGS4gMusDo1wkzxxj/ROBEzsXkZmZmZmZ\nmfWSDcoOwMzMzMysCiSdJWmlpJ8U5s2VtEzSrflvv8Kyj0taJOkeSXuXE7WZmVl7uIDIzMzMzCyZ\nD+zTYP4pEbFr/lsIIGln4GBgl7zNVyRt2LVIzczM2qypJmaSzgIOAFZGxCvzvG2AC4EZpP5NDoqI\nRyUJ+AKpI7CngCMi4pb2h25mZo202jHo4nn7tykSM+uUYp7PmbmGIyaY987zxiLiWkkzmlx9NnBB\nRDwN3C9pEbAb8KMOhWdmZtZRzfZBNB84FTinMO844KqImCfpuDz9MWBf0qhIO5KGETwt/zczMzMz\n60XHSjoMuAmYExGPAlOB6wvrLM3z1iPpaOBogKGhIUZGRiYdyOrVq1vavlvmzFzT0vZDm7e2j154\njWp65ZyaWf9rqoBolF9TZpNGTQI4GxghFRDNBs7JvcVfL2lK3XDbZmZmZma94jTgBNKooCcAJwHv\nmcgOIuJ04HSAWbNmxfDw8KSDGRkZoZXtm9FqTdSktbFw5sxcw0l3TH4fi9893NLzd1M3zqmZWTNa\n6YNoqFDo8yAwlB9PBZYU1hv11xQzMzMzsyqLiBUR8UxEPAucQWpGBrAMmF5YdVqeZ2Zm1pPaMsx9\nRISkmMg27axq24pmq3S2Wk22W1qtjttpEz3PrnJrZmZmZaqrCf92oDbC2aXAeZJOBnYgda9wYwkh\nmpmZtUUrBUQrahdMSdsDK/P8pn5NaWdV21Y0W6Vzop0/lqXV6ridNtHqvq5ya2ZmZt0i6XxSFwrb\nSloKfAoYlrQrqYnZYuB9ABFxp6QFwF3AGuCYiHimjLjNzMzaoZWShEuBw4F5+f8lhfnHSrqA1Dn1\n4+5/yMx6RXv6XTAzs14UEYc0mH3mGOufCJzYuYjMzMy6p9lh7hv9mjIPWCDpKOAB4KC8+kLSEPeL\nSMPcH9nmmM3MzMzMzMyshzXzw+ycmWt6pjVPP2h2FLNGv6YA7NVg3QCOaSUoMzMzMzMzMzPrnup2\nVmNmZmZmZjYJ7Wgyvnje/m2IxMysd7QyzL2ZmZmZmZmZmfUBFxCZmZmZmZmZmQ04FxCZmZmZmZmZ\nmQ0490Fk1icknQUcAKyMiFfmedsAFwIzgMXAQRHxqCQBXyCNOPgUcERE3FJG3GZmZmZmg6bVfrLc\nR5Z1gmsQmfWP+cA+dfOOA66KiB2Bq/I0wL7AjvnvaOC0LsVoZmZmZmZmFeQCIrM+ERHXAo/UzZ4N\nnJ0fnw0cWJh/TiTXA1Mkbd+dSM3MzMzMzKxq3MTMrL8NRcTy/PhBYCg/ngosKay3NM9bXpiHpKNJ\nNYwYGhpiZGSko8E2Y/Xq1R2NY87MNR3bdzOGNi8/hk6f506fQzMbn4cANzMzs3ouIDIbEBERkmKC\n25wOnA4wa9asGB4e7kRoEzIyMkIn4ziiDV+aWjFn5hpOuqPcj+bF7x7u6P47fQ7NzMzMzGzi3MTM\nrL+tqDUdy/9X5vnLgOmF9ableWZmZmZmZjaAXIPIrL9dChwOzMv/LynMP1bSBcDuwOOFpmhmZmYD\ny6OCmpk1px3Nla1aXIPIrE9IOh/4EbCTpKWSjiIVDL1F0r3Am/M0wELgPmARcAbwdyWEbGZmVkXz\n8aigZmY2gFyDyKxPRMQhoyzaq8G6ARzT2YjMzMx6T0RcK2lG3ezZwHB+fDYwAnyMwqigwPWSpkja\n3rVyzcysF7mAyMzM1tFqdWGPbDQ5khYDq4BngDURMWu0Zi1lxWg2wCozKmg3RoIsezRNGIxRPWs8\nuqdNxkTv1+bMXLPeYCy+Z7N6LiAyMzOrjjdGxEOF6VqzlnmSjsvTHysnNDOD8kcF7cZIkGWP6AmD\nMapnjUf3NLOqcB9EZmZm1TWb1JyF/P/AEmMxG2QeFdSsR0haLOkOSbdKuinP20bSFZLuzf+3LjtO\nsypyDSIzM7NqCODyXDPha7nGwWjNWp7TzqYrY6k1gbhj2eMt7WfOzNbiqEKzkyrFAeXFUv9e6/Nm\nMh4V1Ky3uEau2SS4gMjMzKwaXh8RyyS9ELhC0k+LC0dr1tLOpitjqTWBKLvpSRWanVQpDigvlvrm\nN/3STCaPCjoMbCtpKfApUsHQgjxC6APAQXn1haQh7heRhrk/susBm1kzRuto3qx0Ver/sxp3NmZm\nZgMuIpbl/yslXQzsRm7WEhHL65q1mFmHeFRQs543qRq5ZuYCIjMzs9JJ2gLYICJW5cdvBT7N6M1a\nzMzMrLFJ1chtpsl2sSltVZoZN6tRc+QvndvabUWrzcabUaUm3RPVrdjb2bzbBURmZmblGwIulgTp\n2nxeRHxP0o9p3KzFzMzMGphsjdxmmmwXm9KW3eR6oqrUNHoiejVu6F7s7RxxseVoJS0GVgHPAGsi\nYpakbYALgRnAYuCgiHi01ecyMzPrRxFxH/BHDeY/TINmLWZmZrY+18g1a027hrl/Y0TsGhGz8nSt\nl/gdgavytJmZmZmZmVmnDAHXSboNuBH4TkR8j1Qw9BZJ9wJvztNmVqdT9Z3cS7yZdV2rIwCYmZmZ\nWe9yjVyz1rSjgMi9xFvTJvoFfs7MNeu0723nEH5mZmZmVTTW/VL9vVEjvl8yM7PJaEcBUcd6ie+G\nYk/0Y+mVntN7uZf3RuqPp6z3iZmZmZmZmVk/a7mAqJO9xHdDsSf6sfRKL/W93Mt7I/XH084e2s3M\nzMzMzMwsaamTaklbSNqq9pjUS/xPWNtLPLiXeDMzMzMzMzOzSmu1qskQcLGk2r7Oi4jvSfoxsEDS\nUcADwEEtPo+ZtUDSYmAV8AywJiJmSdoGuBCYASwGDoqIR8uK0czMzMzMzMrTUgGRe4k36ylvjIiH\nCtPHAVdFxDxJx+VpjzZoZmZmZmY2gPqns5pxjDYaRDMjQZj1qdnAcH58NjCCC4jMzMzMzMwG0sAU\nEJkNuAAuzyMKfi13Ej8UEcvz8gdJTUbXUZXRBovGGnmwH0bw64eRCMd7nzQ7eqSZVVv9j28T/dGt\nF4did5NtMzPrZy4gMhsMr4+IZZJeCFwh6afFhRERufCIuvmVGG2waKyRB/uhNmA/jEQ43miDzY4e\naWZWUW6ybWZmfamlUczMrDdExLL8fyVwMbAbsELS9gD5/8ryIjQzM+tZs0lNtcn/DywxFjMzs0nr\n7Z+pzWxckrYANoiIVfnxW4FPA5cChwPz8v9LyovSzMysJ3SlyfZYTY2baYrcajPeKjR1rkKT6241\nh3bTazOrChcQmfW/IeBiSZBy/ryI+J6kHwMLJB0FPAAcVGKMwOidyRe5Y3kzMytRV5psj3Wda6Yp\n8nhNfcdThetsFZpct/o6NstNr82sKlxAZNbnIuI+4I8azH8Y2Kv7EZmZmfWmYpNtSes02Y6I5W6y\nbWZmvcwFRGZm1lbj1QRrphZYL45uZGb9zU22zcys37mAyMzMzMxsfD3TZNvMzGwyXEBkZmZmZjYO\nN9m2iWqmb0UYvWata9OaWbd5mHszMzMzMzMzswHnGkRmZmZmZmZ1mq0BZGbWL1xAZGZmNkAm+4Wn\nmc7FzawaXLBhZmaT4SZmZmZmZmZmZmYDzgVEZmZmZmZmZmYDzgVEZmZmZmZmZmYDzgVEZmZmZmZm\nZmYDzp1Um5mZmZmZVUw7OhtfPG//NkRiZoOiZwqIPBqDmZmZmZmZmVln9EwBkRn4lxQzMzMzMzOz\nTnABkZm1jWv6mZmZmZmZ9SZ3Um1mZmZmZmZmNuA6VoNI0j7AF4ANga9HxLxOPZeZTY7z1Kqq1dpo\n/dSU1HlqVn3OU7Pqc56aja8jBUSSNgS+DLwFWAr8WNKlEXFXJ57PbCL8xTNxnppVn/PUrPqcp1Zl\nvu9NnKdmzelUE7PdgEURcV9E/Ba4AJjdoecys8lxnppVn/PUrPqcp2bV5zw1a4Iiov07ld4B7BMR\nf5OnDwV2j4hjC+scDRydJ3cC7ml7IM3ZFniopOfuBB9P+V4SEduVHcR4eixPi3rxPTER/X58UI1j\ndJ5OXBXOGziORqoSS7vjcJ42VpXz3WmDcpzQ28c6aHnay+eqV2Pv1bihOrE3naeljWIWEacDp5f1\n/DWSboqIWWXH0S4+HmunquRpUb+/J/r9+GAwjrGbupWnVTlvjmN9VYmlKnFUUTvzdFBe50E5This\nY62yZvK0l89Vr8beq3FDb8beqSZmy4DphelpeZ6ZVYfz1Kz6nKdm1ec8Nas+56lZEzpVQPRjYEdJ\nL5W0CXAwcGmHnsvMJsd5alZ9zlOz6nOemlWf89SsCR1pYhYRayQdC3yfNIzgWRFxZyeeqw0q1Xym\nDXw81pQey9Oifn9P9PvxwWAcY1tULE+rct4cx/qqEktV4uiqEvJ0UF7nQTlOGKxjLUUb87SXz1Wv\nxt6rcUMPxt6RTqrNzMzMzMzMzKx3dKqJmZmZmZmZmZmZ9QgXEJmZmZmZmZmZDTgXEAGS/l3STyXd\nLuliSVPKjmkyJO0j6R5JiyQdV3Y8rZA0XdLVku6SdKekD5Ydk1VDv+RrI/2Uw/Wc0/2hKvkn6Z35\nffSspK4PH1uVXJV0lqSVkn5SYgzO7RJUJRc7pSo51knOnd7Uy7lX9rVzMnr1s6AK1+fJcgFRcgXw\nyoh4FfAz4OMlxzNhkjYEvgzsC+wMHCJp53KjaskaYE5E7AzsARzT48dj7dPz+dpIH+ZwPed0f6hK\n/v0E+Avg2m4/ccVydT6wT0nPXePcLkdVcrHtKpZjneTc6U29nHulXTsno8c/C+ZT/vV5UlxABETE\n5RGxJk9eD0wrM55J2g1YFBH3RcRvgQuA2SXHNGkRsTwibsmPVwF3A1PLjcqqoE/ytZG+yuF6zun+\nUJX8i4i7I+KeMp6bCuVqRFwLPFLGcxdicG6XoCq52CGVybFOcu70pl7OvZKvnZPRs58FVbg+T5YL\niNb3HuC7ZQcxCVOBJYXppfTJRUbSDODVwA3lRmIV1Kv52kjf5nA953Tf6Kf8m4iBydWJcm6Xpt9y\nceByzLnTs/ot96pm4D4LqmCjsgPoFklXAi9qsOgTEXFJXucTpOqe53YzNhudpC2Bi4APRcQTZcdj\n3eF87V/O6eqrSv41E4dVh3O7/aqSi9ZZzp3q6eXc87XTWjUwBUQR8eaxlks6AjgA2CsioitBtdcy\nYHphelqe17MkbUy6YJ4bEd8uOx7rngHI10b6LofrOad7Q1Xyb7w4StT3uTpRzu3OqEoulmBgcsy5\nU029nHsVvnZOxsB8FlSJm5iRekcHPgr8eUQ8VXY8k/RjYEdJL5W0CXAwcGnJMU2aJAFnAndHxMll\nx2PV0Sf52khf5XA953R/6OP8m4i+ztWJcm6Xo89zcSByzLnTm/o896pmID4LqkYVK/QshaRFwKbA\nw3nW9RHx/hJDmhRJ+wGfBzYEzoqIE0sOadIkvR74IXAH8GyefXxELCwvKquCfsnXRvoph+s5p/tD\nVfJP0tuBLwHbAY8Bt0bE3l18/krkqqTzgWFgW2AF8KmIOLPLMTi3S1CVXOyUquRYJzl3elMv517Z\n187J6NXPgipcnyfLBURmZmZmZmZmZgPOTczMzMzMzMzMzAacC4jMzMzMzMzMzAacC4jMzMzMzMzM\nzAacC4jMzMzMzMzMzAacC4jMzMzMzMzMzAacC4jMzMzMzMzMzAacC4jMzMzMzMzMzAacC4jMzMzM\nzMzMzAacC4jMzMzMzMzMzAacC4jMzMzMzMzMzAacC4jMzMzMzMzMzAacC4gGiKQZkkLSRmXHYmZm\nZmZmZmbV4QIiM7NRSJor6Ztlx2FmjTlHzXqDc9XMGvFnQ/W4gKhkrs1jZmXLF+ffSVqd/+6W9Jdl\nx2Vma0naUdIFkn4l6QlJ90r6kqRpZcdmZknd9fQxSf8r6XVlx2VWhnYV/hRawdTuU1dI+oqkjdsR\np63LBUQlkLRY0sck3Q48KWmmpJF8IblT0p8X1h2R9DeF6SMkXVeYDknvzzeKj0n6siTlZRtK+pyk\nhyTdB+xfF8eIpBMk/Y+kVZIul7RtYfke+cL2mKTbJA3XxXFf3u5+Se/O818u6RpJj+fnvbADL6GZ\ntd+FEbFlRGwJfAj4pqShsoMys3RtBW4Afgm8OiKeD+wJ/Bx4fZmxmdl6LszX0m2Bq4H/LDkes34x\nJefWTOB1wDElx9OXXEBUnkNIBTbbAhcDlwMvBP4eOFfSThPY1wHAa4FXAQcBe+f5783LXg3MAt7R\nYNu/Ao7Mz70J8I8AkqYC3wE+A2yT518kaTtJWwBfBPaNiK2APwFuzfs7IR/L1sA04EsTOA6z0uRC\n22W50PMeSXvVLd9Y0vmSLpK0iaQNJB0n6eeSHpa0QNI2ed2zJc3Jj6fmgtxj8vTLJD2Stx+WtFTS\nHEkrJS2XdGThOTfNhby/yL+WfFXS5nnZtpIuywW4j0j6oaQNmjmW8UTE94FVwMtaeU3N2mnAc3Qu\n8D8R8eGIWAoQESsj4vMRcUGbXmKzthjwXH1ORKwBzgWmStqu1dfVrMoa5Mr+wPHAu5Rq/dyW13up\nUmWCVZKuIH0XnpCIWAlcAezc1oMwwAVEZfpiRCwBdgW2BOZFxG8j4gfAZaQCpGbNi4jHIuIXpF8q\nds3zDwI+HxFLIuIR4LMNtv2PiPhZRPwaWFDY9q+BhRGxMCKejYgrgJuA/fLyZ4FXSto8IpZHxJ15\n/u+AlwA7RMRvIuI6zCpOqUD2WOC1udBzb2BxYfnmwH8BTwMHRcRvSYW5BwJvAHYAHgW+nDe5BhjO\nj98A3Af8WWH6hxHxbJ5+EfACYCpwFPBlSVvnZfOAV5Dy8uV5nX/Ky+YAS4HtgCHSRTjGO5YmXgvl\ni/omwF3NbmfWSc5R3gxcNM46ZqVzrq7zWmwCHAY8nI/JrC+Nkis/Bf6FtTXU/yivfh5wM6lg6ATg\n8Ek83w75Oa5vQ/hWxwVE5VmS/+8ALClc3AAeIF24mvVg4fFTpAKn5/Zdt99mt30J8M78a8pjkh4j\nVWPfPiKeBN4FvB9YLuk7kv4gb/dRQMCNSs3l3jOB4zAryzPApsDOkjaOiMUR8fO87PnA90hNOY6M\niGfy/PcDn4iIpRHxNOkX/nco9St2DfD6/AvknwH/RmoOAumG9prCc/8O+HRE/C4iFgKrgZ0kCTga\n+IeIeCQiVpEutAcXttseeEne9ocREeMcy1gOynm+GrgU+JeIeKy5l8+s4wY9R7elcL2WdGy+Nq+W\ndEZzL6FZVwx6rsLa6+mvSbX535FrE5n1q6ZyRdKLSa1e/l9EPB0R1wL/PYHneSjn1jLgSeBbbYjd\n6riAqDyR//8SmF6rypq9mPTGh/Tmf15h2Ysm8BzLgel1+23WEuAbETGl8LdFRMyD1AQlIt5CuqD+\nFDgjz38wIt4bETsA7wO+otR3glllRcQiUr87c4GVSh3B7pAX70Fqvjkv3zDWvAS4uFCAejfpAjmU\nL4pPkn6p/FNSrcBf5l9Y6m9oH667cawV1G5Hyv2bC8/xvTwf4N+BRcDlSv2BHdfEsYxlQS3PSU3L\nDpP0via2M+s45ygPk663tdfj1IiYAnwecCedVhnOVSBfT0m1kX4C/HET25j1rAnkyg7Ao7myQU2j\nCgyj2Tbn1vOA/wG+P8mQbQwuICrfDaQL2EeV2mQPA28Dan0K3Ar8haTn5YKWoyaw7wXAByRNy1Vs\nj5vAtt8E3iZpb6XOrjdTat89TdKQpNlKfRE9TfqF5lkASe/U2hFVHiUVhD3b8BnMKiQizouI15Nu\nVAP417zoclLzzKu0bqfNS0j9cBULUTeLiFrh7jWkfr82yfOuIVWj3Zq1fXaN5SHSr4+7FPb/gkid\n8xERqyJiTkT8PvDnwIdrfSOMcSzNvhaLge+SPovMKmHAc/Qq4C+aiMmsdAOeq8XX4SFSzaW5krYf\nb32zXjZKrkTdasuBrfN3yJqJVGCoPdevgfnAHioMsGTt4QKikkVqe/02YF/SBewrwGER8dO8yinA\nb4EVwNmkzu6adQapZPU24Bbg2xOIawkwm9QO+1eki/dHSO+ZDYAPk2o/PUL6Bedv86avBW6QVGum\n8sGIuG8CMZt1naSdJL1J0qbAb0g3ks8VbEbEv5HaTF9VuBB9FThR0kvyPraTNLuw22tI7bGvzdMj\nefq6QrX6UUVqdnoGcIqkF+bnmCpp7/z4AKVRAwU8Tvq19dnxjqXJ12MasA9w53jrmnWDc5S5wJ9K\nOllpEAnycf7heHGadZNzdb3nvod0L/7RiWxn1kvGyJUVwIxaS5mIeIDUp+0/K3VQ/3om8WNkfp5D\nSU2vH27TYVjmAqISRMSMiLiyMH1nRLwh/5qxc0RcXFj2UES8NSK2iog9I2JuLp2tLVeu1lebPiIi\nPpkfr4mIf4iI34uIl0bEl/P6a/Ly4Yj4emHb+XX7viHHtU1EbBcR+0fELyJ1Sl2Ld0rez115m49G\nxNRInZG9LCJO79TraNZGm5I6sHyIdLF5IfDx4goRcQKpY80rlUZX+QKpEPRySatIHeXtXtjkGmAr\n1t7QXkeqEnstzfsYqdr79ZKeAK4EaiMc/n/27j9Ysru87/z7A8KEQlQkRfbNICkZUpHZEkwszEQi\nhXdzsbAtEJuBrURBUQECrcepSGuzO1VmkHcDMcvWOLZE4eDIHkoqSRtAKAGCFskGoXCjZQthJFnW\n6AcyY7gsMzVoDJJBAzbeKz/7R58Lrav7u3+d7vN+Vd3qPt8+ffo59/TT9/Zzvt/vObtZPgF8Afj3\nVfW5zezLGpavMnEC+BK9rrv/ZguxSqPU6Rytqj9pYj8T+ONmf/4feidq/rctxCuNWqdzdQ2/Cexd\nLk5JM2itXPmPzePfTnJfc/9f0Mvvx4F3ATdt4XX+vPk/9TF6l7n/J1W1speSBhR/p5IkSZIkSd1m\nDyJJkiRJkqSOs0AkSR2Q5PeXh5Ct+Llq0rFJMkelaWGuSsOX5NI18sr5MMfMIWaSJEmSJEkdd9Kk\nAwA4/fTTa+fOnVt+3ve+9z2e//znb7ziGBnT5sxyTPfee++3qurHhxBSq2w3T/u18bhvlrGP3yjj\nnvU8ndZjvsz4J68N+zDredpGbTjuw+T+jJ55ur42HTNjaW8c0KL/e6tq4j8vf/nLazs+97nPbet5\no2RMmzPLMQH3VAvyatg/283Tfm087ptl7OM3yrhnPU+n9ZgvM/7Ja8M+zHqetlEbjvswuT+jZ56u\nr03HzFieqS1xVLXn/17nIJIkSZIkSeo4C0TSDEhyVpLPJXk4yUNJfqVpf3eSo0nub35e2/ecdyY5\nnOTRJL8wueglSZIkSZPWijmIJA1sCdhXVfcleQFwb5I7msfeV1W/1b9yknOANwIvAV4IfDbJT1bV\nU2ONWpIkSZLUCvYgkmZAVR2rqvua+08CjwBnrPOUPcDNVfWDqvoacBg4b/SRSpIkSZLayAKRNGOS\n7AReBnyxaboyyQNJrk9yatN2BvCNvqcdYf2CkiRJkiRphjnETFuyc/9tAz1/8cBFQ4pEq0lyMvAx\n4O1V9d0k1wLvAaq5vRp42xa2txfYCzA3N8fCwsJA8Z04cWLgbUzKuGI/dPQ7A29j1xl/82nL0/p7\nn9a4Nfs2+lu4b9cSl22wjn8PpdHauf+2TeXieszTdkpyPfA64HhVvbRpezfwi8CfNatdVVW3N4+9\nE7gceAr45ar69NiDnlHb/W64nJvDyLFBvp/u27XE/MARzBYLRNKMSPIcesWhD1XVxwGq6rG+xz8I\nfKpZPAqc1ff0M5u2p6mqg8BBgN27d9f8/PxAMS4sLDDoNiZlXLEP8o/sssVL55+2PK2/92mNW5Ik\njdQNwAeAm1a0O++mNKANh5g1w1KOJ3mwr80rI0ktkiTAdcAjVXVNX/uOvtXeACzn8a3AG5M8N8mL\ngLOBPxxXvJIkSdJ2VNVdwOObXN15N6Ut2EwPohuwQiu13SuBNwGHktzftF0FXJLkXHpDzBaBXwKo\nqoeS3AI8TO8KaFeYp5IkSZpiVyZ5M3APvav7PkFvjs27+9ZZc97NYU+tAO0aLj+KWPbtWtrW8+ae\n13vuMOLZbgzLcczy8dmODQtEVXVXM+ntZvywQgt8LclyhfYL245Q0oaq6vNAVnno9nWe817gvSML\nShOzciz2VudgcM4FSV2V5Cx6J0Xn6J1cOVhV73d+E6n1Bpp3E4Y/tQK0a7j8KGLZ7tQI+3YtcfWh\nk54xLcI4Y1iO4+IZPj7bMcgcRANVaLvICZ4lSZJabYne/7X3JXkBcG+SO5rH7D0vtdSg825K6tlu\ngWjgCu0wuvC1pRtWv/ViGqT7G2y/+9swf0/D2odpO3aSJGn2VdUx4Fhz/8kkj7D+yU57z0stkGRH\nk7/wzHk3P5zkGnpFXOfdlNaxrQLRMCq0w+jC15ZuWP3Wi2nQqxNttwveMH9Pw9qHaTt2kjSoJH8D\nuAt4Lr2/v/+pqt7VTBR/M/C3gHuBN1XVXyV5Lr2hLi8Hvg3886panEjwUgc1Uyy8DPgivbn+tt17\nfhRzm4zCLJ0s27dr6YfznGxX234Xs3R8BpHkI8A8cHqSI8C7gHnn3ZQGt60CkRVaSZK27AfAz1bV\niSTPAT6f5PeB/4Xe0JWbk/wuvblMrm1un6iqv5/kjcBvAP98UsFLXZLkZOBjwNur6rtJBuo9P4q5\nTUZhlk6WXbb/th/Oc7Jdw5gfZZhm6fgMoqouWaX5unXWd95NaZM2c5n7j9DrJvviJEeSXA78BZbu\n9QAAIABJREFU2ySHkjwAvAr4n6FXoQWWK7R/gBVaSZIAqJ4TzeJzmp8Cfhb4T037jcDrm/t7mmWa\nxy9Istpk9JKGqCngfgz4UFV9HHq956vqqar6a+CD/Ogy2c5vIkmaGZu5ipkVWkmShiDJs+kNI/v7\nwO8Afwr8eVUtj4HoH55yBvANgKpaSvIdesPQvrVim88YujLtwxDaHv9GQ1Y2M6ylzfsH7T8Go9IU\nYa8DHqmqa/ra7T0vSUM26EWcNHyDXMVMkiRtQdOr9twkpwCfAP6bIWzzGUNXpn0YQtvj32g+vs0M\na2nb0JWV2n4MRuiVwJuAQ0nub9quAi5xfhNJ0qyzQCRJ0phV1Z8n+Rzwj4BTkpzU9CLqH56yPHTl\nSJKTgL9Jb7JqSSNSVZ8HVhvKefs6z7H3vCRpJmw4B5EkSRpckh9veg6R5HnAzwGPAJ8D/mmz2luA\nTzb3b22WaR7/L1VV44tYkiRJXWIPIkmSxmMHcGMzD9GzgFuq6lNJHgZuTvK/A3/Ej+b5uw74P5Mc\nBh4H3jiJoCVJktQNFogkSRqDqnoAeNkq7V/lR1dE6m//S+CfjSE0SZIkySFmkiRJkiRJXWcPIkmS\nJEmt4uWvJWn8LBBJkiRJktQxFmK1kgWiDvEDQJIkSZIkrcY5iCRJkiRJkjrOApEkSZIkSVLHWSCS\nJEmSJE2FJNcnOZ7kwb6230zy5SQPJPlEklOa9p1J/iLJ/c3P704ucqn9LBBJkiRJkqbFDcCFK9ru\nAF5aVf8A+BPgnX2P/WlVndv8/MsxxShNpQ0LRFZopfZLclaSzyV5OMlDSX6laT8tyR1JvtLcntq0\nJ8lvJznc5PFPT3YPJEmSpI1V1V3A4yvaPlNVS83i3cCZYw9MmgGb6UF0A1ZopbZbAvZV1TnAK4Ar\nkpwD7AfurKqzgTubZYDXAGc3P3uBa8cfsiRJkjR0bwN+v2/5RUn+KMl/TfLfTiooaRpseJn7qror\nyc4VbZ/pW7wb+KfDDUvSVlTVMeBYc//JJI8AZwB7gPlmtRuBBeAdTftNVVXA3UlOSbKj2Y4kSZI0\ndZL8Gr0Tpx9qmo4Bf6eqvp3k5cB/TvKSqvruKs/dS+/EKXNzcywsLAwcz4kTJ4aynWFYLZZ9u5ZW\nX3nE5p43uddeGUebj88kbFgg2oS3AR/tW35Rkj8Cvgv8r1X1fw/hNSRtUlPQfRnwRWCur+jzTWCu\nuX8G8I2+px1p2p5WIBr2H8q2fPBtx7hiH8Ufy63+EW7LMZrm94skSRqvJJcBrwMuaE6CUlU/AH7Q\n3L83yZ8CPwncs/L5VXUQOAiwe/fump+fHzimhYUFhrGdYVgtlsv23zaRWPbtWuLqQ8MoRQwex6/+\nwfcG2sbigYuGEktb3isDHZVJV2jb+OVhvZgG/eK33X1djqkNVdrlfZi2YzctkpwMfAx4e1V9N8kP\nH6uqSlJb2d6w/1C25YNvO8YV+yj+UG/1j/DipfNDj2E7pvn9spokZwE30SvUFnCwqt6f5N3ALwJ/\n1qx6VVXd3jznncDlwFPAL1fVp8ceuCRJLZfkQuBXgX9cVd/va/9x4PGqeirJ36M3vcJXJxSm1Hrb\nLhC1oULbxi8P68U06Be/7X5pW45pUhXifsv7MG3HbhokeQ694tCHqurjTfNjy0PHkuwAjjftR4Gz\n+p5+ZtMmaXSW5wq7L8kLgHuT3NE89r6q+q3+lZt5xN4IvAR4IfDZJD9ZVU+NNWpJklokyUfoTaFw\nepIjwLvozYn7XOCO5gTp3c18uP8d8OtJ/j/gr4F/WVWPr7phSdsrEFmhldolvb+E1wGPVNU1fQ/d\nCrwFONDcfrKv/cokNwPnA99x/iFptNaZK2wte4Cbm5MvX0tyGDgP+MLIg5U6ap2efqfRm1JhJ7AI\nXFxVTzR/f98PvBb4PnBZVd03idilrqiqS1Zpvm6NdT9G7wSqpE3YsEBkhVaaCq8E3gQcSnJ/03YV\nvcLQLUkuB74OXNw8dju9f2YP0/uH9q3jDVfqthVzhb2SXsH2zfR63O6rqifoFY/u7nva8lxhK7f1\njCHb0z5ktu3xbzRkezPzfrV5/6D9x2CE1urpdxm9q4IeSLKf3lVB38HTrwp6Pr2rgp4/kcglSRrQ\nZq5iZoVWarmq+jyQNR6+YJX1C7hipEFJWtUqc4VdC7yHXm+F9wBX07sAxKasNmR72ofMtj3+jYZs\nb2ber7bM9bWWth+DUfGqoJKkLpv81OGSJHXEanOFVdVjfY9/EPhUs+hcYdIEtfmqoKPSpp5jw7i4\nyqCX0m7L72JZm46PpNlkgUiSpDFYa66wFb0N3gA82Ny/FfhwkmvoTVJ9NvCHYwxZ6qy2XxV0VNrU\nc2wYF1cZ9FLabevp16bjI2k2WSCSJGk81por7JIk59IbYrYI/BJAVT2U5BbgYXrzolzhFcyk0fOq\noJKkrrJApLHa2ZwN2rdraVtnhhYPXDTskCRpLNaZK+z2dZ7zXuC9IwtK0tN4VVBJUpdZIJIkSRqz\nnQMOn/GEych4VVBJUmd1pkDkP2KSJElaj1cFlSR12bMmHYAkSZIkSZImqzM9iCRJm2OPS0mSJKl7\n7EEkSZIkSZLUcRaIJEmSJEmSOs4CkSRJkiRJUsdZIJIkSZIkSeo4J6meItudOHbfriUuG3DSWUmS\nJElqgyTXA68DjlfVS5u204CPAjuBReDiqnoiSYD3A68Fvg9cVlX3TSJuqe021YMoyfVJjid5sK/t\ntCR3JPlKc3tq054kv53kcJIHkvz0qIKXJEmSJHXODcCFK9r2A3dW1dnAnc0ywGuAs5ufvcC1Y4pR\nmjqbHWJ2AyagJEmSJGnCquou4PEVzXuAG5v7NwKv72u/qXruBk5JsmM8kUrTZVNDzKrqriQ7VzTv\nAeab+zcCC8A76EtA4O4kpyTZUVXHhhGwJEmSJEkrzPV95/wmMNfcPwP4Rt96R5q2p30/TbKXXgcH\n5ubmWFhYGDigEydODGU7w7BaLPt2LU0klrnnTe61hx3HsI5vW94rg8xBNFACSpLUJUnOAm6i9/ey\ngINV9X7nTJAkabiqqpLUFp9zEDgIsHv37pqfnx84joWFBYaxnWFYLZZJzVO7b9cSVx+a/HTIw4hj\n8dL5ocTSlvfKUI7KdhJwGBXarVTZxlUZXC+mrldo+203plFWVdtStZU0s5aAfVV1X5IXAPcmuQO4\njN6Q7QNJ9tMbsv0Onj5k+3x6Q7bPn0jkkiS132PLI1eaIWTHm/ajwFl9653ZtElaYZAC0UAJOIwK\n7VaqbINWRzdbGVwvpq5XaPttN6ZhVWhX05aqraTZ1PS6PdbcfzLJI/R62DpkW5Kkwd0KvAU40Nx+\nsq/9yiQ30zvR8p1Z+Fu61Stce2VrbcZmJ6lezXICwjMT8M3N1cxewYwkoNRma1xp8N1Jjia5v/l5\nbd9j72yuNPhokl+YTNRSdzXz+r0M+CJbH7ItSVKnJfkI8AXgxUmOJLmcXmHo55J8BXh1swxwO/BV\n4DDwQeBfTSBkaSpsqgtHk4DzwOlJjgDvopdwtzTJ+HXg4mb12+nNl3CY3pwJbx1yzJKe6QbgA/Tm\nN+n3vqr6rf6GJOcAbwReArwQ+GySn6yqp8YRqNR1SU4GPga8vaq+25tqqGdYQ7anfchs2+PfaIj0\nOIZ2j/r30/ZjIKnbquqSNR66YJV1C7hitBFJs2GzVzEzAaUWW+NKg2vZA9xcVT8AvpbkMHAevbMw\nkkYoyXPoFYc+VFUfb5qHPmR72ofMtj3+jbroj2No9yiHXEP7j4EkSRq+dk1MI2nYrkzyZuAeepPj\nPkFviMrdfeusOWxl2Jf7nOYz0uOKfRS9DsY9Uf2sXe5zWJqrkl0HPFJV1/Q91Kk5EyRpWmx1jpeV\nFg9cNKRIJGk8LBBt0mb/QDj5l1rkWuA99C6n/R7gauBtW9nAsC/3Oc1npDcb+6D/TI7iY3ncE9XP\n2uU+h+iVwJuAQ0nub9quwiHbUmskuR54HXC8ql7atL0b+EXgz5rVrqqq25vH3glcDjwF/HJVfXrs\nQUuSNCQWiKQZVVWPLd9P8kHgU82il/qUJqCqPg9kjYcdsi21ww04p58kqaMGuYqZpBZr5jJZ9gZg\n+QpntwJvTPLcJC8Czgb+cNzxSZLUNlV1F/D4Jlf/4Zx+VfU1er39zhtZcJIkjZg9iKQZsMaVBueT\nnEtviNki8EsAVfVQkluAh4El4ArPdkqStK6B5vSTJGkaWCCSZsAaVxq8bp313wu8d3QRSZI0Mwae\n02/YF30YlTZdHGAYF1cY90UaVhr277JNx0fSbLJAJEmSOmXwyeTVJcOY02/YF30YlWFeHKANF20Y\n90UaVhrWRRuWzeDFGyS1jAUiSZIkaQ1JdlTVsWZx5Zx+H05yDb1Jqp3TT9KmebJCbWSBSJIkScI5\n/SRJ3WaBSJIkScI5/SRJ3eZl7iVJkiRJkjrOApEkSZIkSVLHOcRMkiRJkjTVkrwY+Ghf098D/jVw\nCvCLwJ817VdV1e1jDk+aChaIJEmSJElTraoeBc4FSPJs4CjwCeCtwPuq6rcmGJ40FbZdILJCK0mS\nJElqoQuAP62qryeZdCzS1Nj2HERV9WhVnVtV5wIvB75Pr0ILvQrtuc2PxSFJkiRJ0ri8EfhI3/KV\nSR5Icn2SUycVlNR2wxpiZoVWkqR1JLkeeB1wvKpe2rS9mzV63SZ5J3A58BTwy1X16bEHLUnSlEny\nY8A/Ad7ZNF0LvAeo5vZq4G2rPG8vsBdgbm6OhYWFgWM5ceLEmtvZt2tp4O1vxdzzxv+aa2lLLMOI\nYxjvE1j/vTJOwyoQrVahfTNwD7Cvqp5Y+YRhJOBWfonjegO25c3eb5ZiGmXStCUpJc2sG4APADet\naH/GvAhJzqH3t/UlwAuBzyb5yap6ahyBSpI0xV4D3FdVjwEs3wIk+SDwqdWeVFUHgYMAu3fvrvn5\n+YEDWVhYYK3tXLb/toG3vxX7di1x9aF2TEHclliGEcfipfNDiWW998o4DXxUtluhHUYCbuWXOK4E\nbMubvd8sxTSsBFxNW5JS0myqqruS7Nzk6nuAm6vqB8DXkhwGzgO+MKLwJEmaFZfQ13khyY6qOtYs\nvgF4cCJRSVNgGFWDbVVoJUkSsHqv2zOAu/vWOdK0PcNqPXKnvUfkqOMfda/acfTcHfXxnfb3kKRu\nSvJ84OeAX+pr/rdJzqXXgWFxxWOS+gyjQGSFVpKk7dlUr9v1rNYjd9p7RI46/lH3Kh5Hz91R9qgF\ne9VKmk5V9T3gb61oe9OEwpGmzkD/vVihlSRp+9bpdXsUOKtv1TObNkmSJGkkBioQWaGVJGn71ul1\neyvw4STX0Juk+mzgDycQoiRJkjqiXTMXS5I0o5J8BJgHTk9yBHgXML9ar9uqeijJLcDDwBJwhVcw\nkyRJ0ihZIJIkaQyq6pJVmq9bZ/33Au8dXUSSJEnSjzxr0gFIGo4k1yc5nuTBvrbTktyR5CvN7alN\ne5L8dpLDSR5I8tOTi1ySJEmSNGkWiKTZcQNw4Yq2/cCdVXU2cGezDPAaenOanE3v8tjXjilGSZIk\nSVILWSCSZkRV3QU8vqJ5D3Bjc/9G4PV97TdVz93AKUl2jCdSSZLayx65kqSucg4iabbN9V0h6ZvA\nXHP/DOAbfesdadqO9bWRZC+9HkbMzc2xsLAwUDAnTpwYeBuTstnY9+1aGn0wWzT3vPHGNaxjPM3v\nF0lT7QbgA8BNfW3LPXIPJNnfLL+Dp/fIPZ9ej9zzxxqtJElDYoFI6oiqqiS1xeccBA4C7N69u+bn\n5weKYWFhgUG3MSmbjf2y/beNPpgt2rdriasPje/jfvHS+aFsZ5rfL5KmV1XdlWTniuY99K5CCL0e\nuQv0CkQ/7JEL3J3klCQ7+k7OSJI0NSwQaarsHMKX78UDFw0hkqnx2PI/qs0QsuNN+1HgrL71zmza\nJEnSMw3UI1eSpGlggUiabbcCbwEONLef7Gu/MsnN9LrCf8eznZIkbWw7PXKHPWR7VIY5tLcNQ67H\nPcR6pWEfZ4deSxo1C0TSjEjyEXrd309PcgR4F73C0C1JLge+DlzcrH478FrgMPB94K1jD1iSpOkx\nUI/cYQ/ZHpVhDu1tw5DrcQ+xXmlYQ66XOfRa0qhZIJJmRFVdssZDF6yybgFXjDYiSZJmhj1yJUkz\nzwKRJEmS1LBHriSpqywQSZIkSQ175ErTLcki8CTwFLBUVbuTnAZ8FNgJLAIXV9UTk4pRaqtnDbqB\nJItJDiW5P8k9TdtpSe5I8pXm9tTBQ5UkSZIkaUOvqqpzq2p3s7wfuLOqzgbubJYlrTBwgahhAkqS\ntIEk1yc5nuTBvrZVT6qk57eTHE7yQJKfnlzkkiRNtT3Ajc39G4HXTzAWqbVGNcRsD72x29BLwAXg\nHSN6LUlSi+wcwpVrFg9cNIRIWukG4APATX1tyydVDiTZ3yy/A3gNcHbzcz5wbXMrSZLWVsBnkhTw\ne81VBOf6JpD/JjC38klJ9gJ7Aebm5lhYWBg4kBMnTqy5nX27lgbe/lbMPW/8r7mWtsQyjDiG8T6B\n9d8r4zSMAtHEEnArv8RxvQHb8mbvZ0xPt9Z7pi1JKWl2VdVdSXauaF7rpMoe4KZmjpO7k5yyfJnt\n8UQrSdJU+pmqOprkJ4A7kny5/8Gqqua7KyvaDwIHAXbv3l3z8/MDB7KwsMBa27lsCCfUtmLfriWu\nPtSOKYjbEstQ4jj0vYHjWDxw0brvlXEaxlGZWAJu5Zc4rgRsy5u9nzE93eKl86u2tyUpJXXOWidV\nzgC+0bfekabNApEkSWuoqqPN7fEknwDOAx5bPsmSZAdwfKJBSi018Dd0E1CSpOFY66TKelbrkTvt\nPSJHHf+oe7COo5fsqI/vtL+HJHVTkucDz6qqJ5v7Pw/8OnAr8BbgQHP7yclFKbXXQAUiE1CSpIGt\ndVLlKHBW33pnNm1Ps1qP3GnvETnq+Efdq3gcvWTX6g07LNP+HpLUWXPAJ5JA77vuh6vqD5J8Cbgl\nyeXA14GLJxij1FqD/vdiAkqSNJi1TqrcClyZ5GZ6k1N/x/mHJElaW1V9FfipVdq/DVww/oik6TJQ\ngcgElCRp85J8hN6E1KcnOQK8i15haLWTKrcDrwUOA98H3jr2gCVJktQZ7Zq5WJKkGVZVl6zx0DNO\nqjRXL7titBFJkiRJPc+adACSJEmSJEmaLAtEkiRJkiRJHWeBSJIkSZIkqeOcg0iSJE2VnSO+TL0k\nSVIX2YNIkiRJkiSp4ywQSZIkSZIkdZxDzKQOSLIIPAk8BSxV1e4kpwEfBXYCi8DFVfXEpGKUJEmS\npsVmhjvv27XEZQ6L1hSxQCR1x6uq6lt9y/uBO6vqQJL9zfI7JhOaJElqC+f5kqRucoiZ1F17gBub\n+zcCr59gLJIktV6SxSSHktyf5J6m7bQkdyT5SnN76qTjlCRpOywQSd1QwGeS3Jtkb9M2V1XHmvvf\nBOYmE5okSVPlVVV1blXtbpaXe+SeDdzZLEuSNHUcYiZ1w89U1dEkPwHckeTL/Q9WVSWplU9qikl7\nAebm5lhYWBgoiBMnTgy8jUnZbOz7di2NPpgtmnteO+Naz8LCwlS/XyR1yh5gvrl/I7CAQ7YlSVPI\nApHUAVV1tLk9nuQTwHnAY0l2VNWxJDuA46s87yBwEGD37t01Pz8/UBwLCwsMuo1J2WzsbZyIcN+u\nJa4+NF0f94uXzk/1+0XSzFrukVvA7zV/JzfskTvsEy6jslyYn7aTCmuZ9AmSYR9nT5ysL8lZwE30\ncrCAg1X1/iTvBn4R+LNm1auq6vbJRCm127a/MZiA0nRI8nzgWVX1ZHP/54FfB24F3gIcaG4/Obko\nJUmaCtvqkTvsEy6jslyYb+PJju2Y9AmSxUvnh7o9T5xsaAnYV1X3JXkBcG+SO5rH3ldVvzXB2KSp\nMMgn5lgTcLWrKXjZQGlT5oBPJIFezn+4qv4gyZeAW5JcDnwduHiCMUqdl2QReBJ4Cliqqt1JTgM+\nCuwEFoGLq+qJScUodd12e+RKGr2mJ9+x5v6TSR4BzphsVNJ02fYk1VV1rKrua+4/CZiAUgtV1Ver\n6qean5dU1Xub9m9X1QVVdXZVvbqqHp90rJKc/FZqqyTPb06K0tcj90F+1CMX7JErtUKSncDLgC82\nTVcmeSDJ9V5pUFrbUPpcrkjAV9JLwDcD99DrZfSMs51bHYu92vjhSY8rXo0xbc4kY1rrvea4bkkt\n5OS3UnvYI1eaAklOBj4GvL2qvpvkWuA99KZFeQ9wNfC2VZ438PfTldr0PcxY2htHmy7OMnCBaLsJ\nuNWx2KsNJZv0uOLVGNPmTDKmtcaDO65b0oQNbfLbtvyTsV0bxd+Gf+bWM45/OEd9fKf9PTQKVfVV\n4KdWaf82cMH4I5K0UpLn0Ptu+qGq+jhAVT3W9/gHgU+t9txhfD9dqU3fw4ylvXG06eIsA/02BklA\nSZL0NEOb/LYt/2Rs10bxt33+wXH8wznsyW9Xmvb3kNQGq82huhWLBy4aUiTdkF73vuuAR6rqmr72\nHX0nW95Ab2iopFUMchUzE1DSzFnrnzknxdeoOfmtJEkDeSXwJuBQkvubtquAS5KcS6+n7iLwS5MJ\nT2q/QU5vmYCSJA1BM+Hts5qrrixPfvvr/Gjy2wM4+a2GaKOeDZspitu7QRqtlXm6nZNVXcrTqvo8\nkFUeun3csUjTatsFIhNQkjQqO/ffNlCvrSn8h9jJb7Ulgw5dkSRJWmnyMzJJYzboEKIp/OIpqeWc\n/FaSJEmTZoFIkiSNzWZ6vjjnlyRJ0vg9a9IBSJIkSZIkabLsQSRJkiTNkO3OUWXvPUnqNnsQSZIk\nSZIkdZwFIkmSJEmSpI6zQCRJkiRJktRxFogkSZIkSZI6zgKRJEmSJElSx3kVM0mSJG3Zdq+UtWzx\nwEVDikSSJA2DBSJJkrRpgxYFJEmS1E4OMZMkSZIkSeo4exBJmhn2bJAkzQL/nmlYHAoqtd/O/bex\nb9cSl20zX4eZpyPrQZTkwiSPJjmcZP+oXkfS9pmnUvuZp1L7madS+5mn0sZGUiBK8mzgd4DXAOcA\nlyQ5ZxSvJWl7zFOp/cxTqf3MU6n9zFNpc0Y1xOw84HBVfRUgyc3AHuDhEb2epK0bep5u1I15o66T\ndmOWnsG/p1L7madS+5mn0iakqoa/0eSfAhdW1f/YLL8JOL+qruxbZy+wt1l8MfDoNl7qdOBbA4Y7\nbMa0ObMc09+tqh8fwnZGaox52q+Nx32zjH38Rhn3rOfptB7zZcY/eW3Yh1nP0zZqw3EfJvdn9MzT\n9bXpmBnLM7UlDmjJ/70Tm6S6qg4CBwfZRpJ7qmr3kEIaCmPaHGOaDsPI037T/Ds29vGb1rjHbbU8\nnfbfnfFP3izsQ5sM++/pqMzacXd/tBWjyNM2HTNjaW8c0J5YRjVJ9VHgrL7lM5s2Se1hnkrtZ55K\n7WeeSu1nnkqbMKoC0ZeAs5O8KMmPAW8Ebh3Ra0naHvNUaj/zVGo/81RqP/NU2oSRDDGrqqUkVwKf\nBp4NXF9VD43gpdrYVdeYNseYJmyMedpvmn/Hxj5+0xr30AyQp9P+uzP+yZuFfRiLCf09HZVZO+7u\nj4CJ5mmbjpmxPFNb4oCWxDKSSaolSZIkSZI0PUY1xEySJEmSJElTwgKRJEmSJElSx019gSjJbyb5\ncpIHknwiySktiOmfJXkoyV8nmdil6pJcmOTRJIeT7J9UHP2SXJ/keJIHJx0LQJKzknwuycPNMfuV\nScfUFUn2Jakkp086ls1o42fNRtr4GbAZ5uXwTFue9ZvGnIPpzbtl5p+mNff6TXse9jMnp1ub8qkN\n31Hbkptt+k7athyf+gIRcAfw0qr6B8CfAO+ccDwADwL/A3DXpAJI8mzgd4DXAOcAlyQ5Z1Lx9LkB\nuHDSQfRZAvZV1TnAK4ArWvJ7mmlJzgJ+Hvh/Jx3LFrTxs2ZNLf4M2AzzcgimNM/6TVXOwdTn3TLz\nT1OXe/1mJA/7mZPTrU35NNHvqC3LzRtoz3fSVuX41BeIquozVbXULN4NnDnJeACq6pGqenTCYZwH\nHK6qr1bVXwE3A3smHBNVdRfw+KTjWFZVx6rqvub+k8AjwBmTjaoT3gf8KjA1s+S38bNmA638DNgM\n83Jopi7P+k1hzsEU590y809Tmnv9pj4P+5mT061N+dSC76ityc02fSdtW45PfYFohbcBvz/pIFri\nDOAbfctH8I/JupLsBF4GfHGykcy2JHuAo1X1x5OOZQDT8FkzE58B5uX2zEie9ZuGnIMZybtl5p+Y\nntzrN1N52M+cnHrTmE/DNLO5OSxtyPGTJvXCW5Hks8DfXuWhX6uqTzbr/Bq97lkfaktMmh5JTgY+\nBry9qr476Xim3Xr5AVxFb9hL67Txs6bLzMv1TWue9TPn2sv8m23m3vQxJ9urTfnkd9Tp1ZYcn4oC\nUVW9er3Hk1wGvA64oKrG0pV+o5ha4ChwVt/ymU2bVkjyHHrJ+KGq+vik45kFa+VHkl3Ai4A/TgK9\n9+V9Sc6rqm+OMcRVtfGzZgBT/RlgXm5sWvOs34zlHEx53i0z/2bfDOZev5nIw37mZLu1KZ9a/h11\n5nJzWNqU41NRIFpPkgvpzbHwj6vq+5OOp0W+BJyd5EX0Eu+NwL+YbEjtk963p+uAR6rqmknHM+uq\n6hDwE8vLSRaB3VX1rYkFtUlT+FkztZ8B5uVgpjnP+k1hzsEU590y809Tmnv9pj4P+5mT020G8mmY\nZio3h6VtOT4LcxB9AHgBcEeS+5P87qQDSvKGJEeAfwTcluTT446hmQztSuDT9Ca6uqWqHhp3HCsl\n+QjwBeDFSY4kuXzCIb0SeBPws8375/4kr51wTGqn1n3WrKetnwGbZF4KpiznYOrzbpn5p6nLvX4z\nkof9zMnp1pp8mvR31DblZsu+k7YqxzN9vUYlSZIkSZI0TLPQg0iSJEmSJEkDsEAkSZLnJUueAAAU\n80lEQVQkSZLUcRaIJEmSJEmSOs4CkSRJkiRJUsdZIJIkSZIkSeo4C0SSJEmSJEkdZ4FIkiRJkiSp\n4ywQSZIkSZIkdZwFIkmSJEmSpI6zQCRJkiRJktRxFogkSZIkSZI6zgKRJEmSJElSx1kg6ogk707y\nHyYdh6T1mauSJEmSJsEC0QwY5hfKJD+W5F8neTTJ95IcTfL7SX5+GNuXumxYuZpkZ5JKcqL5WUyy\nfxgxSpIkSeqmkyYdgFrnPwFnAG8G/qhp+1ngIuAzkwpK0qpOqaqlJLuB/5rk3qq6Y9JBSZIkSZo+\n9iCaMkne0fTqebLp5XMRcBXwz5ueBH/crPeiJP+1We8O4PRNbPvVwM8Be6rqi1X1V83PH1TVr4x0\nx6QZM8pcXamq7gEeAs4d6k5IkiRJ6gwLRFMkyYuBK4F/WFUvAH4B+DLwfwAfraqTq+qnmtU/DNxL\n78vme4C3bOIlXg18saqODD14qUPGkKsrX+8VwEuBw0MIX5IkSVIHOcRsujwFPBc4J8mfVdUiQJKn\nrZTk7wD/EHh1Vf0AuCvJ/7WJ7Z8OfLNvO6cBXwUCPLeq/sYwdkLqgFHn6rJvJXku8DeAq4H/PITY\nJUmSJHWQPYimSFUdBt4OvBs4nuTmJC9cZdUXAk9U1ff62r6+iZf4NrCj7/Uer6pTgJfT+7IraRPG\nkKvLTgdOBvYB88BzthWwJEmSpM6zQDRlqurDVfUzwN8FCviN5rbfMeDUJM/va/s7m9j8ncA/THLm\nUIKVOmzEudr/Ok9V1TXAXwL/aoCQJUmSJHWYBaIpkuTFSX62GVLyl8BfAH8NPAbsTPIsgKr6OnAP\n8G+ay9b/DPDfb7T9qvoM8DngPyc5v3nuc4BXjGiXpJk06lxdwwHgV5M4FFSSJEnSllkgmi7Ppfcl\n8Fv05gr6CeCdwH9sHv92kvua+/8COB94HHgXcNMmX+MNwKeA/wD8OfA14FJ6k+xK2pxx5OpKtwFP\nAL+4zedLkiRJ6rBUrRzxIEmSJEmSpC6xB5EkSZIkSVLHWSDqmCSXJjmxys9Dk45N0o+Yq5IkSZLG\nySFmkiRJkiRJHWcPIkmSJEmSpI47adIBAJx++um1c+fOkb7G9773PZ7//OeP9DUmbdb3cVr27957\n7/1WVf34pOMYtnHk6UrTcswH0YV9hPbt56zmqSRJkrRdrSgQ7dy5k3vuuWekr7GwsMD8/PxIX2PS\nZn0fp2X/knx90jGMwjjydKVpOeaD6MI+Qvv2c1bzVJIkSdouh5hJkiRJkiR1nAUiSZIkSZKkjrNA\nJEmSJEmS1HEWiCRJkiRJkjrOApEkSZIkSVLHteIqZtqcnftvW/fxfbuWuGyddRYPXDTskCQN2UZ5\nvhnmuiRJkqStsgeRJEmSJElSx1kgkiRJkiRJ6jiHmEnSEG11iNhGQ0MlSZIkaRzsQSRJkiRJktRx\nFogkSZIkSZI6zgKRJEmSJElSx1kgkiRJkiRJ6jgLRJIkSZIkSR23YYEoyVlJPpfk4SQPJfmVpv20\nJHck+Upze2rTniS/neRwkgeS/PSod0KSJEmSJEnbt5keREvAvqo6B3gFcEWSc4D9wJ1VdTZwZ7MM\n8Brg7OZnL3Dt0KOWJEmSJEnS0GxYIKqqY1V1X3P/SeAR4AxgD3Bjs9qNwOub+3uAm6rnbuCUJDuG\nHrkkSZIkSZKGYktzECXZCbwM+CIwV1XHmoe+Ccw1988AvtH3tCNNmyRJkiRJklropM2umORk4GPA\n26vqu0l++FhVVZLaygsn2UtvCBpzc3MsLCxs5elbduLEiZG/xqjt27W07uNzz1t/nWnf/1k4hqOS\n5CzgJnqF2gIOVtX7k5wGfBTYCSwCF1fVE+kl8PuB1wLfBy5b7ikoSZIkSeqeTRWIkjyHXnHoQ1X1\n8ab5sSQ7qupYM4TseNN+FDir7+lnNm1PU1UHgYMAu3fvrvn5+e3twSYtLCww6tcYtcv237bu4/t2\nLXH1obUP6eKl80OOaLxm4RiO0PJcYfcleQFwb5I7gMvozRV2IMl+enOFvYOnzxV2Pr25ws6fSOSS\nJEmSpInbzFXMAlwHPFJV1/Q9dCvwlub+W4BP9rW/ubma2SuA7/QNRZM0As4VJkmSJEkaxGZ6EL0S\neBNwKMn9TdtVwAHgliSXA18HLm4eu53esJXD9IauvHWoEUta14BzhT2tmDvuoaArTeOwwo2Ggq60\n0dDQ7Wjj72waj6UkSZLUJRsWiKrq80DWePiCVdYv4IoB45K0DcOeK2zcQ0FXmsZhhRsNBV1po6Gh\n29HG4aTTeCwlSZKkLtnSVcwktdd6c4U1j295rjBJkiRJUjdYIJJmgHOFSZIkSZIGMdxxDZImxbnC\nJEmSJEnbZoFImgHOFSZJkiRJGoQFog7ZucXJc1ezeOCiIUQiSZIkSZLaxALRGA2jQCNJkiRJkjRs\nTlItSZIkSZLUcRaIJEmSJEmSOs4CkSRJkiRJUsdZIJIkSZIkSeo4C0SSJEmSJEkdZ4FIkiRJkiSp\n4ywQSZIkSZIkdZwFIkmSJEmSpI6zQCRJkiRJktRxFogkSZIkSZI6zgKRJEmSJElSx1kgkiRJkiRJ\n6jgLRJIkSZIkSR1ngUiSJEmSJKnjLBBJkiRJkiR1nAUiSZIkSZKkjrNAJEmSJEmS1HEbFoiSXJ/k\neJIH+9reneRokvubn9f2PfbOJIeTPJrkF0YVuCRJkiRJkoZjMz2IbgAuXKX9fVV1bvNzO0CSc4A3\nAi9pnvPvkzx7WMFKkiRJkiRp+DYsEFXVXcDjm9zeHuDmqvpBVX0NOAycN0B8kjbBnn6SJEmSpEGc\nNMBzr0zyZuAeYF9VPQGcAdzdt86Rpu0ZkuwF9gLMzc2xsLAwQCgbO3HixMhfYyP7di2NdPtzzxv9\na0zyd9iGY9hiNwAfAG5a0f6+qvqt/oYVPf1eCHw2yU9W1VPjCFSSJEmS1D7bLRBdC7wHqOb2auBt\nW9lAVR0EDgLs3r275ufntxnK5iwsLDDq19jIZftvG+n29+1a4upDg9T8NrZ46fxIt7+eNhzDtqqq\nu5Ls3OTqP+zpB3wtyXJPvy+MKDxJkiRJUstt6ypmVfVYVT1VVX8NfJAfDSM7CpzVt+qZTZukybgy\nyQPNELRTm7YzgG/0rbNmTz9JkiRJUjdsq7tJkh1VdaxZfAOwPO/JrcCHk1xDb+jK2cAfDhylpO0Y\nuKffuIeCrjSNwwq3OsxzFEND2/g7m8ZjKUmSJHXJhgWiJB8B5oHTkxwB3gXMJzmX3hfPReCXAKrq\noSS3AA8DS8AVzmsiTUZVPbZ8P8kHgU81i5vu6TfuoaArTeOwwq0OJR3F0NBJDgVdyzQeS0mSJKlL\nNvxWUlWXrNJ83Trrvxd47yBBSRqcPf0kSZIkSZs12hmNJY2FPf0kSZIkSYOwQCTNAHv6SZIkSZIG\nYYFIkmbMzi3Og7TS4oGLhhSJJEmSpGmxrcvcS5IkSZIkaXbYg0iS+gza+0aSJEmSppE9iCRJkiRJ\nkjrOHkTaEuc2kSRJkiRp9tiDSJIkSZIkqeMsEEmSJEmSJHWcBSJJkiRJkqSOs0AkSZIkSZLUcRaI\nJEmSJEmSOs4CkSRJkiRJUsdZIJIkSZIkSeo4C0SSJEmSJEkdZ4FIkiRJkiSp4ywQSZIkSZIkddxJ\nkw5gWuzcf9ukQ5AkSZIkSRoJexBJkiRJkiR1nAUiSZIkSZKkjrNAJEmSJEmS1HEWiCRJkiRJkjpu\nUwWiJNcnOZ7kwb6205LckeQrze2pTXuS/HaSw0keSPLTowpekiRJkiRJg9tsD6IbgAtXtO0H7qyq\ns4E7m2WA1wBnNz97gWsHD1OSJEmSJEmjsqkCUVXdBTy+onkPcGNz/0bg9X3tN1XP3cApSXYMI1hJ\na7OnnyRJkiRpu04a4LlzVXWsuf9NYK65fwbwjb71jjRtx/raSLKXXg8j5ubmWFhYGCCUjZ04cWKg\n19i3a2l4wYzI3PPaH+cgx2DQY9gBNwAfAG7qa1vu6Xcgyf5m+R08vaff+fR6+p0/1mglSZIkSa0x\nSIHoh6qqktQWn3MQOAiwe/fump+fH0Yoa1pYWGCQ17hs/23DC2ZE9u1a4upDQzmkI7N46fy2nzvo\nMZx1VXVXkp0rmvcA8839G4EFegWiH/b0A+5OckqSHX1FX0mSJElShwxSTXhs+QtlM4TseNN+FDir\nb70zmzZJ4zdVPf1WmkSvsXH3wmtjz79R/M7tAShJkiS12yAFoluBtwAHmttP9rVfmeRmekNWvmOv\nBGnypqGn30qT6DU27t6Cbez5N0hPv7XYA1CSJElqt019K0nyEXrDVE5PcgR4F73C0C1JLge+Dlzc\nrH478FrgMPB94K1DjlnS5tnTT5IkSZK0oU0ViKrqkjUeumCVdQu4YpCgJA2NPf0kSZIkSRtq17gG\nSdtmTz9JkiRJ0nZZIJJmhD39YOcUXG1QkiRJktroWZMOQJIkSZIkSZNlgUiSJEmSJKnjLBBJkiRJ\nkiR1nAUiSZIkSZKkjrNAJEmSJEmS1HEWiCRJkiRJkjrOApEkSZIkSVLHWSCSJEmSJEnqOAtEkiRJ\nkiRJHWeBSJIkSZIkqeMsEEmSJEmSJHWcBSJJkiRJkqSOs0AkSZIkSZLUcRaIJEmSJEmSOs4CkSRJ\nkiRJUsdZIJIkSZIkSeo4C0SSJEmSJEkdZ4FIkiRJkiSp4ywQSZIkSZIkdZwFIkmSJEmSpI47adAN\nJFkEngSeApaqaneS04CPAjuBReDiqnpi0NcaxKGj3+Gy/bdNMgRJG9i5Ikf37VoybyVJkiRpDIbV\ng+hVVXVuVe1ulvcDd1bV2cCdzbKkCUmymORQkvuT3NO0nZbkjiRfaW5PnXSckiRJkqTJGNUQsz3A\njc39G4HXj+h1JG2ehVxJkiRJ0qqGUSAq4DNJ7k2yt2mbq6pjzf1vAnNDeB1Jw2UhV5IkSZIEQKpq\nsA0kZ1TV0SQ/AdwB/E/ArVV1St86T1TVqSuetxfYCzA3N/fym2++eaA4NnL88e/w2F+M9CUmbu55\ntH4fd53xN7f93BMnTnDyyScPMZrReNWrXnVvXy+dVkjyNeAJegXd36uqg0n+fDlPkwR4oj9vm/ax\n5umho9952vI0vKcH1cZ9HCRP19K2/G1jnkqSJEmTNPAk1VV1tLk9nuQTwHnAY0l2VNWxJDuA46s8\n7yBwEGD37t01Pz8/aCjr+ncf+iRXHxp4d1tt366l1u/j4qXz237uwsICo36fzLCf6S/kJvly/4NV\nVUmeUS0ed56unJB6Gt7Tg2rjPg6Sp2sxfyVJkqR2G2iIWZLnJ3nB8n3g54EHgVuBtzSrvQX45CCv\nI2kw/YVc4GmFXIC1CrmSJEmSpG4Y9LT1HPCJ3ugUTgI+XFV/kORLwC1JLge+Dlw84OtI2qamePus\nqnqyr5D76/yokHsAC7nqs3NFT66tWjxw0ZAikSRJkjQuAxWIquqrwE+t0v5t4IJBti1paCzkSpIk\nSZLW1a6JLyQNnYVcSZIkSdJGhnGZe0mSJEmSJE0xC0SSJEmSJEkdZ4FIkiRJkiSp45yDSGM1yNWR\n9u1aYn54oUiSJEmSpIY9iCRJkiRJkjrOApEkSZIkSVLHWSCSJEmSJEnqOAtEkiRJkiRJHWeBSJIk\nSZIkqeOm5ipmg1z9CmDfriEFIkla12qf1/t2LXHZFj7HFw9cNMyQJEmSJG3AHkSSJEmSJEkdZ4FI\nkiRJkiSp46ZmiJkEgw81BIeuSJIkSZK0kj2IJEmSJEmSOs4CkSRJkiRJUsc5xEzS0AxjCKAkSZIk\nafzsQSRJkiRJktRxFogkSZIkSZI6ziFmkqTWGXS4olcrlCRJkrbGHkSSJEmSJEkdZ4FIkiRJkiSp\n40ZWIEpyYZJHkxxOsn9UryNp+8xTSZIkSRKMaA6iJM8Gfgf4OeAI8KUkt1bVw6N4PWkrnNukxzyV\nJEmSJC0bVQ+i84DDVfXVqvor4GZgz4heS9L2mKeSJEmSJGB0BaIzgG/0LR9p2iS1h3kqSZIkSQIm\neJn7JHuBvc3iiSSPjvL1fhlOB741yteYtFnfx7bsX35jw1X+7hjCGItx5+lKbTnmo9SFfYTx72eX\n8lSSJEkahlEViI4CZ/Utn9m0/VBVHQQOjuj1nyHJPVW1e1yvNwmzvo+zvn8T0Lo8XakLx7wL+wjd\n2U9JkiRpWo1qiNmXgLOTvCjJjwFvBG4d0WtJ2h7zVJIkSZIEjKgHUVUtJbkS+DTwbOD6qnpoFK8l\naXvMU0mSJEnSspHNQVRVtwO3j2r72zCxYTJjNOv7OOv7N3YtzNOVunDMu7CP0J39lCRJkqZSqmrS\nMUiSJEmSJGmCRjUHkSRJkiRJkqZEpwpESX4zyZeTPJDkE0lOmXRMw5DkwiSPJjmcZP+k4xm2JGcl\n+VySh5M8lORXJh2TxmNWc3bZrOcumL+SJEnStOjUELMkPw/8l2Zy3t8AqKp3TDisgSR5NvAnwM8B\nR+hdmeqSqnp4ooENUZIdwI6qui/JC4B7gdfP0j5qdbOYs8u6kLtg/kqSJEnTolM9iKrqM1W11Cze\nDZw5yXiG5DzgcFV9tar+CrgZ2DPhmIaqqo5V1X3N/SeBR4AzJhuVxmFGc3bZzOcumL+SJEnStOhU\ngWiFtwG/P+kghuAM4Bt9y0eY4S9fSXYCLwO+ONlINAGzkrPLOpW7YP5KkiRJbTayy9xPSpLPAn97\nlYd+rao+2azza8AS8KFxxqbBJDkZ+Bjw9qr67qTj0XCYs91g/kqSJEntNnMFoqp69XqPJ7kMeB1w\nQc3GBExHgbP6ls9s2mZKkufQ+3L5oar6+KTj0fB0MGeXdSJ3wfzV/9/eHdpEFERRAL0vkNAUCQJD\nKIEKkGg8llABCU3QAIYESXB0QKAEHmJ3FfZnJ/vnHDnqmivmihkAAA7BbI9UXyS5T3LW3V+j8yyh\nqo6zeej2PJvL5VuSq+7+GBpsQVVVSZ6S/HT3zeg87M8aO7szQ3cT/QUAgEMx20D0meQkyff26LW7\nrwdGWkRVXSZ5SHKU5LG77wZHWlRVnSZ5SfKe5Hd7fNvdz+NSsQ9r7ezO2rub6C8AAByKqQYiAAAA\nAP6b+RczAAAAAGIgAgAAAJiegQgAAABgcgYiAAAAgMkZiAAAAAAmZyACAAAAmJyBCAAAAGByBiIA\nAACAyf0BTKbD94QV6N4AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x1440 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "_5HQbaMYDL9b",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Split the Dataset"
      ]
    },
    {
      "metadata": {
        "id": "EEdYliAMDVbm",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# Pembagian data training & testing\n",
        "x_train, x_test, y_train, y_test = train_test_split(data, label, stratify=label, test_size=0.3)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "C8ZSLxL8f5to",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "x_train = np.array(x_train)\n",
        "x_test = np.array(x_test)\n",
        "y_train = np.array(y_train)\n",
        "y_test = np.array(y_test)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "HL2dLoJtDZj0",
        "colab_type": "code",
        "outputId": "a0bcbd2a-bd49-4d42-f508-916edc062806",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        }
      },
      "cell_type": "code",
      "source": [
        "n_input = x_train.shape[1]\n",
        "n_output = len(np.unique(y_train))\n",
        "print('Input Neuron:', n_input)\n",
        "print('Output Neuron:', n_output)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Input Neuron: 27\n",
            "Output Neuron: 13\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "e5k9ZLh4NqTv",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "## Classification"
      ]
    },
    {
      "metadata": {
        "id": "wYtEnZT4NJVz",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "class LVQ(object):\n",
        "\n",
        "    def __init__(self, sizeInput, sizeOutput, max_epoch, alpha=np.random.random(), threshold=np.random.random(), version='1'):\n",
        "        \"\"\"\n",
        "        Inisialisasi class (constructor)\n",
        "        :param sizeInput (int): Banyaknya input neuron sesuai dengan banyaknya parameter (fitur pada data latih)\n",
        "        :param sizeOutput (int): Banyaknya output neuron sesuai dengan banyaknya label (kelas pada data latih)\n",
        "        :param max_epoch (int): Maksimal epoch yang diizinkan\n",
        "        :param alpha (float): learning rate\n",
        "        :param threshold (float): nilai ambang batas\n",
        "        :param version (string): versi dari jaringan LVQ. Bisa diisi dengan '1', '2', '2.1', '3'\n",
        "        \"\"\"\n",
        "\n",
        "        self.sizeInput = sizeInput\n",
        "        self.sizeOutput = sizeOutput\n",
        "        self.max_epoch = max_epoch\n",
        "        self.alpha = alpha\n",
        "        self.threshold = threshold\n",
        "        self.version = version\n",
        "        self.weight = np.zeros((sizeOutput, sizeInput))\n",
        "\n",
        "    def getWeight(self):\n",
        "        \"\"\"\n",
        "        Mendapatkan bobot jaringan LVQ setelah proses training\n",
        "\n",
        "        :return: weight (nilai bobot)\n",
        "        \"\"\"\n",
        "\n",
        "        return self.weight\n",
        "\n",
        "    def train(self,train_data,train_target):\n",
        "        \"\"\"\n",
        "        Proses pelatihan jaringan LVQ\n",
        "        :param train_data (numpy array atau pandas dataframe): Matriks yang berisi data latih\n",
        "        :param train_target (numpy array atau pandas series): Array yang berisi label dari data latih\n",
        "        :return: bobot dan label dari bobot\n",
        "        \"\"\"\n",
        "\n",
        "        weight_label, label_index = np.unique(train_target, True)\n",
        "        # print(weight_label)\n",
        "        # print(label_index)\n",
        "        # Inisialisasi bobot\n",
        "        self.weight = train_data[label_index].astype(np.float)\n",
        "        # Hapus data yang digunakan untuk inisialisasi bobot\n",
        "        train_data = np.delete(train_data, label_index, axis=0)\n",
        "        train_target = np.delete(train_target, label_index, axis=0)\n",
        "\n",
        "        epoch = 0\n",
        "        iterasi = 0\n",
        "        while epoch <= self.max_epoch:\n",
        "            epoch += 1\n",
        "            # print('\\nEpoch', epoch)\n",
        "            for data, target in zip(train_data, train_target):\n",
        "                iterasi += 1\n",
        "                # print('Iterasi', iterasi)\n",
        "                distance = np.sqrt(np.sum((data - self.weight) ** 2, axis=1))\n",
        "                idx_min = np.argmin(distance)\n",
        "                idx_sort = np.argsort(distance)\n",
        "                idx_winner, idx_runnerUp = idx_sort[0], idx_sort[1]\n",
        "                min_distance = min(distance[idx_winner]/distance[idx_runnerUp], distance[idx_runnerUp]/distance[idx_winner])\n",
        "                max_distance = max(distance[idx_winner]/distance[idx_runnerUp], distance[idx_runnerUp]/distance[idx_winner])\n",
        "                # print(distance, idx_sort)\n",
        "\n",
        "                if self.version == '2':\n",
        "                    if (\n",
        "                        (weight_label[idx_winner] != weight_label[idx_runnerUp]) and\n",
        "                        (target == weight_label[idx_runnerUp] and\n",
        "                        (distance[idx_winner]/distance[idx_runnerUp] > 1-self.threshold and\n",
        "                         distance[idx_runnerUp]/distance[idx_winner] < 1+self.threshold))\n",
        "                    ):\n",
        "                        self.weight[idx_winner] = self.weight[idx_winner] - self.alpha * (data - self.weight[idx_winner])\n",
        "                        self.weight[idx_runnerUp] = self.weight[idx_runnerUp] + self.alpha * (data - self.weight[idx_runnerUp])\n",
        "                    else:\n",
        "                        if target == weight_label[idx_min]:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] + self.alpha * (data - self.weight[idx_min])\n",
        "                        else:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] - self.alpha * (data - self.weight[idx_min])\n",
        "\n",
        "                elif self.version == '2.1':\n",
        "                    self.threshold = 0.35\n",
        "                    if (\n",
        "                        (target == weight_label[idx_winner] or target == weight_label[idx_runnerUp]) and\n",
        "                        (min_distance > 1-self.threshold and max_distance < 1+self.threshold)\n",
        "                    ):\n",
        "                        self.weight[idx_winner] = self.weight[idx_winner] + self.alpha * (data - self.weight[idx_winner])\n",
        "                        self.weight[idx_runnerUp] = self.weight[idx_runnerUp] - self.alpha * (data - self.weight[idx_runnerUp])\n",
        "                    else:\n",
        "                        if target == weight_label[idx_min]:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] + self.alpha * (data - self.weight[idx_min])\n",
        "                        else:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] - self.alpha * (data - self.weight[idx_min])\n",
        "\n",
        "                elif self.version == '3':\n",
        "                    self.threshold = 0.2\n",
        "                    m = np.random.uniform(0.1, 0.5)\n",
        "                    beta = m * self.alpha\n",
        "                    if (min_distance > (1-self.threshold) * (1+self.threshold)):\n",
        "                        if (weight_label[idx_winner] != weight_label[idx_runnerUp]):\n",
        "                            if (target == weight_label[idx_winner] or target == weight_label[idx_runnerUp]):\n",
        "                                self.weight[idx_winner] = self.weight[idx_winner] + self.alpha * (data - self.weight[idx_winner])\n",
        "                                self.weight[idx_runnerUp] = self.weight[idx_runnerUp] - self.alpha * (data - self.weight[idx_runnerUp])\n",
        "                        else:\n",
        "                            self.weight[idx_winner] = self.weight[idx_winner] + beta * (data - self.weight[idx_winner])\n",
        "                            self.weight[idx_runnerUp] = self.weight[idx_runnerUp] + beta * (data - self.weight[idx_runnerUp])\n",
        "                    else:\n",
        "                        if target == weight_label[idx_min]:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] + self.alpha * (data - self.weight[idx_min])\n",
        "                        else:\n",
        "                            self.weight[idx_min] = self.weight[idx_min] - self.alpha * (data - self.weight[idx_min])\n",
        "\n",
        "                else:\n",
        "                    if target == weight_label[idx_min]:\n",
        "                        self.weight[idx_min] = self.weight[idx_min] + self.alpha * (data - self.weight[idx_min])\n",
        "                    else:\n",
        "                        self.weight[idx_min] = self.weight[idx_min] - self.alpha * (data - self.weight[idx_min])\n",
        "\n",
        "            self.alpha = self.alpha * (1 - epoch / self.max_epoch)\n",
        "\n",
        "        weight_class = (self.weight, weight_label)\n",
        "        return weight_class\n",
        "\n",
        "    def test(self, test_data, weight_class):\n",
        "        \"\"\"\n",
        "        Proses pengujian jaringan LVQ\n",
        "        :param test_data (numpy array atau pandas dataframe): Matriks yang berisi data uji\n",
        "        :param weight_class (tuple): Tuple yang berisi pasangan bobot dan labelnya\n",
        "        :return: Nilai prediksi label/class\n",
        "        \"\"\"\n",
        "\n",
        "        weight, label = weight_class\n",
        "        output = []\n",
        "        for data in test_data:\n",
        "            distance = np.sqrt(np.sum((data - self.weight) ** 2, axis=1))\n",
        "            idx_min = np.argmin(distance)\n",
        "            output.append(label[idx_min])\n",
        "\n",
        "        return output"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "RQNJicRu6w87",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### LVQ1"
      ]
    },
    {
      "metadata": {
        "id": "d6lIc19-aFmP",
        "colab_type": "code",
        "outputId": "831f2745-e32b-4089-df55-ddb37af3f5ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1562
        }
      },
      "cell_type": "code",
      "source": [
        "# Training\n",
        "lvq = LVQ(sizeInput=n_input, sizeOutput=n_output, max_epoch=10, version='1')\n",
        "bobot_dan_label = lvq.train(x_train, y_train)\n",
        "bobot = lvq.getWeight()\n",
        "print('Bobot: ', bobot)\n",
        "print('Ukuran Bobot:', bobot.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Bobot:  [[-2.61244200e-01  3.40377587e-01  2.33968765e-01  3.50917364e-01\n",
            "   2.26238844e-01  6.92439005e-01 -3.72049151e-01  5.50413475e-01\n",
            "  -2.90574696e-01 -2.07662329e-01 -5.52828617e-01  1.40689130e+00\n",
            "   1.32695566e+00  1.18266031e+00  1.66476129e-01 -9.15152820e-02\n",
            "   1.23403457e+00 -1.01161110e+00 -1.00970397e+00 -1.17117839e+00\n",
            "  -8.22988620e-01 -2.69920335e-01 -1.34150861e+00 -1.19488995e+00\n",
            "   4.24755731e-01  5.01375542e-02  1.13392343e+00]\n",
            " [-1.53444164e+00  2.07738419e+00  1.57323000e+00 -7.24227912e-01\n",
            "  -7.77823865e-01 -1.66179870e+00  1.29688630e+00  1.82878819e+00\n",
            "  -1.63504583e-01 -7.41284919e-01  5.55298733e-02  7.84721045e-01\n",
            "   7.69618968e-01 -8.30891918e-01 -9.97393955e-01 -1.38183127e+00\n",
            "  -9.61366547e-01 -5.30368083e-01 -4.95571454e-01  8.27856182e-01\n",
            "   7.77585023e-01  1.11740649e+00  8.46756866e-01 -1.57055441e+00\n",
            "   1.56790585e+00  1.19355059e+00  1.46042518e+00]\n",
            " [-8.64043538e-01 -4.40830575e-02  8.51096158e-01  1.22053988e+00\n",
            "   1.24036924e+00  6.30875360e-01 -5.10640707e-01  9.20627506e-01\n",
            "   1.27343562e+00  1.14954565e+00 -5.48971371e-01  8.01976400e-01\n",
            "   1.38898509e+00 -6.85324616e-01  1.38604627e+00  3.05463077e-01\n",
            "  -4.51999304e-01 -6.29330309e-01 -1.25444744e-01  5.86824228e-01\n",
            "  -1.09888917e+00 -1.02054038e+00  6.34012497e-01 -9.42017842e-02\n",
            "  -3.32732020e-01 -3.98116393e-01  9.15600245e-03]\n",
            " [-1.16919323e+00  5.08225418e-01  1.18087550e+00  8.82193487e-01\n",
            "   8.55220305e-01 -1.71381233e+00 -3.47991233e-01  1.17485139e+00\n",
            "   1.28152876e+00  9.20967498e-01  1.33012980e+00  1.69464133e-03\n",
            "   1.35540396e-01 -8.53496030e-01 -1.86779928e-01 -4.23501507e-01\n",
            "  -8.03491215e-01  1.69858373e-01  1.16030558e-01  8.20482135e-01\n",
            "  -1.40446344e-01 -4.46729621e-01  8.98277054e-01 -7.22541607e-01\n",
            "   1.06919811e+00  6.85378035e-01  8.80940822e-01]\n",
            " [ 8.28729691e-01 -5.04389280e-01 -8.33704376e-01 -1.55039298e-01\n",
            "  -2.64705912e-01  2.06440176e-01  7.08564160e-01 -7.12797296e-01\n",
            "  -6.12854668e-01 -5.13741012e-01 -6.05471346e-01 -7.52479964e-01\n",
            "  -4.53883112e-01  6.20678412e-02  1.44188517e+00  1.19556843e+00\n",
            "   2.90793177e-01 -1.64328263e-01 -1.23695935e-01 -1.02195365e-01\n",
            "  -1.21363206e+00 -1.32233071e+00 -2.29944985e-01  1.60560239e+00\n",
            "  -1.27101804e+00 -1.56310095e+00 -1.57148554e+00]\n",
            " [ 3.98884154e-01  4.02880607e-01 -4.19262571e-01 -6.71530418e-01\n",
            "  -7.26597211e-01  1.66620396e-01 -3.90924348e-01 -1.42909752e-01\n",
            "  -8.94628055e-01 -7.41391695e-01 -1.57567666e-01  6.26073365e-01\n",
            "   6.43857423e-01  4.75615366e-01  3.16696254e-01  3.10252452e-01\n",
            "   7.37925301e-01 -3.00994419e-01 -3.13972721e-01 -2.25183741e-01\n",
            "  -4.47968492e-01 -3.84977934e-01 -2.15985826e-01  9.30140922e-01\n",
            "  -1.30088931e+00 -1.11874388e+00 -1.07724552e+00]\n",
            " [-1.32320507e+00 -2.10525010e+00  1.34211260e+00  1.75376714e+00\n",
            "   2.07011074e+00 -3.28000963e-01 -4.45219068e-01 -2.35826333e-01\n",
            "   2.34765974e+00  2.70391622e+00  2.00805221e+00 -5.65336729e-01\n",
            "  -4.26004128e-01 -1.23497181e+00  4.76822360e-01  8.53945778e-01\n",
            "  -1.28404231e+00  6.01052587e-01  7.40517368e-01  1.17073022e+00\n",
            "  -6.35759126e-03 -2.64383898e-01  1.17033696e+00  1.54999632e+00\n",
            "  -1.36113875e+00 -3.76468877e-01 -1.45518500e+00]\n",
            " [ 1.36400136e+00  4.30588415e-01 -1.33409029e+00 -1.43365477e+00\n",
            "  -1.30929502e+00  8.92073517e-01 -1.80925620e+00 -1.20456142e+00\n",
            "  -1.25672538e+00 -8.84255678e-01 -6.21933726e-01 -1.61449610e+00\n",
            "  -1.66679509e+00 -5.44583332e-01 -7.01561287e-01 -1.44730697e-01\n",
            "  -5.02058072e-01  1.93873266e+00  2.03835973e+00  5.69220454e-01\n",
            "   1.64414077e+00  1.36114984e+00  6.62526668e-01 -3.80751709e-01\n",
            "   4.18963537e-01  1.10043620e+00  3.27957067e-01]\n",
            " [-5.22252199e-01  9.19297916e-02  5.01500367e-01  6.79877940e-01\n",
            "   6.19460841e-01  8.35900015e-01  1.01851301e-01  7.15929157e-01\n",
            "   3.56106772e-01  3.33536425e-01 -5.81485955e-01  2.72041855e-01\n",
            "   3.65332906e-02  1.21188735e+00 -2.22730523e-03 -4.74625743e-02\n",
            "   1.10438156e+00 -3.39314621e-02  1.44891130e-01 -1.06532083e+00\n",
            "  -4.27376915e-01 -3.48132494e-02 -9.82542380e-01  6.80012578e-02\n",
            "  -8.22237235e-02 -4.00297219e-01 -5.08802807e-02]\n",
            " [ 6.95485646e-01 -8.76441981e-01 -7.05665623e-01  7.06562306e-01\n",
            "   6.42060736e-01  9.66758936e-01 -4.81712096e-01 -8.02073977e-01\n",
            "   3.54775045e-01  3.27512160e-01 -8.25895299e-01 -7.89519484e-01\n",
            "  -1.57551415e-01  6.44614876e-01 -7.07881188e-01 -1.28856355e+00\n",
            "  -9.37662467e-02 -1.52848834e+00 -1.55643797e+00 -9.05812137e-01\n",
            "   7.25832077e-01  9.60541317e-01 -5.43881237e-01  4.24997507e-02\n",
            "  -2.16319454e-01  8.66957485e-02 -3.56294001e-02]\n",
            " [ 1.26444711e-01  6.28527578e-01 -1.51573537e-01 -1.42481827e+00\n",
            "  -1.30538523e+00 -4.81641630e-01  9.80614507e-01  1.70324243e-01\n",
            "  -9.72244189e-01 -8.83287852e-01  3.41938531e-01  2.79837211e-01\n",
            "  -5.66082005e-01  7.39308346e-01 -1.60128663e+00 -9.04475944e-01\n",
            "   3.64029853e-01  1.77048351e-01 -2.08782686e-01 -7.22919835e-01\n",
            "   7.16874961e-01  8.83950040e-01 -4.92816149e-01 -5.15715631e-01\n",
            "   6.91941336e-01  4.04438455e-01  6.58980257e-01]\n",
            " [ 8.15905586e-01 -7.04381993e-02 -8.20165472e-01 -1.24076149e+00\n",
            "  -1.15720179e+00 -1.05350465e+00  9.86133829e-01 -7.63956388e-01\n",
            "  -7.01599477e-01 -8.31276917e-01  1.29820233e+00 -6.98699415e-01\n",
            "  -1.03277525e+00 -1.77273293e-01 -2.50988597e-01  7.77160304e-01\n",
            "  -2.44608258e-01  8.11750822e-01  5.24796713e-01 -4.38543516e-03\n",
            "   7.13197730e-01  1.09203964e-01 -1.49525800e-01 -1.80641733e-01\n",
            "   8.33887140e-01  3.44610392e-01  1.44390413e-03]\n",
            " [ 1.46243673e+00 -1.05089286e+00 -1.42794522e+00  2.48097784e-01\n",
            "   1.35312497e-01  7.18441373e-01  2.28441921e-02 -1.58433238e+00\n",
            "  -2.97490758e-01 -2.29797438e-01 -8.86044386e-01 -2.60625762e-01\n",
            "  -7.30136232e-01  8.64076337e-01  2.80669944e-01  8.17297352e-01\n",
            "   1.12747718e+00  6.55571841e-01  3.90686262e-01 -7.87264473e-01\n",
            "  -8.11849119e-02 -5.97597177e-01 -1.07352763e+00  5.73411692e-01\n",
            "  -3.40071983e-01 -4.72726411e-01 -5.11864760e-01]]\n",
            "Ukuran Bobot: (13, 27)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "I0yM8Rmik4PY",
        "colab_type": "code",
        "outputId": "2cef566c-2cbe-4cc2-dccc-415062454a99",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Testing\n",
        "y_pred = lvq.test(x_test, bobot_dan_label)\n",
        "# print('Label Pred: ', y_pred)\n",
        "# print('Label True: ', y_test)\n",
        "print('Accuracy:', accuracy_score(y_test, y_pred))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy: 0.9180887372013652\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "KpSsHF0D6_o_"
      },
      "cell_type": "markdown",
      "source": [
        "### LVQ2"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "9f9bc5b2-303b-45be-d3ad-42b3272da0df",
        "id": "NTsYNQOq6_pD",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1562
        }
      },
      "cell_type": "code",
      "source": [
        "# Training\n",
        "lvq = LVQ(sizeInput=n_input, sizeOutput=n_output, max_epoch=10, version='2')\n",
        "bobot_dan_label = lvq.train(x_train, y_train)\n",
        "bobot = lvq.getWeight()\n",
        "print('Bobot: ', bobot)\n",
        "print('Ukuran Bobot:', bobot.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Bobot:  [[-2.82526131e-01  3.44900100e-01  2.55885248e-01  3.63889483e-01\n",
            "   2.40653192e-01  6.80951765e-01 -3.57223524e-01  5.69456011e-01\n",
            "  -2.64509384e-01 -1.91226540e-01 -5.61333010e-01  1.40382101e+00\n",
            "   1.32142264e+00  1.13448557e+00  1.74533484e-01 -9.95090773e-02\n",
            "   1.19738125e+00 -9.66330289e-01 -9.42914525e-01 -1.12167096e+00\n",
            "  -8.16727319e-01 -2.71131066e-01 -1.29240239e+00 -1.16026870e+00\n",
            "   3.98876023e-01  6.18094965e-02  1.10093072e+00]\n",
            " [-1.53093658e+00  2.06660768e+00  1.56952081e+00 -7.21406341e-01\n",
            "  -7.75452105e-01 -1.65287330e+00  1.30725197e+00  1.82443562e+00\n",
            "  -1.58381637e-01 -7.40324211e-01  6.04687015e-02  8.31942984e-01\n",
            "   7.92840945e-01 -7.81261967e-01 -9.81085056e-01 -1.36206169e+00\n",
            "  -9.11403078e-01 -5.33745733e-01 -4.88671402e-01  7.74785154e-01\n",
            "   7.61340239e-01  1.10829125e+00  8.03567223e-01 -1.57692980e+00\n",
            "   1.55667306e+00  1.19919213e+00  1.46691939e+00]\n",
            " [-8.38637380e-01 -2.67136415e-02  8.25071963e-01  1.20056896e+00\n",
            "   1.21559454e+00  6.74092502e-01 -5.78150146e-01  9.02074104e-01\n",
            "   1.22866611e+00  1.10825699e+00 -5.62508528e-01  8.45654898e-01\n",
            "   1.41017145e+00 -6.20283400e-01  1.35624966e+00  2.95993767e-01\n",
            "  -3.86529953e-01 -6.64380092e-01 -1.78620147e-01  5.20308194e-01\n",
            "  -1.10907389e+00 -1.00241555e+00  5.50072506e-01 -1.21432214e-01\n",
            "  -3.37300472e-01 -3.62095052e-01  3.34857680e-02]\n",
            " [-1.16919372e+00  5.08227083e-01  1.18087602e+00  8.82193112e-01\n",
            "   8.55219843e-01 -1.71381196e+00 -3.47992319e-01  1.17485228e+00\n",
            "   1.28152782e+00  9.20966534e-01  1.33013075e+00  1.69340517e-03\n",
            "   1.35538015e-01 -8.53493398e-01 -1.86776429e-01 -4.23495405e-01\n",
            "  -8.03486538e-01  1.69860773e-01  1.16032897e-01  8.20480580e-01\n",
            "  -1.40445846e-01 -4.46730722e-01  8.98275186e-01 -7.22538569e-01\n",
            "   1.06919580e+00  6.85375430e-01  8.80937979e-01]\n",
            " [ 8.25984511e-01 -4.93482380e-01 -8.30972195e-01 -1.59042860e-01\n",
            "  -2.68585315e-01  2.10079468e-01  6.86971956e-01 -7.08741958e-01\n",
            "  -6.16769504e-01 -5.16380827e-01 -6.12360329e-01 -7.10994471e-01\n",
            "  -4.13277795e-01  6.17218144e-02  1.43337631e+00  1.17310917e+00\n",
            "   2.96619358e-01 -1.52010112e-01 -1.18608350e-01 -9.76780784e-02\n",
            "  -1.19208572e+00 -1.29695099e+00 -2.24546097e-01  1.60712022e+00\n",
            "  -1.28673895e+00 -1.55884345e+00 -1.57475348e+00]\n",
            " [ 4.01211525e-01  3.95543368e-01 -4.21497220e-01 -6.67227207e-01\n",
            "  -7.23420939e-01  1.65249198e-01 -3.73543781e-01 -1.45730555e-01\n",
            "  -8.95026848e-01 -7.41193886e-01 -1.57355530e-01  6.21566887e-01\n",
            "   6.49212470e-01  4.56394213e-01  3.33654314e-01  3.23203615e-01\n",
            "   7.21061547e-01 -3.09492144e-01 -3.16669661e-01 -2.05494324e-01\n",
            "  -4.62779186e-01 -4.05900646e-01 -2.03162390e-01  9.27695302e-01\n",
            "  -1.29526896e+00 -1.12295387e+00 -1.07550221e+00]\n",
            " [-1.32320507e+00 -2.10525010e+00  1.34211260e+00  1.75376714e+00\n",
            "   2.07011074e+00 -3.28000963e-01 -4.45219068e-01 -2.35826333e-01\n",
            "   2.34765974e+00  2.70391622e+00  2.00805221e+00 -5.65336729e-01\n",
            "  -4.26004128e-01 -1.23497181e+00  4.76822360e-01  8.53945778e-01\n",
            "  -1.28404231e+00  6.01052587e-01  7.40517368e-01  1.17073022e+00\n",
            "  -6.35759125e-03 -2.64383898e-01  1.17033696e+00  1.54999632e+00\n",
            "  -1.36113875e+00 -3.76468877e-01 -1.45518500e+00]\n",
            " [ 1.36371014e+00  4.30644960e-01 -1.33382161e+00 -1.43313134e+00\n",
            "  -1.30894135e+00  8.91805024e-01 -1.80970344e+00 -1.20423593e+00\n",
            "  -1.25661766e+00 -8.84210899e-01 -6.21830296e-01 -1.61226362e+00\n",
            "  -1.66503830e+00 -5.42752501e-01 -6.99820219e-01 -1.42739531e-01\n",
            "  -4.99862713e-01  1.93805604e+00  2.03735750e+00  5.68161395e-01\n",
            "   1.64323576e+00  1.36048090e+00  6.61421372e-01 -3.79452341e-01\n",
            "   4.17482832e-01  1.09847997e+00  3.26760579e-01]\n",
            " [-5.25501418e-01  9.30614031e-02  5.04839339e-01  6.71335792e-01\n",
            "   6.09337059e-01  8.25964101e-01  1.51587360e-01  7.22712366e-01\n",
            "   3.41651733e-01  3.19654805e-01 -5.93323248e-01  3.19958480e-01\n",
            "   6.66525590e-02  1.19835566e+00  2.63892477e-02 -1.09536547e-02\n",
            "   1.11770885e+00 -5.70494708e-02  1.12879502e-01 -1.05030252e+00\n",
            "  -4.81184000e-01 -8.31781919e-02 -9.82415431e-01  6.57537945e-02\n",
            "  -8.48006063e-02 -4.01804931e-01 -5.01861262e-02]\n",
            " [ 6.95485646e-01 -8.76441981e-01 -7.05665623e-01  7.06562306e-01\n",
            "   6.42060736e-01  9.66758936e-01 -4.81712096e-01 -8.02073977e-01\n",
            "   3.54775045e-01  3.27512160e-01 -8.25895299e-01 -7.89519484e-01\n",
            "  -1.57551415e-01  6.44614876e-01 -7.07881188e-01 -1.28856355e+00\n",
            "  -9.37662467e-02 -1.52848834e+00 -1.55643797e+00 -9.05812137e-01\n",
            "   7.25832077e-01  9.60541317e-01 -5.43881237e-01  4.24997507e-02\n",
            "  -2.16319454e-01  8.66957485e-02 -3.56294001e-02]\n",
            " [ 1.28690631e-01  6.24205665e-01 -1.53810160e-01 -1.43604155e+00\n",
            "  -1.31146951e+00 -4.81052749e-01  1.00252777e+00  1.67955444e-01\n",
            "  -9.73328486e-01 -8.83754405e-01  3.43003821e-01  2.71031559e-01\n",
            "  -5.70716756e-01  7.29363952e-01 -1.58649135e+00 -8.78844064e-01\n",
            "   3.62640327e-01  1.86004469e-01 -2.04111019e-01 -7.09866888e-01\n",
            "   7.13581195e-01  8.70521308e-01 -4.81557626e-01 -5.02678046e-01\n",
            "   6.83218613e-01  3.97918244e-01  6.46136469e-01]\n",
            " [ 7.99790782e-01 -6.98823240e-02 -8.04708956e-01 -1.24229792e+00\n",
            "  -1.15566076e+00 -1.05887556e+00  1.02108255e+00 -7.45847114e-01\n",
            "  -6.96145041e-01 -8.28929307e-01  1.30061201e+00 -6.39720633e-01\n",
            "  -9.72034660e-01 -1.62072629e-01 -2.45847000e-01  7.56280960e-01\n",
            "  -2.20008756e-01  7.95502809e-01  5.17297448e-01 -1.52814989e-02\n",
            "   6.64880825e-01  7.17515896e-02 -1.63770962e-01 -1.84346105e-01\n",
            "   8.15251224e-01  3.32082863e-01  4.46745231e-03]\n",
            " [ 1.46005334e+00 -1.04658278e+00 -1.42575930e+00  2.47735282e-01\n",
            "   1.34839088e-01  7.12697574e-01  1.18256026e-02 -1.58141951e+00\n",
            "  -2.97562194e-01 -2.30447910e-01 -8.87887794e-01 -2.54876132e-01\n",
            "  -7.26692820e-01  8.45708386e-01  2.86204710e-01  8.22703446e-01\n",
            "   1.11375346e+00  6.61491448e-01  4.00904336e-01 -7.69656511e-01\n",
            "  -7.84713012e-02 -5.87208391e-01 -1.05165437e+00  5.88930584e-01\n",
            "  -3.56485853e-01 -4.74374801e-01 -5.24527041e-01]]\n",
            "Ukuran Bobot: (13, 27)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "456a6d5c-7da7-4505-edc1-0e55986d52b1",
        "id": "1dMVRive6_pT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Testing\n",
        "y_pred = lvq.test(x_test, bobot_dan_label)\n",
        "# print('Label Pred: ', y_pred)\n",
        "# print('Label True: ', y_test)\n",
        "print('Accuracy:', accuracy_score(y_test, y_pred))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy: 0.9146757679180887\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "cZH9B4Q17K3y"
      },
      "cell_type": "markdown",
      "source": [
        "### LVQ2.1"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "c84e2c50-4ec4-4c75-a567-1f003138f76c",
        "id": "TxQxSZTN7K31",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1344
        }
      },
      "cell_type": "code",
      "source": [
        "# Training\n",
        "lvq = LVQ(sizeInput=n_input, sizeOutput=n_output, max_epoch=10, version='2.1')\n",
        "bobot_dan_label = lvq.train(x_train, y_train)\n",
        "bobot = lvq.getWeight()\n",
        "print('Bobot: ', bobot)\n",
        "print('Ukuran Bobot:', bobot.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Bobot:  [[ -1.78751455   1.96411717   1.71637305   1.55740643   0.76015447\n",
            "    0.78494329   0.94487347   3.08708728  -2.6470253   -2.05991977\n",
            "   -0.97530849   5.65833278   4.68649405   6.68715769   2.61039315\n",
            "    3.77932637   7.91638721  -4.6638122   -6.70568629  -6.81269774\n",
            "   -7.70711931  -4.64978137  -8.51708908  -8.98503285   6.43037306\n",
            "   -1.39274608   8.64819134]\n",
            " [ -6.43972068   9.57845044   6.72832867  -3.46531928  -3.89283427\n",
            "   -6.7871742    6.02765458   7.22830048  -1.24323431  -4.16029396\n",
            "   -1.96968459   2.97377324   3.78726722  -4.50045449  -3.51299225\n",
            "   -5.96644515  -4.87310355  -2.50031989  -1.66985852   4.51818394\n",
            "    3.87365704   5.80207316   3.98353117  -5.79383252   5.56945128\n",
            "    4.37929234   4.51010101]\n",
            " [ -3.91175683   0.52532371   3.89909784   4.98413833   5.51876562\n",
            "    3.82164192  -5.9161999    3.96566065   7.01170775   6.7129404\n",
            "   -2.14092142   4.16303471   7.21745627  -5.00110325   9.22389879\n",
            "    4.88243825  -4.49368447   0.18768263   2.60066668   4.82747335\n",
            "   -8.04476588  -8.92245141   4.95488273   2.08138734  -4.53143298\n",
            "   -4.50354437  -2.77368511]\n",
            " [ -4.12488668   2.37515551   4.21162945   5.15195907   4.98528062\n",
            "  -11.72261445  -5.852513     4.62449182   7.62031958   5.89015041\n",
            "    9.15871152  -2.31465419  -1.90551918  -2.36388711  -1.57995385\n",
            "   -2.34753389  -2.28764466   3.17930498   1.83125743   2.31430951\n",
            "   -0.1594595   -3.22759909   2.82306099  -3.7666695    6.87913809\n",
            "    4.07137784   5.33214915]\n",
            " [  2.39096258  -2.84102693  -2.42848684   0.60513442   0.14567827\n",
            "   -0.0971906    4.66915987  -2.1414852   -1.10632538  -1.04517327\n",
            "   -1.60143454  -8.40796242  -6.31497576  -1.71184754  10.1950312\n",
            "    9.34330529  -2.05757048  -1.49872288  -0.62481462   0.51713616\n",
            "   -6.80282393  -7.85504287   0.29436696   8.09604625  -4.61442845\n",
            "   -7.68685237  -7.30200577]\n",
            " [  1.44897043   2.30245016  -1.57255477  -1.8452072   -2.81013735\n",
            "    8.11393118  -2.64529491   0.35530876  -6.43691836  -3.98256202\n",
            "   -3.75318145   2.5537194    0.29460771  -8.44027222  -6.33391027\n",
            "   -2.51217231  -7.29376406  -0.70036313  -0.50346683   9.46110111\n",
            "    2.68194592   0.60935903  10.34130733   5.99510662  -6.65501616\n",
            "   -8.28954099  -6.66203946]\n",
            " [ -4.43999999  -8.87858299   4.5307935    5.25720546   6.74253614\n",
            "   -0.45147847  -0.96561849  -2.30827974   7.96865865   9.78791475\n",
            "    8.09574794  -2.54242647  -2.81467705  -4.15291203   0.38474919\n",
            "    3.30139608  -4.79062146   3.01340662   3.26610606   3.94911533\n",
            "    1.73990968   0.78009865   3.86198932   6.08836132  -5.50918896\n",
            "   -1.14207166  -5.85624352]\n",
            " [  3.99647962   2.48158021  -3.82853545  -4.41180686  -3.83260897\n",
            "    4.92436573 -10.38100114  -3.61445562  -3.75391722  -2.03840071\n",
            "   -3.50722697  -6.52666472  -5.18470506  -3.27189272  -0.76630378\n",
            "   -0.71926113  -2.45234534   8.20881205  10.0023312    3.57870335\n",
            "    5.77019446   5.56821975   4.10208651  -2.22883718   1.17987855\n",
            "    4.93834497   1.99745287]\n",
            " [ -7.57821288   2.77061733   7.43402014   5.05381513   5.09872994\n",
            "    6.61552352   3.07550433   9.32002414   4.58362646   4.15078244\n",
            "   -3.31690004  -5.12340022  -6.66362011   7.21705602  -1.90624321\n",
            "   -0.84040626   4.17871026   4.79915119   8.22665136  -5.93374301\n",
            "   -0.91862717   2.03462176  -3.04948176   2.20695511   1.24205097\n",
            "   -2.11127655  -1.73601817]\n",
            " [  3.49693217  -5.72576698  -3.50901188   4.03694402   3.91742777\n",
            "    3.08957421  -1.74223016  -5.03472624   3.3447689    2.82481405\n",
            "   -2.55930872  -8.23090389  -2.59097572   1.21085309  -4.61907092\n",
            "   -8.30856914  -4.20287895  -9.75333933 -10.13798988  -3.36825369\n",
            "    6.09837934   6.38735268  -0.33893047   0.57880209  -0.43539249\n",
            "    1.48334397  -0.64157865]\n",
            " [  0.54534454   2.10235401  -0.8638332   -9.90929202  -8.55715786\n",
            "   -2.22192677   7.55722516   1.15126149  -6.2304347   -4.31674226\n",
            "    3.4986543    2.84408359  -6.27227708   5.28767179 -12.84741008\n",
            "   -5.79431188   3.35723957   1.40420985  -3.20671159  -3.72758462\n",
            "    1.36557745   3.63437263  -2.3756587   -0.55112183   2.52170926\n",
            "    0.09014672   3.38781365]\n",
            " [  3.92425668  -4.32029991  -3.91157652  -2.05578945  -2.37583259\n",
            "   -7.74645559   8.6882187   -5.08331208  -0.41254865  -2.40627666\n",
            "   12.26362281  -0.24933033   1.3695729   -1.35996941   2.55977335\n",
            "    5.21669925  -0.92653071  -1.58675034  -1.00429429   0.67723406\n",
            "   -8.18922775  -9.92949574   0.44946914  -5.63740281   6.7652052\n",
            "    1.98272825   4.21386824]\n",
            " [  9.6655071   -9.28555328  -9.25361383   3.68755305   2.97565427\n",
            "    2.48566211   2.66893512 -11.91718677   0.66738753   0.48301086\n",
            "   -4.89807304  -0.58400112  -6.3674283    3.60055827  -0.99860135\n",
            "    4.579952     5.99547797   8.28414805   5.47943936  -3.41508921\n",
            "    1.95730082  -3.61642316  -5.92018807   1.14169337   1.79139308\n",
            "    0.82802357  -0.22472284]]\n",
            "Ukuran Bobot: (13, 27)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "8aebca60-07eb-4dab-b8c4-86146d72a4f3",
        "id": "E_ipeDId7K4H",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Testing\n",
        "y_pred = lvq.test(x_test, bobot_dan_label)\n",
        "# print('Label Pred: ', y_pred)\n",
        "# print('Label True: ', y_test)\n",
        "print('Accuracy:', accuracy_score(y_test, y_pred))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy: 0.764505119453925\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "eGBjIAxy7PWN"
      },
      "cell_type": "markdown",
      "source": [
        "### LVQ3"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "26c7f4de-8108-4d86-97a7-c492009a0a11",
        "id": "UQbLp3Y97PWQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1562
        }
      },
      "cell_type": "code",
      "source": [
        "# Training\n",
        "lvq = LVQ(sizeInput=n_input, sizeOutput=n_output, max_epoch=10, version='3')\n",
        "bobot_dan_label = lvq.train(x_train, y_train)\n",
        "bobot = lvq.getWeight()\n",
        "print('Bobot: ', bobot)\n",
        "print('Ukuran Bobot:', bobot.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Bobot:  [[-2.56197030e-01  3.12448491e-01  2.28931621e-01  3.54779264e-01\n",
            "   2.36042625e-01  7.25993740e-01 -3.41466489e-01  5.37768023e-01\n",
            "  -2.60026719e-01 -1.80383072e-01 -5.67794927e-01  1.42572906e+00\n",
            "   1.30137646e+00  1.15991833e+00  2.56461242e-01  4.48848880e-02\n",
            "   1.24447782e+00 -1.05707373e+00 -1.06911029e+00 -1.14901232e+00\n",
            "  -9.30099395e-01 -4.00253404e-01 -1.30595375e+00 -1.12204323e+00\n",
            "   3.79235834e-01 -3.73121581e-02  1.06136522e+00]\n",
            " [-1.51851774e+00  2.04951752e+00  1.55628177e+00 -7.11458147e-01\n",
            "  -7.66507019e-01 -1.61595680e+00  1.29412136e+00  1.81346986e+00\n",
            "  -1.65435568e-01 -7.36544998e-01  4.69353121e-02  8.30364456e-01\n",
            "   7.92092619e-01 -7.84883549e-01 -9.72824925e-01 -1.35207132e+00\n",
            "  -9.10783679e-01 -5.38271707e-01 -4.95638443e-01  7.78789849e-01\n",
            "   7.43099739e-01  1.09177971e+00  8.09442398e-01 -1.56416610e+00\n",
            "   1.54058553e+00  1.18580934e+00  1.45666806e+00]\n",
            " [-8.56231303e-01 -7.16898318e-03  8.43064971e-01  1.16421821e+00\n",
            "   1.17826200e+00  6.16543598e-01 -4.56679134e-01  9.26897181e-01\n",
            "   1.19320224e+00  1.08007882e+00 -5.29112596e-01  8.10275861e-01\n",
            "   1.35761724e+00 -7.14200484e-01  1.33423328e+00  3.09994015e-01\n",
            "  -4.80467379e-01 -6.23024986e-01 -1.44571322e-01  6.24355878e-01\n",
            "  -1.10806822e+00 -1.01537702e+00  6.78222633e-01 -4.00430056e-02\n",
            "  -3.68541587e-01 -4.07464065e-01 -4.61405489e-02]\n",
            " [-1.16810951e+00  5.12271197e-01  1.17970987e+00  8.80437276e-01\n",
            "   8.52799222e-01 -1.71334268e+00 -3.45214033e-01  1.17705103e+00\n",
            "   1.27916118e+00  9.17045803e-01  1.32806164e+00  1.12492017e-03\n",
            "   1.35761827e-01 -8.54010193e-01 -1.89410486e-01 -4.27739778e-01\n",
            "  -8.04223081e-01  1.68751148e-01  1.14719789e-01  8.21185848e-01\n",
            "  -1.39511985e-01 -4.45855642e-01  8.99149146e-01 -7.24279645e-01\n",
            "   1.07056632e+00  6.82587062e-01  8.82524281e-01]\n",
            " [ 8.20178737e-01 -5.11422528e-01 -8.25528777e-01 -1.32245143e-01\n",
            "  -2.42644630e-01  2.13795712e-01  6.95561183e-01 -7.06477055e-01\n",
            "  -5.94108835e-01 -4.99251161e-01 -6.22016490e-01 -7.20231903e-01\n",
            "  -4.60336560e-01  9.61418594e-02  1.46321666e+00  1.25349906e+00\n",
            "   3.49758048e-01 -1.58393239e-01 -1.20725343e-01 -1.34438790e-01\n",
            "  -1.25394735e+00 -1.37058732e+00 -2.70866560e-01  1.58185742e+00\n",
            "  -1.24589464e+00 -1.55298235e+00 -1.54202314e+00]\n",
            " [ 3.76827907e-01  4.02733612e-01 -3.97058194e-01 -6.59983806e-01\n",
            "  -7.16427988e-01  1.68276743e-01 -3.37085114e-01 -1.21304271e-01\n",
            "  -8.84150679e-01 -7.36246667e-01 -1.61162132e-01  6.04404243e-01\n",
            "   6.31492579e-01  4.89251579e-01  3.51482016e-01  3.37511170e-01\n",
            "   7.69009105e-01 -3.05871331e-01 -3.17230590e-01 -2.46908869e-01\n",
            "  -5.23101787e-01 -4.47477298e-01 -2.48193559e-01  9.09951063e-01\n",
            "  -1.26101222e+00 -1.13544535e+00 -1.05365843e+00]\n",
            " [-1.32320511e+00 -2.10525012e+00  1.34211265e+00  1.75376716e+00\n",
            "   2.07011076e+00 -3.28001001e-01 -4.45219062e-01 -2.35826322e-01\n",
            "   2.34765976e+00  2.70391626e+00  2.00805229e+00 -5.65336684e-01\n",
            "  -4.26004101e-01 -1.23497183e+00  4.76822377e-01  8.53945825e-01\n",
            "  -1.28404233e+00  6.01052578e-01  7.40517347e-01  1.17073023e+00\n",
            "  -6.35761946e-03 -2.64383946e-01  1.17033697e+00  1.54999634e+00\n",
            "  -1.36113878e+00 -3.76468907e-01 -1.45518503e+00]\n",
            " [ 1.36373790e+00  4.30638491e-01 -1.33384728e+00 -1.43317828e+00\n",
            "  -1.30897309e+00  8.91830555e-01 -1.80966218e+00 -1.20426698e+00\n",
            "  -1.25662757e+00 -8.84214911e-01 -6.21837926e-01 -1.61246917e+00\n",
            "  -1.66520419e+00 -5.42917140e-01 -6.99980854e-01 -1.42918221e-01\n",
            "  -5.00061226e-01  1.93811781e+00  2.03745039e+00  5.68257170e-01\n",
            "   1.64331800e+00  1.36054029e+00  6.61520381e-01 -3.79571515e-01\n",
            "   4.17619360e-01  1.09865926e+00  3.26870616e-01]\n",
            " [-5.07066094e-01  6.27352306e-02  4.85776233e-01  6.96796386e-01\n",
            "   6.38561749e-01  8.58654557e-01  8.28709227e-02  6.94377854e-01\n",
            "   3.77910495e-01  3.55014688e-01 -5.94013528e-01  2.18750639e-01\n",
            "   4.11149017e-03  1.20003928e+00 -2.86464826e-03 -5.72307671e-02\n",
            "   1.07369001e+00 -3.89554201e-02  1.40244814e-01 -1.06091680e+00\n",
            "  -4.19024617e-01 -2.81716145e-02 -9.63411815e-01  8.73625232e-02\n",
            "  -8.44388911e-02 -4.46891506e-01 -6.81263554e-02]\n",
            " [ 6.95485650e-01 -8.76441985e-01 -7.05665626e-01  7.06562307e-01\n",
            "   6.42060736e-01  9.66758942e-01 -4.81712096e-01 -8.02073982e-01\n",
            "   3.54775045e-01  3.27512160e-01 -8.25895299e-01 -7.89519479e-01\n",
            "  -1.57551416e-01  6.44614886e-01 -7.07881198e-01 -1.28856355e+00\n",
            "  -9.37662410e-02 -1.52848834e+00 -1.55643797e+00 -9.05812148e-01\n",
            "   7.25832084e-01  9.60541320e-01 -5.43881248e-01  4.24997508e-02\n",
            "  -2.16319455e-01  8.66957504e-02 -3.56294000e-02]\n",
            " [ 1.26444713e-01  6.28527570e-01 -1.51573539e-01 -1.42481828e+00\n",
            "  -1.30538523e+00 -4.81641625e-01  9.80614545e-01  1.70324241e-01\n",
            "  -9.72244190e-01 -8.83287853e-01  3.41938528e-01  2.79837232e-01\n",
            "  -5.66082003e-01  7.39308397e-01 -1.60128670e+00 -9.04476012e-01\n",
            "   3.64029889e-01  1.77048267e-01 -2.08782771e-01 -7.22919876e-01\n",
            "   7.16874909e-01  8.83950016e-01 -4.92816182e-01 -5.15715677e-01\n",
            "   6.91941369e-01  4.04438472e-01  6.58980320e-01]\n",
            " [ 8.17848241e-01 -6.72723390e-02 -8.22026312e-01 -1.24573349e+00\n",
            "  -1.16118586e+00 -1.05091873e+00  9.80023057e-01 -7.65381669e-01\n",
            "  -7.04646530e-01 -8.32654624e-01  1.29406662e+00 -7.09478826e-01\n",
            "  -1.04694425e+00 -1.76950192e-01 -2.57445427e-01  7.78747448e-01\n",
            "  -2.47112585e-01  8.18352047e-01  5.28083618e-01 -5.15343168e-03\n",
            "   7.28699829e-01  1.23116324e-01 -1.50232759e-01 -1.78956293e-01\n",
            "   8.37358345e-01  3.45969927e-01  2.47908888e-05]\n",
            " [ 1.49847227e+00 -1.08065407e+00 -1.46197866e+00  2.48556661e-01\n",
            "   1.34705903e-01  7.01418875e-01  4.66889244e-02 -1.63032923e+00\n",
            "  -2.98290519e-01 -2.32581850e-01 -8.74549092e-01 -3.17685512e-01\n",
            "  -7.42562601e-01  8.11350774e-01  2.33404601e-01  7.23536553e-01\n",
            "   1.03886249e+00  6.89199527e-01  4.30663804e-01 -7.43351890e-01\n",
            "   3.04142721e-02 -4.83430980e-01 -1.01400552e+00  5.97615678e-01\n",
            "  -3.50589649e-01 -4.37018086e-01 -5.34098834e-01]]\n",
            "Ukuran Bobot: (13, 27)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "outputId": "eaae6751-103b-4efb-d206-c0913aae2218",
        "id": "ouDkuoEf7PWp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "# Testing\n",
        "y_pred = lvq.test(x_test, bobot_dan_label)\n",
        "# print('Label Pred: ', y_pred)\n",
        "# print('Label True: ', y_test)\n",
        "print('Accuracy:', accuracy_score(y_test, y_pred))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Accuracy: 0.9249146757679181\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}