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Flask_5G/app.py ADDED
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+ # pip install flask
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+
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+ from flask import Flask,render_template,request
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+ import tensorflow as tf
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+ import pickle
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+ import pandas as pd
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+ import numpy as np
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+ from sklearn.ensemble import RandomForestRegressor
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+ from sklearn.preprocessing import MinMaxScaler
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+
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+
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+
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+ # If you need to inverse transform, you can use scaler.inverse_transform(scaled_data)
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+
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+
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+ # loading the label encoder
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+ #le=pickle.load(open('label_encoder.pkl','rb'))
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+
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+ # loading my mlr model
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+ model=pickle.load(open('modelrff.pkl','rb'))
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+
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+ #loading Scaler
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+ scalar=pickle.load(open('scaler.pkl','rb'))
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+
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+ # Flask is used for creating your application
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+ # render template is use for rendering the html page
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+
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+
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+ app= Flask(__name__) # your application
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+
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+
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+ @app.route('/') # default route
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+ def home():
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+ return render_template('home.html') # rendering if your home page.
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+
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+ @app.route('/pred',methods=['POST']) # prediction route
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+ def predict1():
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+ '''
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+ For rendering results on HTML
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+ '''
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+
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+ rd = request.form["Signal_Strength"]
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+ ad= request.form["Latency"]
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+ ms = request.form["Required_Bandwidth"]
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+ s = request.form["type"]
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+ p = request.form["Allocated_Bandwidth"]
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+ t = np.array([[float(rd),float(ad),float(ms),float(s),float(p)] ])
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+ x=scalar.transform(t)
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+ output =model.predict(x)
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+
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+
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+ return render_template("home.html", result = "The predicted Resource_Allocation is "+str(np.round(output[0])))
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+
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+
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+
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+ # running your application
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+ if __name__ == "__main__":
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+ app.run()
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+
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+ #http://localhost:5000/ or localhost:5000
Flask_5G/label_encoder.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:bfdb45e3c1c63f7ed34e5f99c50cbb955cbd53e56fd70fb93aa759f69ff88f08
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+ size 417
Flask_5G/model.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:3462352bcd7f816421bc9289d1d15b57ac48bdbfbc6b4759c27fd93eb0ff415a
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+ size 346957
Flask_5G/modellr.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:d526080f306256810b6a392c95c75b0a5afdb93e740194a6178070364c0b0a20
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+ size 660
Flask_5G/modelrff.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:c16c1b6b194d92e86b62a0921eda4c22764938f3db81bf79504a008ed4f76e68
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+ size 349901
Flask_5G/scaler.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:60fb700bd382eabf7cce28fdb282aa71ea859f0aae1bc6d0f9f11f13c29e8b57
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+ size 858
Flask_5G/static/images/download.jpg ADDED
Flask_5G/templates/home.html ADDED
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+ <!DOCTYPE html>
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+ <html lang="en">
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+
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+ <head>
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+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <style>
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+
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+ body {
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+ position: relative;
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+ font-family: Arial, sans-serif;
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+ margin: 0;
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+ padding: 0;
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+ display: flex;
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+ flex-direction: column;
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+ justify-content: center;
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+ align-items: center;
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+ height: 100vh;
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+ }
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+
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+ body::before {
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+ content: "";
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+ position: fixed;
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+ top: 0;
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+ left: 0;
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+ width: 100%;
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+ height: 100%;
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+ background: linear-gradient(rgba(0, 0, 0, 0.3), rgba(0, 0, 0, 0.5)), url('../static/images/download.jpg');
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+
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+ background-repeat: no-repeat;
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+ background-attachment: fixed;
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+ background-size: cover;
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+ z-index: -1;
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+ }
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+
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+ .heading-row {
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+ display: flex;
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+ justify-content: center;
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+ align-items: center;
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+ flex-direction: column;
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+ padding-top: 20px;
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+ }
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+
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+ h1 {
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+ color: white;
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+ text-align: center;
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+ }
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+
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+ .form-row {
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+ display: flex;
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+ justify-content: center;
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+ align-items: center;
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+ }
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+
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+ form {
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+ background-color: rgba(255, 255, 255, 0.1);
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+ padding: 20px;
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+ border-radius: 10px;
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+ width: 300px;
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+ text-align: center;
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+ box-shadow: 0 0 10px rgba(0, 0, 0, 0.9); /* Add shadow effect */
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+ }
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+
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+ label {
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+ display: block;
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+ margin-top: 10px;
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+ font-size: 20px;
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+ color: white;
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+ font-weight: bold;
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+ }
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+
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+ select,
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+ input {
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+ width: 100%;
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+ padding: 8px;
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+ margin: 5px 0;
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+ box-sizing: border-box;
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+ background-color: rgb(178, 178, 224);
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+ }
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+
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+ input[type="text"]{
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+ background-color: rgb(178, 178, 224);
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+ color: rgb(0, 0, 0);
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+ }
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+
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+ input[type="submit"] {
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+ background-color: #4caf50;
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+ color: white;
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+ cursor: pointer;
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+ }
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+
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+ input[type="submit"]:hover {
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+ background-color: #45a049;
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+ }
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+
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+ .result {
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+ margin-top: 20px;
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+ color: white;
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+ }
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+ </style>
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+ </head>
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+
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+ <body>
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+ <div class="heading-row">
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+ <h1>AI-Driven Optimization Of 5G Resource Allocation For Network Efficiency</h1>
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+ </div>
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+
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+ <div class="form-row">
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+ <form action="/pred" method="POST">
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+ <label for="type">Application Type:</label>
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+ <select name="type">
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+ <option value="2">File_Download</option>
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+ <option value="0">Background_Download</option>
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+ <option value="1">Emergency_Service</option>
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+ <option value="3">Online_Gaming</option>
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+ <option value="4">Streaming</option>
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+ <option value="5">Video_Call</option>
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+ <option value="6">Video_Streaming</option>
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+ <option value="7">VoIP_Call</option>
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+ <option value="8">Voice_Call</option>
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+ <option value="9">Web_Browsing</option>
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+ </select>
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+
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+ <label for="Signal_Strength">Signal Strength:</label>
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+ <input type="text" name="Signal_Strength">
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+
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+ <label for="Latency">Latency:</label>
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+ <input type="text" name="Latency">
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+
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+ <label for="Required_Bandwidth">Required Bandwidth:</label>
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+ <input type="text" name="Required_Bandwidth">
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+
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+ <label for="Allocated_Bandwidth">Allocated Bandwidth:</label>
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+ <input type="text" name="Allocated_Bandwidth">
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+
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+ <input type="submit">
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+
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+ <div class="result">
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+ {{result}}
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+ </div>
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+ </form>
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+ </div>
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+ </body>
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+
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+ </html>