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Create soaa.js
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src/tokens/soaa.js

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// src/tokens/soaa.js - Self-Optimizing Adoption Accelerator Module
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import axios from 'axios'; // For making API requests
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import { MachineLearningModel } from './mlModel'; // Import a mock ML model
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class SelfOptimizingAdoptionAccelerator {
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constructor() {
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this.userData = {};
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this.educationMaterials = [];
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this.satelliteNodes = [];
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this.mlModel = new MachineLearningModel(); // Initialize the ML model
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}
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// Method to initialize the SOAA
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async initialize() {
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try {
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await this.loadEducationMaterials();
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await this.loadUser Data();
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this.optimizeUser Experience();
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this.distributeSatelliteNodes();
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} catch (error) {
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console.error('Initialization error:', error);
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}
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}
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// Load educational materials from an external API
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async loadEducationMaterials() {
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try {
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const response = await axios.get('https://api.example.com/education-materials');
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this.educationMaterials = response.data;
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} catch (error) {
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console.error('Error loading educational materials:', error);
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this.educationMaterials = this.getFallbackMaterials(); // Fallback materials
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}
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}
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// Load user data for personalization from an external API
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async loadUser Data() {
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try {
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const response = await axios.get('https://api.example.com/user-data');
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this.userData = response.data;
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} catch (error) {
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console.error('Error loading user data:', error);
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this.userData = this.getFallbackUser Data(); // Fallback user data
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}
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}
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// Optimize user experience based on data
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optimizeUser Experience() {
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const preferredMaterials = this.educationMaterials.filter(material =>
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this.userData.preferences.preferredTopics.includes(material.title)
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);
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this.displayEducationalContent(preferredMaterials);
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}
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// Display educational content to the user
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displayEducationalContent(materials) {
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materials.forEach(material => {
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console.log(`Title: ${material.title}`);
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console.log(`Content: ${material.content}`);
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// Here you could integrate a UI framework to display content interactively
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});
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}
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// Method to distribute satellite nodes intelligently
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distributeSatelliteNodes() {
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const optimalLocations = this.mlModel.predictOptimalLocations(this.educationMaterials);
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this.satelliteNodes = optimalLocations.map(location => ({
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location,
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status: 'active', // Set status based on some criteria
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}));
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console.log('Distributed satellite nodes:', this.satelliteNodes);
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}
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// Fallback educational materials
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getFallbackMaterials() {
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return [
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{ id: 1, title: 'Introduction to GTC/GU', content: 'Fallback content for GTC/GU.' },
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{ id: 2, title: 'Benefits of GTC/GU', content: 'Fallback content for benefits.' },
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];
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}
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// Fallback user data
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getFallbackUser Data() {
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return {
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preferences: {
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preferredTopics: ['GTC', 'GU'],
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interactionHistory: [],
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},
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};
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}
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}
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export default SelfOptimizingAdoptionAccelerator;

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