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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…In conclusion, this project validates the feasibility of integrating IoT and machine learning to optimize waste management. The system reduces environmental impact and promotes sustainability, offering a scalable framework for addressing global waste challenges.…”
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An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification
Published 2024“…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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Smart waste management system with IoT monitoring
Published 2023“…Through advanced data analytics and machine learning algorithms, the platform predicts waste accumulation patterns, optimizes collection routes, schedules pickups based on fill-level data, and detects any abnormal conditions. …”
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Novel Approaches to Plastic Pollution: Leveraging Machine Learning and Metaproteomics for Advanced Plastic Degradation
Published 2025journal::journal article::research article -
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Efficient Model for Waste Load and Route Optimization
Published 2024“…The model utilizes machine learning techniques to forecast the quantity of waste collected by GPTs. …”
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Wind power forecasting with metaheuristic-based feature selection and neural networks
Published 2024“…Inaccurate forecasts can lead to a mismatch between wind power generation and energy demand, resulting in wasted energy, increased emissions, and reduced grid stability. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…This study examines the utilization of different Machine Learning algorithms, such as Linear Regression, Decision Trees, Support Vector Machines (SVM), Gradient Boosting, Random Forest, K-Nearest Neighbors (KNN), Convolutional Neural Network (CNN) Regression, and Particle Swarm Optimization (PSO), in the domain of predictive modeling and cost optimization in the field of construction project management. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Mixed waste classification based on vision inspection / Hassan Mehmood Khan
Published 2022“…Classification of dry waste garbage is crucial since incorrect labelling of dry waste types may contribute huge loss to waste industry. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater
Published 2024“…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications
Published 2015“…This research work was limited to Java based web applications. In future research, the method can be extended to include other programming languages as well as other similar web application security vulnerabilities.…”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)...
Published 2019“…The model training flow will have 2 classifier groupings which are control group and auto machine learning (ML) where feature selection with redundancy elimination method to be applied on input data to reduce the number of variables to minimum prior modeling flow. …”
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