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1887 articles for “m-learning” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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Cloud Enabled Machine Learning Framework for Medicine System
Abstract: The Medicine Generic App is a cutting-edge mobile application designed to empower users with information about generic medications. Given the rising expenses of healthcare and prescription medications, this app acts as a useful resource for consumers to make informed decisions regarding their medication options. The Medicine Generic App aims to promote generic drug usage, reduce healthcare costs, and improve medication management for users. By providing detailed information and price transparency, …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Detecting Fake Accounts on Social Media Using Machine Learning
Abstract: The growing frequency of fake accounts on social media platforms underscores the critical necessity for effective detection methods. In response to this challenge, our study leverages state-of-the-art machine learning techniques to identify and counter deceptive entities effectively. By conducting a thorough analysis of social media data, our approach unveils intricate patterns indicative of fraudulent accounts, enabling proactive measures against them. Through the application of advanced algorithms, we present a comprehensive …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 21–32 Read article
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An Overview of the Design and Optimization of Antennas Employing Machine Learning Algorithms and Methodologies
Abstract: This paper offers a comprehensive exploration of the integration of machine learning (ML) techniques in antenna design and optimization, reflecting the burgeoning interest and potential impact of ML in emerging technologies. The first segment conducts a detailed literature survey, elucidating conventional computational electromagnetic and numerical methods preceding an in-depth discussion on the core facets of ML, encompassing diverse learning categories and frameworks. Additionally, it provides a mathematical exposition on regression …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 10, Issue 3, 2023 · pp. 1–12 Read article
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Utilizing Machine Learning for Self Assessment of Mental Well-being, Informed by Expert Insights and Student Experiences
Abstract: Monitoring one's own well-being is of utmost importance in bolstering mental health. Recent research involving college student populations has investigated the long-term feasibility of recording daily emotional states, activities, and social interactions. The prevalence of mental health issues is on the rise, particularly among young adults and adolescents, placing university students at a heightened risk due to challenges related to fitting in and forming connections in diverse social environments. Many …
Published in Research and Reviews: A Journal of Health Professions · Vol. 13, Issue 2, 2023 · pp. 55–64 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Machine Learning Approach to Predict the Mental Health Issues of Employees in Tech Companies
Abstract: Mental disorders are conditions that have an impact on your emotions, thoughts, and behaviour. It may happen infrequently or have a persistent effect. The topic of mental health has been major and challenging, especially for working professionals. Over time, the urbanized living and workload put a strain on people, making them more vulnerable to mental disorders like anxiety and mental disorders. Working professionals therefore seem to be at an elevated …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 3, 2022 · pp. 1–10 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article
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Machine Learning Based Approaches for the Detection and Classification of Crop Leaf Diseases
Abstract: Crop leaf diseases pose a significant threat to agricultural productivity worldwide, leading to substantial crop losses and economic consequences. Timely and precise identification and categorization of these diseases are vital for effective disease management and safeguarding crops. Over the past years, machine learning methods have gained prominence due to their potential to automate disease diagnosis and classification procedures. This review paper presents an overview of the various machine learning based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 31–38 Read article
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Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Towards a Machine Learning Oriented Expert System for Intrusion Detection Model
Abstract: AbstractIn this paper, we describe the possibility of using machine learning and expert system for constructing a new intrusion detection model. The first main idea is to construct the classifier on the KDD intrusion data using a machine learning algorithm. For constructing the classifier J48 decision tree machine learning algorithm is used. The other key idea is to collect domain expert knowledge, and building an expert system to interpret and …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 24–30 Read article
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Analysis of Machine Learning Algorithms for the Detection of Mental Health Problems in Employees
Abstract: Mental health-related issues are more critical issues in the workplace. Mental health has been a major and challenging issue, especially for working professionals. A bad work environment can cause a variety of physical and physiological problems as well as decreased productivity. People are reluctant to ask for help from mental health specialists, according to studies. The fundamental reason for this is the stigma attached to mental illness. Working professionals therefore …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 12–24 Read article
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AI-Driven Dairy Ledger: Enhancing Efficiency with Machine Learning
Abstract: The dairy business nevertheless has ongoing difficulties with financial management, record-keeping, and operational effectiveness, which frequently lead to resource mismanagement, human mistakes, and revenue losses. These problems are most noticeable on small- to medium-sized farms where manual labor is the primary method. This study introduces an AI-driven Dairy Ledger, a complete machine learning-powered system designed to automate and optimize key dairy functions, such as tracking cow feed orders, managing milk …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 36–46 Read article
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Stock Price Movement Prediction using Machine Learning Algorithms and Time Series Models: A Review
Abstract: The stock market is a very important place for investment in a country. It also serves as the index of the growth for an economy. To determine the behavior of the stock market trends has been the focal point of researchers for very long. The nonlinear structure of the stock market makes it challenging to predict how the stock price will change. But it has been demonstrated that stock market …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 2, 2022 · pp. 7–13 Read article
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Revolution of Artificial Intelligence and Machine Learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are profoundly transforming various industries by introducing groundbreaking technologies such as deep learning, federated learning, reinforcement learning, and natural language processing. These innovations are not only reshaping the way organizations operate but are also opening new avenues for solving complex problems across diverse sectors, including healthcare, finance, transportation, and more. This study provides a comprehensive exploration of these emerging technologies, emphasizing their practical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 38–44 Read article
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A Comprehensive Review: Effectiveness Of Multi-Sensory Learning Strategies for Learning Disability Students
Abstract: A person's ability to learn new things can be severely hampered by a range of neurodevelopmental diseases known as difficulties with learning. Multisensory learning is an instructional strategy that offers learners multiple ways to perceive information through different sensory signals. The purpose of this review is to assess how learning disabilities, Dyslexia, Dysgraphia, and Dyscalculia can be treated with a multisensory learning approach. A thorough evaluation of past papers published …
Published in International Journal of Education Sciences · Vol. 1, Issue 2, 2024 · pp. 01–09 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article