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1473 articles for “E-learning”
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Effects of the Embryonic Bisphenol an Exposure on The Postnatal Development, Learning and Memory of Rat Offspring: Fundamental Study
Abstract: We studied the morphologic changes in some organs and changes of learning and memory of the rat offspring after the embryonic bisphenol A exposure. Background: Bisphenol A, widely used as polycarbonate plastics material to manufacture food packaging, toys, glasses, computers, kitchen utensils and medical instruments, is one of the most common endocrine-disrupting chemicals. It is demonstrated that bisphenol A may be mingled with foodstuff and beverage from package and receptacle. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 58–63 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Content-based Image Retrieval: Recent Trends and Techniques
Abstract: Due to the affordability of digital devices and the accessibility of internet technologies, a vast number of multimedia databases have been established for various applications. These image databases increase the need for efficient picture retrieval search strategies that meet user requirements. When compared to other systems, the content-based image retrieval (CBIR) system is one of the most widely used systems for retrieving images from enormous databases. Much work has been …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 01–32 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Depression Detection using Machine Learning: A Comprehensive Review
Abstract: Depression is a leading mental health disorder worldwide, often underdiagnosed due to subjective assessment methods. The increasing availability of digital behavioral data and the advancement in machine learning (ML) have opened new avenues for automated depression detection. This review presents a comprehensive overview of recent developments in ML- based approaches for detecting depression. It explores data sources, feature extraction techniques, learning algorithms, evaluation methods, and highlights current challenges and future …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 Read article
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Role and Importance of Machine Learning in Social Media
Abstract: The widespread adoption of social media platforms has transformed the way individuals interact and communicate. Going beyond personal connections, social media has evolved into a potent tool for sharing information, shaping ideas, and fostering participation across various industries. Machine learning is pivotal in enhancing social media's impact. Social media generates vast data daily, and machine learning is essential for extracting insights. Sentiment analysis, a machine learning application, identifies emotions in …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 23–30 Read article
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Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Don’t We Have Anything to Learn From the Past? Perspective of Epidemics
Abstract: History gives us the chance to learn from the past. In this article, a few of history’s biggest outbreaks, epidemics, and pandemics have been chronicled. The difference between these three are: an outbreak is when an illness occurs in an unexpectedly high number of individuals. It may stay in one area or extend more widely. An outbreak lasts up to several days to years. Sometimes, a single case of a …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 Read article
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The Double-edged Sword: Evaluating the Benefits and Challenges of AR and VR in Education
Abstract: Incorporating augmented reality (AR) and virtual reality (VR) into education is transforming traditional learning settings by boosting interactivity, engagement, and accessibility. AR and VR technologies provide immersive experiences that transform theoretical concepts into visual and practical applications, effectively catering to various learning styles. This abstract explores the impact of AR and VR on educational outcomes, examining their applications across various disciplines, including STEM (science, technology, engineering, mathematics), humanities, and vocational …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 5–11 Read article
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A Machine learning approach to asses carbon emission, utility to produce biomaterial
Abstract: The transportation sector, and the automotive industry in particular, has grown significantly over the last ten years. However, these quick advancements have also brought about important problems that require workable answers. The problem of carbon emission is responsible for global warming due to greenhouse gas emission. The present work is focused on CO2 emission from public and personal transport within Agra city on a real-time basis. In the context of …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 22–30 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article