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947 articles for “effective learning”
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article
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Facial Expression Recognition using Convolutional Neural Network
Abstract: Machine learning is a subset of Artificial intelligence. Machine learning enables self-learning from past data and predicts the future. Machine learning is used in many applications such as self-driving cars, Google translate etc. Deep learning is a subset of machine learning. CNN is a convolutional neural network. The CNN approach is very effective in image classification. The target of this exploration is to assist a look acknowledgment framework dependent on …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 1, 2021 · pp. 30–35 Read article
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Optimized Household Energy Management System for Demand Response using DFDGCN- BWWPO Technique
Abstract: Energy management in smart homes is becoming one of the main requirement because of fast growth in electricity demand, renewable sources, and electric vehicles. A proper household energy management system not only reduce the energy cost but also help to maintain stability of power grid. Demand Response (DR) program play very big role in this process by shifting or controlling the load according to price and availability of renewable power. …
Published in Trends in Electrical Engineering · Vol. 16, Issue 3, 2025 Read article
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Assessment of Effective use of Online Webinars, Workshop, Conference and Quizzes on Library Science Professionals during Covid Scenario: A Survey
Abstract: Due Covid-19 virus around the globe all sectors have been jeopardized and came to halt. Libraries were not exceptions too, where library professionals started learning and sharing professional knowledge through different e-platforms on different Library Science themes, issues and challenges after a covid scenario in the libraries. The study explored the library science professionals on effective use of online webinars and other series during covid times. The study employed quantitative …
Published in Journal of Advancements in Library Sciences · Vol. 9, Issue 4, 2022 · pp. 1–11 Read article
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System Learning Method Using Spam Filter
Abstract: System learning method can figure out how to perform essential tasks by generalizing from examples. This is often feasible and more effective where human programming is not. As large data becomes available, more ambitious problems can be tackled. As a result, System learning method is broadly used in computer science and other fields. However, developing successful System learning method using spam filter applications requires a substantial amount of “black art” …
Published in Journal of Advances in Shell Programming · Vol. 3, Issue 1, 2016 · pp. 19–27 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Accurate & Efficient Plant Disease Detection using Transfer Learning with Edge Impulse
Abstract: Transfer learning is a powerful machine learning technique that allows optimization of pre-trained models for related tasks on small datasets. In this research paper, we explore the application of Edge Impulse & transfer learning for plant diseases and aim to detect on edge devices more effectively at low cost. We collected and preprocessed many plant images and used this data to fine-tune a neural network model pre-trained by Edge Impulse. …
Published in Recent Trends in Sensor Research & Technology · Vol. 10, Issue 1, 2023 · pp. 30–41 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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To Diagnose the Broken Tooth Fault, Signal Processing Techniques and Machine Learning Technique are Applied
Abstract: The objective of this research is to study the diagnosis of broken tooth fault of spur gear using vibration signals with signal processing and machine learning techniques. In this study, experiment has been performed and analyse on the broken tooth fault and healthy spur gear conditions. This paper describes two approaches to signal processing techniques from acquired vibration signals, which are time-domain and frequency domain, involving statistical characteristics of vibration …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 3, 2023 · pp. 45–53 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article
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Security Challenges and Solutions in Wireless Sensor Networks: a Case study of Afghanistan
Abstract: Due to their capability to collect and relay data from locations without supervision, Wireless Sensor Networks (WSNs) have become essential for numerous contemporary applications (such as environmental monitoring, smart cities, and healthcare). However, the open and resource-constrained nature of WSNs makes them particularly vulnerable to security threats. This paper reviews the key security Issue faced by WSNs and the solutions proposed in recent literature. We examine the unique constraints of …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 27–35 Read article
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Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education during Covid-19 Pandemic
Abstract: The global Covid-19 pandemic has severely affected very aspects of human life, including education. The virus' stunning spread created havoc in the educational system, causing educational institutions to close. As an effect, students must quickly adopt to the change to synchronous online learning. This study identified the different aspects affecting the adaptability level of students in online class. It also identifies the student’s adaptability level in different circumstances in online …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 4, 2023 · pp. 1–8 Read article
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article