Search
327 articles for “training system”
-
Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
-
Automated Vehicle Entry Monitoring System Using YOLOv5
Abstract: This project showcases an innovative You Only Look Once (YOLO) object detection model-based Automated Vehicle Entry Monitoring System for community gates. By using YOLO, the system transforms conventional access control paradigms by accurately and in real-time detecting vehicles that are seeking to gain entry. Unlike traditional approaches, the project leverages YOLO's effectiveness in vehicle recognition, classification and Number Plate Detection to improve residential security. By providing communities with a cutting-edge …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 34–38 Read article
-
Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
-
The MCDM Technique is Being Utilized to Develop Sustainable Supply Chain Management in the Textile Industries
Abstract: Sustainable Supply Chain Management (SSCM) of production systems is crucial in the current globalization setting. Many businesses are having a lot of issues with supply chain management. In order to determine the most effective SSCM techniques, this research will rank the primary SSCM hurdles. The fuzzy analytical hierarchy process (FAHP) is used to rank the primary barriers in SSCM. A committee of three specialists was assembled to score various variables. …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 28–42 Read article
-
Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
-
An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
-
Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
-
Developmental Responses to Structured Training Loads in Competitive Youth Judo
Abstract: This study investigates the influence of a planned and regulated training-load structure on the physical and technical growth of elite youth Judoka aged 10 to 16. A four-week training program progressively modified the key variables of training intensity, frequency, and volume to support performance development while avoiding over-fatigue and injury. Ten athletes participated with performance assessed before and after training using tests for Muscular endurance, Core stability, Lower body explosive …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 07–15 Read article
-
Impact of E-Learning on Secondary Education in Patna District: The Role of Teachers in Supporting Higher Secondary Students during the COVID-19 Crisis
Abstract: This study assesses the impact of e-learning on secondary education in the Patna district during the unprecedented COVID-19 crisis, focusing on the vital role of teachers in supporting higher secondary students. Utilizing a quantitative survey design with a sample of 150 higher secondary teachers from various schools in Patna, the research identifies both the benefits and significant challenges of the rapid transition to digital education. The findings confirm a major …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 28–32 Read article
-
AI Bias: Causes, Impacts, and Ways to Address It
Abstract: As artificial intelligence (AI) continues to permeate various aspects of society, from healthcare and criminal justice to finance and hiring, concerns over its ethical implications have gained increasing attention. A significant ethical concern is the existence of bias in AI systems. Such biases, often rooted in the prejudices present in training data, can lead to unfair and discriminatory consequences, disproportionately affecting marginalized groups. This paper examines the ethical challenges related …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 55–62 Read article
-
Effectiveness of Structured Teaching on Immunization Knowledge and Attitude Among Mothers of Children Under-5 years of Age at Bal Mahila Chikitsalaya, Lucknow
Abstract: This section offers a thorough overview of the study's background, explaining the significance of vaccination, the variables affecting vaccination coverage, the role mothers play in the decision-making process regarding vaccinations, and the necessity of focused interventions to improve immunization uptake among children under five. As a fundamental component of preventive healthcare, immunization shields both individuals and communities from a variety of infectious diseases. In order to comprehensively assess changes in …
Published in International Journal of Children · Vol. 1, Issue 1, 2024 · pp. 5–22 Read article
-
Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
-
Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
-
Rail and Coil Gun Based Levitating Hybrid Train
Abstract: Hybrid train is a train which is a hybrid of the concept ideas of coil gun, rail gun, halback array, magnetic levitation etc. Theoretically this train could achieve the fastest Speed an object could reach respect to its mass. This train could surpass sound barrier and could even be made to go to speed exceeding mach 3. But due to travel safety a certain speed limit can be implemented in …
Published in Trends in Electrical Engineering Read article
-
An Integrated Autonomous Rover-Drone System for Intelligent Exploration and Environmental Monitoring
Abstract: This paper presents a hybrid autonomous exploration platform integrating a ground rover and aerial drone, enhanced by swarm intelligence and a custom-trained YOLO V8 object detection model. The rover is equipped with GPS, IMU, and environmental sensors (DHT11, MQ135, BMP180), while the drone performs real-time aerial mapping and obstacle prediction. A YOLO V8 model, trained on 500 annotated terrain images (six classes: rocks, pits, trees, water, animals, vegetation), achieves a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
-
Navigating the Future: Exploring the Best Employee Management Systems of Today
Abstract: In this paper, we discussed an effective employee management system with the help of Python GUI Technology. A company's ability to successfully manage its workforce is essential to its success. The Employee Management System enables employers to easily manage all records. Python GUI Technology is used in the development of the application-based staff management system. In previous studies, there were two applications developed to manage employee details and another to …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 25–29 Read article
-
Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
-
Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article
-
Case Study on Snake Bite
Abstract: Snakebites are a major public health concern in India, with the World Health Organization (WHO) estimating approximately 5 million cases annually. Out of these, around 2.7 million involve envenomation, where venom is injected through the snake's bite. These venomous bites pose significant medical emergencies and can lead to severe complications, including permanent physical impairments if not treated promptly. Immediate medical intervention is crucial to mitigating the adverse effects of snakebites. …
Published in Research and Reviews : Journal of Surgery · Vol. 13, Issue 2, 2024 · pp. 21–25 Read article
-
Enhancing Control with Embedded Ssvep-Bci
Abstract: Brain–Computer Interface (BCI) technology establishes a direct communication link between the human brain and external devices without relying on muscular activity. Among various BCI paradigms, the Steady-State Visually Evoked Potential (SSVEP)-based approach has gained significant attention due to its high signal-to-noise ratio, minimal user training, and suitability for real-time applications. However, implementing such systems on embedded hardware presents challenges such as limited computational resources, signal noise, and latency in processing. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 41–52 Read article