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262 articles for “Training Methods”
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A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics
Abstract: The research is targeted at the creation of innovative solution "Fingerprint Based Blood Group Prediction" for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 9–18 Read article
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Human Resource Cell Support for Employees Mental Health and Well Being
Abstract: This study explores the persistent issue of mental health in the workplace and evaluates how collaboration among human resource (HR) teams can improve the day-to-day experiences of employees living with mental health conditions. To capture an accurate and timely understanding of effective organizational responses, the research employs a mixed-methods approach to examine the strategies required to address the ongoing mental health challenge. Additionally, this study aims to close the gap …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 Read article
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Face Recognition Attendance System Using Local Binary Pattern Histogram Algorithm
Abstract: Maintaining accurate and tamper-proof attendance records in educational and corporate environments has long been a challenge due to the limitations of manual and biometric systems. This study introduces the development and deployment of a contactless, automated attendance system that utilizes facial recognition through the local binary pattern histogram (LBPH) algorithm. The primary goal is to offer a secure and efficient substitute for conventional attendance methods by harnessing the power of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 29–34 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Artificial Intelligence in Education: Enhancing Usability and Adoption Among Educators in Digital Classrooms
Abstract: The use of Artificial Intelligence (AI) in education has changed digital learning environments. It provides new tools to improve teaching and boost student engagement. However, even with more AI-enabled technologies available, not all educators are using them equally. This uneven adoption is mainly due to problems with usability, accessibility, and digital readiness. This study addresses the critical gap between the potential of AI in education and its practical utilization by …
Published in Recent Trends in Social Studies · Vol. 3, Issue 2, 2026 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Open Source Software Empowering Artificial Intelligence, Machine Learning, and Cyber Security: A Comprehensive Research Study
Abstract: Open Source Software (OSS) has become a foundational pillar for rapid innovation across Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. This paper delivers a comprehensive, journal-length analysis of OSS-driven ecosystems, emphasizing collaborative development, transparency, and accelerated deployment. By providing freely available libraries, tools, and frameworks, OSS makes it easier for developers and researchers to experiment, build models, and deploy solutions quickly. This study examines how OSS can be combined …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 Read article
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Reviving Indigenous Agricultural Practices Through Curriculum Innovations in Rural Schools: A Case Study of Punjab
Abstract: The traditional indigenous agricultural practices in Punjab are inter-generational in nature but are eroding due to modern industrial farming and lack of education integration. There is scope to preserve agriculture by merging this traditional knowledge with school education systems. A descriptive cross-sectional study was performed with a structured questionnaire distributed among 865 respondents in different rural districts of Punjab. The study population consisted of students, teachers, school administrators, parents, and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–9 Read article
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Animal/Object Recognition and Monitoring
Abstract: This study focuses on teaching a computer to identify leopards in images through a process called Object Detection and Image Recognition. We created a special set of pictures (dataset) containing thousands of leopard images. Using a small camera module called ESP32 CAM, we trained the computer to recognize leopards by comparing the images it captures with the ones in the dataset. The results were obtained using a Convolutional Neural Network …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article
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Smart Soil Health Monitoring: Leveraging Sensors and Big Data to Optimize Crop Growth
Abstract: The increasing demand for sustainable farming practices has necessitated the development of innovative technologies that improve crop productivity while reducing environmental harm. This study investigates the combination of internet of things (IoT) sensors and big data analytics for real-time soil health monitoring, with the aim of maximizing crop yield and efficient resource management. This allows for informed decision-making in key agricultural practices, such as fertilization, irrigation, and crop rotation, based …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 36–43 Read article
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Awareness and Utilization of Open Educational Resources Among P.G. Students of Science and Social Science at Aligarh Muslim University: A Comparative Study
Abstract: Open Educational Resources (OER) have become an important component of higher education by providing free and openly licensed learning materials that support teaching, learning, and research. OERs help reduce the financial burden on students, promote equitable access to knowledge, and encourage lifelong learning. Despite the availability of numerous OER platforms, their effective use largely depends on students’ awareness, accessibility, and institutional support. The present study examines the awareness and utilization …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 61–75 Read article
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Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Physiotherapeutic Strategies to Enhance Throwing Accuracy in Cricket Players
Abstract: Background: Throwing accuracy is a crucial skill for cricket players, impacting both individual performance and team success. Physiotherapeutic strategies can enhance throwing mechanics, strength, and flexibility, leading to improved accuracy. Objectives: This study aims to outline effective physiotherapeutic interventions that optimize throwing accuracy in cricket players. Methods: A comprehensive review of current literature and practices was conducted with 3 articles found through PubMed, Google Scholar & Research Gate year range …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 2, Issue 2, 2024 · pp. 30–34 Read article
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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
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Role of Public Libraries in Bridging the Digital Divide: Ensuring Equal Access to Online Library Resources
Abstract: In the digital age, access to online library resources has become an essential part of learning, research, and development. However, the digital divide continues to be a significant challenge, limiting equitable access to these resources for many individuals, particularly those from marginalized communities. Despite the vast transformation the internet has brought to information access, the gap between the digitally privileged and disadvantaged populations persists due to factors such as digital …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 10–14 Read article
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Morphological Heterogeneity and Ethnic Patterning of Anthropometric Traits in Ethiopian Inter-Scholastic Athletes
Abstract: Introduction: Anthropometric characteristics such as body size, proportions, and composition are fundamental determinants of morphological suitability for sport. Ethiopia’s significant ethnic diversity suggests potential variability in these traits; however, systematic data on anthropometric differences among adolescent athletes from different ethnic and demographic backgrounds remain limited. Understanding these variations is critical for talent identification and sports specialization at the school level. Methods: A cross-sectional study was conducted among inter-scholastic athletes representing …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 25–34 Read article
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Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials
Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article