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262 articles for “Training Methods”
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Human Resource Management System in Higher Education Institutions in Azerbaijan
Abstract: The actuality of the subject: The significance of human resource management in tertiary institutions is considerable, particularly regarding employee engagement, motivation, and retention, given its influence on research outcomes and educational standards. The presence of actively involved and inspired faculty and staff is critical in cultivating a favorable academic atmosphere and enhancing the standing of the institution. Retention issues have the potential to result in escalated expenditures on recruitment and …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 2, 2025 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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To evaluate the effectiveness of a structured educational program on knowledge about hypoglycemia and its management among diabetes patients living in selected urban slums of Durgapur, West Bengal
Abstract: INTRODUCTION: Diabetes Mellitus (DM) is a significant global health issue characterized by chronic hypoglycemia and an imbalance in the metabolism of carbohydrates, fats, and proteins. It has multiple underlying causes. Hyperglycemia refers to high blood glucose levels, while low blood glucose levels are known as hypoglycemia. Raising awareness about the signs and symptoms of diabetes among individuals with the condition can potentially minimize complications. OBJECTIVES: 1. To evaluate the initial …
Published in International Journal of Community Health Nursing And Practices · Vol. 1, Issue 1, 2023 Read article
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Electromagnetic Propulsion Train for Future Transportation
Abstract: The Electromagnetic Propulsion Train project focuses on the development and analysis of a prototype system that achieves linear motion through the application of controlled electromagnetic forces. Unlike conventional railway systems that rely primarily on mechanical drive mechanisms such as wheels, axles, and traction motors, this project explores an alternative propulsion approach based on electromagnetic interaction. In this system, a sequence of electromagnets is strategically positioned along the track to generate …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 2, 2025 · pp. 25–31 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Education Needs Augmented Reality
Abstract: Augmented reality, or AR for short, is the integration of information in digital format, including the real image of a particular user. Many universities now use virtual reality. Using technology for education can create smart universities and Colleges. Thus, this essay will go over the different areas in which augmented reality can be applied. In education, augmented reality (AR) has become a game-changing tool that combines digital content with the …
Published in International Journal of Education Sciences · Vol. 1, Issue 1, 2024 · pp. 18–24 Read article
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Convolutional Neural Network Based Ripeness Detection of Fruits
Abstract: The accurate and efficient assessment of fruit ripeness plays a crucial role in ensuring the quality of fruits and optimizing supply chain management. This paper presents a novel approach for the automated detection of apple and banana ripeness using Convolutional Neural Networks (CNNs). The suggested method supports the capability of CNNs to learn hierarchical features from images, variations in color and shape associated with different ripeness stages. The online dataset …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 30–36 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 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 3, 2026 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Enhancing Language Proficiency: Comprehensive Vocabulary Building Strategies for Effective English Teaching
Abstract: This study investigates the effectiveness of vocabulary building strategies (VBS) in enhancing English language instruction at the University of Duhok, emphasizing student perceptions gathered through a quantitative questionnaire. A total of 86 participants were surveyed to evaluate the impact of VBS on vocabulary acquisition, aiming to identify the most effective teaching methods in this context. The analysis reveals that students have a generally positive perception of VBS, indicating that these …
Published in Emerging Trends in Languages · Vol. 2, Issue 1, 2025 · pp. 1–09 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Impact of Self-Help Groups (SHGs) on Sustainable Livelihood Development in Rural Uttarakhand: A Study on the Influence of DAY-NRLM in Income Generation and Community Empowerment
Abstract: Self-Help Groups (SHGs) have emerged as a vital mechanism for fostering sustainable livelihoods in Uttarakhand, a region challenged by poverty, migration, and unemployment. This study examines the role of SHGs in expanding livelihood programs and empowering members, particularly in income generation, while highlighting the importance of group-based approaches for vulnerable communities like small farmers and craftsmen. Data collection for the study involved a questionnaire targeting 288 respondents across 100 SHGs …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 46–54 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article