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567 articles for “Training”
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Monitoring System for Students During Online Exams
Abstract: Remote learning has taken residence owing to the effect of COVID-19. Despite the details and many educational institutes were compulsory to close, students were able to complete their degrees using online platforms. Exams, on the other hand, remain unsolved. It’s been modified to a copy-and-paste assignment form for around, while others have just canceled them. If our current lifestyle is to become the new standard, there necessity to be a …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 22–29 Read article
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Reactive Strength Index as a Predictor of Jump Height and Agility in Basketball Athletes
Abstract: This study examines the relationship between the Reactive Strength Index (RSI) and specific performance metrics, namely jump height and agility, in youth basketball players. The RSI, a measure derived from drop jump testing, provides insight into an athlete’s explosive strength and reactive capabilities—essential qualities for success in basketball, where quick directional changes and reactive power are integral to performance. A cohort of forty youth athletes, comprising 20 males and 20 …
Published in Recent Trends in Sports · Vol. 1, Issue 2, 2024 · pp. 8–13 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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Evaluation of Emergency Response Plans in Industrial Environments Using Simulation Techniques
Abstract: Industrial facilities, particularly those in the chemical, manufacturing, and energy sectors, face significant hazards due to their complex operations and the handling of hazardous materials. Ensuring the safety of workers and minimizing the impact of incidents require robust and effective emergency response plans (ERPs). Traditional evaluation methods, such as drills and tabletop exercises, often fall short in replicating the complexities of real-world emergencies. These methods may lack the realism needed …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 6–10 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
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AI-Driven Exam Evaluation Systems: Challenges, Innovations, and Future Directions
Abstract: A proposed AI system is used to grade exams automatically. It addresses inefficiencies in human assessment. A GPT model trained on graded replies is used for evaluation, and TrOCR is used for precise handwritten text recognition. Efficiency and less bias are provided by this method, although there are still issues. More work is needed to assess open-ended questions and make sure they are understandable. To automate many aspects of exam …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 7–13 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 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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Generative Artificial Intelligence with Emphasis on Large Language Models: Review and Current Trends
Abstract: Generative Artificial Intelligence deals with AI systems that generate new content, such as text, and images. It accomplishes this by using data patterns of texts and images that already exist. Generative AI began an era of major advancement in AI, producing more refined and human-like results. Large Language Models, LLMs, is a part of Generative AI with applications in Natural Language Processing such as text generation, translation, summarization, sentiment detection …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 40–46 Read article
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Effectiveness of A structured teaching program on Leucorrhoea and it's management for women of Reproductive age group at selected college in Honavar
Abstract: Leucorrhea, also known as leucorrhea, is a white, yellow, or green discharge from a woman's vagina, which may be normal or asign of an infection. Leucorrhea is common during pregnancy and is typically normal if the discharge is thin, white, and odorless.Physiological leucorrhea is a condition that occurs in young women several months to a year after the onset of menstruation. It sometimes occurs in newborn girls and usually lasts …
Published in International Journal of Women's Health Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 40–44 Read article
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A Descriptive Study to Assess Knowledge Regarding POSH Act Among Staff of Chirayu Medical College and Hospital, Bhopal, Madhya Pradesh
Abstract: Introduction: Sexual harassment is a significant health issue with severe effects on employees’ self-respect, physical mental health, and dignity. This descriptive study aimed to assess knowledge scores regarding the POSH (Prevention of Sexual Harassment) Act among staff of Chirayu Medical College and Hospital. A convenience sampling method was employed, and data were gathered using a self-designed knowledge questionnaire. The findings indicated that 41% of the staff had poor knowledge, while …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
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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
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Vocational Education in Higher Secondary Schools: A Review of Factors Influencing Student Interest and Attitudes
Abstract: The study investigates the essential aspects influencing students' motivation and attitudes toward vocational education in higher secondary schools, emphasizing its changing importance in current educational systems. Vocational education, which focuses on hands-on training and real-world applications, is critical in closing the gap between academic learning and the labor market. Despite its promise to promote employment, diversity, and economic development, vocational education faces considerable obstacles, such as societal stigma, insufficient resources, …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 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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Drone Safety Protocols Developing and Implementing Safety Procedures
Abstract: The increasing utilization of drones across various sectors, including agriculture, logistics, surveillance, and recreational activities, necessitates the establishment of robust safety protocols to mitigate risks associated with their operation. This study explores the development and implementation of comprehensive safety procedures for drone operations, focusing on both regulatory compliance and technological advancements. The study emphasizes how crucial it is to comprehend the legal frameworks set forth by aviation authorities, including the …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 44–49 Read article
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Green Human Resource Management: Awareness, Perception, and Its Impact on Employee Well-being and Work-Life Balance
Abstract: This study explores the growing significance of Green Human Resource Management (Green HRM) and its impact on employee well-being and work-life balance. As organizations face increasing pressure to adopt sustainable and environmentally responsible practices, Green HRM emerges as a strategic approach that aligns ecological objectives with human resource policies. The research aims to assess employee awareness and perception of Green HRM initiatives and how these perceptions influence their job satisfaction, …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 2, 2025 Read article
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article