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1978 articles for “CLA” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Machine Learning-Driven Early Prediction and Prevention of Obesity and Overweight
Abstract: Obesity has become a global health concern, with its prevalence reaching alarming levels in recent years. By classifying obesity-level, healthcare professionals can assess an individual's risk and develop appropriate treatment and prevention strategies. Healthcare professionals can customize interventions and create personalized treatment plans based on individual needs. This paper delivers a system provides an overview of obesity, highlighting the importance of accurate and standardized categorization for effective management and treatment …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 31–40 Read article
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Exploring Psychotropic Trends of Medication Use in Psychiatric Outpatients: An Observational Study at a Tertiary Care Hospital
Abstract: Background: Psychotropic medications are essential in managing a wide range of psychiatric disorders, including depression, anxiety, bipolar disorder, and schizophrenia. Prescribing habits in outpatient clinics can differ a lot depending on things like the patient’s age, background, and medical conditions. Aim: This study aims to explore the trends in psychotropic medication use among psychiatric outpatients at a tertiary care hospital, with a focus on understanding prescribing patterns, demographic factors, and …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 2, 2025 · pp. 15–23 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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A Critical Appraisal of Nutritional Value of Mashadi Modaka in Ativyayama Janit Poshana Abhava (Relative Energy Deficiency) in Sports Persons
Abstract: Background: Sports Medicine is defined as physical fitness, treatment and prevention of injury related to sports and exercise. As per Ayurvedic classical texts, in the concept of Dinacharya, Vyayama is defined as physical exercise and is advised to be performed at Ardhashakti (~half of one’s capacity). Otherwise, Atiyoga Lakshana, such as Shrama (~excessive fatigue), Klama (~exhaustion), Kshaya (~depletion), etc., may be observed. Nowadays, it is observed that most sportspersons consume …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 2, 2025 · pp. 15–23 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Self-Healing Polymer Nanocomposites: A Comprehensive Review of Design Strategies, Mechanisms, and Emerging Applications
Abstract: Self-healing polymer nanocomposites (SHPNs) are a new class of materials that can autonomously repair themselves to prolong their lifetime and improve their application performance. Herein, we provide a comprehensive overview of the design strategies, healing mechanisms, and emerging applications of SHPNs. Incorporating nanofillers (nanoparticles, nanofibers, and/or nanotubes) into polymer matrices leads to requisite functionalization that significantly enhances mechanical properties and is essential in self-healable products including improved cross-linking, high dispersion, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 281–293 Read article
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Geospatial Assessment of Land Use and Land Cover Changes in Debrigarh Wildlife Sanctuary, Odisha: A Twenty-Year Perspective
Abstract: Among the recorded dynamic processes on the surface of the earth is the change in land use and land cover (LULC) pattern as an outcome of several anthropogenic practices. Planning, development, and management of land for sustainable usage of land depend on plotting and tracing the vagaries in LULC. Anthropogenic activity, generally for forestry and food production, is altering the land surface. The steadily diminishing landscape also has tragic implications …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 2, 2025 · pp. 12–27 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
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Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Bridging the digital divide for school students with Specific Learning Disability in India: A Systematic Literature Review
Abstract: This systematic literature review aims to investigate the educational materials now utilized in inclusive classrooms in India to close the digital divide for children with specific learning disabilities (SLD). With an emphasis on policy, assistive technology, and teacher preparedness, the goal is to assess how well these resources work to create inclusive learning environments and look at how they might be tailored to help different learners. The review followed PRISMA …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 17–25 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Controlling Animals and People Near Railway Tracks Using the Internet of Things
Abstract: A lot of people are opting to use the train instead of the bus now as bus tickets have become so expensive. In order to keep the railroad network running well, it is necessary to constantly inspect and monitor the tracks. Till now, the train track inspection process and monitoring system are done manually, which is laborious and wasteful since human error is likely to happen at any point. Because …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 01–10 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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A Comprehensive Review on Piezoelectric Composites for Energy Harvesting and Sensing
Abstract: The capacity of piezoelectric composites to transform mechanical energy into electrical energy and vice versa has drawn a lot of interest recently. This property makes them very appealing for use in energy harvesting and sensing applications. These materials combine the high piezoelectric performance of ceramics with the mechanical flexibility and processability of polymers or other matrices, enabling a wide range of practical uses in flexible electronics, wearable systems, and embedded …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 19–24 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Advances in Polymer-Based Materials for Dental Applications: A Case Study on PVC and Ceramic Coatings in Digital Mouth Mirrors
Abstract: Polymeric materials play a crucial role in modern dentistry, providing improved mechanical properties, biocompatibility, and enhanced functionality in dental instruments. These materials contribute significantly to the advancement of dental tools, ensuring durability, safety, and efficiency. This study explores the application of polyvinyl chloride (PVC), ceramic coatings, and anti-fog polymer layers in the development of a digital mouth mirror. The integration of these materials results in enhanced durability, corrosion resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 244–252 Read article