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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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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Homeopathy and Miasms: Exploring Their Vital Importance
Abstract: An individual’s susceptibility to disease is not solely an internal matter but is also profoundly shaped by a variety of external influences. These influences can be broadly categorized into meteoric factors – such as climate, weather changes, seasonal variations, and atmospheric conditions – and telluric factors, which include environmental and terrestrial elements like soil, water, living conditions, and geographical surroundings. When such external influences act upon the human organism, they …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 16–21 Read article
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Smart Attendance System Using Face Recognition with OpenCV
Abstract: In the past, the conventional method of recording student attendance relied heavily on teachers manually marking entries in a physical register. While simple, this approach is not only time-consuming but also highly vulnerable to errors such as accidental omissions, incorrect entries, or even malpractice in the form of proxy attendance. Moreover, traditional registers lack real-time accessibility, making it difficult to analyze or monitor data instantly. To address these limitations, modern …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 30–39 Read article
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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT
Abstract: The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 18–31 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Post Halela Zard (Terminalia chebula Retz.): A Review on Medicinal Utility from the Perspective of Unani Medicine
Abstract: Halela Zard (Terminalia chebula Retz.), commonly known as Haritaki in Sanskrit and Chebulic Myrobalan in English, is a cornerstone of Unani pharmacotherapy due to its remarkable therapeutic versatility. The dried pericarp of its fruit has been extensively employed in traditional medicine for the treatment of a wide spectrum of ailments, ranging from digestive disturbances to chronic systemic disorders. This review aims to present a comprehensive overview of Halela Zard by …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 19–26 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Integrating Co-Curricular Activities with Academic Achievement in Light of NEP 2020 and NCF-SE
Abstract: This research paper investigates the impact of co-curricular activities on the academic achievement of senior secondary students. The study emphasizes the significance of holistic development in education, where co-curricular activities (CCAs) play a vital role alongside formal academics. CCAs include a range of non-classroom engagements such as debates, music, sports, drama, arts, and community service that contribute to the cognitive, social, emotional, and physical growth of students. These activities are …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 59–66 Read article
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Anti-Cancer Drugs-Common Types in Libya Tamoxifen: Structure and Synthesis
Abstract: This research reviews the role of anticancer organic compounds, focusing on Tamoxifen as a Selective Estrogen Receptor Modulator (SERM) and briefly comparing it to Vincristine and Vinblastine (Vinca alkaloids). At first, the review includes: classification of cancer stages, revealing symptoms of each stage. Moreover, the review gives an overview of the general classification of most of the cancer drugs, types of cancer drugs used specially in Libya, their structural differences …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 114–123 Read article
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Effectiveness of 3-D Printing Technology in Education and Teaching-Learning
Abstract: Education is the key to releasing the true potential of human ingenuity. The emphasis of education should be on both academic and practical, hands-on techniques. It covers the gap between conceptual understanding and real-world execution. 3-D printing, a new educational technology, claims that it will equip pupils for a more technologically advanced future. By incorporating 3-D printing into education, cutting-edge technology is made accessible to ambitious students and future entrepreneurs. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 113–125 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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A Study on Science Teachers’ Perception of Newly Developed Science Workbooks and Their Effectiveness in Fostering Scientific Attitude in Learners
Abstract: This study examines science teachers’ perceptions of newly developed science workbooks and evaluates their effectiveness in fostering scientific attitude among learners. Using a structured opinionnaire, the research gathered comprehensive feedback from teachers across multiple grade levels regarding the clarity, relevance, and pedagogical value of the workbooks. Analysis of opinionnaire responses revealed strong teacher agreement regarding the workbook’s clarity, activity-based structure, and alignment with curriculum goals. Teachers reported noticeable improvements in …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 82–90 Read article
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Cosmeceuticals: Integrating Therapeutic Functionality into Cosmetic Science
Abstract: Cosmeceuticals are a quickly growing group of skincare products that are in between cosmetics and drugs. These products have biologically active components that are said to provide medical or drug-like advantages for a number of skin problems, including ageing, hyperpigmentation, acne, and damage from the sun. Cosmetics are not medications, but cosmeceuticals are made to affect skin function at the cellular level. This article talks about what cosmeceuticals are, how …
Published in Recent Trends in Cosmetics · Vol. 2, Issue 2, 2025 · pp. 19–35 Read article
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Polyurethane: Chemistry, Production, Applications, and Future Prospects—An Overview
Abstract: Polyurethane (PU), a class of versatile polymers, has emerged as one of the most significant materials in modern industry owing to its remarkable mechanical strength, elasticity, durability, and resistance to abrasion, chemicals, and environmental degradation. Its wide range of tunable properties has made PU indispensable across multiple sectors, including fashion, automotive, manufacturing, biomedical, coatings, and construction. This review emphasizes the diverse applications of polyurethane and explores how its unique chemistry …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 17–25 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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Hierarchical Computational Modeling of Physical Structure Across Quark, Nuclear, and Atomic Scales
Abstract: We present a modular, multi-scale computational framework that integrates physical modeling and visualization across quark, nuclear, and atomic scales within a unified pipeline. Developed to address the traditional fragmentation between sub-nucleonic, nuclear, and electronic representations, the system provides a continuous data flow and visualization bridge spanning from femtometers to ångströms. The framework consists of three primary modules: a particle-level module illustrating nucleons as confined quark-triplets with effective flux-tube geometries; a …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 38–53 Read article