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68 articles for “IDS performance evaluation”
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Evaluating AI-Driven Adaptive Learning Models in Mathematics: A Contemporary Perspective
Abstract: Artificial Intelligence (AI) continues to transform mathematics education through data-driven personalization and adaptive learning technologies. This study investigates how AI-enabled adaptive platforms influence student performance and engagement in mathematics classrooms. Using a quantitative approach across two institutions, pre- and post-assessment results were compared between students using AI-assisted adaptive learning tools and those receiving conventional instruction. The findings reveal that AI-driven learners demonstrated significantly higher gains in conceptual understanding and engagement …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 8–12 Read article
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From Molecular Mechanics to Nanocomposites: Engineering Polytetrafluoroethylene (PTFE) for High-performance Coating Applications
Abstract: Polytetrafluoroethylene (PTFE) exhibits remarkable chemical inertness, hydrophobicity, antifriction, self-lubrication, and high-temperature resilience, making it an ideal polymer for various industrial applications, including coatings for medical implants, machinery parts, and corrosion-resistant structures. This study presents a comprehensive analysis of PTFE’s structural properties, focusing on helix reversals within its helical carbon-fluorine chains and their effects on mechanical behavior. The phase transitions of PTFE at temperatures from ambient to high (198°C and above) …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 2, 2024 · pp. 14–19 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Injection Pressure Optimization for Non-edible Biodiesel Blends in CRDI Engines: A Comparative Study
Abstract: The growing demand for clean and sustainable energy has increased interest in biodiesel produced from non-edible oil sources. These fuels are renewable, biodegradable, and do not compete with food resources. However, the effective use of biodiesel blends in modern diesel engines requires proper control of fuel injection parameters, particularly injection pressure. In common rail direct injection (CRDI) engines, injection pressure strongly influences spray formation, air–fuel mixing, combustion behaviour, and exhaust …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 24–34 Read article
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Exploring Oroxylum indicum Phytochemicals as VEGFR-2 Inhibitors: A Molecular Docking Approach for Cancer Management
Abstract: Cancer is still a major health problem around the world and is one of the top causes of death. A protein called VEGFR-2 (vascular endothelial growth factor receptor 2) is important because it helps blood vessels grow by supporting the survival, movement, and growth of certain cells. This process is essential for tumors to grow and spread to other parts of the body. This study focused on evaluating the binding …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 48–62 Read article
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Atmospheric Modeling: A Comprehensive Review of Numerical Approaches and Applications
Abstract: Atmospheric modeling plays a crucial role in understanding and predicting atmospheric processes, weather patterns, and climate variability. This review synthesizes current methodologies and applications across several types of atmospheric models, including numerical weather prediction (NWP), climate models, air quality models, and chemical transport models. We explore the intricacies of data assimilation, model evaluation, parameterization, and the importance of high-performance computing in advancing model accuracy and efficiency. Special emphasis is placed …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 16–21 Read article
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The Role of BIM and Parametric Intelligence in Architectural Practice: A Study of Architects in Uttarakhand
Abstract: Dehradun, the capital city of Uttarakhand, represents one of India’s youngest and most dynamic urban centers in Uttarakhand. Since its designation as the state’s capital, the city has experienced a rapid evolution in architectural development and construction technology. As urbanization and design demands increase, architectural practices in Dehradun and across Uttarakhand are progressively shifting from conventional methods toward advanced digital tools that promote precision, efficiency, and sustainable outcomes. Among these, …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 19–38 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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Mapping the Literature on Digital Payment: A Comprehensive Review and Bibliometric Analysis
Abstract: This study essentially performs a comprehensive and in-depth analysis of the current research on digital payment systems. It examines and evaluates 346 journal papers from reliable sources like Scopus and Web of Science that were published between 2015 and 2023. The study intends to give readers a thorough grasp of the state of the art in the field of digital payments research, pinpoint new directions, and emphasize important issues. Among …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 41–59 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments
Abstract: The present investigation focuses on evaluating the performance of turning operations in alloy steel with particular emphasis on the effect of cutting parameters on surface roughness. In the machining of alloy steel, tool life and surface integrity are significantly influenced by parameters such as spindle speed, depth of cut, and feed rate. Among these, feed rate has been observed to exert the most prominent effect on surface roughness. To systematically …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Role of Inflammatory Markers and Lipid Abnormalities in Glycemic Dysregulation Among Type 2 Diabetics
Abstract: Background: Diabetes mellitus (DM) is a chronic metabolic disorder characterized by systemic inflammation and associated with various complications in multiple organs. Type 2 diabetes mellitus (T2DM) specifically involves insulin resistance, hyperglycemia, and inflammatory responses. This study investigates the levels of various inflammatory markers and their correlation with glycaemic control in T2DM patients. Objective: To evaluate the levels of inflammatory markers (including NLR, PLR, SII, SIRI, CRP, IL-6, TNF-α, TGF-β, MCP-1, …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Prediction of Molecular Targets for Anthraquinone and Its Analogs for Treatment of Good Pasteur Syndrome
Abstract: Objective: In order to find prospective molecular targets for the treatment of Good Pasteur Syndrome (GPS), a rare autoimmune disease that affects the kidneys and other organs, computational methods and network pharmacology were applied in this work. The goal of the study is to identify particular human proteins that might interact with anthraquinone and its analogues as well as to uncover potential mechanisms of action by which these drugs might …
Published in International Journal of Bioinformatics and Computational Biology Read article
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A Quasi-Experimental Study to Assess the Effectiveness of a Structured Teaching Programme on Knowledge and Skill of Cardiopulmonary Resuscitation Among Students at Selected Colleges
Abstract: A quasi-experimental study was conducted to evaluate the effectiveness of a structured teaching program (STP) on the knowledge and skills related to cardiopulmonary resuscitation (CPR) among students in selected colleges of Jodhpur. The objectives were to assess and compare the knowledge and skills of students in the control and experimental groups, determine the correlation between knowledge and skill levels, and identify associations with selected demographic variables. The study was guided …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 61–105 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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A Study on Fracture Sem Analysis by Optimization of FSW When a Composite Material Al 6061 Mixed with Fly Ash is Done with Cooper Using Anova Method
Abstract: The current study aims to examine how different parameters in friction stir spot welding influence hardness and tensile strength, while identifying the most suitable parameter combinations to enhance the overall quality of the fabricated components. The experimental work involves joining dissimilar materials, where one specimen consists of Aluminum alloy 6061 reinforced with 10% fly ash, and the other is a copper alloy. Various process conditions are altered during testing to …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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A Novel Direct Weighted Deviation (DWD) Method for Agricultural Enterprise Selection: A Case Study of Namakkal District, Tamil Nadu
Abstract: The study proposes a novel Direct Weighted Deviation (DWD) method for Multi-Criteria Decision Making (MCDM) by eliminating normalization, distance metrics, and pairwise comparisons. DWD is thereafter used to evaluate and select ten rainfed agricultural enterprises against ten generic and context-specific viability criteria in Namakkal District, Tamil Nadu, a water-scarce region in India. Subsequently, other methods (AHP, SAW, WPM, and TOPSIS) are used to obtain a comparative second opinion and validate …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Fracture Toughness in Advanced Materials: A Comparative Review of Testing Methods and Standards
Abstract: Fracture toughness is a key material property used to assess a material's ability to resist crack propagation, which is vital for ensuring the reliability and durability of structures and components in high-performance applications. It is particularly important in advanced materials such as composites, ceramics, and high-strength alloys, which are increasingly used in demanding industries such as aerospace, automotive, and civil engineering. Fracture toughness testing helps determine the material's behavior under …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 17–21 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article