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244 articles for “Explainability”
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HPV and Cardiovascular Risk: Unpacking a Novel Link Between Viral Infection and Heart Disease
Abstract: Human papillomavirus (HPV) is best known for its oncogenic potential, yet a growing body of evidence suggests that persistent HPV infection may also contribute to cardiovascular disease (CVD). In 2025, pooled analyses and conference reports galvanized attention by estimating that HPV‐positive individuals have ~40% higher risk of CVD and approximately double the risk of coronary artery disease (CAD) compared with HPV‐negative peers, even after adjustment for traditional risk factors. These …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Impact of Anxiety and Affect on Quality of Life among Youth
Abstract: Youth well-being is an important phenomenon comprising physical, psychological, and social health, where the psychological factors such as anxiety and affect play an essential role in determining Quality of Life (QOL). Young people experience multiple transitions and they are at risk of anxiety disorders that in turn can have adverse effects on academic achievement, physical health, emotional well-being and relationships. Furthermore, affect has a role in the management of emotions …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 1–13 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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Examining the Relationship Between Academic Stress, Maladaptive Perfectionism and Trauma-Related Responses Among University Students
Abstract: Academic stress is a significant concern among university students, frequently contributing to maladaptive perfectionism and trauma-like responses. While perfectionism can enhance performance, its maladaptive variant may be exacerbated by academic stress which can induce trauma-like responses. This study investigates the correlation between academic stress, maladaptive perfectionism and trauma-like responses. Validated self-report measures were used in a quantitative, correlational study involving 101 university students. Linear regression analysis and Kendall’s Tau-B correlation …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 145–154 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 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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Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models
Abstract: Software as a Service (SaaS) solution has revolutionized the contemporary business processes as scalable and service-on-demand solution on cloud networks. Yet, this expansion has brought in sophisticated cybersecurity risks because of a multi-tenant environment facing the internet in the SaaS environment. The key to assure the service availability and protection of the data stored off-site is effective threat detection in such dynamic ecosystems. This review article seeks to discuss the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 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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A Survey of Role-Based Access Control Implementation in HMI Systems for Industrial Automation
Abstract: The convergence of Role-Based Access Control (RBAC) and Human-Machine Interface (HMI) systems presents a transformative approach to secure and efficient industrial automation in Industry 4.0. By integrating RBAC with Multi-Factor Authentication (MFA), this framework enhances cybersecurity while maintaining operational flexibility, mitigating both external threats and internal vulnerabilities. Modern adaptive HMIs further optimize user experience through personalized and intuitive interfaces, though challenges remain in balancing functionality with simplicity in complex industrial …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 10–19 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 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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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Clinical Trial to Find the (Asbab) Aetiology and (Ilaj) Treatment of (Marz-e-Akyās Khusyat-ur-Rahim) Polycystic Ovarian Syndrome (PCOS)
Abstract: Introduction: Polycystic Ovarian Syndrome (PCOS) is common endocrine disorder. It is clinically defined as the syndrome characterized by amenorrhoea, hirsutism and obesity associated with polycystic ovaries. Diagnosis is made on the Rotterdam criteria, established in 2003. The criteria require the presence of 2 of the following 3 criteria: 1. Oligo-ovulation or an ovulation. 2. Hyperandrogenism. 3. Polycystic ovaries through ultrasound evaluation. Methods: Diagnosed patients were enrolled in the trial into …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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The Mediating Role of Label Trust in Shaping Green Purchase Attitudes Among Young Consumers: Sustainable Chemical Transparency in FMCG Packaging
Abstract: This study looks at the function of Perceived Chemical Transparency (PCT) in influencing consumers' Green Purchase Attitude (GPA) in the Fast-Moving Consumer Goods (FMCG) sector, with Label Trust (LT) serving as a significant mediating factor and Environmental Concern (EC) acting as a direct predictor. Based on the Theory of Planned Behavior and Signaling Theory, the study hypothesizes that clear disclosure of chemical and polymer-related information increases trust in eco-labels and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1308–1319 Read article
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Revolutionizing Financial Technology: AI and FinTech
Abstract: The ground-breaking notion of incorporating AI into financial technology by entering the market has been steadily advancing toward dominance. It has become a lever steering innovation, increasing the pace of productivity and minimizing the likelihood of risk. From digital banking to insurance and payments to compliance with regulations, AI is playing the role of a veteran guide to reinvent the old FinTech models and readdress them as a modernistic and …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 07–13 Read article
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Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article
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Modeling Galaxy Formation in a Hierarchical Universe: A Fiducial Approach and Comparison with Observational Data
Abstract: We have developed a detailed model to understand how galaxies form in the framework of hierarchical theories of structure formation. Our model accounts for key processes like the formation and merging of dark matter halos, the heating and cooling of gas inside these halos, the regulation of star formation driven by energy from evolving stars and supernovae, galaxy mergers, and the changes in star populations over time. This approach is …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 · pp. 30–36 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article