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1974 articles for “approach” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Review of Diagrid and Conventional Frame Systems for Modern Building Design
Abstract: The demand for high-rise buildings in modern cities has accelerated the development of structural systems that balance safety, efficiency, and architectural innovation. Conventional moment-resisting frames, though widely adopted, often become inefficient in tall structures due to higher material consumption and greater lateral displacements under seismic and wind loading. Diagrid systems, defined by their diagonally inclined members forming triangulated grids, provide an alternative approach with enhanced lateral stiffness, reduced drift, and …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 47–53 Read article
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Multi-Objective Optimization of Carbon-Glass Fiber Polymer Drilling Process Based on Fuzzy Grey Entropy Weighing Method
Abstract: In recent years, the machining characteristics of hybrid fiber polymer composites have garnered significant research attention due to their growing industrial applications. This study specifically focuses on the drilling of hybrid carbon-glass fiber reinforced (CGFR) epoxy composites, fabricated using the hand layup technique. The key machining characteristics evaluated in this drilling process include surface roughness and circularity error. The influence of critical drilling process parameters, such as spindle speed, drill …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 100–112 Read article
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Impact of Friendship Quality on Self-Esteem and Resilience among Adolescents
Abstract: Adolescence is an integral developmental stage of change in social, emotional and psychological aspects of an individual's life. Friendship is an essential component of this period that helps to provide social support and emotional comfort. The present research gaps are not fully addressed by the existing literature on friendship quality, self-esteem, and resilience among adolescents. Hence, the present study sought to establish whether friendship quality and its sub-dimensions of safety, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 2, 2025 · pp. 39–49 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article
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Exploring the Therapeutic Potential of Ilāj-Bil-Ghizā (Dietotherapy) in Depression: A Systematic Review
Abstract: Background: Depression is a common mental health condition characterized by feelings of sadness, diminished interest in activities, and physical symptoms that disrupt daily activities functioning. Emerging research indicates that nutrition and dietary habits can significantly influence the management of depression. This review aims to explore the connection between diet and mental health, highlighting how nutritional approaches may complement traditional treatments for depression. Objective: This review aims to evaluate the relationship …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 10–18 Read article
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Creating a ‘Sustainable Future’ through Secured-AI
Abstract: It is imperative in the present world that we need to figure out a way to move to a ‘Sustainable future’. However, a ‘Sustainable future’ from an energy standpoint can only be built by a ‘Sustainably intelligent’ society. But the individuals who come together to form a society tend to neglect any discussion around ‘Sustainability’ considering it as something to be driven in top-down manner. In reality, with the massive …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 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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Influence of Hybrid Fiber Reinforcement on the Interfacial Bonding and Fracture Toughness of Epoxy-Based Polymer Composites Under Cyclic Loading
Abstract: This study investigates the influence of hybrid fiber reinforcement on the interfacial bonding and fracture toughness of epoxy-based polymer composites under cyclic loading. Carbon, glass, and aramid fibers, both individually and in hybrid combinations, were incorporated into the epoxy matrix to evaluate their thermal, mechanical, and fatigue-resistant properties. Thermal characterization revealed distinct material behaviors, with carbon fibers exhibiting superior thermal conductivity, while glass and aramid fibers provided enhanced thermal stability. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 799–824 Read article
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Unveiling the Relationship Between Anxiety and Self-Esteem in Adult Populations
Abstract: The purpose of this study was to investigate the intricate connection between anxiety and self-esteem in adult Delhi National Capital Region (NCR) residents. A purposive sample approach was employed to select seventy people from this region. The study measured participants' self-worth and gathered pertinent background data using the Rosenberg Self-Esteem Scale (RSES) and a sociodemographic data form. In the data analysis, a t-test was employed to assess significant differences between …
Published in International Journal of Children · Vol. 2, Issue 2, 2025 · pp. 35–44 Read article
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Pharmacology in Clinical and Therapeutic Settings
Abstract: Polypharmacy, which refers to the practice of taking many medications at the same time, is becoming more common among elderly populations as a result of the steadily increasing prevalence of chronic conditions. The clinical and therapeutic consequences of polypharmacy are investigated in this paper, with a particular emphasis placed on drug-drug interactions, altered pharmacokinetics, and patient safety. The physiological changes that occur with advancing age have a substantial impact on …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 51–58 Read article
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Optimizing DevOps Pipelines with Maven: Advanced Build Automation Techniques
Abstract: As modern software development continues to evolve, DevOps has become a fundamental methodology for integrating development and operations teams to enhance collaboration, reduce software delivery time, and improve overall product quality. Automating builds is a crucial aspect of any DevOps pipeline, as it helps maintain consistency and dependability throughout the different phases of the development process. Maven, a robust build automation tool commonly used in Java projects, is instrumental in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 06–11 Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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A Comprehensive Survey on Detection of Video Transitions
Abstract: Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 17–26 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article