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1976 articles for “bending-mode piezoresistivity” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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The Evolving Role of Librarians in Shaping Modern Spaces
Abstract: Today, libraries have transformed from being merely quiet sanctuaries for reading and research into vibrant, interactive spaces that promote learning, creativity, and collaboration. These modern libraries serve as hubs of innovation, where community members can engage with not only books but also technology, multimedia resources, and each other. This evolution reflects a broader shift in the role of librarians, who are no longer just custodians of books and information but …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 2, 2025 · pp. 65–71 Read article
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Advanced Micromachining with Abrasive Jet Machining: Experimental Observations and Model Comparisons
Abstract: Abrasive Jet Machining (AJM), also known as Micro Blast Machining, is a non-traditional machining process that removes material through the erosive action of a high-velocity gas jet carrying fine abrasive particles. This process is particularly effective for machining intricate shapes in hard and brittle materials that are heat-sensitive and prone to chipping. Similar to sandblasting, AJM is widely utilized for tasks such as deburring, rough finishing, and micromachining, especially in …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 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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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Global Supply Chain Agility Through ERP Systems: A Decision Support Model for Emerging Economies
Abstract: In today’s highly dynamic and interconnected global markets, supply chain agility—the capacity to sense environmental changes and respond rapidly and effectively—has emerged as a critical success factor. This is particularly significant for firms operating in emerging economies, where market volatility, infrastructural limitations, policy uncertainties, and resource constraints pose persistent challenges. Enterprise Resource Planning (ERP) systems, with their ability to integrate cross-functional processes, centralize data, and provide real-time decision-making support, offer …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 31–37 Read article
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Surajmukhi (Helianthus annuus L.): Medicinal Importance in Unani Literature and Modern Evidence
Abstract: Helianthus annuus L. (Sunflower), belonging to the family Asteraceae, is a well-recognized plant in both traditional and modern systems of medicine. In Unani medicine, it is described under the name “Shams-ul-Nahar,” attributed with specific Mizaj (temperament) and pharmacological actions. The plant is considered to possess a hot and moist temperament (Har Ratab), and different parts, including its seeds, oil, and leaves, have been employed in classical formulations. Sunflower seeds are …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 68–75 Read article
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Mathematical Modeling of Tumor Growth and Immune System Interaction Incorporating Time Delays and Suppression Effects for Tumor Control
Abstract: Cancer growth is a complex biological process influenced by various factors, including the dynamic interaction between tumor cells and the host immune system. Mathematical modeling serves as a powerful tool to understand these interactions and predict the outcomes of different therapeutic strategies. This study presents a mathematical framework that captures the essential dynamics of tumor-immune interactions, specifically incorporating the effects of time delay and immune suppression mechanisms. Time delay accounts …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 · pp. 25–34 Read article
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Application of B-trees for Design of Optimal Page Replacement Technique in Modern Operating Systems
Abstract: Algorithms related to replacing the memory pages in operating systems are critical components of modern operating systems that manage virtual memory efficiently. Current algorithms such as LRU (Least Recently Used), Clock algorithms as well as FIFO (First-In-First-Out), often struggle with the increasing demands of contemporary applications and larger memory hierarchies. This research work proposes a novel approach utilizing B-tree data structures to design an optimal page replacement technique. The proposed …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 23–30 Read article
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Emerging Trends in Interdisciplinary Perspectives and Future Frontiers in Modern Symmetry
Abstract: Symmetry, long recognized as a cornerstone of the natural sciences, has increasingly found relevance across a variety of disciplines, from physics and mathematics to economics, architecture, and systems theory. This interdisciplinary review explores the expanding role of symmetry as a conceptual and analytical tool, highlighting its applications in diverse fields. In classical and quantum physics, symmetry principles form the foundation for conservation laws, particle interactions, and field equations. In economics …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 26–30 Read article
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Adversarial Attacks on Machine Learning Models in Cybersecurity: A Systematic Literature Review
Abstract: Adversarial machine learning (AML) is a field that is growing swiftly, especially as machine learning models are employed more and more in places where security is critical. This review goes into great depth over 746 publications from the Scopus database, with an emphasis on the connection between AML and network security. Using Biblioshiny and Scopus tools, we looked at trends in publications, study fields, productive authors, collaboration networks, and theme …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 23–38 Read article
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A Survey on Quality Team Effectiveness in Modern Service Factories
Abstract: In today’s increasingly competitive environment, service‐oriented factories—i.e., operations that deliver services rather than physical goods but use a factory‐style process (such as outsourcing centres, shared service centres, processing hubs, digital service factories)—are under pressure to enhance both quality of output and team effectiveness. This survey paper explores the role of quality teams within modern service factories, and investigates the factors influencing their effectiveness, the mechanisms by which they contribute to …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 25–30 Read article
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Quantitative Mass Balance Modelling for the Synthesis and Production of Ten High-Volume Insecticides
Abstract: This study presents a detailed quantitative mass balance analysis for the industrial synthesis and production of ten high-volume insecticides: acequinocyl, acetamiprid, acynonapyr, alpha-cypermethrin, benzpyrimoxan, bifenazate, bifenthrin, bistrifluron, broflanilide, and bromofos, focusing on material flows, process efficiencies, and environmental implications. These compounds, spanning diverse chemical classes like neonicotinoids, pyrethroids, and meta-diamides, are essential for crop protection but pose challenges due to resource-intensive syntheses and waste generation. For each insecticide, standardized manufacturing …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 3, 2025 · pp. 36–55 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Modeling and Simulation of a Grid-Connected Solar-Wind Hybrid Renewable Energy System with Controlled Inverter
Abstract: Solar and wind energy offer eco-friendly and renewable options to conventional energy sources, holding great promise for the future. This research delves into the modeling and simulation of a grid-connected solar-wind hybrid renewable energy system employing a controlled inverter. The study examines the individual photovoltaic (PV) and wind energy conversion systems and investigates their seamless integration to create a powerful hybrid generation system. To maximize energy use, the application of …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 22–32 Read article
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Experimental Analysis and Predictive Modeling of Mechanical Behavior in Epoxy Composites Reinforced with Waste Tyre Rubber Particles
Abstract: The disposal of end-of-life tyres poses a significant environmental and resource challenge owing to their large volumes and non-biodegradable nature. In this work, we explore the incorporation of waste tyre rubber particles (WTRP) into an epoxy resin matrix to develop sustainable polymer composites and examine their mechanical behavior both experimentally and through predictive modelling. Composites with differing epoxy: WTRP ratios (80:20, 75:25, 70:30 wt.%) and varying rubber particle mesh sizes …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1754–1765 Read article
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Magnetorheological Composite Dampers for Railway Wagon Suspension: Modelling Validation and Performance Analysis
Abstract: Railway wagons encounter continuous vibrations due to track irregularities, resulting in reduced ride comfort and higher dynamic loads. Conventional suspension systems based on springs, hydraulic dampers, or air suspensions provide only limited vibration mitigation. This work investigates the application of magnetorheological (MR) fluid-based dampers, where a polymeric carrier oil (silicone oil) reinforced with carbonyl iron particles serves as a smart composite suspension medium. The MR fluid is synthesized and characterized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 43–63 Read article