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934 articles for “adaptive systems”
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Reverse Engineering’s Neural Network Approach to the Human Brain
Abstract: The organic components of the brain are capable of performing consistently and successfully in noisy situations. Brain components with highly adaptive or flexible interactions that could be low-precision, unpredictable, or excessively simultaneous are used to construct biological circuits. Two of the most remarkable characteristics of brain networks are their propensity to self-organize and their pattern organization. Recent research on neural networks, including artificial neural networks and convolutional neural networks (CNN), …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 17–24 Read article
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Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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The Digital Lifeline: How Computers Shape Everyday Life
Abstract: Computers have become an integral part of everyday life, significantly influencing the way the common man interacts with the world. From revolutionizing communication to transforming industries, education, healthcare, and entertainment, computers have reshaped the fabric of modern society. This study explores the multifaceted impact of computers on daily life, examining how they have made tasks easier, faster, and more efficient. While enhancing productivity and connectivity, computers have also introduced new …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 33–47 Read article
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Adaptive Maximum Power Point Tracking Using Improved Cuckoo Search for Solar Panels During Variable Sunlight and Shaded Conditions
Abstract: India's government seeks to keep up with the country's quickly increasing energy needs, which are mostly satisfied by burning coal and oil. By 2030, 40% of the country's energy is expected to originate from renewable sources, according to official plans. By 2022, New Delhi hopes to generate 175 GW of renewable energy, primarily from solar and wind power, with a target of 100 gigawatts. Although India has very few renewable …
Published in Journal of Thermal Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 34–45 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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Nutrient Sensing and Microbiota Crosstalk: Driving Determinants Shaping Metabolic Stability and Adaptive Physiology for Animal Health
Abstract: Nutrient sensing is a fundamental cellular process that enables animals to adapt to fluctuating dietary inputs while maintaining metabolic homeostasis and health. Recent advances reveal that the gut microbiota functions as an active metabolic partner, producing bioactive metabolites that directly influence host nutrient-sensing pathways and downstream cellular responses. This review synthesizes current knowledge on the integration of key signalling networks, including adenosine monophosphate activated protein kinase (AMPK), mechanistic target of …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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Wireless I/O Interfaces for Industrial Controllers: An Educational Approach
Abstract: Due to technological advances, the need for versatile and flexible applications in the field of industrial automation is continuously growing. Digitalization, flexibility, connectivity, high-speed transmission, data analysis and integration of different systems are now requirements in most industries. Industrial communication networks are the main tool in accomplishing those requirements. The proposed work is focused in the development of a solution for collecting remote field signals and transmit them by wireless …
Published in Journal of Microcontroller Engineering and Applications · Vol. 10, Issue 1, 2023 · pp. 8–25 Read article
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A Review of Brief Study on Nyctanthes arbor-tristis
Abstract: Nyctanthes arbor-tristis, commonly called Parijat or Night-Flowering Jasmine, is a medicinal shrub with significant therapeutic value. This article provides a detailed examination of the plant’s pharmacological effects, traditional applications, phytochemical composition, and botanical features, along with its potential for therapeutic use. Known for its longstanding role in Ayurvedic and other traditional medical practices, Nyctanthes arbor-tristis has been traditionally used to treat a wide range of ailments, with recent studies confirming …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 2, 2025 · pp. 24–30 Read article
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Gene Editing in Dairy Cows: Advancing Milk Yield, Health, and Resilience for Sustainable Dairy Development
Abstract: Gene editing has emerged as a transformative tool in dairy science, offering unprecedented opportunities to enhance productivity, improve animal health, and bolster resilience against environmental challenges. This study explores the potential of gene editing technologies, including CRISPR-Cas9, in advancing milk yield, optimizing milk composition, and addressing genetic disorders in dairy cows. Specific applications include targeting genes associated with mastitis resistance, improving feed efficiency, and introducing heat tolerance traits to adapt …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Thermophilic Adaptation of Anaerobic Sludge for Electricity Production
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Anaerobic digestion of biogas inside the digester occurs in a particular temperature range. Research shows that the production can be increased by 33% by switching over from mesophilic temperature range (3040 ° C) to thermophilic temperature range (5060 ° C). Even then, biogas plants generally work in mesophilic range because a large amount of energy is required to maintain the high digester …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 2, Issue 2, 2011 · pp. 30–39 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Dynamic Data Flow Based Spatial Sorting Method for GPUs: Software Based Autonomous Parallelization
Abstract: The direct communication between distant parts of a computer system for a mesh or grid based scalable parallel system isn't cost effective. Thus, we have presented and evaluated the performances of spatial sorting method for multi-core GPUs (Graphic Processing Unit) computing. It is a parallel sorting algorithm for autonomous threading of workload which is considerably faster than Thrust Merge sorting, which is known to be the best comparison based sorting …
Published in Recent Trends in Parallel Computing · Vol. 1, Issue 2, 2014 · pp. 11–14 Read article
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Exploring Electric Skateboards: Comprehensive Insights into Design and Modeling
Abstract: Environmental protection and energy conservation have become primary concerns in the 21st century, prompting accelerated efforts to plan and develop electric vehicle (EV) technology. EVs offer numerous advantages, including zero emissions, the establishment of a new automobile industry, economic development, and the creation of efficient and smart transportation systems. This project introduces a foot-controlled steering system designed to enhance vehicle control, making it suitable for various road conditions and reducing …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 · pp. 39–45 Read article
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The Role of Mathematical Reasoning in Legal Analysis: Bridging Two Disciplines
Abstract: This research paper explores the integration of mathematical reasoning into legal analysis, emphasizing the inherent similarities between the two disciplines. Both fields rely on logical structures, such as deductive reasoning, inductive reasoning, and other formal methods of thought. By examining these parallels, the paper reveals the nascent but growing interaction between mathematics and law, uncovering how the organizational schemes that underpin mathematical principles can enhance legal argumentation, decision-making, and analysis. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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AI-Driven DevSecOps Automation: An Intelligent Framework for Continuous Cloud Security and Regulatory Compliance
Abstract: Cloud-native systems, microservices, and infrastructure-as-code (IaC)–oriented CI/CD pipelines have accelerated the pace of software delivery, yet they have also introduced new layers of operational complexity and widened the overall security exposure of modern applications. Traditional DevSecOps workflows still depend heavily on isolated scanners, manual reviews, and static governance processes that are not well-suited for the elasticity and constant change characteristic of multi-cloud environments. To address these limitations, this paper introduces …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 01–15 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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Smart Wireless Charging Infrastructure for Electric Vehicles
Abstract: Wireless Power Transfer (WPT) of Electric Vehicles (EVs) is a potential technology with large scale potential to change how EVs may be charged, eliminate range anxiety, and simplify charging infrastructure. As opposed to the existing conductive charging systems that necessitate physical contact between two charging points, WPT makes power transfer possible regardless of an air gap between charging and the receptive points, making it possible to recharge EVs practically automatically, …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 30–42 Read article
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Scrutinizing and Extract the cause of Scaling Concerns for Fin-FET
Abstract: AbstractRecent Trend in the adaption of New Technological Innovations suggests that People are looking for Power in compactly sized alternatives which suggest that Devices are shrinking down day by day. With increasing demands of Power to Body ratio, it is becoming difficult for the Researchers to cope up with this current scenario. Fin-FET seems to be a possible alternative to combat these expectations but with every new invention comes its …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 3, 2019 · pp. 8–11 Read article
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Physics-Adaptive Digital Twin with Neural-Operator Reduced-Order Modelling
Abstract: This study proposes a novel Physics-Adaptive Digital Twin with Neural-Operator Reduced-Order Modelling (PADT-NO) framework for predictive modelling of complex, nonlinear, and multiscale fluid flows. The proposed mathematical framework integrates fundamental conservation laws, Navier–Stokes dynamics, physics-constrained neural operators, adaptive reduced-order modelling, and uncertainty-aware state estimation within a unified computational architecture. Unlike conventional computational fluid dynamics and purely data-driven approaches, the proposed model dynamically couples high-fidelity physical information with a low-dimensional latent …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 · pp. 89–103 Read article