Search
303 articles for “dynamic adaptation”
-
Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
A Decade of Viral Evolution (2015–2025): Emergence, Mutations, and Implications for Global Health
Abstract: Over the past decade (2015-2025), viral evolution has profoundly reshaped the global health landscape, challenging healthcare systems, diagnostic tools, therapeutic strategies, and vaccine efficacy. This review comprehensively analyzes the evolutionary trajectories of major human and zoonotic viruses, with a focus on pandemic-prone, drug-resistant, and emerging pathogens. Viral evolution is driven by diverse molecular mechanisms including high mutation rates, recombination, reassortment, host immune pressure, and antiviral interventions, leading to genetic diversification, …
Published in International Journal of Vaccines · Vol. 2, Issue 2, 2025 · pp. 31–40 Read article
-
Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
-
Computer and Commerce – Relationship for The Future
Abstract: The relationship between computers and commerce has evolved dramatically over the past few decades, transforming the way businesses operate and how consumers interact with markets. This synergy continues to grow and holds significant potential for the future. Computers, through advancements in artificial intelligence (AI), machine learning, cloud computing, and big data analytics, have revolutionized commerce by enhancing efficiency, improving decision-making, and fostering innovation. In the future, we can expect even …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 42–59 Read article
-
Diet-Gene Interactions in Farm Animals: Molecular Dynamics, Gene Expressions, Signalling Pathways and Precision Nutrition for Sustainable Productivity
Abstract: Diet-gene interactions represent a central mechanism through which nutrition influences growth, health, and productivity in farm animals. Recent advances in molecular biology and genetics have revealed that nutrients act not only as metabolic substrates but also as signalling molecules capable of modulating gene expression, cellular pathways, and epigenetic regulation. This review synthesizes current knowledge on the molecular dynamics of nutrient utilization in farm animals, with emphasis on nutrigenomic responses, nutrient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
-
A Review Study of Bio-Psycho-Social Challenges and Interventions for Women During their Perinatal Period
Abstract: Pregnancy causes women to face dynamic and sudden changes in their body and psyche, and sometimes they might as well feel dissociated or separated from the journey. Even though they mentally adapt to the pregnancy, they require constant support at all levels to face the challenges during this crucial period. The goal of the current research is to examine the bio-psycho-social challenges and interventions for women during their perinatal period. …
Published in International Journal of Children · Vol. 1, Issue 2, 2024 · pp. 31–37 Read article
-
Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
-
Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
-
Dynamic Simulation of Load-Responsive Vapor Compression Refrigeration Systems
Abstract: Because of their dependable operation and effectiveness, vapor compression refrigeration systems, or vapor compression refrigeration (VCRS), have become popular in commercial, industrial, and residential settings. However, under different thermal loads, classic vapor compression refrigeration (VCR) systems may perform less well in that they are usually built for steady-state conditions and run at consistent speeds. In order to improve a load-responsive VCR system’s flexibility, energy efficiency, and response to changing cooling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 32–37 Read article
-
The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
-
Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
-
A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
-
Adaptive Hospitality: Designing Modular Hotel Rooms for Multi-Functional Use in Urban Micro Hotels
Abstract: This research investigates the concept of adaptive hospitality through the lens of modular design, focusing on the creation of multi-functional hotel rooms in urban micro-hotel settings. With the rise in urban populations and increasing scarcity of land, hospitality design must adopt innovative spatial strategies that prioritize flexibility, efficiency, and user experience The research explores how modular and transformable design solutions can respond to the spatial constraints of dense urban environments. …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 39–51 Read article
-
Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article
-
Automatic Flame Detection and Tracking
Abstract: Recent advancements in independent robotics, embedded systems, and intelligent perception have appreciably improved the capability of firefighting robots designed for early fire detection, flame localization, and suppression. A broad range of studies explores vision-based and sensor-fusion techniques designed for reliable flame discovery in complex environments. Image-processing approaches—including adaptive edge-detection, infrared/thermal imaging, color-space analysis, and profound learning—are extensively implement to enhance real-time fire gratitude, even in the presence of smoke or …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 6–12 Read article
-
Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
-
Current Developments In 4D Printing Technology
Abstract: The perception of four-dimensional (4D) printing expertise was prompted through the time dimension inclusion in three-dimensional (3D) printing. Many other industries, including engineering, health, and the arts, have revealed a great deal of attention it. Recently, innovations in bioscience have been established that can be implemented using 4D printing. The ability to integrate time with situational variations has many benefits, but perceptibility and adaptability are merely two. Smart material, stimulus, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 108–120 Read article
-
AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
-
Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
-
A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article