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634 articles for “Architecture”
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Approximation-Aware Computation for Graceful QoS Degradation in Modern Multiprocessor Operating Systems
Abstract: Modern multiprocessor operating systems face unprecedented challenges in maintaining Quality of Service (QoS) guarantees under dynamic workload conditions and resource constraints. Traditional approaches to resource management often result in abrupt service degradation or complete task failure when system resources become scarce. This study presents a comprehensive framework for approximation-aware computation that enables graceful QoS degradation in multiprocessor environments. We explore the integration of approximate computing paradigms with operating system schedulers, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Hybrid Best-Response Algorithms for Mobile Computing Offloading: A Comprehensive Review
Abstract: The exponential growth of mobile applications with intensive computational requirements has necessitated innovative offloading strategies in mobile computing ecosystems. This comprehensive review examines hybrid best-response offloading algorithms integrated with game-theoretic optimization frameworks to address resource allocation challenges in mobile edge computing (MEC) environments. The proliferation of Internet of Things (IoT) devices and bandwidth-intensive applications has created unprecedented demands on mobile network infrastructure, compelling researchers to develop sophisticated offloading mechanisms that …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 20–26 Read article
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A Literature Review on Internet of Medical Things
Abstract: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment planning, and patient management through data-driven insights and automation. The Internet of Medical Things (IoMT) represents a significant shift in modern healthcare, enabling real-time patient monitoring, data-driven decision-making, and enhanced medical outcomes. This literature review explores the architecture of IoMT, including perception layer, network layer, transport layer and application layer. It also thoroughly explores key challenges like ensuring data security, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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NOVA: The Virtual Desktop Assistant
Abstract: This research work details the design, development, and implementation of a voice-controlled desktop assistant aimed at streamlining everyday tasks and boosting user productivity. The assistant seamlessly integrates with various desktop applications and core operating system functions to automate routine operations, deliver relevant contextual information, and provide personalized suggestions based on observed user behavior and preferences. A standout feature of the system is its ability to monitor user activity levels and …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 19–25 Read article
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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Design and Analysis of G+4 Building with Ductile Detailing
Abstract: This study presents the structural design and analysis of a G+4 residential building, with a specific focus on ductile detailing to enhance seismic performance. Ductility plays a crucial role in enabling structures to absorb and dissipate energy during seismic events, thereby minimizing structural damage and improving safety. The project emphasizes key reinforcement strategies such as beam-column junction detailing and confining reinforcement, which are critical to preventing brittle failures and improving …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Advancing Conductive Ink Formulations for DIW with Graphene and Hybrid Nanostructures
Abstract: The development of solvent-based conductive inks for direct ink writing (DIW) has gained significant attention as a pathway toward flexible, wearable, and scalable electronic devices. This review critically examines conductive fillers, binders, solvent systems, and hybrid ink strategies reported in recent literature. Graphene and carbon nanotubes (CNTs) remain the most studied fillers due to their high intrinsic conductivity and unique dimensionality, but challenges such as restacking, bundling, and high viscosity …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 36–49 Read article
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Innovations and Practices in Ornamental Horticulture: Integrating Landscape and Garden Design for Sustainable Aesthetics
Abstract: Ornamental horticulture is a specialized branch of horticultural science focusing on the cultivation, management, and utilization of plants for decorative and environmental purposes. With growing urbanization and lifestyle shifts, the importance of aesthetically pleasing and ecologically sustainable green spaces has significantly increased. Landscape design and garden design, both integral components of ornamental horticulture, contribute not only to the beautification of spaces but also to environmental conservation, mental well-being, and biodiversity …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 13–19 Read article
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Histological Effects of the Antibiotic Gentamicin on the Ovarian Tissue of Female White Laboratory Rats
Abstract: This study aimed to evaluate the histological alterations induced by Gentamicin in the ovarian tissue of white laboratory rats. A total of 12 adult female rats were used and randomly divided into two groups, with each group consisting of six animals. The experimental group received Gentamicin at a dose of 120 mg/kg body weight administered as an injection once daily, while the control group received an equivalent volume of normal …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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Advances in Shell Programming: Techniques, Tools, and Emerging Trends
Abstract: Shell programming has undergone a significant transformation, shifting from simple command-line interactions to a mature, versatile scripting environment that supports modern computing needs. Over time, shells such as Bash, Zsh, and PowerShell have expanded far beyond basic task execution, evolving into powerful tools capable of handling complex automation workflows, system configuration tasks, and cross-platform orchestration. These environments now offer improved error handling, stronger security features, integrated performance-monitoring options, and more …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
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Recent Developments in Hybrid and Nanostructured Basalt Fiber Composites: A Review of Mechanical and Processing Innovations
Abstract: This review delivers a critical analysis of recent advancements in basalt fiber-reinforced hybrid composites (BFRHCs), emphasizing their transformative potential for advanced structural and high-performance applications. Basalt fibers, derived from volcanic rock, exhibit superior tensile strength, excellent thermal stability, and chemical resistance, offering a sustainable and cost-effective alternative to conventional glass and carbon fibers. Hybridization of basalt fibers with synthetic (e.g., carbon, glass) and natural fibers (e.g., flax, hemp) results in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 885–894 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 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
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Effectiveness of 3-D Printing Technology in Education and Teaching-Learning
Abstract: Education is the key to releasing the true potential of human ingenuity. The emphasis of education should be on both academic and practical, hands-on techniques. It covers the gap between conceptual understanding and real-world execution. 3-D printing, a new educational technology, claims that it will equip pupils for a more technologically advanced future. By incorporating 3-D printing into education, cutting-edge technology is made accessible to ambitious students and future entrepreneurs. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 113–125 Read article
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IoT-Enabled Flexible Polymer Sensors for On-Body Health Monitoring and Real-Time Data Transmission
Abstract: Wearable health monitoring systems have grown increasingly vital in shifting care beyond clinical settings, yet many existing technologies remain hamstrung by rigid substrates and unreliable data streaming, impeding continuous and comfortable physiological assessment. Despite advances in flexible materials, most current sensor platforms suffer from limited mechanical endurance, signal instability under dynamic conditions, or an inability to sustain real-time wireless transmission. This work addresses those deficiencies by introducing a fully integrated, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 188–200 Read article
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RTL-to-GDSII Flow Optimization for Low-Power 32-bit RISC-V Processor
Abstract: This paper presents the implementation and optimization of a 32-bit RISC-V processor, transitioning from Register Transfer Level (RTL) design to final GDSII using Synopsys Fusion Compiler over 32nm technology node. The processor architecture is based on the RV32I base instruction set and incorporates a 5-stage pipeline to achieve a balanced trade-off between performance and design complexity. The design methodology involved RTL synthesis, gate-level netlist generation, and successive physical design stages …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 1–10 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article