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504 articles for “high-performance computing”
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The Principles and Applications of Structural Symmetry in Natural and Engineered Systems: A Comprehensive Review
Abstract: Structural symmetry is a fundamental constraint across scientific domains, dictating the stability, functionality, and efficiency of systems from the subatomic to the macroscopic. In physics and chemistry, symmetry is mathematically defined through Group Theory, specifically point groups (e.g., Cnv, Oh). These groups govern molecular orbital interactions; high-symmetry configurations, such as the icosahedral C60 fullerene, achieve optimal energy distribution and structural resilience. In Structural Biology, symmetry is an evolutionary strategy for …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 30–34 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
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Analyze the Linux Performance in Network Management
Abstract: Computational models utilized for experiments in high-energy physics are progressively becoming globally distributed and grid based. This shift is driven by both technical factors, such as the proximity of computing and data resources and increased demand, as well as strategic considerations, including investment strategies. This transformation poses unprecedented challenges for network infrastructure, end systems, and computing and storage solutions. Among the significant challenges is the reliable and efficient transfer of …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 2, 2023 · pp. 20–28 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Architectural Evolution of RISC Processors: From Early Research Prototypes to Modern Industrial Implementations
Abstract: This paper surveys the architectural evolution of Reduced Instruction Set Computer (RISC) architectures from early research prototypes to modern industrial processors, tracing four decades of design refinement across academic, embedded, server, mobile, and open- hardware ecosystems. Core ISA principles, pipeline evolution, compiler–hardware co-design, and quantitative performance modeling are analyzed through four representative industrial implementations: MIPS 74K, SPARC T4, ARM Cortex-A72, and SiFive U74 (RISC-V). Each processor is examined in terms …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 29–39 Read article
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A Systematic Review of Advanced Composite Materials for High-Performance Spur Gear Applications
Abstract: This is a review which provides specific and detailed information regarding the fiber-reinforced polymer (FRP) composite to replace traditional steel in high-performance spur gears with emphasis on mechanical performance, computational modeling, and experimental validation. Methods: The current literature was thoroughly investigated that includes material properties, material simulation (e.g., finite element analysis, FEA), and experimental gear testing procedures (e.g., DIN 51354, ASTM G99). Certain case studies in the aerospace and automotive …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 209–220 Read article
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Self-Driving Cars and Computer Vision: Enhancing Computer Vision for Autonomous Vehicle Navigation
Abstract: Autonomous vehicles, commonly known as self-driving cars, are transforming the transportation sector by aiming to enhance road safety, ease traffic congestion, and boost overall efficiency. Central to the operation of these vehicles is computer vision, which enables them to perceive and understand their environment. This paper examines how computer vision contributes to the navigation of autonomous vehicles and highlights its continuous developments. Specifically, it examines key challenges such as real-time …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 1–10 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Choosing the Right Machine: A Comparative Analysis of Desktops and Laptops
Abstract: This study provides a comparative analysis of desktop and laptop computers, focusing on factors such as performance, portability, cost, and user requirements. Desktops are highlighted as the preferred option for resource-intensive tasks like gaming, video editing, and handling large-scale data because of their powerful processors, efficient cooling mechanisms, and expandability. These systems are well suited for users who prioritize high performance and the ability to upgrade components over time. On …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 41–49 Read article
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Carbon Fiber Impact Attenuator: A Comprehensive Design and Analysis Approach
Abstract: In the high-stakes world of Formula One competition, accidents are a sad reality. The primary causes of these accidents are violent overtaking, high speeds, and environmental factors. All of these causes result in accidents, such as a car colliding head-on with barricades, two automobiles colliding, a car skidding on a wet track, etc. Driver safety must be improved, and accidents of this nature must be avoided. One such safety elements …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 452–468 Read article
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Optimization of Lightweight Polymer Composites Using Finite Element Analysis Machine Learning and Topology Optimization Techniques for Aerospace Applications
Abstract: The advancement of aerospace engineering depends on lightweight polymer matrix composites (PMCs) because they help decrease weight while improving fuel efficiency and payload capacity together with increased structural integrity. Research developed a computer program comprising FEA with ANN and TO optimize high-performance PMCs through integrated design approaches. The combination of Python-controlled LS-DYNA simulations measured hybrid composite laminate resistance to impact while an ANN model obtained data from simulations to forecast …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 693–709 Read article
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A Novel Efficient VLSI Architecture for Matrix Multiplication using Compressor-based Multiplier
Abstract: Due to advancement of new technology in the field of VLSI, there is an increasing demand of high speed processor. Matrix multiplication is highly used in different types of computations. Speed of processor greatly depends on its multiplier (used in matrix multiplication) performance. Due to which high speed multiplier architecture become important. Several multiplication techniques have been developed to increase the efficiency of the multiplier. These techniques help in reducing …
Published in Journal of VLSI Design Tools and Technology · Vol. 5, Issue 2, 2015 · pp. 23–28 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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A Study on Shortest Route Planning in Road Transportation Networks Using Remote Sensing Technology
Abstract: In the present scenario, information technology plays a major role in the world economics. If we get the timely information about the resources of the city then we could plan and manage its resources in a better way, for the economically and environmentally sustainable urban development. Land cover and the human or natural alteration of land cover play a major role in global scale patterns of climate. Rapid urbanization and …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 1, 2017 · pp. 23–28 Read article
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Chemical Reactor Design and Analysis: A Review
Abstract: Chemical reactors play a critical role in industries such as oil and gas, chemical processing, and power generation, where they operate under extreme pressure and handle highly toxic, compressible fluids. The growing need for alternative energy sources has led to an increased demand for vessels capable of withstanding high pressure and temperature, especially in the chemical and petroleum industries. Recent innovations in chemical reactor technology have concentrated on creating new …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 49–59 Read article
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Dynamic Priority-based Adaptive Scheduling (DPAS) for Modern Operating Systems
Abstract: Dynamic Priority-based Adaptive Scheduling (DPAS) is an innovative CPU scheduling algorithm designed to optimize system performance and resource utilization in modern computing environments. As computing systems become increasingly complex and diverse, traditional static scheduling algorithms often struggle to adapt efficiently to the dynamic nature of workloads. DPAS addresses this challenge by introducing a dynamic and adaptive approach to process prioritization and resource allocation. DPAS leverages real-time feedback, machine learning, and …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 2, 2023 · pp. 6–15 Read article