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504 articles for “high-performance computing”
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Distributed Data Mining Cloud Based System
Abstract: When traditional data mining systems are used for cloud computing, there are performance bottlenecks and scalability difficulties. In this study, it states that a data mining platform is directly based on the cloud computing. As compared with the traditional data mining systems, the platform is highly scalable, with massive data processing capabilities, service-oriented and low hardware costs. The platform can support the design and application of various distributed data mining …
Published in Journal of Operating Systems Development & Trends · Vol. 5, Issue 3, 2018 · pp. 10–14 Read article
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Forest Fire Hazards Vulnerability and Risk Assessment in Bhajji Forest Range of Himachal Pradesh (India): A Geospatial Approach
Abstract: The vulnerability of the Indian forests to fire varies from place to place depending upon the type of vegetation and climate. The coniferous forest in the region is very prone to fire. Objective of the current work is to prepare a model which articulate the forest fire risk and assess the fire vulnerability so that the concerned authorities can minimize the fire danger. Fire hazard mapping was performed using knowledge …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 25–40 Read article
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Computational and Experimental Analysis of Nitride Coated Cutting Tools
Abstract: 800x600 Utilization of harder and tougher cutting tool materials is essential in cutting tool industry.Nitride coated cutting tools are becoming alternative materials for machining various materials due to its high mechanical and tribological properties. Demand for coated cutting tools is increasing because of reduced cutting force, increased hardness and wear resistance.In this research article, the TiAlN and CrN coated cutting tool materials for metal removal are studied and compared with …
Published in Journal of Experimental & Applied Mechanics · Vol. 6, Issue 3, 2015 · pp. 65–72 Read article
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Hybrid Additive-Subtractive Manufacturing of Multi-Material Functionally Graded Components: Integration of Laser Powder Bed Fusion with High-Speed CNC Finishing for Aerospace Applications
Abstract: The synergy involved in the merging of additive and subtractive manufacturing technologies is the game changer to generate multi-material functionally graded components to be used in the aerospace industries. The paper is an in-depth review of a proposed hybrid additive-subtractive manufacturing, which synergistically merges laser powder bed fusion (LPBF) fashioning with rapid computer numerical control finishing production processes. The multi-material deposition, thermal issues, and optimization of post-processing are the challenges …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 398–418 Read article
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Molecular Docking Studies of Nyctanthes arbor-tristis Phytochemicals for Targeting TNF Receptor in Arthritis
Abstract: Rheumatoid Arthritis is an autoimmune disorder which results in inflammation. Tumor necrosis factor-alpha (TNF-α) is responsible for the progression of inflammatory arthritis by promoting immune cell activation and cytokine release. The present study explores the potential of bioactive compounds derived from Nyctanthes arbor-tristis (Parijat) in modulating TNF receptor activity through molecular docking. Computational methods were employed to evaluate the binding affinity of selected phytocompounds from N. arbor-tristis against the extracellular …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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A Review Study on CPU-Optimized Parameter-Efficient Fine-Tuning for Large Language Models to Increase Accuracy Using LoRA
Abstract: The fast proliferation of large language models (LLMs) has increased the need to optimize the process of fine-tuning, but the existing workflows that require a graphics processing unit (GPU) are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of parameter-efficient fine-tuning (PEFT) based on low-rank adaptation (LoRA). The major purpose …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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Graph Neural Networks for Molecular Scale Property Prediction and Inverse Design of Thermoset Polymer Nanocomposites: A Computational Framework
Abstract: Thermoset polymer nanocomposites exhibit properties that are highly sensitive to molecular scale formulation decisions, yet the vast design space remains largely unexplored because of the high cost of experimental characterisation and fully atomistic simulation. This paper presents TNC GNN, a dual mode graph neural network framework developed for the computational design of thermoset nanocomposite formulations. The forward module employs an attention augmented Message Passing Neural Network with 3D geometric encoding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Intelligent Paradigms in Subsea Connectivity: A Comprehensive Review of Artificial Intelligence in Underwater Communications
Abstract: Underwater wireless communication (UWC) plays a critical role in ocean exploration, environmental monitoring, offshore energy operations, disaster management, and naval defense. However, the underwater environment presents significant communication challenges, including severe signal attenuation, multipath propagation, Doppler effects, limited bandwidth, high latency, and energy constraints. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising solutions to address these limitations and enhance the efficiency, reliability, and adaptability …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Harmonic Elimination in Photovoltaic (PV) Systems Using Various Multilevel Inverter Topologies
Abstract: The increasing penetration of photovoltaic (PV) systems into modern power grids necessitates advanced power electronic interfaces capable of delivering high-quality electrical power with minimal harmonic distortion. Multilevel inverters (MLIs) have emerged as an effective solution due to their ability to synthesize near-sinusoidal output voltages with reduced switching losses and electromagnetic interference. This study presents a comprehensive investigation of harmonic elimination in grid-connected PV systems using 5-level, 7-level, and 11-level multilevel …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 01–18 Read article
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Workload Division by Replication for High Availability in Cloud Computing: A Review
Abstract: AbstractThis paper presents a comprehensive study about the problem of increase in the workload on the data nodes in case of node deletion or error occurrence in connection with server. In cloud computing fast and concurrent access to data is required which may increase the probability of overloading of available nodes due to failure of any node. It is considered as a serious problem when there is a continuous increase …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 25–28 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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Traffic Density Estimation Using Image Frames in Python
Abstract: Traffic congestion is a critical challenge in modern urban environments, leading to significant delays, environmental pollution, and increased accident rates. With the rapid growth of vehicle populations in metropolitan areas worldwide, the need for intelligent and automated traffic monitoring systems has become increasingly urgent. Traditional monitoring approaches, such as inductive loop detectors and manual surveillance, are limited in scalability, deployment cost, and adaptability to dynamic traffic scenarios. This paper presents …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 38–45 Read article
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Blind Image Quality Assessment: An Overview
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment.. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach relies on a simple Bayesian inference model to predict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The estimated parameters of the model are …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 3, 2021 · pp. 1–3 Read article
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Raspberry Pi-Based Real-Time Object Recognition for Smart Item Recovery
Abstract: In today’s fast-paced world, individuals often lose valuable time searching for misplaced items such as keys, phones, and remote controls—an estimated 2.5 days per year. This paper introduces a cost-effective, computer vision-based system that helps users efficiently locate everyday objects. The system utilizes a 1080p camera and the YOLO (You Only Look Once) object detection algorithm to enable accurate, real-time object recognition. Designed for practical usability, it stores detected object …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 28–36 Read article
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A Novel Design for High Speed & Area Efficient Compressor Based Vedic Multiplier
Abstract: Multipliers are the most important part in any arithmetic and logic unit, AbstractMultipliers are the most important part in any arithmetic and logic unit, accumulators and digital signal processors. Due to the increasing constraints on delay, the design of faster multipliers is emphasized. Among several multipliers, Vedic multipliers are preferred for their speed of operation. Here the proposed Vedic multiplication techniques are based on “URDHVA TIRYAKBHYAM” a fast and efficient …
Published in Journal of Microelectronics and Solid State Devices · Vol. 5, Issue 3, 2018 · pp. 1–10 Read article
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Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing
Abstract: Fibre orientation and void distribution are critical microstructural features that govern the mechanical performance and reliability of polymer composite materials. Accurate and simultaneous characterisation of these features remains challenging due to their complex spatial interactions and dependence on processing conditions. In this work, an integrated image-processing framework is proposed for the quantitative analysis of fiber orientation and void distribution in polymer composite structures. High-resolution composite microstructure images are processed through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 925–933 Read article
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New Generation Waste Material as Sustainable Ingredient in Concrete: An Experimental Approach
Abstract: E-waste, including devices like phones and computers, poses serious environmental risks. To mitigate these, the construction industry is exploring e-waste as a material to enhance concrete strength and durability. Hence, the present study assesses the performance of M40-grade high-strength concrete by replacing coarse aggregates with 0% to 30% e-waste plastics at various intervals. As the e-waste replacement increased, fresh concrete's workability decreased gradually. The mix containing 30% e-waste experienced the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 141–156 Read article
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Optimization and CFD Analysis of Fin-Enhanced Cooling Systems for Improved PV Efficiency
Abstract: This study is about optimizing and doing a CFD (Computational Fluid Dynamics) analysis of fin-enhanced cooling systems to improve the efficiency of photovoltaic (PV) systems. Photovoltaic (PV) panels are sensitive to temperature changes; the temperature influences the performance and lifespan of these panels. High temperatures cause their electrical output to reduce, thereby limiting their performance. In order to address this problem, several coolants such as air, liquid, phase change materials, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 1, 2025 · pp. 19–29 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article