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288 articles for “high performance computing”
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Investigation of the Solvent Extraction Using Alcohol and Water on Bryophylum pinnatum Leaves for Total Petroleum Hydrocarbon Degradation on Loamy Soil
Abstract: Investigation of the solvent extraction using alcohol and water on Bryophylum pinnatum leaves for total petroleum hydrocarbon degradation on loamy soil was monitored for the purpose of evaluating the Micheal’s Menten functional parameters as well as the coefficients. The maximum specific rate of the total petroleum hydrocarbon (TPH), which was expressed as Vmax and the rate of the dissociation of the TPH, which is denoted as Km was computed in …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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An Examination of Energy-Saving Techniques for UAV Communication
Abstract: Unmanned aerial vehicles (UAVs), or drones, have become essential in various industries due to their low deployment costs and exceptional versatility. As a result, they are widely used in industries like mining, agriculture, logistics, and search and rescue. The effectiveness of UAV applications is largely dependent on robust communication technology, which is crucial for control, data transmission, and coordination. However, the limited capacity of the low-power batteries used in UAVs …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 1–7 Read article
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Research Paper A Review of Symmetry in Mechanical Systems: Theoretical Systems Foundations and Engineering Applications
Abstract: In mechanical system analysis and design, symmetry is of mechanical systems. This article examines the idea of symmetry in mechanical systems, exploring its mathematical foundations (such as Lie algebras and group theory) and how these ideas help explain the behavior, stability, and control of the system. We explore the applications of symmetry in a range of mechanical systems, from basic mechanical connections to intricate multi-body dynamics, emphasizing the benefits of …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 15–19 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Design and Manufacturing of Suspension and Steering System of a F3 Vehicle
Abstract: The suspension and steering systems are critical subsystems of any formula-style racing vehicle, directly influencing its stability, handling, and driver safety. This paper focuses on the design, analysis, and manufacturing of suspension and steering systems for a Formula Student F3 vehicle. The primary objective is to develop a lightweight, reliable, and efficient design that complies with Formula Student competition rulebooks while ensuring optimum ride quality and performance. Using advanced computer-aided …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 1–12 Read article
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Flame-Retardant Polymeric Materials: Recent Advances and Future Directions
Abstract: This review explores essential flame-retardant polymers that play a vital role in various industries such as electrical & electronics, automobile, manufacturing, and firefighting. This review also highlights the latest progress in the design and synthesis of flame-retardant polymers, highlighting novel approaches such as the incorporation of nanomaterials, bio-based flame retardants, and the use of intumescent systems. Recent advancements include high-throughput screening, computational design, bio-based and sustainable flame retardants, self-healing materials, …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 125–132 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Java’s Enduring Popularity: Unraveling the Factors Behind Its Preference
Abstract: Java remains one of the most widely used programming languages across various industries, owing to its robust architecture, platform independence, and extensive ecosystem. Its versatility, scalability, and security make it a preferred choice for developing a wide range of applications, from enterprise software to mobile and web solutions. This study delves into the key factors contributing to Java’s sustained relevance in software development, highlighting its adaptability to evolving technological trends. …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 8–15 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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The Interface of Hardware and Intelligence: The Function of Operating Systems
Abstract: Operating systems play a central role in bridging the gap between computer hardware and user interaction. They simplify complex machine-level operations and transform them into user-friendly and efficient digital experiences. At their core, operating systems are responsible for managing essential tasks such as process scheduling, memory allocation, file system organization, and device coordination. By handling these functions effectively, they ensure that hardware resources are used in an optimal and balanced …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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QCA-based Implementation of Budget-friendly and Energy-Efficient Exclusive-OR/Exclusive-NOR Gates
Abstract: Quantum-dot cellular automata (QCA) is a novel nanoscale computational approach that proposes reduced dimensions, lower power consumption, increased speed, and deliberate design as a solution to the scaling challenge associated with CMOS technique. QCA is a nascent nanotechnology that utilizes the Coulomb repulsion principle. Quantum computing has emerged as a highly effective paradigm for the creation of energy-efficient hardware at the nanoscale. This article presents implementation of a very efficient …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 2, 2023 · pp. 1–6 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Assessment of Matrix Cracking and Fiber Breakage in Hybrid Composite Materials.
Abstract: Hybrid composite materials, combining two or more distinct fiber or matrix constituents, have emerged as advanced structural solutions for aerospace, automotive, marine, and civil engineering applications. However, their complex microstructure makes them susceptible to multiple interacting damage mechanisms, particularly matrix cracking and fiber breakage. This study provides a comprehensive assessment of these damage modes, emphasizing their initiation, evolution, and combined effects on the mechanical integrity of hybrid composites. Matrix cracking …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Enhanced Heat Transfer in Double Pipe Heat Exchanger with Circular Fins Using Copper Nanofluid and Twisted Tape Inserts: A Computational Study
Abstract: The enhancement of convective heat transfer in a double-pipe heat exchanger utilizing circular finned twisted tape inserts and helical screw-tapes with centre rods, in conjunction with copper oxide nanofluid as the heat transfer medium was studied in this project. Computational Fluid Dynamics (CFD) simulations were conducted across Reynolds numbers ranging from 500 to 5000 to analyse heat transfer characteristics. The investigation focuses on Nusselt number improvement and friction factor analysis …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 11–22 Read article