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288 articles for “High-performance computing”
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
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 depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are …
Published in Recent Trends in Electronics Communication Systems Read article
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Stress based topology optimization of axial tubes under impact to improve energy absorption
Abstract: The present study is aimed at designing a stress constrained topology optimized tube to improve the specific energy absorption (SEA) and reduce the peak crushing force. The research was aimed to develop an axial tube to withstand high impact loads thus improving the crash worthiness of the structure. Crash analysis of a 3D deformable circular tube having different thickness of 0.5 mm, 1 mm, 1.5 mm and 2 mm with …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 210–220 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Energy Efficiency and Awareness in Edge Computing: A Critical Review of Challenges, Strategies, and Future Directions"
Abstract: Edge computing enhances distributed systems by processing data near its source, yet its rapid growth, driven by IoT, 5G, and smart applications, escalates energy consumption across billions of devices. This study critically analyzes energy-saving techniques across hardware, software, and network layers, highlighting the role of AI tools and user education in promoting energy awareness. It explores trade offs between energy efficiency and system performance, identifies scalability challenges in large-scale deployments, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 32–36 Read article
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Analytical Study on DNA-based Modern Cryptographic Techniques
Abstract: Today, as the amount of information being stored and shared continues to grow rapidly, ensuring the security of that information has become more important than ever.To ensure information security, a variety of techniques are employed, including traditional cryptographic methods such as substitution and transposition techniques, hashing functions, and encryption algorithms like DES, RSA, AES, IDEA, and ECC. DNA cryptography is also new emerging technique for providing security to data and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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A Review: Advancements and Applications of Investment Casting Technology in Aerospace Industries
Abstract: A conventional method for producing intricate and superior metal components is investment casting. It utilizes a wax pattern, a refractory shell, and molten metal to create a near-net-shape product. This method has been around for more than 5,000 years and is still relevant in various industries today, especially in aerospace. Investment casting, also known as lost-wax casting, is essential to the aerospace industry's ability to produce complex, high-performance parts. The …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 1, 2025 · pp. 61–66 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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CFD Analysis: Double Pipe Heat Exchanger, Latent Heat Storage, and BIM-CFD Integration
Abstract: This is a review work covering four research papers. Heat exchangers transport thermal energy across fluids; research in SolidWorks 2014 compared flow simulation to the effectiveness-NTU approach. Slow PCM charging/discharging is a global concern in latent heat storage; research on the influence of flow rate and temperature on melting and solidification durations discovered efficiency in a triple tube heat exchanger design. Advances in computational fluid dynamics for forecasting separated flows …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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Evaluation of Lemon Grass (Cymbopogon Citratus) Performance for Petroleum Hydrocarbon Degradation in Soil Environment
Abstract: The evaluation of lemon grass (cymbopogon citratus) performance for petroleum hydrocarbon degradation in soil environment was monitored with respect to contact time or period of exposure. Models were developed in this research to demonstrate the potential of the first-order kinetic, Michaelis Menten and the LineWeaver Burk Plot, and the evaluation of the effect of the biostimulant dosage was monitored in accordance the total petroleum hydrocarbon degradation. The performance of lemon …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 1, 2024 · pp. 33–49 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation Read article
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Nanofluids: Advanced Synthesis Methods, Innovative Applications, and Future Directions
Abstract: Nanofluids, a novel mixture of nanoparticles and base fluids, is an innovative blend that has appeared as a transformative advancement in heat transfer and thermal management technologies. This study is going to discuss advanced synthesis methods, properties, and extensive applications of nanofluids in various fields, such as biomedical engineering, electronics cooling, solar energy, and machining. Optimization techniques such as nanoparticle selection, concentration control, and computational fluid dynamics modelling are also …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Implementation of the Tridiagonal Matrix Algorithm (TDMA) in C: A Practical Approach
Abstract: This paper presents a practical implementation of the tridiagonal matrix algorithm (TDMA), also known as the Thomas algorithm, using the C programming language. The TDMA is a commonly used algorithm for solving systems of linear equations where the coefficient matrix is tridiagonal. The paper draws a detailed step-by-step process of the algorithm’s development, from forward elimination to backward substitution, with a focus on minimizing computational difficulty compared to standard Gaussian …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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Architectural and Technological Progress in Modern Mobile Computing
Abstract: Over the last decade, mobile technologies have experienced rapid and transformative growth, reshaping the way individuals interact with the world and redefining multiple sectors, including healthcare, education, communication, and commerce. Continuous improvements in mobile hardware, such as faster processors, enhanced sensors, and longer-lasting batteries, have significantly improved device performance and usability. At the same time, the widespread development of mobile applications has expanded the functional scope of smartphones, enabling personalized, …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 20–31 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