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504 articles for “high-performance computing”
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VME Interfacing for SLAVE PCB on FPGA by using VIVADO
Abstract: Abstract: In this paper, we have presented a brief review on VME bus interface. Various studies have revealed that the VME bus is a widely used industrial bus, which is applied in military, industrial, aerospace, communication and control applications. It uses the Euro card format, its high performance, and its versatility are some of the reasons that it appeals to a wide range of users. The designer friendly and user-friendly …
Published in Current Trends in Signal Processing · Vol. 9, Issue 1, 2019 · pp. 26–29 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 · pp. 8–17 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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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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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, specialized schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that can learn, forecast, and react to the actual real-world conditions in the system. Artificial intelligence middleware is also an attractive solution to this …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 23–31 Read article
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Computer Aided Circuit Design for Diagnosis of Dust Impact on Solar Panels
Abstract: AbstractSolar panels have come up as a promising methodology for extracting solar energy and yielding electricity. However, there exist many barriers in its path to become an indispensable part of today's era. The decreasing panel efficiency due to several factors such as temperature, irradiance, photoactive material, dust, panel orientation, is an issue of concern. Amongst these, dust is the least acknowledged, yet the most crucial parameter responsible for deteriorating panel …
Published in Journal of Electronic Design Technology · Vol. 9, Issue 3, 2018 · pp. 11–16 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 · Vol. 14, Issue 4, 2023 Read article
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Application of Compressive Sensing for Sampling and Reconstruction of MRI Images
Abstract: In recent years, a new theory of compressive sensing has evolved which asserts that super resolved signals and images can be recovered with far fewer samples than that demanded by the Nyquist sampling theorem. It is required that the signal being sensed has a low information-rate meaning that it is sparse in original or some transform domain. Former approaches capture the complete signal and process it to extract the information. …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 42–48 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 · Vol. 14, Issue 1, 2023 · pp. 9–22 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 an Adaptive Filter Algorithm with Subband Filtering Approach on Acoustic Echo Cancellation
Abstract: This paper focuses on model and its realization on digital signal processors (DSP) for suppressing annoying acoustic echoes in telephone and mobile communication applications. For cost sensitive subscriber devices and high quality voice communications the aims are 1) minimum computational complexity 2) maximum convergence speed and 3) maximum echo attenuation. The chosen method for the echo cancellation involves a sub band decomposition performing the adaptive filtering in subbands at a …
Published in Current Trends in Signal Processing · Vol. 4, Issue 3, 2014 · pp. 28–34 Read article
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Identification of Specificity Determining Positions through Phylogenetic Studies and Molecular Modeling of ICP27 as a Drug Target of Herpes Simplex Virus-1
Abstract: An ever-growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization can be achieved through computational approaches. Herpes simplex is an infection that is caused by a herpes simplex virus (HSV), and is one of the most common human infections transmissible to a body site. Infection with HSV can result in several diseases ranging from apparent infections …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 2, Issue 1, 2015 · pp. 32–43 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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Hardware Design using Flexible Hk-Means
Abstract: High performance hardware is required to meet the necessities of consumer electronics. Color quantization and image partition are an inevitable part for different applications, and HKMeans is the main algorithm that is used for color quantization and image partition owing to its low cost, less computational time and the hardware area required. The computational time and the hardware area increases as the quantization number increases. Hierarchical K-means or HK-Means is …
Published in Journal of Electronic Design Technology · Vol. 6, Issue 1, 2015 · pp. 30–35 Read article