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40 articles for “data-intensive computing”
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Carbon-Aware Autonomous AI Systems: Reinforcement Learning for Sustainable Cloud and Edge Computing
Abstract: The field of communication and information technology is expanding quickly. Because of this, a significant amount of carbon emissions are produced by cloud data centres and edge computing nodes. In fact they are now responsible for 3 to 4 percent of the worlds total greenhouse gas emissions. Most of the time people who manage these resources focus on how they are working and how quickly they can get things done.. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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Photonic-Assisted Spintronic Solid-State Switching Model for High-Speed Memory Devices
Abstract: The rapid advancement of high-speed computing and data-centric applications has intensified the demand for energy-efficient and ultra-fast memory technologies. This paper proposes a Photonic-Assisted Spintronic Solid-State Switching Model for next-generation high-speed memory devices. The proposed framework integrates photonic excitation mechanisms with spintronic switching dynamics to enhance data transfer speed, minimize switching delay, and reduce power dissipation in solid-state memory architectures. By combining optical pulse-assisted spin polarization with magnetic tunnel junction-based …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Ferroelectric Materials for Next-Generation Non-Volatile Memory Applications
Abstract: The continuous scaling of conventional memory technologies is increasingly constrained by limitations in power consumption, speed, endurance, and integration density. As data-intensive applications such as artificial intelligence, Internet of Things, and edge computing demand fast and energy-efficient memory solutions, alternative non-volatile memory technologies have gained significant attention. Ferroelectric materials, characterized by their reversible spontaneous polarization, offer a promising pathway toward next-generation non-volatile memory due to their intrinsic non-volatility, low operating …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 1–9 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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Leveraging Deep Learning and Cloud Computing for Water Usage Optimization in Agriculture: A Study
Abstract: Water scarcity and inefficient irrigation practices are significant challenges in modern agriculture. This research investigates how deep learning and cloud computing can be combined to enhance water efficiency in agricultural practices. Leveraging advancements in deep learning and cloud computing, researchers have developed innovative solutions for optimizing water usage. This review examines the state-of-the-art methodologies, technologies, and applications in smart irrigation systems. It explores how deep learning models and cloud platforms …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 83–91 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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Smart Patient Monitoring and Motion Tracking System
Abstract: The integration of smart technologies in healthcare has revolutionized patient monitoring and diagnostics. This paper presents a Smart Patient Monitoring and Motion Tracking System designed for hospitals, leveraging EEG (Electroencephalogram) signals to track patient movements and monitor neurological health. The proposed system combines motion tracking with real time EEG signal analysis to enhance patient safety, especially for individuals prone to seizures, neurological disorders, or other mobility-related risks. The system employs …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 9–23 Read article
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Algorithmic Ecology: A Framework for Achieving Carbon-Neutrality in Global Data Infrastructure
Abstract: The exponential growth of digital infrastructure has positioned data centers as critical enablers of the global digital economy, yet their environmental impact has become a paramount concern. Data centers consumed approximately 205 TWh globally in 2018, representing about 1% of global power usage with a steady 6% growth trend. This review synthesizes current literature on green algorithms and sustainable data center technologies, examining the intersection of artificial intelligence, machine learning …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 33–48 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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Energy-Aware Task Offloading in 6G-Enabled Mobile Edge Computing Environments
Abstract: The emergence of sixth-generation (6G) wireless communication networks is expected to revolutionize future mobile systems by enabling ultra-low latency communication, extremely high data rates, massive connectivity, and intelligent network management. In parallel, mobile edge computing (MEC) has gained significant attention as a promising paradigm that brings computational resources closer to end users, thereby alleviating network congestion and reducing end-to-end service delays. Despite these advantages, the rapid growth of computation-intensive and …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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A Python-Based Investigation of Clinical Data and Ultrasound Images for PCOS Diagnosis
Abstract: PCOS is a common endocrine disorder that impacts women in their reproductive years characterized by irregular menstrual cycles, hyperandrogenism, and polycystic ovaries. The full diagnostic plan is mainly a combination of a pelvic ultrasound besides blood tests of specific parameters that indicate the presence of PCOS. Since PCOS is a hard-to-diagnose widespread hormonal disorder, blood tests, symptoms, and other parameters with the help of a computer can form a new …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Enhancement of Horizontal Jet Impingement Heat Transfer Analysis on Vertical Flat Plate
Abstract: This research investigates the heat transfer characteristics and heat flux distribution associated with parallel jet impingement on a vertical flat plate. A comprehensive computational fluid dynamics (CFD) analysis is carried out and systematically validated against available experimental data to ensure the accuracy and reliability of the numerical model. The jet length is maintained constant at 12 mm, while the jet-to-plate separation distance is varied at 6, 12, 18, and 24 …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 65–80 Read article