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116 articles for “workload.”
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Analysis of impact of Meditation on Cognitive Workload using EEG Signals
Abstract: AbstractMental activities can be indicated by the Cognitive workload which are useful in applications like Biomedical, Human Machine Interaction and Task analysis. The mental effort applied on the Working memory at a certain given time is commonly known as Cognitive load. The EEG Signals of Cognitive Workload can be studied and classified. The features such as Entropy, Energy, Power, etc. can be extracted from the EEG signals and processed using …
Published in Current Trends in Signal Processing · Vol. 10, Issue 1, 2020 · pp. 29–39 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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Memory Reclamation Behavior Under cgroups v2 Versus Legacy cgroups: A Measurement Framework for Containerized Workloads
Abstract: Linux control groups (cgroups) are the kernel mechanism that lets container runtimes such as Docker, containerd, and CRI-O enforce per-container CPU, memory, and I/O limits, and the transition from the legacy cgroups v1 hierarchy to the unified cgroups v2 hierarchy changed several aspects of how the memory controller signals and responds to reclaim pressure most notably through the introduction of memory.low/memory.high soft-limit semantics and system-wide Pressure Stall Information (PSI). Kernel …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 27–34 Read article
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Air Computing: A Parallel Computing Module for Offloading Computational Workload on Neighboring Android Devices
Abstract: Developing complex applications which requires the increasing computational requirements is sophisticated and remains a daunting task. For application developers, countering the real-time computing in mobile devices has always remained a demanding job to ask for more computational power and energy usage than that offered by devices of present generation. In this paper, the author presents an out of the box air computing technology which aids the developers to run real-time …
Published in Recent Trends in Parallel Computing · Vol. 1, Issue 3, 2014 · pp. 10–13 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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Artificial Intelligence-Based Workforce Analytics Framework for Predicting Employee Engagement and Continuous Performance Improvement: Evidence from Tata Steel
Abstract: In large, diversified manufacturing organizations, managing employee engagement and sustaining performance require systematic understanding of workload distribution, employee sentiment, and workplace experience. This study examines the role of AI-enabled workforce analytics as a strategic human resource management tool through a case study of Tata Steel. The research positions artificial intelligence not as a technical innovation, but as a people-analytics decision-support mechanism that assists HR leaders in identifying early indicators of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Common Health Related Problems in Female Constables in Mumbai, India
Abstract: Job of a female constable is very demanding physically as well as mentally as it ranges from desk job to daily proactive patrol activities and specific criminal activities. Apart from the hectic job, being a woman, mother, wife, daughter, they have additional responsibility towards their homes. Most of the times they neglect their pain, tiredness, sufferings because they have no time left for themselves. And in-spite of these conditions, they …
Published in Research and Reviews: A Journal of Medicine · Vol. 1, Issue 1, 2011 Read article
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Dynamic Priority-based Adaptive Scheduling (DPAS) for Modern Operating Systems
Abstract: Dynamic Priority-based Adaptive Scheduling (DPAS) is an innovative CPU scheduling algorithm designed to optimize system performance and resource utilization in modern computing environments. As computing systems become increasingly complex and diverse, traditional static scheduling algorithms often struggle to adapt efficiently to the dynamic nature of workloads. DPAS addresses this challenge by introducing a dynamic and adaptive approach to process prioritization and resource allocation. DPAS leverages real-time feedback, machine learning, and …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 2, 2023 · pp. 6–15 Read article
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A Comprehensive Methodology for Data Security and Privacy in Cloud Computing Systems
Abstract: Cloud computing encompasses computing with a pool of virtualized computer resources. A cloud provides for self-recovering highly-scalable programming models, workloads to recover from hardware/software failures and rebalance allocations, can host different workloads and allows workloads to be deployed/scaled-out on-demand by rapid provisioning of virtual or physical machines. The idea is to move desktop computing to a service-oriented platform using server clusters and huge databases at data centers. Cloud computing has …
Published in Journal Of Network security · Vol. 2, Issue 2, 2014 · pp. 5–9 Read article
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Job Satisfaction Evaluation Based on Pay (as per the 7th Pay)
Abstract: The present study highlights the job satisfaction evaluation based on pay (as per the 7th pay). The given pay is as per the 7th pay commission of India. The intensely satisfied and satisfied respondents have been added to know the analysis’s satisfaction level based on pay. The respondents’ satisfaction level has been found after that. The study explores all of the most considered and more appropriate government postgraduate and graduate …
Published in Journal of Advancements in Library Sciences · Vol. 7, Issue 3, 2020 · pp. 39–43 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Challenges in Parallel Computing for Big Data Analytics
Abstract: The integration of parallel computing into the realm of big data analytics promises accelerated processing speeds and enhanced scalability, but it is not without its formidable challenges. This study explores the multifaceted hurdles faced in the pursuit of efficient parallel processing for large-scale data analytics. The intricate task of distributing and partitioning massive datasets across multiple processing units demands adept strategies to ensure equitable workloads. Load balancing emerges as a …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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Fingerprint-Based Attendance Monitoring System Using Arduino
Abstract: This system uses Arduino to enable an attendance monitoring system through the use of fingerprints. The system guarantees effective, safe and automated recording of attendance with biometric scanning. It lessens mistakes because of automatic marking, keeps absentee proxies out and reports the final results instantly. When a fingerprint scan is successful, the system automatically records attendance by comparing it with biometric data that has been recorded. Effective monitoring and reporting …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 9–16 Read article
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Work–Life Balance Among Professional Nurses – A Mixed Methods Study
Abstract: Background & Objectives: Work–life balance (WLB) is an essential component of nurses’ psychological well-being and professional effectiveness. Nurses in India frequently experience heavy workloads, shift duties, and emotional strain that disrupt personal–professional harmony. This study aimed to assess the level of WLB among professional nurses, determine its association with coping practices, and explore their lived experiences in managing work and personal responsibilities across healthcare settings. Methods: A mixed-methods descriptive design …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 · pp. 21–30 Read article
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An Overview of Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial-intelligence techniques with core operating system services is ushering in a new class of platforms—intelligent operating systems (iOS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self-healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS primitives with three …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 21–28 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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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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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 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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Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems
Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article