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70 articles for “overhead”
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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A Meta-Analysis of the Role of Serverless Computing Models in Modern e-Healthcare Systems
Abstract: The integration of serverless computing models in e-healthcare systems represents a paradigm shift in healthcare technology infrastructure. This meta-analysis examines the role, benefits, and challenges of serverless architectures in modern healthcare applications, focusing on studies published between 2019 and 2025. Serverless computing offers unprecedented scalability, cost-efficiency, and operational flexibility, making it particularly suited for healthcare applications handling variable workloads such as medical imaging processing, real-time patient monitoring, and electronic health …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 49–58 Read article
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 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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Enhancing Trust in Education Through Blockchain- Based Credential Authentication
Abstract: Academic credentials such as degree certificates, transcripts, and course completion records are fundamental for validating an individual’s educational achievements. However, conventional credential management systems largely rely on centralized databases and physical documentation, making them vulnerable to forgery, unauthorized modification, data loss, and inefficient verification processes. These limitations reduce trust among educational institutions, employers, and learners, while also increasing administrative overhead. This study proposes a blockchain-based credential authentication framework designed to …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 1–7 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article
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Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications
Abstract: Efficient resource sharing is a cornerstone of high-performance parallel computing. While proportional-share scheduling has long been a foundational approach for distributing resources according to predefined weights, its effectiveness can be compromised by tasks that over-consume their allocated share, leading to system-wide performance degradation and unfairness. This review article investigates the application of the “Proportional-Share with Punishment” (PSWP) principle, a hybrid scheduling paradigm designed to address this challenge. PSWP integrates the …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Power and Area - Aware Recursive Multiplier Architecture Utilizing Polymer Composites for Neural Network Acceleration
Abstract: Approximate computing is widely applied in error - tolerant systems as an effective technique to enhance circuit performance by deliberately allowing occasional inaccuracies instead of strictly ensuring precise results for every computation. Among the fundamental building blocks of digital systems, multipliers play a crucial role in signal processing, control systems, and machine learning applications; however, they demand significant power, silicon area, and timing resources. Leveraging error - tolerant approximate multipliers …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1320–1337 Read article
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An Efficient Vision-Based Algorithm for Hand Pose Estimation and Cursor Control
Abstract: Conventional input devices like the keyboard and mouse are no longer necessary because gestures are becoming more popular as the most natural way to interact with computers. This project has demonstrated a novel real-time system that lets users control their computer cursors using simple hand gestures. The system facilitates an easy operation for us in terms of the use of a cursor by using techniques and hand mark detections. The …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 24–35 Read article
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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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Performance Analysis of AES Encryption Using LFSR-Based Key Expansion in VLSI
Abstract: Secure data transmission has become increasingly important with the rapid growth of digital communication and embedded systems. Protecting sensitive information from unauthorized access requires reliable cryptographic solutions. Among the available techniques, the Advanced Encryption Standard (AES) is widely recognized for its strong security and efficient implementation in both hardware and software environments. In this work, the design and performance evaluation of an AES-based crypto processor with LFSR-driven key expansion is …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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A Comprehensive Study of Risk-Adaptive Access Control in Advanced Database Management Systems
Abstract: The current control methods for accession of a crucial resource often struggle to provide adequate security in dynamic and complex advanced database management systems (DBMS). These static models lack the flexibility to adapt to evolving threats and contextual changes, leaving potential vulnerabilities. Risk-Adaptive Access Control (RadAC) emerges as a sophisticated solution, integrating real-time risk assessment into authorization decisions to dynamically adjust access permissions. This review article provides a comprehensive study …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Cyber-Secure IoT Framework for Monitoring Fiber-Reinforced Polymer Composites Using Embedded Sensors
Abstract: The present research paper suggests a cyber-safe Internet of Things system in real-time monitoring of fiber-reinforced polymer composites with inbuilt sensors. It is aimed at enhancing structural health maintenance, using sensual, intelligent analysis, and data protection in the same platform. Multi-layer architecture An embedded sensor, signal processing, anomaly detection and lightweight layer of cyber-security are developed. Experimental validation is done under controlled conditions and the performance is measured by these …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 434–458 Read article
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article