Search
473 articles for “computing performance”
-
Website Usability Using AI
Abstract: This article introduces a comprehensive framework that leverages artificial intelligence (AI), automated tools, and APIs to enhance the evaluation of website usability. The proposed framework integrates AI-driven models with traditional usability assessment techniques to create a more dynamic and effective evaluation process. Specifically, it utilizes Google Lighthouse to conduct in-depth audits on website performance, search engine optimization (SEO), and accessibility. Additionally, chatbot APIs are incorporated to gather real-time user feedback, …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 19–27 Read article
-
A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
-
A Study on Precision Blood Propulsion in Motor-Driven Artificial Hearts
Abstract: The development of biocompatible, energy-efficient pumping mechanisms is pivotal for advancing artificial heart (AH) technology. This study explores a motor-driven centrifugal pump designed to replicate the physiological dynamics of natural ventricles while mitigating complications associated with conventional axial and pulsatile systems. The proposed system employs a brushless DC motor with closed-loop control, integrated with pressure and flow sensors to modulate rotational speed (RPM) and generate biomimetic cardiac output. The suggested …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 53–59 Read article
-
Recognition and Detection of Content in Video Using OpenCV
Abstract: The emergence and continued reliance on the Internet and related technologies has resulted in massive amounts of data that can be analysed. Humans, on the other hand, do not have the cognitive abilities to comprehend such vast amounts of data. Machine learning (ML) is a mechanism that enables humans to process large amounts of data, gain insights into the data's behaviour, and make more informed decisions based on the analysis's …
Published in International Journal of Image Processing and Pattern Recognition Read article
-
Parallel and Concurrent Computing with Shell Commands: Exploring CPU Architecture, LAN Interconnection and Command Languages for Green Sustainability
Abstract: Parallel and concurrent computing are essential ways of thinking in the digital age, where the cost indexes are efficiency, speed and sustainability. By far performance relevance of each metaphor Contemporary computational environments covering everything from dumb terminals to distributed workstations and intelligent network systems such as the command-line interface (CLI) can never do well on its performance when throughput is needed most the era's fact that there is no hitting …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
-
Cutting-Edge Developments and Innovations in Amazon Web Services (AWS)
Abstract: In 2025, Amazon Web Services (AWS) continues to dominate the cloud computing industry through groundbreaking innovations in artificial intelligence (AI), strategic partnerships, data center advancements, and expansion into new markets. These initiatives help AWS maintain its position as a top provider of secure, scalable, and efficient cloud services, adapting to the ever-changing demands of businesses across the globe. One of AWS’s most significant advancements is its AI-driven cloud services, which …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
-
Bringing Serverless Edge Computing to School Administration: Challenges and Opportunities
Abstract: Serverless edge computing is revolutionizing app development by creativity in infrastructure management. However, traditional cloud-based serverless architectures can suffer from latency and reliability issues when serving users at the edge of the network. While edge computing brings storage and computing closer to data sources, upgrading performance and reducing network issues. This paper explores the convergence of serverless edge computing, examining the opportunities and challenges that arise from this integration. Delving …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
-
Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
-
Enhancing Control with Embedded Ssvep-Bci
Abstract: Brain–Computer Interface (BCI) technology establishes a direct communication link between the human brain and external devices without relying on muscular activity. Among various BCI paradigms, the Steady-State Visually Evoked Potential (SSVEP)-based approach has gained significant attention due to its high signal-to-noise ratio, minimal user training, and suitability for real-time applications. However, implementing such systems on embedded hardware presents challenges such as limited computational resources, signal noise, and latency in processing. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 41–52 Read article
-
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
-
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
-
A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
-
Computational Modeling of Polymer Semiconductors for Electronic Applications
Abstract: Polymer semiconductors have become important materials in modern electronic applications because they combine semiconducting behavior with mechanical flexibility, low-cost processing, and tunable molecular structure. Their growing use in organic field-effect transistors, organic photovoltaics, organic light-emitting diodes, and flexible sensing devices has increased the need for accurate computational approaches that can predict material properties and device performance before experimental fabrication. This paper reviews the major computational modeling techniques used for polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 132–146 Read article
-
Face Recognition Attendance System Using Local Binary Pattern Histogram Algorithm
Abstract: Maintaining accurate and tamper-proof attendance records in educational and corporate environments has long been a challenge due to the limitations of manual and biometric systems. This study introduces the development and deployment of a contactless, automated attendance system that utilizes facial recognition through the local binary pattern histogram (LBPH) algorithm. The primary goal is to offer a secure and efficient substitute for conventional attendance methods by harnessing the power of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 29–34 Read article
-
The Interface of Hardware and Intelligence: The Function of Operating Systems
Abstract: Operating systems play a central role in bridging the gap between computer hardware and user interaction. They simplify complex machine-level operations and transform them into user-friendly and efficient digital experiences. At their core, operating systems are responsible for managing essential tasks such as process scheduling, memory allocation, file system organization, and device coordination. By handling these functions effectively, they ensure that hardware resources are used in an optimal and balanced …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
-
Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
-
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
-
A Computational Study of Lift and Drag Characteristics for NACA 4415 and NACA 2412 Aerofoils
Abstract: The performance of an aerofoil is crucial in designing wind turbine blades, aircraft wings, and other aerodynamic surfaces. This project presents a comparative analysis of two widely used aerofoil profiles, NACA 4415 and NACA 2412, to study their lift and drag characteristics under different flow regimes. The aerofoil geometries were developed using the NACA four-digit notation and modeled in ANSYS Design Modeler. Numerical simulations were conducted in ANSYS Fluent for …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1298–1315 Read article
-
Delay Analysis of HS-14T 45nm CMOS SRAM with Different SRAM Techniques for Improvement in Speed
Abstract: This paper presents a novel HS-14T design aimed at significantly improving read and write delays compared to conventional 6T and other memory cells RHRD-12T, SEUH-12T, and NHRC-14T. As technology scales, the demand for faster and more stable memory cells becomes increasingly critical. Our proposed HS-14T incorporates additional transistors to enhance stability and reduce access times, resulting in notable performance gains. Comprehensive simulations reveal that the HS-14T SRAM cell substantially reduces …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 1–13 Read article