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473 articles for “computing performance”
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Stilbenes: A Molecular Docking and ADMET Analysis Approach on an Emerging Resource for Scavenging Reactive Oxygen Species in the Field of Colon Malignancy
Abstract: Objective: Colon malignancy, also referred to as colon cancer, originates as precancerous polyps in the colon or rectum, which have the potential to thrive and progress into cancerous tumors over time. This study delves into various bioactive compounds (from natural sources like plants) to assess their potential efficacy in inhibiting colon malignancy as compared to conventional methods. Methods: The objective of this study was to employ computational methodologies to evaluate …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 3, 2024 · pp. 29–38 Read article
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Exploring Oroxylum indicum Phytochemicals as VEGFR-2 Inhibitors: A Molecular Docking Approach for Cancer Management
Abstract: Cancer is still a major health problem around the world and is one of the top causes of death. A protein called VEGFR-2 (vascular endothelial growth factor receptor 2) is important because it helps blood vessels grow by supporting the survival, movement, and growth of certain cells. This process is essential for tumors to grow and spread to other parts of the body. This study focused on evaluating the binding …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 48–62 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Crystal Defects and Their Characterization in Modern Materials Science
Abstract: The physical and chemical properties of crystalline solids are fundamentally dictated by deviations from structural perfection, known as crystal defects. From the point-scale vacancies that drive diffusion to the planar boundaries that determine mechanical strength, defects serve as the primary "tuning knobs" in material design. This review provides a comprehensive examination of point, line, and planar defects, exploring their formation energetics and their role in plastic deformation via crystallographic slip. …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 15–19 Read article
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Hand-Tracking-Based Mouse Control for Touchless Human-Computer Interaction: Feasibility and Future Enhancement
Abstract: This paper presents a novel approach to human-computer interaction through a hand-tracking-based mouse control system using computer vision. The system utilizes OpenCV, MediaPipe, and the Cvzone Hand Tracking Module to identify and monitor hand movements in real-time. By utilizing hand landmarks, the system maps finger positions to cursor movement and enables essential functions such as clicking, scrolling, and double-clicking. The primary motivation for developing this system is to create a …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 18–25 Read article
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Cyber Security Evaluation for a Petroleum Refinery Using Attack Tree Methodology and Economic Indexes
Abstract: Information Technology (IT) is vital and valuable to our society. An important type of IT system is Supervisory Control and Data Acquisition (SCADA) systems. The most common misconception regarding the security of SCADA was that this network was electronically isolated from other networks and hence attackers could not access them. Over the years SCADA systems have become incorporated with other IT systems, which has made them becoming increasingly vulnerable to …
Published in Emerging Trends in Chemical Engineering Read article
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A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Targeting Homogentisate Dioxygenase Dysfunction in Alkaptonuria: Investigating Curcuma longa’s Therapeutic Potential
Abstract: Objectives: Alkaptonuria is known to have a faulty gene HGO in the metabolic process. In the present research work, the focus is towards investigating the therapeutic capabilities of the Curcuma longa upon the faulty Homogentisate dioxygenase gene using ligand-protein binding, which would assist in the corrective tyrosine metabolism. Methods: This study is based on the computational approach using different phytochemicals for evaluation of the potency against the abnormal Homogentisate dioxygenase …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 2, 2024 · pp. 1–11 Read article
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Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles
Abstract: Digital twin technology in battery management systems (BMS) for electric cars (EVs) represents a major development in the automotive industry. Digital twins provide predictive maintenance, modelling, and real-time monitoring by creating virtual copies of real-time monitoring, actual battery systems. This paper describes the functional components, architecture, and design of Digital Twin technology along with how it may be included into BMS. Emphasizing how consistent data flow from sensors improves battery …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 Read article
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In silico Molecular Docking Analysis of Stephania glabra phytocompounds Targeting Thymidylate Kinase for potential Antituberculosis Activity
Abstract: Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It mainly affects the lungs and spreads through the air when a person with active TB in their lungs coughs, sneezes, or spits. This study investigates several bioactive compounds derived from plants to forecast how effective plant-based ligands will be at preventing tuberculosis. The purpose of the study was to use computational techniques to assess the effectiveness of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 2, 2025 Read article
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Future-Ready Communication Systems: Exploring High-Speed, Adaptive, and Secure Network Solutions
Abstract: The domain of electronics communication systems has experienced rapid transformation due to the growing demand for high-speed, reliable, and intelligent communication networks. This paper presents a comprehensive analysis of emerging trends such as Fifth Generation (5G) communication systems, Internet of Things (IoT), Artificial Intelligence (AI)-enabled networks, Software-Defined Networking (SDN), optical communication advancements, and cybersecurity mechanisms. The combination of cloud computing, edge computing, and network virtualization which improve system flexibility, allow …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Encoding-Decoding Algorithm Using the Catalan Transform of Weighted Tribonacci Sequence
Abstract: In order to improve information security, this paper presents a unique algorithm for encoding and decoding messages utilizing the Catalan Transform of a Weighted Tribonacci Sequence. Utilizing the Catalan and Tribonacci sequences, the methodology combines the concepts of number theory and combinatorics to create an effective encryption and decryption process. First, an array is created by mapping each character in the plaintext message to its corresponding ASCII value. The ASCII-weighted …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 12–16 Read article
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In Silico Exploration of Podophyllum Hexandrum-Derived Phytocompounds as Potential Therapeutics Against Small Cell Lung Cancer (SCLC): A Molecular Docking Approach
Abstract: Small Cell Lung Cancer (SCLC) is a fast-growing and aggressive type of lung cancer that spreads quickly strongly associated with smoking. It is characterized by symptoms, such as persistent cough, breathing difficulties, or hoarseness, though it can sometimes be asymptomatic which makes early detection challenging. The tumor suppressor gene TP53 is critical in regulating the cell cycle and preventing uncontrolled cell division. Mutations in TP53 result in the loss of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 1–11 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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Supply Chain Design Considering Social and Environmental Risks
Abstract: The aim of the research is to design a supply chain taking into account social and environmental risks. In this research, an attempt was made to present a model that, by considering variables close to the real world, simultaneously considers cost and sustainability issues for designing a meat supply chain network, including locating facilities, using technology in them, how products flow in the network, etc. In order to examine the …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 35–43 Read article
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Gene prioritization of colorectal cancer using computational approach
Abstract: Colorectal cancer (CRC) continues to be a major worldwide health issue, underscoring the need to pinpoint crucial genetic elements influencing its initiation and advancement. In this investigation, we utilize sophisticated computational methods to prioritize potential genes linked to CRC development. Through the utilization of various bioinformatics tools and comprehensive methodologies, we systematically examine extensive microarray datasets to identify potential genetic contributors. Initially, a vast amount of CRC microarray data (approximately …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 39–52 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article