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141 articles for “log analysis”
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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An Investigative Study on Secure Coding Practices with Shell Scripting
Abstract: This investigative research delves into secure coding practices within shell scripting, aiming to reduce prevalent security vulnerabilities and improve the overall security stance of shell scripts. It emphasizes three key areas: static analysis, dynamic analysis, and manual code review. Through static analysis, the code structure, usage of unsafe functions, and potential vulnerabilities are examined without executing the script. Dynamic analysis entails running the script in controlled settings to detect runtime …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 1, 2024 · pp. 16–23 Read article
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Dynamic Vibration and Damping Analysis of Sustainable Nano-Reinforced Polymer Composite Elements for Vehicle Suspension Applications
Abstract: This paper presents an analytical investigation into the dynamic vibration characteristics of nano-reinforced polymer composite elements intended for vehicle suspension applications. A single-degree-of-freedom (SDOF) quarter-car model is employed to derive fundamental expressions for natural frequency, damping ratio, logarithmic decrement, and displacement transmissibility. The primary contribution lies in establishing explicit analytical linkages between material-level viscoelastic properties specifically storage modulus and loss modulus and system-level suspension parameters including stiffness and damping coefficients. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 561–570 Read article
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What Is the Meaning and Purpose of Risk Management in Cyber Security?
Abstract: Organizations and their information systems are increasingly exposed to risk and uncertainty from a variety of sources, including computer fraud, espionage, and sabotage or cyber-attacks. The purpose of this article is to outline several steps, protocols, and factors that any organization should consider in the event of a cyber-attack. Over time, some damage causes, including denial of service or intrusion attacks, have grown more frequent, aggressive, and complex. Complete security …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 46–53 Read article
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Smart Supply Chain Inventory Management Using Blockchain Technology
Abstract: This study examines the significant potential of blockchain technology in enhancing smart supply chain inventory management. It tackles ongoing issues like inconsistent inventory records, data update delays, and high operational costs due to manual processes and the involvement of intermediaries. Blockchain uses a decentralized and immutable ledger to provide all participants in the supply chain with real-time access to accurate data, promoting transparency and reducing discrepancies. The research emphasizes the …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 1, 2025 · pp. 1–6 Read article
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Integration of Wind and Solar Energy with Fuzzy Logic Control MPPT for Grid-Connected Hybrid Renewable Power Generation
Abstract: The utilization of renewable energy sources, such as wind and solar energy, has gained significant attention due to their eco-friendly nature and sustainability. This research paper explores the mechanisms behind wind generation and its integration with solar power, focusing on the adoption of Fuzzy Logic Control (FLC) for Maximum Power Point Tracking (MPPT) in a grid-connected hybrid renewable energy system. The paper outlines the principles of wind and solar energy …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 1–19 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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A Majority Function Based Full Subtractor
Abstract: In the present landscape of very large-scale integration (VLSI) technology, the imperative to implement Boolean functions with minimal gate count remains a cornerstone of efficient circuit design. This pursuit has only grown more critical with the evolution of low-power design strategies, which now offer significantly enhanced benefits compared to traditional approaches. The trifecta of performance, affordability, and dependability continue to drive innovation in this field, shaping the trajectory of technological …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 2, 2024 · pp. 8–14 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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Comparative Analysis of CMOS CNFET and Memristor Based Full Adder Circuits and CMOS Memristor Based Multiplexer Circuits
Abstract: Continued developments in microelectronics technology have led to a myriad of new compute- intensive applications at the micro-edge, such as artificial intelligence and signal and image processing. Multiplication is a crucial arithmetic process in such applications. However, large logic complexities typically seen in traditional multipliers generate combinatorial blocks with long chains of cascaded carry addition. As such, energy efficiency has remained a primary design challenge for these applications, when powered …
Published in Journal of VLSI Design Tools and Technology Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions. Methods: A total of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Harnessing Hydrolgeological Parametrs: Prediction of Water Probability and Levels for Water Well Construction Using Ai-Enabled Models
Abstract: The AI-Based Decision Support System for Water Well Construction utilizes data from the National Aquifer Mapping and Management System (NAQUIM) and employs advanced AI techniques like regression analysis, decision trees, and neural networks. This system predicts crucial parameters for water well construction, including location suitability, water-bearing zone depths, and groundwater quality. By integrating large datasets such as lithology, geophysical logs, and aquifer maps provided by the Central Ground Water Board …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 16–28 Read article
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Supply Chain Optimization Using Big Data
Abstract: In the references to add productivity and short the appendences, and increase customer value, supply chain optimization is a very crucial part of contemporary business operations. Supply chain management has been transformed by the emergence of big data, which can provide analysis and insight from many different sources of information. This content explores the importance of using big data analytics to improve the delivery process. Thanks to the evolution of …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 19–25 Read article
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Botanical Blockade: Phytochemical Targeting Of Nf-Κb in Cancer Therapy
Abstract: The control of inflammation, corpuscle survival, proliferation, and allowed response are all influenced by the acute archetypal agent NF-κB. Its abnormal activity is typically seen in a range of malignancies, where it aids in bump advancement, metastasis, and treatment waste. The function of NF-κB in scar analysis is discussed in this product, along with significant phytochemicals that seem to be interested in targeting this pathway, based on recent investigation. It …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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QSAR Modeling of a Novel Series of Methoxylated Chalcones as Antioxidant Agents Against Gram-Positive Bacteria Staphylococcus aureus
Abstract: Background: Chalcones are aromatic ketones belonging to the flavonoid family. They are plant-based compounds and are widely found in nature. For centuries, these bioactive molecules have been utilized in various traditional medicines for the treatment of several ailments. Chalcones have antibacterial, antiviral, antimalarial, antifungal, antioxidant, and antileishmanial properties. They are also used to treat inflammation and cancer. Chalcones act as angiogenesis inhibitors, an important factor in cancer progression and metastasis. …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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A Study on Unmanned Air Vehicles (UAV)
Abstract: Unmanned Air Vehicles (UAVs), commonly known as drones, represent one of the most transformative technologies of the 21st century, rapidly evolving from their initial military applications into a diverse array of civilian and commercial uses. This study explores the rapid proliferation of UAV technology, highlighting its profound impact across sectors such as logistics, agriculture, infrastructure inspection, communication, and public safety. We discuss the inherent advantages UAVs offer, including enhanced efficiency, …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 24–36 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article