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253 articles for “Reliability Measurement.”
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Investigation of Undesirable Event by Fault Tree Analysis - Study of domestic LPG Gas Leak
Abstract: Fault tree analysis (FTA) is a dependable and commonly used method for analyzing and identifying the combinations of failures, faults, or events that could result in a specified top event, which is typically a system failure or malfunction. FTA is widely used in risk assessment, reliability engineering, and system safety analysis, and it has proven to be an effective tool for determining the likelihood and consequences of potential system failures. …
Published in Journal of Industrial Safety Engineering · Vol. 10, Issue 1, 2023 · pp. 13–18 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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IOT Based Bidirectional Energy Metering with Auto-Bill Generation in Solar PV Systems
Abstract: AbstractFor a soon to be developed India, the renewable energy resources will be the centre around which the wheel of growth will revolve. In our country the energy shortage problem and the alarming rate at which pollution is rising have given way to the domestic solar photovoltaic ON grid system. This leads to the problem of bidirectional metering of electrical energy. In response to this problem we are developing this …
Published in Journal of Microelectronics and Solid State Devices · Vol. 7, Issue 1, 2020 · pp. 11–17 Read article
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Comparative Study of Oxidation and Hot Corrosion Behavior of Uncoated and Detonation Gun Sprayed Cr3C2-25NiCr Coating on SA516 Boiler Steel at 800°C
Abstract: In the present investigation Cr3C2-25NiCr powder was deposited on boiler steel SA 516 (Grade 70) by detonation gun process. The oxidation and hot corrosion performance of coated as well as bare boiler steel was studying in the air and aggressive environment of Na2SO4–50% NaCl under cyclic conditions at an elevated temperature of 8000C. Oxidation and hot corrosion of metals and alloys has been recognized as a serious problem for elevated-temperature …
Published in Journal of Aerospace Engineering & Technology · Vol. 8, Issue 1, 2018 · pp. 5–10 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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Study on the Profile and Flow Field Variation of Parachute Coating by Seven-hole Probe Method
Abstract: In general, the parachute test is a long test cycle, expensive, and difficult to measure with accuracy, which makes it a very laborious and time-consuming task. Therefore, attempts have been made to overcome this by using a parachute test stand or by simulation, but in our country, there is no numerical simulation of the parachute and there is no research on it. In this paper, the variation of the shape …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 26–37 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Multi-Layer Aluminum–Polymer Hybrid Structures for Improved Automotive Impact Performance
Abstract: Layered metal–polymer hybrid laminates have emerged as promising candidates for lightweight automotive structures requiring high impact resistance and structural reliability. In this study, aluminum/glass–epoxy hybrid laminates were fabricated using a symmetric stacking sequence through hot compression molding to evaluate their mechanical and energy absorption performance. Density analysis revealed an average measured density of 2.34 g/cm³, closely matching the theoretical value of 2.36 g/cm³, with a deviation of approximately 1.02%, indicating …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 42–53 Read article
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A Classified Survey of Component-based Software
Abstract: Software reuse is the process of creating software systems from existing software rather than building software systems from scratch. The last decade performed the real attempt to turn software development into engineering through the concepts of Component-Based Software Development (CBSD) and Commercial Off-The-Shelf (COTS) components. This paper surveys the progress of component-based software in recent years with emphases on Architecture and measurement for component-based applications. CBSD has emerged as the …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 3, Issue 1, 2016 · pp. 20–28 Read article
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Comparative Realization of 2DoF PID Controllers for Flow Process with Measurement Delay
Abstract: Two Degree-of-Freedom (2DoF) PID control techniques presented in this paper were developed based on optimal control theory and with the Anti-Integral Windup (AIW) scheme. The controllers were implemented for a laboratory flow process setup. First Order Process with Dead Time (FOPDT) models had been identified by step testing. The process responses showed a significant non-minimum phase dynamics exhibited for the specific step inputs applied. The measurement delay was considered as …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 1, 2015 · pp. 1–8 Read article
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A Review on Two-Wheeled Self-Balancing Robot Using Spartan-3E FPGA for Sensor Fusion and Real-Time Motor Control
Abstract: Two-wheeled self-balancing robots (TWSBR) are a popular application of embedded control and robotics because they operate on the inverted pendulum concept, which is naturally unstable. The main objective of such robots is to continuously maintain balance by estimating the tilt angle and applying corrective motor action in real time. In most practical systems, low-cost inertial sensors such as accelerometers and gyroscopes are used for tilt measurement. However, accelerometer readings are …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 17–27 Read article
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Navigating Privacy and Security in Cloud Computing
Abstract: Cloud computing has rapidly evolved, serving as a cornerstone for storage, information processing, and various applications. Its adoption has surged across enterprises and small businesses alike, offering them efficient means to store and process data. However, alongside its undeniable benefits, the cloud also presents inherent risks to privacy and security, as data traverses and resides on remote servers. Employing tactics such as data encryption, multifactor authentication, access control, and intrusion …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Optimal Abrasive Jet Machining Parameters for Glass Fiber Reinforced Plastics
Abstract: Abrasive jet machining (AJM) is a best choice for processing of glass fiber reinforced plastics (GFRP). Inherent to the nonlinear behavior of performance characteristics during repeated experiments are inevitable variations, attributed to measurement errors and unknown influencing input variables. This study employs the Taguchi method with an orthogonal array to systematically identify optimal input variables through a limited number of experiments. The paper introduces a direct and reliable Taguchi-based multi-objective …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 247–255 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Heart Attack Prediction System Using Machine Learning
Abstract: There is an unrestrained increase in the rate of heart strokes at puerile ages. So, there is a need to develop a system that can predict this disease at an early stage and hence preventive measures can be taken at the initial stage. It is infeasible for common people to take tests such as ECG on a regular basis and hence we require a system that is easily approachable and …
Published in Recent Trends in Programming languages · Vol. 8, Issue 2, 2021 · pp. 11–16 Read article
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Examining the role of banks in financing nuclear power programs for a green economy and clean energy transition
Abstract: Nuclear power programs have the potential to contribute to deep, multi-sector and economy-wide decarbonization as sources of reliable, low emissions intensity thermal and electrical energy. However, nuclear power projects are complex, capital-intensive ventures with significant financial risks associated with them. Therefore, financing has been a critical issue for these projects. To accelerate their deployment to meet clean energy transition targets of nations and institutions, financial institutions like banks can play …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 28–39 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article
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Determination of Free Chlorine Water Content in Jalandhar City Using Colorimeter
Abstract: Water is the ultimate source of life on this universe. Water is vital for the survival of humans, animals, and plants, and the issue of freshwater is becoming increasingly critical in society. With the human body composed of 64% water, contaminated water, inadequate waste disposal, and poor water management contribute to severe public health issues such as cholera, typhoid, and malaria annually. Globally, the quality and quantity of water are …
Published in Journal of Water Pollution & Purification Research · Vol. 11, Issue 1, 2024 · pp. 1–5 Read article