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134 articles for “machine error”
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Prediction of Excitation Current of Synchronous Machines Based on Neural Network Model
Abstract: There are several difficulties found to estimate the excitation current & and optimum input parameters of synchronous motors. Heuristic methods are frequently used to weightt the problem's parameters or optimum coefficients. As a result, a neural network model is modified in this study to explore the best parameters and estimate the excitation current of a synchronous motor with minimal prediction errors for both the testing dataset and cross validation. Excitation …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 1, 2023 · pp. 28–33 Read article
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Online State Estimation and Fault Detection of a Doubly Fed Induction Machine by an Interconnected High Gain Observer
Abstract: This article presents the states and disturbance estimation of a doubly fed induction machine by the use of an interconnected high gain observer. The supply is made of a rectifier, a filter and an inverter. We consider the parameters such as the load couple, the electromagnetic couple and the speed on the only basis of the electric quantities. The results show that the error between the estimated and measured parameters …
Published in Journal of Control & Instrumentation · Vol. 8, Issue 3, 2017 · pp. 1–11 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article
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DESIGN AND MACHINEWORK INVOLVED IN FIRE-FIGHTING ROBOT
Abstract: Due to a lack of technological advancement, battling fires has long been a dangerous job that frequently results in devastating losses. A human being is prone to error, and current firefighting techniques are ineffectual and inefficient. The use of robots rather than people to deal with fire dangers is a recent idea that has gained popularity. Our project entails building a robot that can recognise and put out a fire …
Published in Trends in Machine design · Vol. 9, Issue 2, 2022 · pp. 1–5 Read article
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Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 · pp. 12–19 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Design and Machine Work Involved in Fire-fighting Robot
Abstract: Due to a lack of technological advancement, battling fires has long been a dangerous job that frequently results in devastating losses. A human being is prone to error, and current firefighting techniques are ineffectual and inefficient. The use of robots rather than people to deal with fire dangers is a recent idea that has gained popularity. Our project entails building a robot that can recognise and put out a fire …
Published in Trends in Machine design · Vol. 9, Issue 2, 2022 · pp. 1–5 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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Multi-variable Analysis and Optimization of Electrical Discharge Machining Process Using a PCA-ANN Based Approach
Abstract: AbstractThe optimum selection of process parameters has played a crucial role in electrical discharge machining (EDM) for improving the material removal rate, reducing the tool wear rate and radial overcut. In this paper, optimum parameters while machining 202 stainless steel using copper electrode as a tool has been investigated. For optimization of process parameters along with multiple quality characteristics, principal component analysis coupled with artificial neural network method has been …
Published in Trends in Opto-electro & Optical Communication · Vol. 6, Issue 3, 2016 · pp. 39–45 Read article
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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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Personality and Behavior Identification Based on Handwriting Analysis
Abstract: Graphing is the process of identifying, evaluating, and understanding a person's personality traits through handwritten patterns. The accuracy of handwriting analysis depends on the skill of the analyst, it is expensive and prone to errors. The proposed approach is therefore focused on building a system that can predict personality traits with the help of machine learning without human intervention. In this project, 657 authors' handwritten samples were taken as datasets. …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 1, 2022 · pp. 42–54 Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 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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Harnessing Shell Scripting for Autonomous System Management: A Vision for the Future
Abstract: As IT systems become increasingly complex, the demand for efficient and automated management solutions is more critical than ever. This paper investigates the pivotal role of shell scripting in the development of autonomous systems that can self-manage and optimize their operations. Shell scripting, with its powerful automation capabilities, serves as a foundational tool for orchestrating various tasks, including system monitoring, data analysis, and deployment processes. We begin by examining current …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 17–31 Read article
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Fluidic Engineering: Investigating Cutting Fluids’ Effect on Machined Surface Roughness
Abstract: The primary goal of this experimental study project is to determine the optimal cutting fluid by experimenting with two distinct oil kinds and compositions. Thirty-six compositions of cutting oil are obtained by mixing three distinct oil compositions, such as mineral oil and paraffin oil, with six different additive and anti-foaming agent compositions. Then, using a trial-and-error methodology, we employed these 36 cutting oil compositions for drilling operations with constant pressure …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 27–42 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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Automatic Laser Welding Machine Using PLCs
Abstract: This paper presents the design and implementation of an automatic laser welding machine controlled by a Programmable Logic Controller (PLC) technology. Laser welding has gained significant attention in various industries due to its precision, speed, and efficiency. However, manual operation of laser welding systems can be labor-intensive and prone to errors. The proposed system aims to address these challenges by automating the welding process using PLC-based control. The system architecture …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 9–15 Read article
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Paradigm of Artificial Intelligence in Business Management
Abstract: Artificial intelligence stands out as a prominent trend in today's technological landscape, enabling machines to engage in human-like thinking, learning from experiences, adapting to new inputs, and making decisions. This capability facilitates rapid and error-free results, akin to human rational decision-making. In the contemporary business landscape, which is often regarded as a cornerstone for national development, artificial intelligence plays a pivotal role. Businesses, ranging from small-scale enterprises to medium-sized ones …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 26–30 Read article
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Bending and Single Edge Notch Bending Test (SENB) Investigation of Natural Fiber- Reinforced Epoxy Composites using Machine Learning
Abstract: The present study aims to determine the behavior of hemp fiber-reinforced epoxy composites in terms of bending behavior and fracture toughness under bending load resembles the substitutive behavior of existing synthetic composites. The fabrication was carried out by hand lay-up assembly of hemp fiber with Lapox-12 epoxy resin volume fraction of 60:40 fiber: matrix volume. Flexural testing revealed an average strength of 93.5 ± 2.8 MPa and SENB testing revealed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 59–69 Read article