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212 articles for “accuracy parameter”
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Parametric Study of Cylindrical Grinding Machine: Review
Abstract: Manufacturing industry has undergone various changes to meet the requirement of customers and to manufacture the components with accuracy and within time limit. For that, study of different parameters that directly or indirectly affect the manufacturing process need to be studied. This paper is review to study the different parameters of cylindrical grinding machine which affect the final outcome (surface roughness and material removal rate) of the component.
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 3, 2015 · pp. 36–40 Read article
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Utilizing Machine Learning to Combat Plant Disease
Abstract: Plant diseases are a significant source of lost income and time for the agricultural industry. Accurately diagnosing an illness requires a high level of experience and dedication. Symptoms of plant diseases, such as spots or streaks of a different colour, are sometimes visible on the leaves of infected plants. Many fungal, bacterial, and viral organisms may also cause illness in plants. The indications and symptoms of a plant disease are …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 20–28 Read article
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Optimization of Resin 3D Printing Process Parameters for Enhanced Dimensional Accuracy and Surface Roughness Using Hybrid Algorithm
Abstract: The advent of 3D printable dental resin has paved the way for minimally invasive dentistry, which helps to retain healthy tooth structure while yet producing pleasing aesthetic outcomes. However, printing these dental resins is being researched to improve their durability and therapeutic efficacy. Frontiers in dental restoration research can aim to fabricate occlusal appliances using resins with optimized parameters for enhanced functionalities. The present study aims to analyze the dimensional …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 26–37 Read article
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A Review Study on CPU-Optimized Parameter-Efficient Fine-Tuning for Large Language Models to Increase Accuracy Using LoRA
Abstract: The fast proliferation of large language models (LLMs) has increased the need to optimize the process of fine-tuning, but the existing workflows that require a graphics processing unit (GPU) are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of parameter-efficient fine-tuning (PEFT) based on low-rank adaptation (LoRA). The major purpose …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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Prediction of Process Parameters of Friction Stir Welding Using Artificial Neural Network
Abstract: In this paper an artificial neural network (ANN) approach is used to predict the process parameters of friction stir welding (FSW). Initially, the experiments are conducted using the design of experiment (DoE) approach on FSW using L27 orthogonal array. The experiments are conducted using speed, feed, and tool tilt angle as input parameters for DoE and tensile strength, hardness, and ductility as output. ANN is created having 25 neurons and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 3, 2023 · pp. 13–25 Read article
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IOT Based Smart System for Parameter Control Interfaced with Android and Cloud
Abstract: The smart embedded system enables real-time monitoring and control of multiple parameters motor speed, LCD brightness, temperature, and humidity through both manual input and remote Android application. The system consists Raspberry Pi 4 Model B as the central processor, integrated with a DHT11 sensor, L298N motor driver, LCD display, and potentiometers. Cloud connectivity is achieved using Firebase to synchronize data between the hardware and a custom-built mobile application. Real-time feedback …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 11–22 Read article
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PREDICTIVE MAINTENANCE IN SEMICONDUCTOR SYSTEMS: INSIGHTS FROM MACHINE INTELLIGENCE AND DATA-DRIVEN METHODS
Abstract: With the fast-paced development of semiconductor technology comes the need to focus on device reliability, or how long devices will function and the likelihood of devices having operational issues. Predicting failures and avoiding downtime with the implementation of timely, actionable, and data-driven maintenance strategies are essential to insure devices function sustainably within predetermined performance levels. The implementation of predictive maintenance within artificial intelligence and machine learning technologies will provide the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
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Comparative Study of Change Detection Methods in High Resolution Images
Abstract: Natural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth's surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 1–5 Read article
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Stationary Wavelet and Recursive Least Square Filtering Based Fetal ECG Data Extraction from Composite Abdominal Signal
Abstract: This paper introduces a fast methodology for fetal ECG extraction based on stationary wavelet and noise canceler adaptive filter with the recursive least square filter. Firstly, signals are preprocessed by moving averaging filter for removing baseline wander. The stationary wavelet and the recursive least square filter is applied on preprocessed signal that effectively separates the maternal ECG and extracts fetal ECG (fECG) from the abdominal ECG. Finally, fetal ECG(fECG) is …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 46–58 Read article
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Quasi-Dimensional Thermodynamic Performance and Emission Modelling for Dual-Fuel SI Engine Operation Using Waste-Based Producer Gas and Methane
Abstract: Rising energy crisis and urgent need for better waste-handling techniques have gained significant attention. Integration of wastes-to-wealth and Green Energy evolution techniques are prime sustainable measures towards countering this menace. Moreover, Internal Combustion (IC) engines are significant energy consumers and their emissions play a major factor in global warming and ecological obliteration. Concerning these aspects, investigations should strive at emissions minimization and reutilization of low-impact industrial byproducts. Thus, using methane …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 446–458 Read article
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The Role of BIM and Parametric Intelligence in Architectural Practice: A Study of Architects in Uttarakhand
Abstract: Dehradun, the capital city of Uttarakhand, represents one of India’s youngest and most dynamic urban centers in Uttarakhand. Since its designation as the state’s capital, the city has experienced a rapid evolution in architectural development and construction technology. As urbanization and design demands increase, architectural practices in Dehradun and across Uttarakhand are progressively shifting from conventional methods toward advanced digital tools that promote precision, efficiency, and sustainable outcomes. Among these, …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 19–38 Read article
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Failed Component Image Acquisition Quality Optimization for Machine Vision System
Abstract: AbstractWith the rapid development of the global semiconductor industry, electronic products are required to have new ideas, diversified functions, and thinness and shortness. The ball grid array (BGA) packaging technique arranges solder balls in a matrix mode on the bottom of the component substrate, so as to increase the functional density. The dye stain test is extensively used for array component failure analysis; however, the operation takes time and extends …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 17–25 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Modeling of Photovoltaic Module with MATLAB/Simulink
Abstract: Abstract The generation of electrical energy from sunlight is achieved with an interface called photovoltaic (PV) module. The PV module plays a vital role for extracting electrical energy from sunlight, thus its accuracy is most important parameter for consideration while developing mathematical model of PV module. For higher accuracy the single diode model with series and parallel resistors combination is used. For simulating this device in MATLAB/Simulink we need weather …
Published in Trends in Opto-electro & Optical Communication · Vol. 9, Issue 1, 2019 · pp. 38–45 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Design & Development a SPM for cutting operation: A case study on power switch assembly
Abstract: Automation is used to improve the productivity in majority of the industries. It helps in reducing the human intervention and improves a quality lot. Assembly process along with the manufacturing of each part needs to be studied, to automate the desire manufacturing processes. Here a case of power switch is investigated and analysis is carried out in terms of the automation strategy. Each process is analyzed by parameters like efficiency, …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 2, 2018 · pp. 7–17 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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Parametric optimization and validation of novel 3D scanning approach for sustainable manufacturing of patient-specific orthodontic retainers
Abstract: The purpose of the proposed study is to identify the ideal procedure parameters for 3D scanning a denture in order to produce customised orthodontic retainers that can be produced sustainably. However, pilot investigations rarely explore parameters like scanning angle, light intensity, or scanning distance. In order to lower acquisition error, the suggested study examines a method for forecasting the ideal values of the previously indicated scanning parameters. Based on the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 265–278 Read article
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Procedure and design of a Gear Hobbing Machine
Abstract: Making gears involves using a hobbing machine. Sprockets, gears, and splined components are cut using a hob, a specialised cutting tool, on a hobbing machine, a sort of milling device. The hob is a cylinder-shaped cutting tool with helical-shaped teeth arranged in rows. Sprockets, gears, and splined components are cut using a hob, a specialised cutting tool, on a hobbing machine, a sort of milling device. The hob is a …
Published in Trends in Mechanical Engineering & Technology · Vol. 12, Issue 2, 2022 · pp. 17–20 Read article
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article