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194 articles for “machining characteristics”
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Effect of Varying Surface Grinding Parameters for AISI 1018 Mild Steel by Taguchi based PCA
Abstract: The main purpose of this work is to study the effects of surface grinding parameters on AISI 1018 Mild steel work surface by using three process parameters like Wheel speed (WS), Table speed (TS) and Depth of cut (DOC). This work was conducted on surface grinding machine with model number HMT-P452. Taguchi’s L16 orthogonal array is used which takes sixteen experimental runs to achieve the design matrix of surface grinding …
Published in Journal of Catalyst & Catalysis · Vol. 5, Issue 2, 2018 · pp. 5–14 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article
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Assessing the Mechanical, Structural and Thermal Performance of Boehmeria Nivea and Agave Sisalana Fiber Reinforced Polymer Composite by using Seashell Powder as a Filler Material
Abstract: Natural fiber composites have replaced plastics and have been used to the maximum extent. Hybridization of natural fibers with filler materials has achieved higher tensile, impact, and flexural strength compared to single fiber composites. In this research, the mechanical properties were investigated with the ramie and sisal hybrid fiber reinforced with seashell powder as filler material. Filler material can enhance the flexural property of the natural fiber. Hybrid composite plates …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 355–369 Read article
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Alternating Inertia-Based Virtual Synchronous Machine Control for Improved Frequency Regulation of Energy Storage Systems
Abstract: The rapid integration of renewable energy sources (RESs), particularly solar photovoltaic and wind energy systems, has significantly increased the penetration of power electronic converter-based distributed generators (DGs) in modern power systems. While these technologies provide substantial environmental, economic, and sustainability benefits, their widespread deployment has introduced new operational challenges. One of the major concerns is the reduction of system inertia and damping due to the replacement of conventional synchronous generators …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Experimental Findings of the EDM Process Parameters for Metal Matrix Composites
Abstract: The process of electrical discharge machining (EDM) shapes hard metals and creates intricately formed, deep holes in a variety of electro-conductive materials by arc erosion. With regard to material removal rate (MRR) in metal matrix composite EDM, this study intends to examine the impacts of operational factors. The material removal rate generated is used to assess the efficacy of the metal matrix composite EDM process. It has been noted that …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 14–18 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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Disc Spring Washer: Design and Axisymmetric analysis using ANSYS
Abstract: Disc spring washer has many applications including in wide variety of bolted connections. Disc spring washer consist of a coned disk, which has typical load deflection characteristics. It is especially useful where very large force is desired for small amount of deflection of spring. In this paper, safe design of disc spring washer is obtained using analytical procedure for given value of nominal force. Axisymmetric analysis of disc spring washer …
Published in Trends in Machine design · Vol. 4, Issue 3, 2017 · pp. 21–25 Read article
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Development and evaluation of multigrain pasta
Abstract: Pasta is one of the most consumed food among the food products prepared from cereals due to low cost, ease in preparation along with pleasant textural and sensory characteristics. This study was performed to prepare multigrain pasta by utilising the numerous health benefits of wheat, chickpea, kodo and ragi flour. Each ingredient was selected according to unique nutritional attributes which will be incorporated in pasta to make it more nutritious …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 · pp. 34–47 Read article
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A Review study of Mn-Zn Ferrite with Applications and Synthesis processes
Abstract: The distinct magnetic characteristics and adaptability of Mn-Zn ferrites make them broadly applicable in a wide range of industries and applications. Temperature stability, high electricity resistivity, magnetic permeability, permittivity, saturation magnetization, and low power losses are among the characteristics of Mn-Zn ferrites. These ferrites particularly in the form of magnetic nanoparticles, have garnered significant interest in cancer research and therapy and the biomedical field. Researchers are keenly interested in the …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 2, 2024 · pp. 15–26 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Integrated engineering on design, development and operation of a Table Top Tokamak for Plasma experiments
Abstract: Making of a Table Top Tokamak is having the acute need for conducting various plasma experimental studies. As pulsed devices, small tokamaks come as handy solutions for plasma experimentalists to study the characteristic behavior of plasma at various operating conditions. In addition, it is a challenge to build a Tokamak from its conceptual design. In this paper, details are brought out for a single mode approach that is required to …
Published in Trends in Machine design · Vol. 5, Issue 2, 2018 · pp. 54–62 Read article
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Birdwatcher’s Assistant: AI- Based Bird Species Classification
Abstract: Many bird species have gone extinct because of human activities and changes in the climate. The loss of habitats is a significant danger to global biodiversity. Therefore, it is important to monitor species distribution and identify the components of biodiversity in an area to develop conservation strategies. The ultimate objective is to build a machine learning model that can accurately differentiate between various bird species based solely on visual cues. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 17–27 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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Contact Stress Analysis of Needle Roller Bearing Used in Synchromesh Gear Box
Abstract: The optimum selection of a bearing generally depends on particular application such as to transfer loads between the rotating and stationary members, and to permit free rotation. From among the wide range of bearings available in the market today has various considerations, such as the load-carrying capacity, the life of the bearing, and the working rotational speed need to be considered before a suitable bearing can be selected. Here for …
Published in Trends in Machine design · Vol. 5, Issue 1, 2018 · pp. 5–20 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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A Review of Torque Ripple Reduction Techniques in Switched Reluctance Motors
Abstract: Switched Reluctance Motors (SRMs) have emerged as a promising alternative to conventional motor technologies due to their rugged structure, low manufacturing cost, high-temperature capability, and suitability for harsh environments. Despite these advantages, the widespread adoption of SRMs in applications such as electric vehicles, household appliances, industrial drives, and aerospace systems is significantly restricted by the issue of torque ripple. Torque ripple manifests as periodic fluctuations in the developed electromagnetic torque, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 45–50 Read article