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1980 articles for “Processes” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Enhancing The Mechanical Performance of Al6061/Graphite Composites Reinforced with Sic and Aluminium Oxide Processed by Stir Casting
Abstract: The study investigates the mechanical properties of aluminum alloy Al6061 reinforced with varying proportions of silicon carbide (SiC) (0 wt%, 4 wt%, 5 wt%, and 6 wt%) and aluminum oxide (Al₂O₃) (0 wt%, 4 wt%, 3 wt%, and 2 wt%), with a constant addition of 1 wt% graphite. The composites were fabricated using the stir casting process, an efficient and economical method for uniformly distributing ceramic reinforcements within the metal …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 66–74 Read article
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Human Skin Abnormality Detection with Process Similarity Criteria Fit Machine Learning Method
Abstract: This method presents a machine learning method that satisfies the defined conditions for healthy waterside beach activities. The boundary conditions of the normal and abnormal radiation spaces were formulated. The objectives of using a Regression Polynomial with Process Similarity Criteria Fit for skin temperature prediction are justified by the analysis of the existing analytical and machine learning approaches. An algorithm for skin temperature prediction using the theories of similarity criteria …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article
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Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "FertileData: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a user-friendly …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article
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Optimization of Turning Process Parameters by Genetic Algorithm Approach
Abstract: In this research, turning parameters were optimized through a genetic algorithm for the purpose to minimize surface roughness and to maximize the material removal rate. High finish quality is guaranteed through minimum surface roughness, and efficient process planning is facilitated through maximum material removal rate optimization. For predicting surface roughness and material removal rate with respect to spindle speed, feed rate, and depth of cut, the empirical models were developed …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 33–41 Read article
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Fabrication of Natural Fibre Reinforced Polymer Composite by Hand Lay-Up Process
Abstract: The recent development in technologies has increased the usage of non-renewable resources during pro- duction due to remarkable properties. However, it has been a threat and unable to be replenished once used. In addition to this, natural fibre strengthens in a more significant way and it’s widely applicable in polymer composites materials. Furthermore, the use of plant fibres in polymer composites is due to its low cost and significant properties. …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 13–19 Read article
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An Experimental Investigation of Process Parameters for Aluminum Alloy Composites
Abstract: The objectives of this work are to develop an aluminum alloy composites and investigate machining process parameters effect on the tool wear rate for composites. The composite is enhanced using silicon carbide and graphite. The composite is made by a method called stir casting. Furthermore, it is investigated both mathematically and experimentally. This study takes trial on aluminum alloy composite to see output characteristics tool wear rate are affected by …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 185–193 Read article
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Squeeze Casting of Hybrid Aluminum Matrix Composites: A Critical Review of Process Optimization, Reinforcement Strategies, and Performance Outcomes
Abstract: Increasing demand for lightweight, performance-oriented components in automotive, aerospace, and defense industries has driven advancements in squeeze casting, a hybrid technique merging forging and die-casting advantages to produce near-net-shape aluminum matrix composites (AMCs) with superior mechanical-tribological properties. This review critically examines the interplay of process parameters (e.g., squeeze pressure: 70–150 MPa, melt temperature: 650–800°C), reinforcement characteristics (volume fraction ≤10%, particle size: 10–71µm), and interfacial engineering strategies (flux-assisted bonding, ultrasonic dispersion) …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 52–60 Read article
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Examining Experimentally the Impact of Spot-Welding Process Variables on Metal Matrix Composites
Abstract: Metal matrix composites work in concert with reinforcement to improve the material's qualities. Reliability in joining metal matrix composites using traditional methods is challenging. Friction Stir Welding has demonstrated the ability to solve numerous issues that arise in traditional welding procedures. Initially, the Friction Stir Welding (FSW) welding procedure produced metal seams that were solid. Additionally, FSW was expanded to join MMCs and their alloys. The purpose of this review …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 193–201 Read article
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An Experimental Study on Multi-Criteria Parameters Optimization of Process for Al6351/SiC/Gr Metal Matrix Composites Using AHP-TOPSIS Approach
Abstract: This research focuses on optimizing the process parameters of Wire Electrical Discharge Machining (WEDM) for a hybrid Metal Matrix Composite (MMC) comprising Al6351 aluminum alloy reinforced with 4% SiC and 6% graphite (Gr), fabricated via squeeze casting. This technique enables the formation of dense, defect-free composites with uniform reinforcement distribution, enhancing both mechanical properties and structural integrity. Microstructural characterization using Scanning Electron Microscopy (SEM) confirmed the even dispersion and bonding …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 303–319 Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Automated Blood Cell Counting and Disease Identification Using Image Processing: Implications for Polymer Composite- Based Biomedical Diagnostic Devices
Abstract: Accurate quantification of blood cells is central to clinical decision-making and to the performance of emerging polymer composite–based diagnostic platforms. This work presents a cost-effective, image-processing pipeline for automated counting of red blood cells (including overlapping cells), white blood cells, and platelets from Leishman-stained peripheral blood smears, and articulates its relevance to polymer composite microfluidic and biosensor devices. Implemented in Python with OpenCV, the workflow performs grayscale conversion, median/Gaussian denoising, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 262–270 Read article
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Fertiledata: Advanced Strategies For Crop Optimization Through Machine Learning Processing
Abstract: The venture, titled "Fertile Data: Advanced Strategies for Crop Optimization Through Machine Learning processing" is created utilizing HTML, CSS, and JavaScript for the front conclusion, and Python for the back conclusion. In a nation like India, where a noteworthy parcel of the populace depends on agribusiness for their vocation, joining progressed advances such as Machine Learning and Profound Learning into cultivating hones can revolutionize the industry. This venture presents a …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 25–35 Read article
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Natural Language Processing in Education: A Review of Applications, Challenges, and Future Directions
Abstract: Natural Language Processing (NLP) has increasingly become a transformative force within the field of education, offering innovative solutions and reshaping traditional methods of teaching, learning, assessment, and educational research. This review explores the evolving landscape of NLP applications in education, shedding light on significant advancements, ongoing challenges, and emerging opportunities. The integration of NLP into intelligent tutoring systems has enabled more personalized learning experiences, while automated assessment tools have enhanced …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 11–18 Read article
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Comparative Analysis of Natural and Synthetic Fibre-Reinforced Composites: Mechanical Properties, Processing, and Sustainability Considerations
Abstract: The development of fibre-reinforced composites has significantly advanced engineering applications due to their excellent strength-to-weight ratio, corrosion resistance, and versatility. Synthetic fibres such as glass and carbon provide superior mechanical performance, but their production is energy-intensive and environmentally harmful. Natural fibres, including jute, flax, banana, and hemp, offer biodegradability, lower cost, and sustainability benefits, though they often fall short in strength and durability. Hybrid composites frequently demonstrate improved performance by …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 77–95 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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Recent Progress in Magnesium Hybrid Metal Matrix Composites: Processing, Properties, and Applications
Abstract: Magnesium hybrid composites have emerged as promising materials to meet the growing demands of advanced sectors such as biomedical, aerospace, defense, automotive, electronics, and marine industries. However, the inherent drawbacks of magnesium, specifically low wear resistance, have encouraged scientists to develop magnesium-based MMC with improved mechanical properties and thermal properties. To achieve this, various mixtures of reinforcement are employed. These include ceramics with high strength and wear resistance; solid lubricants …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1287–1301 Read article
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Process Optimization of Spot Welding for Galvanized Automotive Steel Sheets
Abstract: Resistance Spot Welding (RSW) is a pillar of the modern automotive industry with the usage of lightweight and high-strength products at the highest point of demand. The optimum weld quality of galvanized steel sheets which is a material of choice because of its additional corrosion protective property is however not achieved easily. This study is a well-developed data-based solution to designing the RSW process in the most efficient way, providing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 32–42 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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Very Short-Term Load Forecasting Using Gaussian Process Regression
Abstract: Very Short-Term Load Forecasting (VSTLF) is critical for real-time grid stability, frequency control, and economic dispatch. This study proposes a Gaussian Process Regression (GPR)-based framework for one-hour-ahead load forecasting using hourly data from January 2020 to April 2024 for Delhi, India. The model incorporates meteorological data such as temperature, humidity, and dew point with lagged load values. The research takes into account time-related dependencies and seasonal changes in order to …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 91–104 Read article