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192 articles for “Machining parameters”
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NutriHeart with Chatbot
Abstract: Heart disease stands as one of the world's principal reasons for human deaths since it causes major preventable fatalities each year. Healthcare institutions currently explore machine learning (ML) integration for establishing new approaches toward predicting, and acting ahead of healthcare developments. NutriHeart presents an AI-based platform that accomplishes cardiovascular risk detection early and extends heart wellness by delivering customized nutritional and lifestyle recommendations. Using Support Vector Machines (SVM) along with …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 22–34 Read article
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Iot Based Environment Monitoring System
Abstract: Pollution combined with climate change is creating long-term problems for natural resources. Their impact on soil, air, and water cleanlinessis growing, requires smart, immediate solutions. In this paper, we report on an IoT-based Environment Monitoring System whose purpose is to monitor the air quality, temperature, humidity, and soil moisture content. It consists of an Arduino Uno, gas sensors (MQ135, MQ9, MQ6), a temperature sensor LM35, a soil moisture sensor, and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 8–14 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Statistical Modeling of Heat Transfer and Fluid Dynamics: Application in Mechanical Engineering Design
Abstract: Understanding and optimizing the intricate processes involved in heat transfer and fluid dynamics—two concepts essential to mechanical engineering design—require statistical modeling. Engineers can forecast, regulate, and enhance the performance of systems including heat exchangers, turbines, cooling mechanisms, and different fluid machinery by using statistical approaches. In order to address uncertainties, variability in material properties, boundary conditions, and operational parameters, this work investigates the integration of statistical modeling tools in the …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 18–22 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 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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Emerging Trends in Membrane-Based Gas Separation Technologies
Abstract: Membrane technology has emerged as a groundbreaking solution in various fields, revolutionizing industries such as water treatment, energy production, biomedicine, and environmental protection. Over the past few decades, significant advancements have been made in membrane materials, fabrication techniques, and performance optimization. With the growing global demand for efficient and sustainable separation processes, research has increasingly focused on enhancing membrane permeability, selectivity, and durability to improve performance across various industries, including …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 16–22 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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Optimizing Mechanical and Durability Properties of Eco-Friendly Composite Materials Using Recycled Fillers and ML Techniques
Abstract: The increasing demand for sustainable construction materials has intensified the exploration of recycled fillers as partial or full replacements for natural aggregates in composite materials. This study investigates the mechanical and durability performance of polymer matrix composites incorporating processed recycled fillers derived from construction and demolition (C&D) waste. Three distinct processing methods were employed to prepare the recycled fillers: untreated (URF), single processed (SPRF), and double processed (DPRF), with replacement …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 269–309 Read article
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Advances in Polymer-Modified Concrete using XAI
Abstract: Industry 4.0 technologies are being quickly adopted by the construction sector, opening new avenues for enduring operational and environmental issues. This sector looks at how explainable AI can forecast air and enhance the quality of building materials. XAI, AI, ML, and big data drive a new paradigm in polymeric material development. The effective XAI and ML-assisted design creates innovative, high-performance polymeric materials. It covers building a database and representing structures, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 133–144 Read article
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Influence of SlS Parameters on Strength and Fatigue Durability of Polyamide-12
Abstract: Selective Laser Sintering (SLS), a laser-based polymer powder bed fusion process, has gained prominence in the fabrication of high-performance thermoplastics such as Polyamide-12 (PA12). This paper provides an extensive review of how key SLS process parameters—such as laser power, scan speed, hatch spacing, and energy density—affect the mechanical properties of PA12 components, with a specific focus on tensile strength and fatigue resistance. Studies demonstrate that increasing energy input enhances particle …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 178–191 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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Investigating the Combined Effect of FDM 3D Printing Parameters on Tensile Behavior of ABS Plastic Using Taguchi Method.
Abstract: Fused Deposition Modelling (FDM) is a commonly utilized method in additive manufacturing. FDM is greatly affected by its printing parameters, which is why selecting the proper parameters is crucial for obtaining the desired properties of 3D printed parts. In this paper we have experimentally and statistically studied the influence of FDM 3D printing parameters (infill pattern, infill density and layer thickness) on tensile strength using Acrylonitrile Butadiene Styrene (ABS) filament. …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 161–169 Read article
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Computer Vision Algorithm for Surface Defects Identification in TIG Welded Joints
Abstract: Quality monitoring of welded joints is still quite a tedious job for many industries. The surface defects on welded joints arises from the improper selection of various input parameters which further result bad quality weld. This paper highlight the application of a computer vision algorithm called discrete Fourier transformation approach for identification of surface defects present on TIG welded joints.
Published in Research and Reviews : Journal of Computational Biology Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 Read article