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816 articles for “machining time”
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Hybrid Machining Processes in Advanced Manufacturing: A Review of Mechanisms and Industrial Applications
Abstract: Hybrid machining processes (HMPs) have gained considerable attention in recent years as an effective approach to address the growing complexity and performance demands of modern manufacturing systems. These processes combine two or more machining techniques—such as mechanical, thermal, chemical, or electrical methods—into a single setup, enabling enhanced productivity, precision, and adaptability, particularly for hard-to-machine materials like ceramics, composites, and superalloys. The integration of distinct energy sources results in synergistic effects …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 19–24 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article
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Assessing the Effectiveness of Industrial Energy Audits: A Literature Review
Abstract: Indian economy plans to conserve the energy which is consumed by the industrial sector. Government of India has made it mandatory to conduct periodic energy audits in the industrial sector which is to be followed up with a practical implementation of energy conservation (ECON) measures as suggested by the energy audit team. Energy audit has been conducted in two phases namely, pre-audit and post audit phase. During pre-audit phase, initially, …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 1, 2024 · pp. 1–7 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Smart Polymer Composite Scaffolds for Tissue Engineering with Integrated Machine Learning Feedback
Abstract: Another potential solution to improving the results of tissue engineering is smart polymer composite scaffolds, which are capable of dynamic adaptation to changing biological factors, but typical scaffolds cannot change dynamically. This paper suggests a comprehensive system to integrate biodegradable polymer composite scaffolds with sensing and machine learning-based feedback to allow the real-time monitoring and active regulation of tissue regeneration events. The system uses biocompatible materials of PLA/PCL composite of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Stiffness Optimization of Control Unit of Vehicle Using Vibration Technique
Abstract: All modern automotive engines are controlled by an ECU. Engine efficiency, combustion, and emission characteristics are all affected by ECU tuning or tune-up. The electrical system in automobiles has evolved over time, and it now incorporates automatic machine control of automotive mechanics. In the beginning, a car’s electrical system consisted solely of primitive wiring technologies for supplying power to other parts of the vehicle. Engine management design specifications for the …
Published in Journal of Automobile Engineering and Applications Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Raspberry Pi-based Self-driving Car Technologies: A Review of Hardware and Software Integration
Abstract: An assessment of the state, possibilities, and difficulties of self-driving car technology. Autonomous vehicles (AVs), also referred to as self-driving cars, are automobiles that can navigate and function without the need for human involvement. They make decisions, sense their environment, and traverse routes safely by combining sensors, cameras, radar, lidar, and sophisticated algorithms. The advancement of autonomous vehicles holds the capacity to completely transform the transportation sector by enhancing security, …
Published in International Journal of Electronics Automation · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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Exploring the Effectiveness of IoT in Virtual Doctor Robot Systems
Abstract: The design and development of a Virtual Doctor Robot (VDR) using Internet of Things technology is presented in this study with the goal of facilitating remote medical assistance. In light of the constraints associated with physical presence, especially in underprivileged areas like isolated parts of India during the COVID-19 pandemic, videoconferencing (VDR) is a viable means of bridging the gap between patients and physicians. The VDR makes accurate diagnostic and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 3, 2024 · pp. 13–23 Read article
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Emotionally Intelligent AI: The Future of Mental Health Care and Emotional Well-being
Abstract: With the potential to improve emotional well-being through sophisticated AI systems, emotionally intelligent AI (EI-AI) represents a revolutionary frontier in mental health treatment. EI-AI can recognize, understand, and react to human emotions in real- time by utilizing recent advancements in machine learning, natural language processing, and emotion detection. These features are being used more and more in mental health settings, where chatbots and other AI-driven interventions help with emotional regulation, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Motorised Dual Side Shaping Machine with IoT Integration
Abstract: This work presents the design, fabrication and testing of a Motorised Dual Side Shaping Machine intended for small-scale workshops and educational laboratories, enhanced by an Internet of Things IoT based motor control system using the ESP32 microcontroller. The machine employs a 250 watt geared motor as the prime mover, transmitting power through a chain and sprocket mechanism to a 20 mm mild steel shaft supported on pedestal bearings (P204), where …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 26–35 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Latest Research Trend of Optimization Techniques and Considerable Parameters in Wire Electrical Discharge Machining (WEDM): Review Article
Abstract: Wire electrical discharge machining (WEDM) is a non-conventional machining method with unique capabilities. WEDM offers a better alternative or sometimes the only alternative to produce complex shaped features and components of difficult-to-machine materials. In today’s highly competitive manufacturing industries, manufacturer’s ultimate goal is to produce high quality product with less time and cost constraint. To achieve these goals, one of the considerations is by optimizing the machining process parameters such …
Published in Journal of Production Research & Management · Vol. 6, Issue 2, 2016 · pp. 30–53 Read article
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Optimization of Machining Parameters on End Milling of Steel Grade EN 8: A Review
Abstract: Nowadays, most of the machining industries are facing a challenge to achieve high quality of product at given time and reasonable price according to customer requirement. The optimization of machining parameters of manufacturing process leads to effective as well as efficient manufacturing. End milling is one of the operations of milling process, which is used to cut horizontal, vertical and inclined profile. So, generated key ways or profile should be …
Published in Trends in Machine design · Vol. 4, Issue 3, 2017 · pp. 8–11 Read article
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Multipurpose Beach Sand And Water Impurities Cleaning Machine
Abstract: In today's world, garbage is a major problem in worldwide attention. Most of the garbage is dumped in waterways in rivers, lakes, ponds which harms aquatic life and disturbs environmental balance, this garbage in turn shows at sand beaches which is cleaned manually by some organizations or else its left as it is and the garbage in the ponds is not cleaned as it is physically not approachable. For this …
Published in Recent Trends in Fluid Mechanics · Vol. 9, Issue 2, 2022 · pp. 15–20 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article