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321 articles for “Automated driving”
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 40–51 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Radio Frequency Next-Generation Advances
Abstract: Radio frequency (RF) technology is a key enabler for modern wireless communications, driving the evolution of telecommunications, healthcare, aerospace, defence and the Internet of Things (IoT). Faster, more reliable and energy-efficient communication systems have been developed at a rapid pace due to recent discoveries in RF engineering. This article discusses novel advancements in RF technologies including enhanced antenna design, millimeter-wave communication, software defined radio, smart spectrum management, and RF-based sensor …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 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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Vision Sense Rover
Abstract: This paper presents the design and implementation of an autonomous obstacle-avoiding robotic system utilizing an Arduino Uno microcontroller, an ultrasonic distance measurement module, a servo-based scanning mechanism, an L298N motor driver module, and an ESP32-CAM for real-time visual monitoring. The proposed system is developed to operate without human intervention, using sensor- driven decision making for navigation. The ultrasonic sensor continuously measures the distance to adjacent obstacles, while the servo motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 38–43 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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Development of a Low-Cost Autonomous Robot for Obstacle Avoidance Using Ultrasonic Sensing
Abstract: In the evolving landscape of automation, autonomous mobile robots are becoming critical for performing tasks with minimal human intervention. This project presents the design and development of a cost-effective, small-scale obstacle-avoiding robot using an Arduino microcontroller and an ultrasonic sensor. The robot operates by scanning its surroundings, identifying nearby obstacles, and navigating by altering its path in real time. Through intelligent programming and sensor integration, the system achieves smooth, collision-free …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 1–11 Read article
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Development and Mechanical Characterization of Hybrid Natural Fiber-Reinforced Polymer Matrix Composites for Structural Applications
Abstract: The growing demand for sustainable, lightweight, and cost-effective materials in engineering has driven significant interest in natural fiber-reinforced polymer composites (NFRPCs). Among various options, hybrid composites combining two or more natural fibers offer a balanced improvement in mechanical properties while maintaining environmental benefits. This study investigates the fabrication and mechanical performance of jute–hemp fiber-reinforced epoxy composites. Specimens were prepared using the hand lay-up technique followed by compression molding to ensure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1181–1189 Read article
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Downshifting Strategy Using Gear Skipping During Normal Braking in Electric Vehicles Equipped with AMT
Abstract: In this paper, the regenerative braking method using optimal downshifting is investigated to increase the recovering energy during normal braking in an electric vehicle equipped with Automatic Manual Transmission (AMT). First, the modeling of the electric vehicle powertrain and consideration of brake force distribution was carried out. Based on these, the method to select general downshifting points was mentioned in the electric vehicle. Second, the effect of power interruption on …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 8–19 Read article
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Fire Accidents and Mitigation Framework of Electric Vehicles in India
Abstract: Over the past decade, electric vehicles (EVs) have profoundly reshaped the global automotive industry, primarily due to significant advancements in lithium-ion (Li-ion) battery technology. However, the safety implications associated with high-energy Li-ion batteries, particularly the risk of fire, have emerged as a significant concern for EVs. This article focuses on recent developments in EV fire safety, particularly concerning thermal runaway and battery fires in Li-ion batteries. Instances of extreme misuse, …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 25–30 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Bharat Charge Alliance: key to India’s Electric Vehicle Transition
Abstract: The Bharat Charge Alliance (BCA) is an inclusive platform dedicated to creating a safer and more interconnected environment for India's Light Electric Vehicle (EV) industry. The BCA's main goal is to create a reliable and interoperable charging network throughout India, involving essential stakeholders like electric vehicle (EV) manufacturers, charging station and component producers, battery and energy suppliers, and charge point operators. This initiative, spearheaded by Kapil Shelke, Founder & CEO …
Published in Journal of Automobile Engineering and Applications · Vol. 11, Issue 3, 2024 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 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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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article