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124 articles for “drying optimization”
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A Comprehensive Study of Radial Load Fluctuation on Alloy Wheels for Electric Vehicles
Abstract: Electric Vehicle’s alloy wheels are designed to allow for better heat dissipation. Manufacturers carry out many tests of a wheel to be sure, that the wheel will fit for safety reason as also their comfortability level is even bigger. Therefore, a specific design was selected for which the simulations of alloy wheel were performed under real loading conditions. The main objective of this research is to analyze the effects of …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 47–56 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Design and Development of Pipe Bending Machine
Abstract: The design and development of a pipe bending machine are crucial for various industrial applications, including the construction, automotive, and manufacturing sectors. Bending is a fundamental metalworking process that involves deforming pipes, tubes, square hollows, and rods without compromising their structural integrity. This study focuses on designing a cost-effective and efficient pipe bending machine that can accommodate different pipe sizes and materials. The key design considerations include selecting an appropriate …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 22–30 Read article
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Pneumatic Operated Engine
Abstract: The increasing awareness of fossil fuel depletion & environmental pollution has accelerated the need for the development of sustainable & eco-friendly alternatives to traditional internal combustion engines. Pneumatically operated engines have been identified as a potential alternative for small-scale mechanical power generation owing to their advantages of zero exhaust emissions, noise reduction & operational safety. This paper describes the design, development & performance analysis of a pneumatically operated engine, which …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Thermodynamic Optimization and Exergy-Based Performance Analysis of Hybrid Thermal Management Systems for Electric Vehicles
Abstract: The transition toward sustainable transportation has brought electric vehicles (EVs) to the forefront of modern engineering innovation. Despite their environmental benefits and improved energy efficiency, EVs face major thermal challenges that affect performance, safety, and durability. Efficient thermal management of batteries, power electronics, and electric drive systems is vital to ensure reliability under diverse operating conditions. This study presents a detailed thermodynamic optimization and exergy-based performance analysis of hybrid thermal …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Smart Solar Garage with PSO-Based Optimization for Energy and Vehicle Performance
Abstract: The swift growth of electric mobility, coupled with a rising global focus on sustainable energy, has propelled the advancement of smart garages that incorporate renewable energy, the Internet of Things (IoT), and sophisticated optimization methods. These systems aim to reduce energy waste, boost operational efficiency, and aid in the development of smart, eco-friendly urban infrastructure. This paper outlines the design and execution of a Smart Solar Garage that utilizes Particle …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 6–18 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 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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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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The Evolution of Student Monitoring Systems in School Buses: A Detailed Review
Abstract: In modern educational institutions, ensuring the safety and well-being of students during transportation is paramount. To address this, we propose a comprehensive Student Monitoring System for buses, designed to enhance safety, efficiency, and communication between stakeholders. The system utilizes advanced technologies such as GPS tracking, RFID tags, and real-time data processing to monitor students' location, track bus routes, and provide instant notifications to parents and school administrators. By integrating these …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 1–6 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments
Abstract: The present investigation focuses on evaluating the performance of turning operations in alloy steel with particular emphasis on the effect of cutting parameters on surface roughness. In the machining of alloy steel, tool life and surface integrity are significantly influenced by parameters such as spindle speed, depth of cut, and feed rate. Among these, feed rate has been observed to exert the most prominent effect on surface roughness. To systematically …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Re-imaging Education Policy of a Framework Based on Indian Knowledge Systems
Abstract: Digital transformation revolutionized education; it enhances teaching and learning, improves administrative tasks, and empowers students and educators. Digital transformation in education and its importance in shaping the future. Integration of technology in classrooms enables interactive and immersive learning. Digital tools offer dynamic learning experiences, enhancing student engagement. This leads to improved comprehension and knowledge retention. Personalized learning experiences are facilitated by digital transformation. Digital transformation creates vast resources and online …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 42–63 Read article
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A Constraint-Driven Generative Design Methodology for Modular Actuated Robotic Components in Decentralized Manufacturing
Abstract: This work formalizes a constraint-driven generative design framework for actuator-integrated robotic components intended for decentralized additive manufacturing. Conventional topology optimization typically prioritizes structural efficiency while treating actuator integration, modular interfaces, and fabrication constraints as secondary considerations. In contrast, the proposed methodology encodes these requirements as first-order geometric and mechanical constraints prior to automated material redistribution. The framework defines preserved actuator geometry, bounded design envelopes, representative loading abstractions, and manufacturability-aware domains …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 Read article
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Optimal Dosage of Pumice in Lightweight Aggregate based Concrete
Abstract: Lightweight concrete (LWC) is a pioneering solution in the construction sector, characterized by its unique composition and versatile applications. Engineered with lightweight aggregates and additives, LWC achieves a significant reduction in dry density compared to conventional concrete, making it 23% to 87% lighter, with densities ranging from 300 to 1,840 kg/m³. This reduced weight makes LWC ideal for projects requiring load minimization, such as high-rise buildings and prefabricated elements. A …
Published in International Journal of Minerals · Vol. 1, Issue 1, 2024 · pp. 23–32 Read article