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68 articles for “High-performance machining”
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Differential Gene Expression Analysis of Human Atrial Fibroblasts Reveals Dysregulation of RNA Metabolism and Translational Machinery in Atrial Fibrillation
Abstract: Atrial fibrillation (AF) is a complex cardiac arrhythmia characterized by extensive structural remodeling and the activation of atrial fibroblasts, which drive the progression of fibrosis. To identify the underlying transcriptomic alterations, we analyzed six human atrial fibroblast RNA-Seq datasets (three control and three AF) retrieved from the Sequence Read Archive. After performing rigorous quality control and adapter trimming, we aligned the reads to the GRCh38 human reference genome using a …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 15–25 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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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Significance of Composite Materials for Making Better Future Society
Abstract: Since in the beginning of human history, Materials had been started in use. We can't imagine our world without materials. In fact, Materials has taken centre position in many developed and developing countries. The materials that humans have chosen to use for engineering projects throughout history, including the Stone, Iron, and Silicon ages. However, in order to meet today's difficulties, new materials must be discovered and developed with the necessary …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 56–62 Read article
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Energy-efficient HVAC System with Decision Tree Classifier and Real-time SMS Notification
Abstract: This research paper explores the design and implementation of an energy-efficient heating, ventilation, and air conditioning (HVAC) system aimed at optimizing energy consumption and enhancing operational efficiency. The system incorporates high-efficiency components, including axial flow fans, motors, and intelligent variable frequency drives, achieving an overall system efficiency of up to 85%. By utilizing both static and dynamic pressures, the HVAC system operates more effectively under varying conditions compared to traditional …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 29–34 Read article
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Evaluating AI-Driven Adaptive Learning Models in Mathematics: A Contemporary Perspective
Abstract: Artificial Intelligence (AI) continues to transform mathematics education through data-driven personalization and adaptive learning technologies. This study investigates how AI-enabled adaptive platforms influence student performance and engagement in mathematics classrooms. Using a quantitative approach across two institutions, pre- and post-assessment results were compared between students using AI-assisted adaptive learning tools and those receiving conventional instruction. The findings reveal that AI-driven learners demonstrated significantly higher gains in conceptual understanding and engagement …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 8–12 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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Comprehensive Review of the Fundamental and Functional Properties of Crystalline Materials
Abstract: Crystalline materials, characterized by their highly ordered atomic arrangements, serve as the backbone of modern engineering and technology. This review provides a detailed examination of their diverse properties, categorized into mechanical, thermal, electrical, and optical domains. We analyze fundamental mechanical parameters such as the elastic modulus, yield strength, and fracture toughness, alongside functional behaviors like fatigue and creep. The discussion extends to thermal transport and expansion, electrical conductivity and resistivity, …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 20–24 Read article
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The Role of Automation in Modern Healthcare: Innovations and Impact.
Abstract: Automation technology encompasses a broad array of systems and tools designed to perform tasks with minimal human intervention, thereby increasing efficiency, reducing errors, and enhancing productivity. This study explores the core components of automation technology, including sensors, actuators, controllers, and software, and examines their applications across various industries. In manufacturing, automation leads to significant improvements in production speed and precision. In healthcare, it enhances patient care and operational efficiency. In …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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A Study on Leveraging Sensors and AI in Insect-Inspired Robotics for Unstructured Environments: Bio-Inspired Autonomy
Abstract: Insects, with their unparalleled agility, resilience, and highly efficient sensory-motor control in complex, unstructured environments, offer a rich blueprint for the next generation of autonomous robots. This study explores the design, implementation, and potential of insect-inspired robots, focusing on the synergistic integration of miniaturized sensor arrays and advanced Artificial Intelligence (AI) algorithms. We delve into bio-mimetic sensing, drawing inspiration from compound eyes, olfactory systems, and tactile hairs, to equip robots …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 7–21 Read article
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Multifunctional Materials for Electro-Mechanical Applications: Synergistic Integration of Strength and Conductivity
Abstract: The integration of mechanical strength and electrical conductivity within a single material system has emerged as a critical requirement in the development of next-generation multifunctional materials. These materials are increasingly sought after in fields such as aerospace, flexible electronics, energy storage, and structural health monitoring, where the traditional separation of structural and functional materials leads to inefficiencies in weight, space, and overall performance. The convergence of these properties enables compact …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article