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368 articles for “Adaptation processes”
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Organic Solar Cell: It’s future prospect
Abstract: Organic solar cells (OSCs) are emerging as a promising frontier in renewable energy technology, distinguished by their lightweight, flexible composition, cost-effective manufacturing processes, and potential for large-scale deployment. Unlike their silicon-based counterparts, which rely on inorganic materials, OSCs harness organic molecules or polymers to convert sunlight into electricity. Their adaptability in design and production is a key strength, facilitated by the ease with which organic materials can be synthesized and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 11, Issue 1, 2024 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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Implement Explainable Machine Learning to Improve Conductivity in Polymer-CNT Nanocomposites: Supporting Adaptive, Flexible, and Long-Lasting IoT Wrap-Around Electronics Applications
Abstract: The rapid growth of Internet of Things (IoT) technologies requires electronic components that are adaptable, lightweight, and durable, and that can continue to function well in diverse contexts and circumstances. Polymer–carbon nanotube (CNT) nanocomposites have become interesting choices for these kinds of uses because they are more flexible, conduct electricity better, and can be made to fit specific needs. However, improving conductivity in these heterogeneous systems remains a major challenge …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 238–254 Read article
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Study of Finite State Machines as Language Recognizer
Abstract: Finite State Machines (FSMs) play a fundamental role in computer science and linguistics as language recognizers. This study presents an exploration of the principles and applications of FSMs as efficient tools for recognizing formal languages. The study delves into the theoretical foundations of FSMs and their practical implementation in various language recognition tasks. The fundamental ideas of FSMs, including as states, transitions, and input symbols, are introduced in this study. …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 18–24 Read article
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IoT-enhanced Real-time Monitoring and Hazard Detection
Abstract: This research explores the innovative application of internet of things (IoT) technology within occupational health and safety management systems (OHSMS) to substantially improve real-time monitoring and hazard detection in industrial settings. IoT sensors and wearable devices are deployed to enable continuous and thorough collection of data on environmental conditions, equipment status, and worker health. Real-time data analysis facilitated by IoT technology allows for the rapid identification and mitigation of potential …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 20–24 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Personalized Virtual Interior Design Using Generative AI
Abstract: This study presents an AI-driven virtual interior design system that allows users to effectively redesign their home or workspace with an integrated shopping experience. The system tailors designs according to room type, style, and purpose, ensuring that the created layouts are aesthetically pleasing, well-organized, and functional. In contrast to conventional interior design, which involves professional skill, hand labor, and much time consumption, this AI-based method uses technology to automate fundamental …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 07–12 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
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Use of the Computer Statistics in Oncology
Abstract: Currently, the use of computer statistics and computer statistical modeling in oncology for obtaining an accurate diagnosis, determination of the choice of treatment method and its correction in the process of ongoing treatment, prediction of the outcome of the disease, and evaluation of the effectiveness of the chosen treatment tactics is a decisive factor. The use of computer statistics, based on an adapted scientific and statistical package of the SSP …
Published in Research & Reviews : Journal of Statistics Read article
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Artificial Intelligence Techniques for Image Dehazing: A Review
Abstract: This review explores the application of artificial intelligence (AI) techniques for image dehazing, addressing the pervasive challenge of enhancing image quality in hazy or foggy conditions. Traditional dehazing methods and their role as a foundation for AI-based approaches are discussed. Deep learning-based methods, including single-image and multi-image dehazing, are examined, highlighting their strengths and limitations. Data-driven approaches, leveraging large-scale datasets and domain adaptation, are also investigated. Furthermore, the review outlines …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 26–30 Read article
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Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Maintain Attendance Using Image Processing Technique
Abstract: Attendance tracking stands as a pivotal pillar in organizational management, bearing significant implications for operational efficiency, resource allocation, and fostering accountability. Traditional methodologies for attendance maintenance frequently exhibit deficiencies in terms of precision, security, and scalability, thus necessitating the exploration of avant-garde solutions. This research endeavors to introduce a pioneering approach to attendance upkeep, harnessing the prowess of image processing techniques synergized with artificial intelligence (AI) algorithms to surmount prevailing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 29–34 Read article
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A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device
Abstract: Precise and rapid mixing of chemical and biological reagents is a critical yet challenging aspect of microfluidic systems, often limited by laminar flow conditions and the need for manual or pre- programmed interventions. Existing mixing strategies frequently lack real-time adaptability and closed-loop control, hindering reproducibility and the execution of complex reaction protocols. This work presents an innovative automatic feedback control system utilizing the study on real- time image processing to …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 32–41 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Design And Optimization Of High-Speed Array Multiplier
Abstract: An array multiplier is a digital circuit used for the rapid multiplication of binary numbers. It employs an array of logic gates to generate partial products concurrently, significantly enhancing speed. The array structure divides the multiplication task into smaller, parallel processes, allowing for efficient parallel processing of multiple bits. Each cell within the array manages specific bit-level multiplications, and their results are summed to produce the final product. This parallel …
Published in Journal of Microelectronics and Solid State Devices · Vol. 11, Issue 3, 2024 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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Rubber Materials: Synthesis, Key Properties, and Cutting-Edge Applications
Abstract: Because of its special blend of flexibility, durability, and ability to adapt, rubber and rubber products have long been essential to many different sectors. The synthesis processes used to produce rubber are discussed in this overview, with a focus on developments in polymer chemistry and processing approaches that improve material qualities. Important characteristics, including tensile strength, resilience, and chemical resistance are brought out, highlighting their significance in a variety of …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 12–23 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article