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509 articles for “optimization. Algorithm”
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Path and Trajectory Planning of Unmanned Ground Vehicles with Vehicle Dynamic Characters
Abstract: Given partial knowledge about its environment (obstacle, road…) and goal position, optimal path and trajectory planning is a key problem for the control of unmanned vehicles. In path planning problem, it is very important to consider the dynamic limits of the vehicle with optimization function. The path planning was implemented by applying optimization methods based on the given obstacle information(virtual or measured by sensor system) and numerical map without considering …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 7–14 Read article
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Smart Dustbin for Household Using Internet of Things (IoT)
Abstract: This article, titled “Smart Dustbin for Household Using Internet of Things (IoT)”, introduces an innovative solution to manage household waste effectively. In today's fast-paced world, many individuals find it challenging to dispose of garbage regularly due to busy schedules. This IoT-based system aims to address this issue by employing sensors and connectivity to monitor the fill-level of dustbins in real time. By utilizing ultrasonic sensors and microcontrollers like the ESP32, …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 2, 2024 · pp. 38–48 Read article
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Optimization of Automatic Energy Management System Using Renewable Resources
Abstract: With the increasing demand for energy efficiency and sustainability, smart home energy management systems (SHEMS) have emerged as promising solutions to optimize residential energy consumption. This paper presents a comprehensive review of SHEMS technologies, focusing on their design, implementation, and impact. SHEMS integrates advanced sensors, real-time data analytics, and intelligent algorithms to monitor, control, and optimize energy usage within the home environment. By leveraging machine learning and predictive modelling techniques, …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Comparing Graphical and Algebraic Methods in Solving Linear Programming Problems
Abstract: Linear Programming (LP) is a fundamental optimization technique widely employed across engineering, manufacturing, transportation, finance, healthcare, and other industrial sectors to support effective resource allocation and informed decision- making. Among the various solution techniques, the graphical and algebraic methods remain the two most fundamental approaches, each offering distinct advantages depending on the complexity and dimensionality of the optimization problem. This paper presents a comprehensive comparative study of these methods by …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 33–43 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Exploring Artificial Intelligence in Operating Systems for Consumer Enhanced Experience: Knowledge-Based Interfaces for Intelligent User Experience and System Optimization
Abstract: The convergence of knowledge-based systems, machine learning algorithms, and natural language interfaces that provide dynamic and context-sensitive behavior is another foundation for this change. AI-based operating systems are important because they can enhance user experiences via automation, self-optimization, and customization. AI signifies a new era of cognitive computing, from adaptive power management for desktops and embedded systems to predictive text and voice recognition on mobile devices. Furthermore, this ability to …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 26–30 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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Intelligent Paradigms in Subsea Connectivity: A Comprehensive Review of Artificial Intelligence in Underwater Communications
Abstract: Underwater wireless communication (UWC) plays a critical role in ocean exploration, environmental monitoring, offshore energy operations, disaster management, and naval defense. However, the underwater environment presents significant communication challenges, including severe signal attenuation, multipath propagation, Doppler effects, limited bandwidth, high latency, and energy constraints. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising solutions to address these limitations and enhance the efficiency, reliability, and adaptability …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Asymptotic Notations: A Review
Abstract: Asymptotic notations play a fundamental role in assessing the efficiency and performance of algorithms, particularly as input sizes grow larger. This paper delves into three key asymptotic notations: Big O, Theta, and Omega, which are essential for understanding the upper, average, and lower bounds of an algorithm’s runtime. Big O notation specifically helps in determining the worst-case scenario of an algorithm’s growth rate, providing an upper bound on time or …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 17–33 Read article
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Hybrid Best-Response Algorithms for Mobile Computing Offloading: A Comprehensive Review
Abstract: The exponential growth of mobile applications with intensive computational requirements has necessitated innovative offloading strategies in mobile computing ecosystems. This comprehensive review examines hybrid best-response offloading algorithms integrated with game-theoretic optimization frameworks to address resource allocation challenges in mobile edge computing (MEC) environments. The proliferation of Internet of Things (IoT) devices and bandwidth-intensive applications has created unprecedented demands on mobile network infrastructure, compelling researchers to develop sophisticated offloading mechanisms that …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 20–26 Read article
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Optimizing Image Processing with Verilog on FPGA: Techniques and Performance Enhancements
Abstract: The integration of image processing algorithms into hardware platforms, particularly FPGAs, presents a compelling opportunity for achieving high performance, low latency, and power efficiency in real-time applications. This study focuses on designing and implementing Verilog HDL-based optimal image processing methods for FPGA-based systems. The study explores the development of core algorithms, including edge detection, image enhancement, and adaptive filtering, to maximize resource utilization and processing speed on hardware platforms. Key …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 3, 2024 · pp. 46–53 Read article
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Image Registration–Implementation and Performance Analysis using Log-polar Transformation
Abstract: This paper presents an image registration algorithm for affine motion recovery. The images which are to be registered may be misaligned due to rotation, scale and translation the algorithm presented in the paper estimates affine transformation parameters to register this images. The parameters are computed using a variation of the Levenberg-Marquadt nonlinear least squares optimization method in a coarse-to-fine hierarchical framework. To precisely registers images with subpixel accuracy this method …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 49–55 Read article
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Artificial Intelligence in Smart Dairy Farming (SDF)
Abstract: Due to increasing demand for quality of milk in dairy farming also for the sustainability, productivity and maintenance of good health of animals. various challenges are faced by dairy farmers and can be addressed using Artificial Intelligence technologies ,By using AI here the individual health ,behavior ,feed management robotic milking and stress free milking system will be implemented .AI technologic implementation will frame the Smart dairy farming in properly and …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 16–20 Read article
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Mitigation of Peak to Average Power Ratio in Orthogonal Frequency Division Multiplexing through SOP-PTS
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is a popular multicarrier modulation technology extensively employed in 4G wireless communication systems to transmit data over a dispersive channel. To address the Peak-to-Average Power Ratio (PAPR) issue in OFDM, a technique called Partial Transmit Sequence (PTS) is commonly utilized. The PTS method involves dividing the data block into non-overlapping sub-blocks and then combining them using phase factors to mitigate PAPR. However, the conventional PTS …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 32–39 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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The Role of AI in Modern Circuit Design and Simulation
Abstract: The integration of artificial intelligence (AI) in circuit design and simulation is revolutionizing the electronics industry by enabling faster, more efficient, and innovative design processes. This article explores the transformative role of AI in automating tasks traditionally reliant on manual expertise, such as schematic generation, component optimization, and fault detection. It highlights how machine learning algorithms and generative AI tools are improving design accuracy, reducing time-to-market, and enabling cost-effective prototyping. …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 9–14 Read article