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9th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2023

作者： Abood, Layla H. Mohamed, Mohamed J. University of Technology Department of Control and System Engineering Baghdad Iraq

ISBN: (纸本)9798350343380

The widespread of Electric vehicle (EV) is increasing fastly because of many reasons like environment safety issue, best performance and its suitable cost for customers and due to these reasons researchers give an importance for using it as a sustainable safety system. Controlling EV speed is an essential issue and need robust and intelligent controllers to maintain this matter, In this study, a robust Fractional Order Tilt (FOTID) controller is used to adjust and maintain the driver speed and tracking the desired speed using a novel Whale Optimization Algorithm(WOA).The Matlab program is used for simulation with a fixed desired speed and with changing desired speed. The numerical analysis indicated an efficient response for the suggested controller in contrast with other classical types (PID controller & FOPID controller) in its stability and performance depending on transient analysis. © 2023 IEEE.

关键词： Controllers

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Loss Balancing for Physics-Informed Neural Networks Considering Procedure for Solving Partial Differential Equations 13

Loss Balancing for Physics-Informed Neural Networks Consider...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Kojima, Manabu Otsuki, Kazuma Suzuki, Masato Abe, Masajiro Baba, Masaaki Yokota, Kazuya Master's Program in Mechanical Engineering Nagaoka University of Technology Nagaoka Japan Nagaoka University of Technology Department of System Safety Engineering Nagaoka Japan Nagaoka University of Technology Department of Mechanical Engineering Nagaoka Japan

ISBN: (纸本)9798350373332

With the development of machine learning, numerical analysis using neural networks has been devised. Remarkably, physics-informed neural networks (PINNs) enable physically consistent numerical analysis by introducing a loss function that conforms to relevant governing equations. Moreover, research is rapidly advancing for the application of PINNs to inverse analysis in areas such as physical property identification. For a PINN to learn governing equations, the weights of the loss functions should be properly determined because they have different roles in components such as boundary conditions, initial conditions, and governing equations. However, weight setting is generally challenging. We propose a loss balancing method considering the procedure for solving partial differential equations. The proposed method is validated through comparisons with conventional solvers. © 2024 IEEE.

关键词： Partial differential equations

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Background Subtraction-based Unlearned Hazardous Object Detection Algorithm for Ceiling Environments

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Journal of Institute of Control, Robotics and systems 2025年第4期31卷 334-342页

作者： Jeon, Jae Woo Kim, Sung Jae Suh, Jin Ho Department of Intelligent Robot Engineering Pukyong National University Korea Republic of The Industrial Science Technology Research Center Pukyong National University Korea Republic of Major of Mechanical System Engineering Pukyong National University Korea Republic of

We propose a background subtraction-based algorithm that uses images from an RGB-D camera to detect unlearned hazardous objects in ceiling environments, thereby facilitating efficient ceiling exploration. We constructed a dataset by compiling various images of ceiling structures and employed the YOLOv8s-seg model to recognize ceiling components. Recognized ceiling structures and regions exceeding a specified depth threshold were designated as background and removed in the first stage. A U-map based on depth information was then used to detect object regions, which enabled the identification of various types of potentially hazardous objects. The positions of the detected objects were continuously updated using a Kalman filter based tracking model, and their relative positions were visually displayed on a 2D map. To validate the performance of the algorithm, we implemented it in a system and conducted hazardous object detection experiments in a ceiling-simulated testbed and an actual ceiling environment. The findings confirmed the applicability of the algorithm in real-world settings. © ICROS 2025.

关键词： Kalman filters

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STUDY ON UTILIZATION OF POINT CLOUD DATA FOR PILE CENTER POSITION MEASUREMENT IN PILE CONSTRUCTION

Journal of Structural and Construction Engineering

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Journal of Structural and Construction engineering 2023年第805期88卷 347-355页

作者： Ikeda, Yuichi Yabuki, Nobuyoshi Construction System and Material Department Technology Research Institute Obayashi Corporation Japan Division of Sustainable Energy and Environmental Engineering Graduate School of Engineering Osaka Univ Japan

During the building construction, contractors are required to measure the completed form and calculate the quantity and are increasingly employing point cloud data for this purpose. Using point cloud data is expected to perform higher productivity than the conventional manual measurement and taking pictures. This paper proposes a new pile center measurement method using point cloud data obtained by Structure from Motion (SfM) and Building Information Modeling (BIM). The efficiency, cost, and accuracy of the proposed approach were investigated compared to the conventional surveying method. © 2023 Architectural Institute of Japan. All rights reserved.

关键词： Piles

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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Automatic Transportation Mode Classification Using a Deep Reinforcement Learning Approach With Smartphone Sensors

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IEEE Access 2024年 12卷 514-533页

作者： Taherinavid, Siavash Moravvej, Seyed Vahid Chen, Yen-Lin Yang, Jing Ku, Chin Soon Yee, Por Lip Iran University of Science and Technology School of Civil Engineering Tehran13114-16846 Iran Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research is motivated by the pressing demand to enhance transportation mode classification, leveraging the potential of smartphone sensors, notably the accelerometer, magnetometer, and gyroscope. In response to this challenge, we present a novel automated classification model rooted in deep reinforcement learning. Our model stands out for its innovative approach of harnessing enhanced features through artificial neural networks (ANNs) and visualizing the classification task as a structured series of decision-making events. Our model adopts an improved differential evolution (DE) algorithm for initializing weights, coupled with a specialized agent-environment relationship. Every correct classification earns the agent a reward, with additional emphasis on the accurate categorization of less frequent modes through a distinct reward strategy. The Upper Confidence Bound (UCB) technique is used for action selection, promoting deep-seated knowledge, and minimizing reliance on chance. A notable innovation in our work is the introduction of a cluster-centric mutation operation within the DE algorithm. This operation strategically identifies optimal clusters in the current DE population and forges potential solutions using a pioneering update mechanism. When assessed on the extensive HTC dataset, which includes 8311 hours of data gathered from 224 participants over two years. Noteworthy results spotlight an accuracy of 0.88±0.03 and an F-measure of 0.87±0.02, underscoring the efficacy of our approach for large-scale transportation mode classification tasks. This work introduces an innovative strategy in the realm of transportation mode classification, emphasizing both precision and reliability, addressing the pressing need for enhanced classification mechanisms in an eve

关键词： Smartphones

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Impact of Fast Frequency Response on Renewable Energy Source Curtailment and Load Shedding

Impact of Fast Frequency Response on Renewable Energy Source...

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CIRED 2024 Vienna Workshop

作者： Panagi, Savvas Lazari, Antonis Koutsoloukas, Vrahimis Aristidou, Petros Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Transmission System Operator of Cyprus Cyprus

ISBN: (纸本)9781837242672

system operators in low-inertia power systems often have to curtail renewable energy sources (RES) and employ strict under-frequency load shedding (UFLS) schemes to ensure frequency security after an event leading to loss of generation. This approach limits the maximum RES penetration in a system and results to the loss of load. To tackle these problems, fast frequency response (FFR) schemes can be used to limit the frequency Nadir after a disturbance and decrease the need for RES curtailments and UFLS. This article provides insights on the interaction between the Kinetic Energy (KE), Frequency Containment Reserves (FCR), and Nadir after a disturbance, which are the driving mechanisms leading to RES curtailment. Then, it analyses the impact of FFR on the Nadir and its ability to alleviate RES curtailment problems. The low-inertia, islanded, Cyprus dynamic model is used to quantify the results and showcase the impact on a real system. © The Institution of engineering & technology 2024.

关键词： Electric load shedding

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Reliability of Quasi-vertical GaN on Silicon Schottky Barrier Diodes With SiO Passivation Layer Under On-State Stress Bias

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IEEE Transactions on Electron Devices 2024年第9期71卷 5296-5304页

作者： Lin, Ya-Xun Chao, Der-Sheng Liang, Jenq-Horng Shen, Yao-Luen Huang, Chih-Fang Hall, Steve Mitrovic, Ivona Z. University of Liverpool Department of Electrical Engineering and Electronics LiverpoolL69 3GJ United Kingdom National Tsing Hua University Department of Engineering and System Science Hsinchu300 Taiwan National Tsing Hua University Nuclear Science and Technology Development Center Hsinchu300 Taiwan National Tsing Hua University Department of Engineering and System Science Institute of Nuclear Engineering and Science Hsinchu300 Taiwan Institute of Electronics Engineering National Tsing Hua University Hsinchu300 Taiwan

On-state stress induced device degradation of gallium nitride quasivertical Schottky barrier diode (SBD) with SiO2 passivation layer was investigated in this article. The devices were stressed at room temperature by biasing them separately at three distinct voltages for 500 s. The longer-term degradation was seen to be dominated predominantly by electron trapping in the oxide passivation layer. Less-severe degradation was observed in passivated devices in comparison with control devices without SiO2 passivation. The control devices were found to exhibit degradation due to the influence of bulk traps near to the metal/GaN interface. Moreover, the anode was held at zero voltage for 500 s to analyse the electron de-trapping mechanism during the recovery phase of SBDs. Current-voltage characteristics of the SBDs were measured to monitor the evolution of forward voltage and barrier height through periodic interruption under stress and recovery. A power-law model and universal recovery function were utilized to evaluate the parameter shifts with respect to time for each phase, respectively. The results demonstrate that border and bulk oxide traps associated with the passivation layer lead to the trapping and de-trapping of electrons. Furthermore, long-time constant bulk oxide traps are thought to be the contributing factor in the partial recovery, indicating that few electrons emit from these traps in the short-term recovery phase. © 1963-2012 IEEE.

关键词： III-V semiconductors

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Mobile Robot Using Unbalanced Road Adaption Device

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Journal of Institute of Control, Robotics and systems 2024年第1期30卷 20-26页

作者： Lim, Ji-Ho Lee, Sang-Yeob Shin, Dongwon Department of Mechanical System Engineering Kumoh National Institute of Technology Korea Republic of AI Robotics R&D Division Korea Institute of Robotics & Technology Convergence Korea Republic of

This study investigated a mobile robot capable of navigating unbalanced road surfaces solely via its mechanical structure, utilizing an unbalanced road adaptation device. This adaptation device was designed by introducing a height adaptor to the existing suspension mechanism, with each component consisting of links and shock absorbers. With these components, the robot excelled in adapting to unbalanced road surfaces. To validate the performance of the designed robot, a degree-of-freedom analysis was conducted, and the robot’s driving stability was evaluated through driving simulations. © ICROS 2024.

关键词： Mobile robots

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Face image authentication scheme based on MTCNN and SLT

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Multimedia Tools and Applications 2025年 1-43页

作者： Thabit, Rasha Al-Askari, Mohanad A. Mohammed, Dunya Zeki Anaam, Elham Abdulwahab Mahmood, Zainab H. Jabbar, Dina Jamal Salih, Zahraa Aqeel Information System Department College of Computer Sciences and Information Technology University of Al-Anbar Al-Anbar Iraq Computer Engineering Department College of Engineering Al-Iraqia University Baghdad Iraq Electronic and Communications Engineering Department College of Engineering Gilgamesh University Baghdad Iraq Faculty of Computing and Informatics Multimedia University Selangor Cyberjaya Malaysia Department of Cybersecurity Engineering College of Information Engineering Al-Nahrain University Baghdad Iraq Electrical Engineering Technical Collage Middle Technical University Baghdad Iraq Department of Business Administration Alamaal University College Baghdad Iraq

DeepFakes and face image manipulation methods have been widely distributed in the last few years and several techniques have been presented to check the authenticity of the face image and detect manipulation if exists. Most of the available manipulation detection techniques have been successfully applied to reveal one type of manipulation under specific conditions, however, many limitations and challenges can be encountered in this field. To overcome some limitations and challenges, this paper presents a new face image authentication (FIA) scheme based on Multi-Task Cascaded Conventional Neural Networks (MTCNN) and watermarking in Slantlet transform (SLT) domain. The proposed FIA scheme has three main algorithms that are face detection and selection, embedding, and extraction algorithms. Different block sizes have been used to divide the image into non-overlapping blocks followed by classifying them into two groups that are blocks from face area (FA) and blocks from the remaining area (RA) of the image. In the embedding algorithms, the authentication information is generated from FA blocks and embedded in the RA blocks. In the extraction algorithms, the embedded information is extracted from RA blocks and compared with the calculated data from FA blocks to reveal manipulations and localize the manipulated blocks if exist. Extensive experiments have been conducted to evaluate the performance of the proposed FIA scheme for different face images. The experimental work included tests for payload, capacity, visual quality, time complexity, and localization of manipulations. The results proved the efficiency of the proposed scheme in detecting and localizing different face image manipulations such as attributes attacks, retouching attacks, expression swap, face swap, and morphing attacks. The proposed scheme overcomes many limitations and it is 100% accurate in localizing the tampered blocks which makes it a better candidate for practical applications. © The Author(s), un

关键词： Authentication

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