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Smart Computing and Application (ICSCA), International Conference on

作者： Fahdah M. Al-Tbenawey Shoayee Alotaibi Marwa Salem Shamaila Mir Zahida Mir Department of Computer Science and Information Computer Science and Engineering College University of Ha'il Hail Saudi Arabia Department of Electrical Communication and Electronics Systems Engineering Faculty of Engineering Modern Science and Arts University (MSA) Cairo Egypt

This paper aims to determine the better technique for kidney stone detection between K-Nearest Neighbor (KNN) and Convolutional Neural Networks (CNNs). As well known, the presence of kidney stones is an important topic that deserves discussion regarding expected medical outcomes. Most of the detection measures comprise CT scans, ultrasounds, and abdominal X-rays. These measures have varying effectiveness levels, hence used in the detection to prepare patients for specific treatment options. Patients' treatment options comprise percutaneous nephrolithotomy (PCNL), extracorporeal shockwave lithotripsy (ESWL), and ureteroscopy. The different detection techniques carried out for the patients are essential to test whether the patient has small or large kidney stones. One essential technique is using conventional neural networks (CNNs) technology. In this paper kidney, stone detection will be carried out using both of K-Nearest Neighbor (KNN) and CNN's techniques. A comparison between both techniques will be carried out to figure out the better. All of the simulations are carried out using MATLAB.

关键词： Support vector machines Image segmentation Ultrasonic imaging Ultrasonic variables measurement Particle separators Neural networks X-rays

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Existence Theorem for Deterministic Optimal control Problems

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Matematica 2023年第3期2卷 659-667页

作者： Kokomo, Eric Mveh-Abia, Chantal Emvudu, Yves Andjiga, Nicolas Gabriel Department of Mathematics and Computer Science Faculty of Science University of Douala Douala Cameroon National Advanced School of Engineering (Polytechnic) University of Yaoundé I Yaoundé Cameroon Laboratory of Mathematics and Fundamental Applications Department of Mathematics Faculty of Science University of Yaounde I Yaoundé Cameroon Department of Mathematics University of Yaoundé I École Normale Supérieure Yaoundé BP 47 Cameroon

In this paper, we give a general formulation of a deterministic Optimal control Problem (OCP) and we transform it in an optimization problem of the form (Formula presented.) where S is a nonempty subset of a Banach space and J a continuous functional defined on S. It is well known according to the Weierstrass theorem that the optimization problem (see above equation) has a solution when S is a compact set and J is a continuous function. Given that the considered set S in our problem of study is non-compact, we consider a weakly* version of the Weierstrass theorem by showing that S is sequentially weakly* compact and J is sequentially weakly* lower semicontinuous. This allows us to obtain a useful existence theorem which gives sufficient conditions for the existence of a solution to an OCP with a general continuous functional J. A sufficient condition on J is also given for the uniqueness of the solution. The obtained result is expanded to optimal control of PDEs with boundary and initial conditions via semigroup theory. © The Author(s), under exclusive licence to Springer science+Business Media LLC, part of Springer Nature 2023.

关键词： Optimal control problem Sequentially weakly* compact Sequentially weakly* continuity Sequentially weakly* lower semicontinuity Weakly* topology

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Dissipative Avoidance Feedback for Reactive Navigation Under Second-Order Dynamics

arXiv

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arXiv 2024年

作者： Smaili, Lyes Tang, Zhiqi Berkane, Soulaimane Hamel, Tarek Department of Computer Science and Engineering University of Quebec in Outaouais GatineauQC Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden Department of Electrical Engineering Lakehead University ON Canada France

This paper addresses the problem of autonomous robot navigation in unknown, obstacle-filled environments with second-order dynamics by proposing a Dissipative Avoidance Feedback (DAF). Compared to the Artificial Potential Field (APF), which primarily uses repulsive forces based on position, DAF employs a dissipative feedback mechanism that accounts for both position and velocity, contributing to smoother and more natural obstacle avoidance. The proposed continuously differentiable controller solves the motion-to-goal problem while guaranteeing collision-free navigation by using the robot’s state and local obstacle distance information. We show that the controller guarantees safe navigation in generic n-dimensional environments and that all undesired ω-limit points are unstable under certain controlled curvature conditions. Designed for real-time implementation, DAF requires only locally measured data from limited-range sensors (e.g., LiDAR, depth cameras), making it particularly effective for robots navigating unknown workspaces. Simulations in 2D and 3D environments are conducted to validate the theoretical results and to showcase the effectiveness of our approach. © 2024, CC BY.

关键词： Feedback

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Optimized control of IoT-Monitored Microgrid systems Using Genetic Algorithm

Optimized Control of IoT-Monitored Microgrid Systems Using G...

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2023 International Conference on Power Energy, Environment and Intelligent control, PEEIC 2023

作者： Vijayalakshmi, N. Yuvaraj, S. Baskar, V. Vijaya Krishnaswamy, R. Sasikala, K. Srinivasan, C. Government Polytechnic College Deputed from Annamalai University Department of Electrical and Electronics Engineering Tamilnadu Coimbatore India Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India University College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Ariyalur India Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350357769

Microgrid (MG) systems have become a good way to make power generation and distribution more efficient, especially when Distributed Energy Resources (DERs) are introduced. The inverter is a critical part of MGs since it regulates the voltage output to the grid. A unique method is proposed to tune the settings of a Proportional-Integral-Derivative (PID) controller for the inverter using Genetic Algorithm (GA). The main aim is to use GAs to improve the inverter control in an MG that is monitored by the Internet of Things (IoT). GA's are very useful for resolving difficult optimization issues. Optimization of voltage regulation, stability, and power transmission to the grid may be achieved by using GA-based tuning of PID controller settings. From the simulation results, the GA-based methodology provides better control performance than conventional tuning approaches, providing exact voltage regulation and improving the MG's stability and dependability. © 2023 IEEE.

关键词： Genetic algorithm and Optimization technique Microgrid Renewable energy Voltage control

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NARXNN Modeling of Ultrafiltration Process for Drinking Water Treatment 22nd

NARXNN Modeling of Ultrafiltration Process for Drinking Wate...

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22nd Asia Simulation Conference, AsiaSim 2023

作者： Razali, Mashitah Che Wahab, Norhaliza Abdul Sunar, Noorhazirah Shamsudin, Nur Hazahsha Gaya, Muhammad Sani Zainal, Azavitra Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Melaka Durian Tunggal Malaysia Department of Electrical Engineering Kano University of Science and Technology Wudil Nigeria Instrumentation and Control Engineering Section Malaysian Institute of Industrial Technology Universiti Kuala Lumpur Johor Johor Bahru Malaysia

ISBN: (纸本)9789819972395

Ultrafiltration (UF) process has gained attention over times, particularly in treating drinking water treatment. A major challenge in achieving high quality of drinking water in UF process is membrane fouling. Membrane fouling has great effects on the performance of filtration process. To overcome fouling accurately, a prediction model is necessary. With prediction model, membrane fouling can be handled in a right way, so that, efficiency of filtration process can be maximize. This paper presents a study on modeling based on non-linear autoregressive with exogenous input neural network (NARXNN) of UF pilot plant specifically from treating drinking surface water. The NARXNN was used to model the permeate flux and transmembrane pressure (TMP). In this work, LM training algorithm was employed. The performance of the model was measured based on mean square error (MSE), root mean square error (RMSE) and correlation of coefficient (R). The simulation results demonstrate that proposed NARXNN modeling able to give high prediction rate with R value of 0.91743. It shows, the prediction values agree well with the actual values. With this model, membrane fouling can be successfully simulated and monitor accordingly. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Membrane fouling

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State Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power systems 2024年第4期40卷 3057-3073页

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-State Estimation (IES-SE) and more established Electric Power System-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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Improving Robot Safety and Efficiency: Integrating Reachability-Based Trajectory Design with Nonlinear Model Predictive control

SSRN

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SSRN 2024年

作者： Shafikhah, Mahmood Razminia, Abolhassan Department of Electrical Engineering Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Process Control Laboratory Faculty of Natural Sciences and Engineering Åbo Akademi University Turku Finland

In today's high-tech world, robots are increasingly used in industry and human assistance, raising safety concerns. This paper proposes a Reachability-based Trajectory Design (RTD) method to ensure safe robot motion. By computing the robot's Forward Reachable Set (FRS), a safe trajectory is chosen for the robot to follow. This approach enhances robot safety and reliability, making them more applicable across industries. Offline RTD and FRS calculations combined with Nonlinear Model Predictive control (NMPC) further improve navigation, motion planning, and control precision. This unique combination significantly improves robot operations, ensuring safety and efficiency. © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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Frequency Domain Auto-tuning of Structured LPV controllers for High-Precision Motion control

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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IEEE Conference on Decision and control

作者： Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory HUNREN Institute for Computer Science and Control Hungary

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

关键词： Technological innovation Sensitivity Frequency-domain analysis Stability criteria Prototypes Throughput Frequency response Motion control Optimization MIMO communication

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Brain-inspired artificial intelligence research: A review

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science China(Technological sciences) 2024年第8期67卷 2282-2296页

作者： WANG GuoYin BAO HuaNan LIU Qun ZHOU TianGang WU Si HUANG TieJun YU ZhaoFei LU CeWu GONG YiHong ZHANG ZhaoXiang HE Sheng Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer and Information Science Chongqing Normal UniversityChongqing 401331China State Key Laboratory of Brain and Cognitive Science Institute of BiophysicsChinese Academy of SciencesBeijing 100101China School of Psychological and Cognitive Sciences Peking UniversityBeijing 100871China State Key Laboratory of Multimedia Information Processing School of Computer SciencePeking UniversityBeijing 100871China Department of Computer Science School of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Faculty of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China The Center for Research on Intelligent Perception and Computing Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Biophysics Chinese Academy of SciencesBeijing 100101China

Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.

关键词： artificial intelligence cognitive science brain science intelligence science large language model

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Blending Synthesized Strategies with Proven Practices for Achieving Business Success 6th

Blending Synthesized Strategies with Proven Practices for Ac...

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6th International Conference on Information systems and Management science, ISMS 2023

作者： Parikh, Swapnil Pandeya, Megha Das, Bidyut Bikash haroon, Syed Department of Computer Science and Engineering Faculty of Engineering and Technology Parul Institute of Technology Parul University Gujarat Vadodara India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Commerce and Management Assam Down Town University Assam Guwahati India Karnataka Bangalore India

ISBN: (纸本)9783031664090

In today’s fast-paced, highly competitive business environment, it takes a well-planned combination of cutting-edge synthesized concepts and time-tested methods to succeed. In this research, we present an all-encompassing approach that balances these factors for peak efficiency. The suggested strategy integrates data-driven insights, a culture of continual learning, and a symmetrical focus on innovation and tradition. Innovation Incubators, Strategic Alliances, Agile Project Teams, Continuous Learning Culture, Data-Driven Decision Making, and a Customer-Centric Approach are some of the conventional techniques we contrast with this one. Our suggested technique is shown to be more efficient than the established methods by a wide margin in this comparison. We demonstrate our method’s advantage by graphically depicting the efficacy of competing strategies. In conclusion, the approach we suggest offers businesses a flexible, data-driven foundation for success in a dynamic market. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： and the capacity to adapt to new situations are all essential to the success of any business Strategy synthesized strategy

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