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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Jingcheng Yang Frank Kulwa Xuanwei Liu Yiqing Lu Yufa Fu Guanglin Li Yaping Huai Xin Zhang Yongcheng Li CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Shenzhen Dapeng New District Nanao People’s Hospital Shenzhen China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen China Brain Cognition and Brain-Computer Intelligence Integration Group Kunming University of Science and Technology Kunming China Shandong Zhongke Advanced Technology Co. Ltd. Jinan China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feature extraction is crutial to build a better decoder. In this study the CEBRA method were employed to extract features first based on electroencephalogram(EEG) data during Motor Execution(ME) and Motor lmagery (Ml) tasks for 20 participants (including 10 stroke patients). The results revealed that, in MI tasks, CEBRA-RF (Random Forests) achieved an average classification accuracy of 91.33%, with an average F1-score of 91.19%, and CEBRA-SVM (Support Vector Machine) achieved an average classification accuracy of 91.32%, with an average F1-score of 90.83%. Compared to other conventional feature extraction methods, CEBRA shows significantly higher accuracy (t-test, p<0.01). However, in ME tasks, CEBRA-RF achieved an average classification accuracy of 75.67%, with an average F1-score of 75.39%, and CEBRA-SVM achieved an average classification accuracy of 76.13%, with an average F1-score of 75.80%. Nevertheless, no significant differences were observed compared to other feature extraction methods. These findings demonstrate the potential of CEBRA in decoding patients’ brain activity. The results of this study hold promise in addressing the current challenges of low decoding accuracy in BCI systems, offering a new approach for designing BCI-assisted rehabilitation systems for stroke patients.

关键词： Support vector machines Brain Accuracy Stroke (medical condition) Feature extraction Motors Brain-computer interfaces Neurorehabilitation Decoding Paralysis

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Intellectual control system for unmanned energy crop combine 1

Intellectual control system for unmanned energy crop combine

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1st International Conference on Intellectual systems and Information Technologies, ISIT 2019

作者： Gunchenko, Yurii Shvorov, Sergey Lukin, Volodymyr Mezhuyev, Vitalii Dept. of Mathematical Support of Computer Systems Odessa I.I.Mechnikov National University Odessa Ukraine Dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Gambang Malaysia

The purpose of the work is to develop methodical bases for the construction of an intelligent control system (ISC) for unmanned combines (UMs) of energy crops (EC) for biogas plants (BP). In order to achieve this goal, the functional structure of the ISC was substantiated in the work, the method of recognition and determination of the volume of biomass EC in fields with unmanned aerial vehicles (UAVs) was developed, the method of synthesis of compromise-optimal routes of the BP with the minimum length of their routes in the process of biomass collection was proposed. and taking into account passive (unmoving) and active (moving) obstacles. With the help of the proposed ISC, the following tasks are solved: monitoring of the EC cultivation process and the determination of EC volumes based on the use of UAVs;determination of the density of changes in the yield of EC, the coordinates of active and passive obstacles in the way of the UMs movement;distribution of UMs by fields and planning of optimal routes and speed parameters of their movement for EC collection. A prerequisite for efficient harvesting combine driving is the constant control of the technological process of harvesting energy crops. Deviations from the work plan in most cases occur due to malfunction of technical equipment or adverse weather conditions. However, there are situations in which the deviation of the "plan-fact" is influenced by other factors, which may lead to a failure of the plan, and vice versa. Failure to complete the plan may be due to a reduction in the intensity of the work or the assumption by the user of errors when entering the initial data into the system, which reduces the adequacy of the model to the real process. The increase in planned indicators may be due to an increase in the speed of technological operations, which may lead to additional losses of biomass or a decrease in its quality. To solve the tasks listed, the ISC is divided into a subsystem of monitoring, planning and

关键词： Biomass

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Multi-modal remote sensory learning for multi-objects over autonomous devices

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Frontiers in bioengineering and biotechnology 2025年 13卷 1430222页

作者： Aysha Naseer Naif Almudawi Hanan Aljuaid Abdulwahab Alazeb Yahay AlQahtani Asaad Algarni Ahmad Jalal Hui Liu Department of Computer Science Air University Islamabad Pakistan. Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia. Department of Computer Science College of Computer Science and Information System Najran University Najran Saudi Arabia. Department of Informatics and Computer Systems King Khalid University Abha Saudi Arabia. Department of Computer Sciences Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia. Department of Computer Science and Engineering College of Informatics Korea University Seoul South Korea. Guodian Nanjing Automation Co. Ltd. Nanjing China. Jiangsu Key Laboratory of Intelligent Medical Image Computing School of Future Technology Nanjing University of Information Science and technology Nanjing China. Cognitive Systems Lab University of Bremen Bremen Germany.

Introduction:There has been an increasing focus on object segmentation within remote sensing images in recent years due to advancements in remote sensing technology and the growing significance of these images in both military and civilian realms. In these situations, it is critical to accurately and quickly identify a wide variety of objects. In many computer vision applications, scene recognition in aerial-based remote sensing imagery presents a common issue. Method:However, several challenging elements make this work especially difficult: (i) Different objects have different pixel densities; (ii) objects are not evenly distributed in remote sensing images; (iii) objects can appear differently depending on viewing angle and lighting conditions; and (iv) there are fluctuations in the number of objects, even the same type, in remote sensing images. Using a synergistic combination of Markov Random Field (MRF) for accurate labeling and Alex Net model for robust scene recognition, this work presents a novel method for the identification of remote sensing objects. During the labeling step, the use of MRF guarantees precise spatial contextual modeling, which improves comprehension of intricate interactions between nearby aerial objects. By simultaneously using deep learning model, the incorporation of Alex Net in the following classification phase enhances the model's capacity to identify complex patterns in aerial images and adapt to a variety of object attributes. Results:Experiments show that our method performs better than others in terms of classification accuracy and generalization, indicating its efficacy analysis on benchmark datasets such as UC Merced Land Use and AID. Discussion:Several performance measures were calculated to assess the efficacy of the suggested technique, including accuracy, precision, recall, error, and F1-Score. The assessment findings show a remarkable recognition rate of around 97.90% and 98.90%, on the AID and the UC Merced Land datasets,

关键词： autonomous devices deep learning computer vision likelihood estimation multi-modal multi-objects posterior probability remote sensing scene analysis

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Offsite Evaluation of Localization systems: Criteria, systems, and Results From IPIN 2021 and 2022 Competitions

IEEE Journal on Indoor and Seamless Positioning and Navigati...

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IEEE Journal on Indoor and Seamless Positioning and Navigation 2024年 2卷 92-129页

作者： Potorti, Francesco Crivello, Antonino Lee, Soyeon Vladimirov, Blagovest Park, Sangjoon Chen, Yushi Wang, Long Chen, Runze Zhao, Fang Zhuge, Yue Luo, Haiyong Perez-Navarro, Antoni Jimenez, Antonio R. Wang, Han Liang, Hengyi De Cock, Cedric Plets, David Cui, Yan Xiong, Zhi Li, Xiaodong Ding, Yiming Franco, Fernando Javier Alvarez Polo, Fernando Jesus Aranda Rodriguez, Felipe Parralejo Moreira, Adriano Pendao, Cristiano Silva, Ivo Ortiz, Miguel Zhu, Ni Li, Ziyou Renaudin, Valerie Wei, Dongyan Ji, Xinchun Zhang, Wenchao Wang, Yan Ding, Longyang Kuang, Jian Zhang, Xiaobing Dou, Zhi Yang, Chaoqun Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Coene, Sander Li, Chenglong Venus, Alexander Leitinger, Erik Tertinek, Stefan Witrisal, Klaus Wang, Yi Wang, Shaobo Jin, Beihong Zhang, Fusang Su, Chang Wang, Zhi Li, Siheng Li, Xiaodong Li, Shitao Pan, Mengguan Zheng, Wang Luo, Kai Ma, Ziyao Gao, Yanbiao Chang, Jiaxing Ren, Hailong Guo, Wenfang Torres-Sospedra, Joaquin Pisa56124 Italy Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing100876 China Chinese Academy of Sciences Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Beijing100190 China Universitat Oberta de Catalunya Faculty of Computer Sciences Multimedia and Telecommunication Barcelona08035 Spain Arganda del Rey28500 Spain Huawei Technologies Company Ltd. Shenzhen100015 China IMEC-WAVES/Ghent University Department of Information Technology Gent9052 Belgium Nanjing University of Aeronautics and Astronautics College of Automation Nanjing210016 China University of Extremadura Badajoz06006 Spain University of Trás-os-Montes and Alto Douro Department of Engineering School of Sciences and Technology Vila Real5000-801 Portugal Universidade Do Minho Centro Algoritmi Guimarães4800-058 Portugal Ame Department of the University Gustave Eiffel Geoloc Laboratory Bouguenais44344 France Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Wuhan University Gnss Research Center Wuhan430072 China AutoNavi Software Company Ltd. China Fraunhofer Institute for Integrated Circuits Iis Fraunhofer Iis Nuremberg90411 Germany Erlangen91058 Germany Graz University of Technology Christian Doppler Laboratory for Location-Aware Electronic Systems Graz8010 Austria Institute of Software Chinese Academy of Sciences Beijing100190 China Purple Mountain Laboratories Pervasive Communication Research Center Nanjing210000 China Beijing University of Posts and Telecommunications Beijing100876 China

Indoor positioning is a thriving research area, which is slowly gaining market momentum. Its applications are mostly customized, ad hoc installations;ubiquitous applications analogous to Global Navigation Satellite System for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the indoor positioning and indoor navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site tracks. In contrast with on-site tracks where competitors bring their systems on-site - which were impossible to organize during 2021 and 2022 - in off-site tracks competitors download prerecorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem. © 2023 CCBY.

关键词： Smartphones

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Reference Architecture and Agile Development Method for a Process-Driven Web Platform based on the BPMN-Standard and Process Engines

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Procedia CIRP 2021年 103卷 146-151页

作者： Eike Schäffer Marvin Schobert Tobias Reichenstein Andreas Selmaier Volker Stiehl Markus Herhoffer Matus Mala Jörg Franke Institute for Factory Automation and Production Systems Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 7 Erlangen 91058 Germany Faculty of Computer Science Ingolstadt University of Technology Esplanade 10 85049 Ingolstadt Germany exentra GmbH Löwenstr. 11 85276 Pfaffenhofen an der Ilm Germany Flowable Germany GmbH Schloßstr. 70 70176 Stuttgart Germany

One of the major trends in the 21st century is the trend towards digital transformation within Industry 4.0. In order to adapt to high volatile market conditions, especially in the context of COVID-19, companies do not only have to transfer their knowledge into digital systems. Furthermore, they have to be able to tailor their business processes rapidly to changing customer’s needs. The implementation of efficient and transparent processes is thereby known as the process of digital transformation and requires its underlying software-architecture to be highly flexible and scalable. Especially a web-based platform represents a highly user-centered application for multi-user purposes and can quickly adapt to its customer needs. While e-commerce and video-streaming platforms, like eBay or Netflix, often already provide a highly flexible, microservice-based architecture, common tools and platforms within the engineering-domain are usually still based on rather monolithic or service-oriented architectures (SOA). Therefore, an adaption to changing market conditions and the integration of proprietary tools is often technically demanding and economically not feasible, especially for small and medium-sized enterprises (SME). In this context, the so-called Process-Driven-Approach (PDA) offers a sustainable and tool-neutral blue-print for a system’s architecture strictly following the separations-of-concerns principle and allowing a user-centered layout. The PDA enables the integration of business processes and tools within an orchestrating framework, provided by a process engine. While the PDA within the engineering domain has been presented in a preceding paper, this paper supposes a reference architecture and agile development method for engineering-platforms via the PDA based on the BPMN-standard and process engines. These concepts are validated by a prototypical implementation of a platform-demonstrator for tool-supported planning of robot-based automation solutions.

关键词： Process-Driven web platform reference architecture ROBOTOP Process-Driven-Approach PDA agile user-centered development method

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Management of services of a hyperconverged infrastructure using the coordinator 1st

Management of services of a hyperconverged infrastructure us...

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1st International Conference on computer Science, Engineering and Education Applications, ICCSEEA2018

作者： Rolik, Oleksandr Telenyk, Sergii Zharikov, Eduard Department of Automation and Control in Technical Systems National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Kyiv Ukraine Department of Theoretical Electrical Engineering and Computer Science Faculty of Electrical and Computer Engineering Cracow University of Technology Cracow Poland

ISBN: (纸本)9783319910079

Modern data centers’ providers are gradually moving away from traditional and multi-vendor IT infrastructures to open, standardized and interchangeable solutions that are based on a software defined approach to managing data center resources. The authors analyze the architectural features, requirements, limitations, hardware and software of hyperconverged infrastructures and their advantages in comparison with traditional and converged architectures deployed in data centers. The authors propose to employ two-level coordination schema to manage compute, storage, network and virtualization subsystems of hyperconverged infrastructure along with the self-management algorithms inside these subsystems. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Digital storage

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Nonlinear Swing down Control of the Acrobot ⁎

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IFAC-PapersOnLine 2020年第2期53卷 5813-5818页

作者： Xin Xin Maki Sakurai Shinsaku Izumi Taiga Yamasaki Jinhua She Yannian Liu Faculty of Computer Science and Systems Engineering Okayama Prefectural University 111 Kuboki Soja Okayama 719-1197 Japan School of Engineering Tokyo University of Technology Hachioji 192-0982 Japan School of Automation Southeast University 2 Sipailou Nanjing 210018 China

In this paper, we concern swing down control of the Acrobot which is a 2-link planar robot with a single actuator driving the second joint, whose control objective is to stabilize the Acrobot to the downward equilibrium point with the two links in the downward position for all initial states of the Acrobot with the exception of a set of Lebesgue measure zero. To achieve this control objective, we design a nonlinear controller by using nonnegative linear feedback of the sine function of the angle of the second joint in addition to the negative linear feedback of its angular velocity. By analyzing globally the solution of the closed-loop system consisting of the Acrobot and the presented controller and focusing on the equilibrium points of the closed-loop system and their stability, we prove that the control objective is achieved provided that some conditions on two control gains are satisfied. We design the two control gains such that the real parts of the dominant poles of the linearized model of the closed-loop system around the downward equilibrium point are minimized. We provide simulation results for two Acrobots to show the effectiveness of the presented controller.

关键词： Underactuated mechanical systems Acrobot swing down control robot control nonlinear control passivity Lyapunov stability motion analysis

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Day-ahead scheduling of CNG station and hybrid CNG and plug-in electric vehicles in the form of virtual power plant

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AIP Conference Proceedings 2023年第1期2795卷

作者： Mohammad Seyfi Mehdi Mehdinejad Behnam Mohammad-Ivatloo Heidarali Shayanfar Zulkurnain Abdul-Malek Center of Excellence for Power Systems Automation and Operation School of Electrical Engineering Iran University of Science and Technology Tehran Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran High Voltage & High Current Institute School of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia

Integrating plug-in hybrid electric vehicles (PHEV) with power systems and supplying their required energy is a challenging issue. Decentralized operation of the power systems can decrease the impacts of PHEVs on power systems. One of the high potential options for developing decentralized networks is the virtual power plant (VPP). In this paper, day-ahead scheduling of VPP consisting of PHEVs, which use compressed natural gas (CNG) as their alternative option for electrical energy, and CNG station is presented. VPP can supply the CNG needed by HPEVs by compressing the natural gas (NG) in the CNG station. Therefore, two sources of energy for HPEVs is provided by participating in the scheduling of the VPP. This structure can improve the flexibility and ability of HPEVs to participate in the scheduling. Also, because of using the CNG instead of gasoline, the developed model reduce the pollutant emissions of the transportation system.

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Developing an AI literacy test for junior secondary students: The first stage

Developing an AI literacy test for junior secondary students...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： King Woon Yau Ching Sing Chai Thomas K. F. Chiu Helen Meng Irwin King Savio Wai-Ho Wong Chandni Saxena Yeung Yam Faculty of Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Curriculum and Instruction The Chinese University of Hong Kong Shatin Hong Kong China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin Hong Kong China Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Educational Psychology The Chinese University of Hong Kong Shatin Hong Kong China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China

Artificial Intelligence (AI) education for K-12 is increasingly important as the emerging AI technologies are pervasively infused into human daily lives. Eleven countries have endorsed and implemented the AI curricula at K-12 levels [1]. The "Five Big Ideas" about AI, as proposed by the Association for the Advancement of Artificial Intelligence (AAAI) and the computer Science Teacher Association (CSTA) have emerged to form the core components of K-12 AI education [2], [3]. However, the assessment of students’ learning in AI education for K-12 is still in its initial stage. Surveys and interviews are the major assessing tools based on students’ self- perceptions. Standardized tests on students’ AI literacy are still rare. This paper focuses on the first stage of an AI literacy test based on the Five Big Ideas for Grade 7 to Grade 9 students. The test aims to measure the changes of students’ AI literacy before and after attending a one-year AI course. The preliminary findings show the students have increased in their AI literacy after attending the course. The test can provide insights for understanding students’ competencies and needs in AI literacy and improving the curriculum guidelines for students’ effective learning.

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Possibilities of vehicle state estimation using big data approaches 16

Possibilities of vehicle state estimation using big data app...

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16th Mini Conference on Vehicle System Dynamics, Identification and Anomalies, VSDIA 2018

作者： Fényes, Dániel Németh, Balázs Gáspár, Péter Asszonyi, Máté Systems and Control Laboratory Computer and Automation Research Institute Kende u. 13-17 Budapest Hungary Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Stoczek u. 2 BudapestH-1111 Hungary

Nowadays, the development of the autonomous vehicles is one of the most important challenges for the automotive industry. In general, these vehicles are equipped with numerous sensors, such as onboard-camera, lidar, radar, ultrasonic sensor, accelerometer and gyroscope. These sensors provide information about the environment and other vehicles. This information is not only processed and used directly on the car but also can be stored on internal or cloud-based memory. This collected data might contain hidden information about the motion and the dynamical behaviour of the car. This hidden information can be brought out of the datasets by using big data-based data mining approaches. The aim of the paper is to create a vehicle state estimation model based on the collected sensor data and using data mining tools. In the paper, the sensor data is collected from a high-fidelity simulation software, CarSim. The estimation model is created by the machine-learning software Weka. Finally, the created model is validated through several CarSim simulations. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： computer software

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