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2023 Cross Strait Radio science and Wireless Technology Conference, CSRSWTC 2023

作者： Zheng, Ruihan Xia, Yu Li, Dongming Wang, Liyang Li, Hung Chun Mak, Peng Un Vai, Mang I. Pun, Sio Hang State Key Laboratory of Analog and Mixed-Signal VLSL University of Macau Macau China Institution of Microelectronics University of Macau Macau China Jt. Lab. of Zhuhai UM Sci. and Technol. Research Institution - Lingyange Semiconductor Incorporated Zhuhai China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering Macau China

ISBN: (纸本)9798350358971

This article aims to demonstrate a signal compression method for the wireless invasive neural recording system. A compression system with spike detection for neural signals is proposed. The input signal is firstly detected in the spike detection part and then the intercepted spike segments are sent to the compression part. A compressed sensing technique is applied in the compression part, and the Minimum Euclidean or Manhattan Distance Cluster-based (MDC) matrix is adopted for compressing neural spike segments. During simulation, the compression rate can surpass 99% and the signal-to-noise distortion ratio is around 37 dB. Moreover, the proposed method is also contrasted with the direct compression of input neural signals. When the input neural signal is directly compressed, the compression ratio is 98%, and the signal-to-noise ratio distortion rate is about 28 dB. By employing spike detection and utilizing this MDC matrix, it becomes possible to compress non-sparse spike segments in the time domain, resulting in a higher compression rate and improved reconstruction performance. © 2023 IEEE.

关键词： compressed sensing neural signal compression spike detection

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Generation of Artificial CT Images using Patch-based Conditional Generative Adversarial Networks

arXiv

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arXiv 2022年

作者： Habijan, Marija Galić, Irena Faculty of Electrical Engineering Computer Science and Information Technology Osijek J.J. Strossmayer University of Osijek Osijek Croatia

Deep learning has a great potential to alleviate diagnosis and prognosis for various clinical procedures. However, the lack of a sufficient number of medical images is the most common obstacle in conducting image-based analysis using deep learning. Due to the annotations scarcity, semi-supervised techniques in the automatic medical analysis are getting high attention. Artificial data augmentation and generation techniques such as generative adversarial networks (GANs) may help overcome this obstacle. In this work, we present an image generation approach that uses generative adversarial networks with a conditional discriminator where segmentation masks are used as conditions for image generation. We validate the feasibility of GAN-enhanced medical image generation on whole heart computed tomography (CT) images and its seven substructures, namely: left ventricle, right ventricle, left atrium, right atrium, myocardium, pulmonary arteries, and aorta. Obtained results demonstrate the suitability of the proposed adversarial approach for the accurate generation of high-quality CT images. The presented method shows great potential to facilitate further research in the domain of artificial medical image generation. © 2022, CC BY-NC-ND.

关键词： Generative adversarial networks

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How can Artificial Intelligence (AI) be used to manage Customer Lifetime Value (CLV)—A systematic literature review

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International Journal of Information Management Data Insights 2024年第2期4卷

作者： Firmansyah, Edo Belva Machado, Marcos R. Moreira, João Luiz Rebelo University of Twente Faculty of Electrical Engineering Mathematics and Computer Science AE Enschede 7500 Netherlands University of Twente Faculty of Behavioural Management and Social Sciences Department of High-Tech Business and Entrepreneurship AE Enschede 7500 Netherlands

Customer Lifetime Value (CLV) represents the total worth of a customer to a company over time, aiding businesses in resource allocation and tailored marketing for profitability. This literature review fills a research gap by examining how customer risk factors are integrated into CLV calculations. We conducted a systematic literature review across databases, adhering to strict criteria for relevance and quality. The review analyzed CLV methodologies and outcomes, highlighting the use of mean–variance analysis to optimize customer portfolios, with customer income fluctuations identified as a major risk factor. The study also explores the evolution of CLV research, particularly in the application of Machine Learning (ML) for risk-adjusted CLV. Our findings offer a comprehensive overview, laying the groundwork for future research and helping businesses refine risk management strategies, identify high-risk customers, and enhance customer value through more dynamic, data-driven models. © 2024 The Author(s)

关键词： Customer value Information systems Machine learning Risk-Adjusted Revenue Systematic literature review

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A Virtual Reality System for Predictive Display Functionality in a Telexistence-Controlled SEED-Noid Humanoid Robot with Evaluation of VR Sickness

A Virtual Reality System for Predictive Display Functionalit...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Taiga Suda Motoki Yodowatari Sosuke Kosaki Koki Yokoyama Eito Yanagisawa Eimei Oyama Kohei Tokoi Hiroyuki Okada Arvin Agah Sousuke Nakamura Graduate School of Science and Engineering Hosei University Japan National Institute of Advanced Industrial Science and Technology Japan College of Engineering Tamagawa University Machida City Tokyo JAPAN Wakayama University Wakayama City Wakayama JAPAN Electrical Engineering and Computer Science The University of Kansas Lawrence KS USA Faculty of Science and Engineering Hosei University Japan

Telexistence technology enables the manipulation of a remote robot using sensory feedback and leader-follower control, giving the operator the impression of controlling their own body. However, the robot’s operability declines significantly due to increasing communication time delays. In order to address this issue, the "Predictive Display" technique has been proposed and developed. This technique displays both the real robot’s movements with time delay and the computer-generated (CG) robot’s movements without time delay. In the Telexistence robot operation system, a predictive display system can be constructed using a virtual reality (VR) system. In this study, we have developed a VR system for Telexistence operation with THK’s SEED-Noid humanoid robot. Unity is utilized, which enables the predictive display function for the stereo camera mounted on the SEED-Noid. We developed and evaluated a display mode without neck joint angle restrictions to reduce VR sickness and workload using the developed VR system. Additionally, we developed a display mode with a limited neck joint angle for comparison purposes.

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Hands in Motion: Developing a Real-Time Gesture Recognition System for Enhanced Communication

Hands in Motion: Developing a Real-Time Gesture Recognition ...

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International Conference on Applied Mathematics & computer science (ICAMCS)

作者： Enachi Andrei Turcu Corneliu Culea George Sghera Bogdan-Constantin Ungureanu Andrei-Gabriel „Ştefan cel Mare” University of Suceava Suceava Romania „Vasile Alecsandri” University of Bacău Bacău Romania Faculty of Electrical Engineering and Computer Science „Ş tefan cel Mare” University of Suceava Suceava Romania Department of Energetics and Computer Science Vasile Alecsandri University of Bacău Bacău Romania

ISBN: (数字)9798350363807

ISBN: (纸本)9798350363814

This paper presents the development of an advanced system that has the ability to recognize hand gestures and also maps new ways for users to access the interfaces, using as main libraries OpenCV, but also a microframework powerful enough MediaPipe to transform sign language into text. The system involves obtaining both static and dynamic images through a real-time camera, from which key hand features such as wrists, joints and degrees of freedom are extracted and identified. The gestures are then categorized based on several labeled datasets and integrated into a friendly interface called Tkinter. Through the use and identification of gestures, users have the possibility to manipulate applications in a way that is free from the human-computer interaction. After some testing, it was concluded that the system is sufficiently robust and precise and also very capable of accommodating the conditions of various environments. This has a strong impact on the users of applications in the field of artificial intelligence, constituting a fundamentally necessary experience that covers and promotes human-computer interaction and social engagement by making it accessible also to members of deaf-mute communities. It is also a way of integrating them into today's society by providing new opportunities and last generation technologies.

关键词： Human computer interaction Wrist computer science Sign language Text recognition Transforms Feature extraction Real-time systems Libraries Testing

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Creating a Surround View Algorithm with Implementation on a Real Embedded ADAS Platform

Creating a Surround View Algorithm with Implementation on a ...

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International Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Ivan Marinić Mario Vranješ Ratko Grbić Marijan Herceg TTTech Auto d.o.o. Cara Hadrijana 10b Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpimira 2B Osijek Croatia

ISBN: (数字)9789532901382

ISBN: (纸本)9798350354614

computer Vision (CV) has seen significant advances, and autonomous driving technologies have been transforming the automotive industry in recent years. Autonomous vehicles require robust CV algorithms, while Advanced Driver Assistance Systems (ADAS) help the driver when driving and increase traffic safety. In this paper, the algorithm for generating a Surround View (SV) of the vehicle is proposed and implemented on a real embedded ADAS platform to test its performance in real hardware scenarios. The algorithm implements geometric operations like image distortion correction, perspective transformation, and image stitching to create a comprehensive and connected surround view. The subjective image quality evaluation results showed that the proposed algorithm achieves a fairly high quality of the final top-view image. The experiments also show that its operating speed when running on a real ADAS platform is suitable for cases when the vehicle speed is not high, such as when parking.

关键词： Industries Image quality Cameras Software Safety Telecommunications Autonomous vehicles Image stitching Vehicles Automotive engineering

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A Deep-Learning-Based Lumbosacral Localization and Landmark Detection Network for Automatic Lumbar Stability and Spondylolisthesis Grading Assessment

A Deep-Learning-Based Lumbosacral Localization and Landmark ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Tingting Hu Rong Zhang Baolin Xu Dongdong Xia Qiang Li Lijun Guo The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China The Department of Orthopedics The First Affiliated Hospital of Ningbo University Ningbo China The Department of Radiology The Afffliated People’s Hospital of Ningbo University Ningbo China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

The accurate detection of vertebral landmarks is crucial for clinical diagnosis and research on the lumbar stability and spondylolisthesis grading. However, the small size of vertebral landmarks in X-ray images and the morphological similarity among vertebrae complicate this detection task. Recent advances in deep learning have enhanced the spinal landmark detection. To further improve the assessment methods for the lumbar stability and spondylolisthesis grading, we propose the LSLD-Net, a novel network based on the lumbosacral localization and landmark detection. In clinical practices, the X-ray images used for evaluating the lumbar spine stability can often include the extraneous information from non-lumbosacral areas, such as the thoracic spine. The proposed LSLD-Net first extracts the lumbosacral region from the complex X-ray images and then performs the precise landmark detection within the identified area. The landmark detection stage integrates the HRNet and U-net architectures, effectively capturing the long-range contextual information, the overall structural layout, and the fine local details in lumbar X-ray images to optimize landmark detection. Additionally, we propose a Multi-Scale Attention Module that enhances the relevant features and suppresses the irrelevant ones through channel and spatial attention, thereby achieving precise landmark detection and improving the robustness of the network. The evaluations on the private and public BUU-LSPINE datasets indicate that the LSLD-Net surpasses other state-of-the-art methods in landmark detection, enhancing the accuracy and efficiency of Sagittal Displacement and Intervertebral Space Angle measurements. This performance excels in assessing the lumbar stability and spondylolisthesis grading, offering the significant support to clinicians for early quantitative diagnosis and evaluation.

关键词： Location awareness Deep learning Accuracy Spine Layout Displacement measurement Feature extraction Extraterrestrial measurements Robustness X-ray imaging

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Cybersecurity in maritime power systems: A comprehensive review of cyber threats and mitigation techniques

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Electric Power Systems Research 2025年 247卷

作者： Mai, V.T. Mohammadzadeh, Ardashir Alattas, Khalid A. Taghavifar, Hamid Ghaderpour, Ebrahim Faculty of Engineering Dong Nai Technology University Bien Hoa City Viet Nam Faculty of Engineering Department of Electrical and Electronics Engineering Sakarya University Sakarya Turkey Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Canada Department of Earth Sciences Sapienza University of Rome Piazzale Aldo-Moro 5 Rome00185 Italy

Integration of communication networks and Shipboard Microgrids (SHMGs) brings significant benefits in the advanced control, monitoring, and remote diagnostics, particularly facilitating the data exchange between various generation components, such as sustainable energy resources, energy storage systems, and connected loads. However, the utilization of communication technologies brings serious cyber-security challenges that highly threaten maritime power systems from a security and stability perspective. This paper aims to present a comprehensive review of cybersecurity issues in marine power systems. Vulnerable points of the system to cyber-attacks, such as phasor measurement units and area control error channels are elaborated. Prevalent attacks in the load frequency control, such as denial of service and false data injection, covert attacks, and reply attacks are discussed. Recent detection/mitigation mechanisms in the cybersecurity field to tackle various cyber-attacks have been introduced. In the detection part, various observers, such as the Kalman filter, Luenberger observer, and machine learning algorithms are studied. In the mitigation mechanism, various methodologies, such as active disturbance rejection control and model predictive control are presented. This survey reviews the recent cyber-security developments and challenges in SHMG, and it is helpful for contemporary researchers in the field of cybersecurity in maritime power systems. © 2025 The Author(s)

关键词： Cyber attacks

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Neumann Series based Linear Bus Injection Model of Three-Phase AC Power Flow for Active Distribution Network

Neumann Series based Linear Bus Injection Model of Three-Pha...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Cheng Gong Chi-Seng Lam State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau China Institute of Microelectronics University of Macau Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Linearization of AC power flow is crucial for simplifying the analysis and optimization of power systems, enabling more efficient and scalable computation for network operation and control. In this paper, a Neumann series expansion based linear bus injection model (NS-BIM) of three-phase AC power flow of active distribution network (ADN) is proposed. First, the full-nonlinear three-phase BIM is built based on AC power flow equations. Then, the mathematical derivation of the proposed NS-BIM is provided. Moreover, the approximation error analysis is given which guarantee the robustness of the NS-BIM. Finally, numerical case studies on different benchmark ADN systems are carried out to verify the accuracy of the NS-BIM in comparing with other representative linear BIMs.

关键词： Analytical models Accuracy Computational modeling Benchmark testing Approximation error Mathematical models Robustness

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A Wireless Charging System with Bipolar Partial Power Conversion for 400V/800V EV Battery

A Wireless Charging System with Bipolar Partial Power Conver...

引用

Annual Conference of Industrial Electronics Society

作者： Muxing Wu Io-Wa Iam Cheng Gong Chi-Seng Lam State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau China Institute of Microelectronics University of Macau Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Currently, electric vehicle (EV) battery platforms typically vary in standard, commonly rated at either 800V or 400V. Conventional wireless charging system (WCS) are limited to single voltage level charging, necessitating wireless communication or additional complex circuits for achieving multi-voltage level charging, which can compromise operational stability and overall efficiency. This article proposes a WCS based on the concept of bipolar partial power conversion. By incorporating reversing series switches on the secondary of the DC/DC converter, regulation voltage control enables switching between positive and negative polarity to supply power to either 800V or 400V battery for EV. This approach ensures high power transmission efficiency, without relying on wireless communication, thereby ensuring stable charging process. Furthermore, this article also presents various combinations of bipolar topologies that can be selectively employed based on application requirements. Finally, simulation results validate the feasibility of the proposed 3.2KW WCS.

关键词： Wireless communication Inductive charging Optical wavelength conversion Switches Regulation Batteries Topology Power conversion Voltage control Stress

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