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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Gu, Hongyan Onstott, Ellie Yan, Wenzhong Xu, Tengyou Wang, Ruolin Wu, Zida Chen, Xiang Anthony Haeri, Mohammad University of California Department of Electrical and Computer Engineering Los Angeles United States University of Kansas Medical Center Department of Pathology and Laboratory Medicine United States

ISBN: (纸本)9798331520526

Z-stack scanning is an emerging whole slide imaging technology that captures multiple focal planes alongside the z-axis of a glass slide. Because z-stacking can offer enhanced depth information compared to the single-layer whole slide imaging, this technology can be particularly useful in analyzing small-scaled histopathological patterns. However, its actual clinical impact remains debated with mixed results. To clarify this, we investigate the effect of z-stack scanning on artificial intelligence (AI) mitosis detection of meningiomas. With the same set of 22 Hematoxylin and Eosin meningioma glass slides scanned by three different digital pathology scanners, we tested the performance of three AI pipelines on both single-layer and z-stacked whole slide images (WSIs). Results showed that in all scanner-AI combinations, z-stacked WSIs significantly increased AI's sensitivity (+17.14%) on the mitosis detection with only a marginal impact on precision. Our findings provide quantitative evidence that highlights z-stack scanning as a promising technique for AI mitosis detection, paving the way for more reliable AI-assisted pathology workflows, which can ultimately benefit patient management. © 2025 IEEE.

关键词： Artificial Intelligence meningiomas mitosis detection Z-stack scanning

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RIS Assisted Dual-Function Radar and Secure Communications Based on Frequency-Shifted Chirp Spread Spectrum Index Modulation

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China Communications 2023年第10期20卷 85-99页

作者： Xiaoping Jin Peng Zhang Chuan Wan Dingyou Ma Yudong Yao Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province College of Information EngineeringChina Jiliang UniversityHangzhou 310018China Key Laboratory of Universal Wireless Communications Ministry of EducationSchool of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China Electrical and Computer Engineering Department Stevens Institute of TechnologyHobokenNJ 07030USA

Reconfigurable intelligent surface(RIS)assisted dual-function radar communications(DFRC)system is a promising integrated sensing and communication(ISAC)technology for future *** this paper,we propose a scheme of RIS-assisted DFRC system based on frequency shifted chirp spread spectrum index modulation(RDFI)for secure *** proposed RDFI achieves the sensing and transmission of target location information in its radar and communication modes,*** both modes,the frequency-shifted chirp spread spectrum index modulation(FSCSS-IM)signal is used as the baseband signal for radar and communications,so that the signal sent by the radar also carries *** scheme implements the RIS-assisted beamforming in the communication mode through the azimuth information of the target acquired in the radar mode,so that the signal received from the eavesdropper is distorted in amplitude and *** addition,this paper analyzes the radar measurement accuracy and communication security of the FSCSS-IM signal using ambiguity function and secrecy rate(SR)analysis,*** results show that RDFI achieves both excellent bit error rate(BER)performance and physical layer security of communications.

关键词： index modulation secure communications ISAC DFRC reconfigurable intelligent surface

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Quantum Assisted Scheduling Algorithm for Federated Learning in Distributed Networks 32

Quantum Assisted Scheduling Algorithm for Federated Learning...

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32nd International Conference on computer Communications and Networks, ICCCN 2023

作者： Wei, Xinliang Fan, Lei Guo, Yuanxiong Gong, Yanmin Han, Zhu Wang, Yu Temple University Department of Computer and Information Sciences PhiladelphiaPA United States University of Houston Department of Engineering Technology HoustonTX United States University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX United States University of Texas at San Antonio Department of Electrical and Computer Engineering San AntonioTX United States University of Houston Department of Electrical and Computer Engineering HoustonTX United States

ISBN: (纸本)9798350336184

The scheduling problem for federated learning (FL) with multiple models in a distributed network is challenging, as it involves NP-hard mixed-integer nonlinear programming. Moreover, it requires optimal participant selection and learning rate determination among multiple FL models to avoid high training costs and resource competition. To overcome those chal-lenges, in literature the Benders' decomposition algorithm (BD) can deal with mixed integer problems, however, it still suffers from limited scalability. To address this issue, in this paper, we present the Hybrid Quantum-Classical Benders' Decomposition (HQCBD) algorithm, which combines the power of quantum and classical computing to solve the joint participant selection and learning scheduling problem in multi-model FL. HQCBD decomposes the optimization problem into a master problem with binary variables and small subproblems with continuous variables. This collaboration maximizes the potential of both quantum and classical computing, and optimizes the complex joint optimization problem. Simulation on the commercial D-Wave quantum annealing machine demonstrates the effectiveness and robustness of the proposed method, with up to 18% improvement of iterations and 81% improvement of computation time over BD algorithm on classical CPUs even at small scales. © 2023 IEEE.

关键词： Scheduling algorithms

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Past, Present, and Future of CASS Educational Programs and Initiatives [Feature]

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IEEE Circuits and systems Magazine 2024年第2期24卷 7-15页

作者： Rokhani, Fakhrul Zaman Zhang, Xinmiao Joshi, Rajiv V. Reis, Ricardo Grimblatt, Victor Tang, Kea-Tiong Li, Yongfu Amara, Amara Delgado-Restituto, Manuel Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication Systems Engineering Serdang43400 Malaysia The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre90010-150 Brazil Synopsys California CA92037 United States National Tsing Hua University Department of Electrical Engineering Hsinchu300 Taiwan Shanghai Jiao Tong University Department of Micro and Nano Electronics Engineering Shanghai200240 China Paris75006 France Institute of Microelectronics of Sevilla Sevilla41092 Spain

The Circuits and systems Society (CASS) places a strong emphasis on advancing education within its domain. Various educational programs and resources have contributed to the professional development of CASS members for more than 20 years now. A major transformation within the Society was started in 2021 with a clear vision to become a premier educational resource within circuits and systems areas of interest. This article provides a comprehensive review of flagship educational programs and past initiatives. Insights from the lessons learned and future trends in the education ecosystem guided society's strategies and frameworks for improving and developing new educational products and services. The benefits of learning with the CASS program are presented, highlighting the Society's deep commitment to serving the community at large in educational pursuit for years to come. © 2001-2012 IEEE.

关键词： engineering education

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A Novel Internet of Medical Thing Cryptosystem Based on Jigsaw Transformation and Ikeda Chaotic Map

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computer systems Science & engineering 2023年第9期46卷 3017-3036页

作者： Sultan Almakdi Mohammed SAlshehri Yousef Asiri Mimonah Al Qathrady Anas Ibrar Jawad Ahmad Department of Computer Science Najran UniversityNajran61441Saudi Arabia Department of Information Systems Najran UniversityNajran61441Saudi Arabia Department of Electrical Engineering Wah Engineering CollegeUniversity of WahWah Cantt47040Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

Image encryption has attracted much interest as a robust security solution for preventing unauthorized access to critical image *** picture encryption is a crucial step in many cloud-based and healthcare *** this study,a strong cryptosystem based on a 2D chaotic map and Jigsaw transformation is presented for the encryption of medical photos in private Internet of Medical Things(IoMT)and cloud storage.A disorganized three-dimensional map is the foundation of the proposed *** dispersion of pixel values and the permutation of their places in this map are accomplished using a nonlinear encoding *** suggested cryptosystem enhances the security of the delivered medical images by performing many *** validate the efficiency of the recommended cryptosystem,various medical image kinds are used,each with its unique *** measures are used to evaluate the proposed cryptosystem,which all support its robust *** simulation results confirm the supplied cryptosystem’s ***,it provides strong robustness and suggested protection standards for cloud service applications,healthcare,and *** is seen that the proposed 3D chaotic cryptosystem obtains an average entropy of 7.9998,which is near its most excellent value of 8,and a typical NPCR value of 99.62%,which is also near its extreme value of 99.60%.Moreover,the recommended cryptosystem outperforms conventional security systems across the test assessment criteria.

关键词： Jigsaw transformation cryptosystem image encryption medical images Ikeda map chaotic system

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Stealthy Attack Detection of controlled ramp meters in freeway networks 63

Stealthy Attack Detection of controlled ramp meters in freew...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Menelaou, Charalambos Zhang, Kangkang Timotheou, Stelios Panayiotou, Christos G. Parisini, Thomas University of Cyprus Kios CoE Dept. of Electrical and Computer Engineering Cyprus Imperial College London Dept. of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

The increasing reliance on intelligent transportation systems (ITS) for traffic management has simultaneously heightened the potential for cybersecurity threats. Malicious cyber attacks on such systems can lead to operational inefficiencies, heightened congestion, and compromised safety. This work introduces a stealthy integrity attack tailored for ramp metered freeway systems. The attack model is conceptualized as a closed-loop dynamical system, formulated as an optimization problem based on the Cell Transmission Model. This work further proposes a distributed detection mechanism designed to identify attack residuals, which, by incorporating an adaptive threshold scheme, can detect the presence of an attack. To demonstrate the efficacy of our detection scheme, we present a scenario illustrating its application in freeway road networks. © 2024 IEEE.

关键词： Cyber attacks

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Automated analysis of fundus images for the diagnosis of retinal diseases: a review

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Research on Biomedical engineering 2024年第1期40卷 225-251页

作者： Berto, Alexa Scarpa, Fabio Tsiknakis, Nikos Manikis, Georgios Fotiadis, Dimitrios I. Marias, Kostas Scarpa, Alberto D-Eye s.r.l. Padua Italy Department of Information Engineering University of Padova Padua35131 Italy Heraklion70013 Greece Department of Biomedical Research Institute of Molecular Biology and Biotechnology FORTH Ioannina45115 Greece Department of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Ioannina45110 Greece Department of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion71004 Greece

Purpose: Colour fundus images are widely used in diagnosis treatment decision of several retinal diseases such as diabetic retinopathy (DR), glaucoma and age-related macular degeneration (AMD). These very common conditions must be detected early and monitored to prevent progression and avoid permanent damage. Fundus images revealed to be useful also for the diagnosis of cataracts. In recent years, various automatic diagnostic support methods have been proposed in the literature, with the aim of facilitating widespread screening and obtaining quantitative, objective, and reproducible information. Methods: In this review paper, an overview of traditional, machine learning and modern deep learning techniques for ophthalmic disease diagnosis (i.e. glaucoma, DR, AMD, and cataract) using retinal fundus images is presented. In addition, various publicly available image datasets used for such purposes are described. Results: The current main challenges and findings are identified, as well as common aspects and discrepancies between the various methods developed for the various diseases. Conclusion: The overview of what has been done about all pathologies, rather than only on a specific one, could favour a migration of the best solutions and, hopefully, the development of a more precise and clinically useful automatic analysis of all pathologies. Important critical insights and research trends are also discussed. Graphical abstract: (Figure presented.) © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2023.

关键词： Pathology

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Towards Seamless Wireless Link Connection 23

Towards Seamless Wireless Link Connection

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21st Annual International Conference on Mobile systems, Applications and Services, MobiSys 2023

作者： Chen, Lili Yu, Bozhong Ren, Ju Gummeson, Jeremy Zhang, Yaoxue Department of Computer Science and Technology BNRist Tsinghua University China School of Information Science and Technology Northwest University United States Department of Electrical and Computer Engineering University of Massachusetts Amherst United States Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798400701108

Sub-6GHz and mmWave complement each other in the next generation of wireless communications for wide coverage and high capacity. However, there is still a gap between current network technology and seamless connection in indoor environments due to the inevitable occlusions that particularly affect higher frequency bands like Wi-Fi 5GHz and mmWave. To overcome this gap, economical tunable metasurfaces offer a promising solution by redirecting the beam direction of incoming waves to bypass blockages. However, existing metasurface technologies focus on a single frequency band and lack a theoretical framework to guide surface design for multiple desired bands, limiting their potential for diverse *** work attempts to provide a general method for cross-band metasurface design, extend wireless link coverage by using a new metasurface prototype called CrossFlit, which can maximize the link quality with efficient aperture usage and low cost. We addressed a series of challenges to enable CrossFlit to independently control the wireless communication links across multiple frequency bands;our proof of concept implementation is for Wi-Fi 5 GHz and mmWave bands. We integrate a fast beam-scanning algorithm into an end-to-end system that actuates the metasurface to optimize links in realtime. Empirical evaluation demonstrates that CrossFlit can enhance multiple wireless links simultaneously, providing 10 dB and 15 dB power improvements for Wi-Fi and mmWave links, respectively. CrossFlit achieves less than 4° beam mismatch even in challenging mobile scenarios. © 2023 Owner/Author(s)

关键词： Wi-Fi

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Equivalent Circuit Model and Stability Analysis of Multi-Paralleled Grid-Tied SiC Inverters with Low Voltage Ride-Through Capability

Equivalent Circuit Model and Stability Analysis of Multi-Par...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Quan, Xuli Dong, Xiaofeng Bosworth, Matthew Li, Hui Florida State University Department of Electrical and Computer Engineering TallahasseeFL United States Tesla Engineering & Technical Department San DiegoCA United States Florida State University Centre for Advanced Power Systems TallahasseeFL United States

ISBN: (纸本)9798350376067

The advantages of applying deadbeat control to grid-tied SiC inverters with an L filter include achieving a fast dynamic response and low-voltage-ride-through (LVRT) capability without a phase-locked loop (PLL). However, the inherently low-inertia nature of the SiC inverter makes the system prone to instability. In this paper, the equivalent circuit model of a deadbeat-based grid-tied SiC inverter is developed, and the corresponding Lyapunov-based method is applied to analyze the stability under large signal transients such as LVRT. In addition, a Nyquist diagram is derived for small signal stability analysis of multi-paralleled inverters. Simulation and experimental results are provided to validate the theoretical analysis. © 2024 IEEE.

关键词： Phase locked loops

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Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

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7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

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