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arXiv 2024年

作者： Wang, Jiayi Mao, Yi-An Ma, Xiaoyu Guo, Sicen Shao, Yuting Lv, Xiao Han, Wenting Christopher, Mark Zangwill, Linda M. Bi, Yanlong Fan, Rui Group The College of Electronics & Information Engineering Tongji University Shanghai201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201210 China School of Life Science Shanghai University 99 Shangda Avenue Baoshan District Shanghai200444 China Department of Ophthalmology Tongji Hospital School of Medicine Tongji University Shanghai200071 China Hamilton Glaucoma Center Division of Ophthalmology Informatics and Data Science Shiley Eye Institute Viterbi Family Department of Ophthalmology University of California San Diego San DiegoCA92037 United States Tongji Eye Institute School of Medicine Tongji University Shanghai200071 China

Optic nerve head (ONH) detection has been a crucial area of study in ophthalmology for years. However, the significant discrepancy between fundus image datasets, each generated using a single type of fundus camera, poses challenges to the generalizability of ONH detection approaches developed based on semantic segmentation networks. Despite the numerous recent advancements in general-purpose semantic segmentation methods using convolutional neural networks (CNNs) and Transformers, there is currently a lack of benchmarks for these state-of-the-art (SoTA) networks specifically trained for ONH detection. Therefore, in this article, we make contributions from three key aspects: network design, the publication of a dataset, and the establishment of a comprehensive benchmark. Our newly developed ONH detection network, referred to as ODFormer, is based upon the Swin Transformer architecture and incorporates two novel components: a multi-scale context aggregator and a lightweight bidirectional feature recalibrator. Our published large-scale dataset, known as TongjiU-DROD, provides multi-resolution fundus images for each participant, captured using two distinct types of cameras. Our established benchmark involves three datasets: DRIONS-DB, DRISHTI-GS1, and TongjiU-DROD, created by researchers from different countries and containing fundus images captured from participants of diverse races and ages. Extensive experimental results demonstrate that our proposed ODFormer outperforms other state-of-the-art (SoTA) networks in terms of performance and generalizability. Our dataset and source code are publicly available at ***/ODFormer. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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On exploration requirements for learning safety constraints

arXiv

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arXiv 2021年

作者： Massiani, Pierre-François Heim, Steve Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

Enforcing safety for dynamical systems is challenging, since it requires constraint satisfaction along trajectory predictions. Equivalent control constraints can be computed in the form of sets that enforce positive invariance, and can thus guarantee safety in feedback controllers without predictions. However, these constraints are cumbersome to compute from models, and it is not yet well established how to infer constraints from data. In this paper, we shed light on the key objects involved in learning control constraints from data in a model-free setting. In particular, we discuss the family of constraints that enforce safety in the context of a nominal control policy, and expose that these constraints do not need to be accurate everywhere. They only need to correctly exclude a subset of the state-actions that would cause failure, which we call the critical set. Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamical systems

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Research on Impedance Matching for Improving Gain in Conductive Intracardiac Communication

Research on Impedance Matching for Improving Gain in Conduct...

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Cross Strait Quad-Regional Radio science and Wireless Technology Conference (CSRWTC)

作者： Jiamei Wang Dongming Li Han Wang Jiejie Yang Sio Hang Pun Mang I. Vai Yueming Gao College of Physics and Information Engineering Fuzhou University China The International Joint Laboratory on Health Intelligent Monitoring Systems Fuzhou University China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China Faculty of Science and Technology University of Macau China

ISBN: (数字)9798331507794

ISBN: (纸本)9798331507800

As an emerging method of intracardiac wireless communication, conductive intracardiac communication (CIC) has the advantages of low power consumption and high security of information transmission, and is suitable for synchronization between multiple leadless pacemakers (LCPs). However, the complicated intracardiac environment increases the measurement uncertainty of intracardiac channel parameters, and current research on intracardiac communication does not take into account impedance mismatch. These may lead to unreliable communication between LCPs. In this paper, an equivalent circuit model of the intracardiac channel is constructed based on the electrical characteristics of cardiac tissue. The intracardiac channel uses an L-type impedance matching circuit to improve the channel gain. The results show that the channel gain increases by more than 7 dB after adding the impedance matching circuit. Especially, the most significant increase is 8.33 dB at 10MHz. This proves the feasibility of the impedance matching method and provides an effective solution for the future design of intracardiac communication transceivers.

关键词： Wireless communication Impedance matching Pacemakers Lead Transceivers Impedance Synchronization Integrated circuit modeling Gain Equivalent circuits

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Identifying Appropriate Probability Density Function for Wind Speed Profiles of Two Coastal Cities in Pakistan for Better Wind Power Assessment

Identifying Appropriate Probability Density Function for Win...

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Emerging Trends in Electrical, Control, and Telecommunication engineering (ETECTE), International Conference on

作者： Ghulam Abbas Arshad Ali Muhammad Zubair Zohaib Mushtaq Umar Farooq Irfan A. Khan Department of Electrical Engineering The University of Lahore Lahore Pakistan Faculty of Computer and Information Systems Islamic University of Madinah Madinah Saudi Arabia College of Engineering and Technology University of Doha for Science and Technology Doha Qatar Department of Electrical Electronics and Computer Systems University of Sargodha Sargodha Pakistan Intelligent Systems Lab & Automation Facility (ISLAF) IEECE University of the Punjab Lahore Pakistan Clean and Resilient Energy Systems (CARES) Lab Texas A&M University Galveston TX USA

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

To assess the wind power potential of a specific wind site, a suitable distribution function that best suits the wind data needs to be known. In this study, we employ four probability density functions (PDFs), namely Weibull, Rayleigh, Log-Normal, and Gamma, on wind speed data obtained from two coastal cities in Pakistan, Gwadar and Karachi, to check which one is the best suited. Cities along the coastline of Pakistan offer greater wind speeds and, thus, greater wind power potential. The maximum likelihood technique is used to estimate the parameters of the density distributions. Three statistical measures-Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R 2 )-are used to assess the goodness of fit for every distribution. These measures give a complete picture of every distribution's correctness in terms of reflecting the recorded wind speed patterns. Numerical results reveal that the Weibull distribution fits well with the wind speeds of the two coastal cities compared to the other three probability distributions, providing insightful analysis for the evaluation of wind resources and possible local energy generation. The MATLAB environment is used to compare the distributions and validate the effectiveness of the proposed methodology.

关键词： Wind energy generation Electric potential Wind energy Wind speed Urban areas Sea measurements Wind power generation Probability density function Probability distribution Weibull distribution

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Testing of Emerging Wireless Sensor Networks Using Radar Signals With Machine Learning Algorithms

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2024年 1卷 49-59页

作者： Shitharth Selvarajan Hariprasath Manoharan Adil O. Khadidos Alaa O. Khadidos School of Built Environment Engineering and Computing Leeds Beckett University Leeds U.K. Department of Electronics and Communication Engineering Panimalar Engineering College Chennai India Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Center of Research Excellence in Artificial Intelligence and Data Science King Abdulaziz University Jeddah Saudi Arabia

In this article, machine learning methods are used to assess how well wireless sensor networks transmit and receive radar signals. Measurements are done with labeled and unlabeled datasets where output functions are modified in relation to transmitted input in order to test the transceiver of radar signals. The main contribution in the proposed method is to focus on the possibility of choosing a free space model that transmits the radar signals in wireless sensor networks without any interruptions. Hence, for such type of transmissions, reference time period is selected in order to perform radar signal classification, and at the same time, separation of unnecessary interruptions is reduced using clustering procedures. Since the radar signals can be monitored with automatic transmission techniques, the outcomes are combined with supervised, unsupervised, and reinforcement learning models to increase the effect of transmissions. Therefore, the objective functions are designed with three scenarios where reinforcement learning proves to provide adequate connections for radar signals to all wireless sensor networks at reduced error of 0.3%. In addition, with reinforcement learning, the distance of radar signal transmission is maximized to a level greater than 75% at minimized noise ratio of 0.8%.

关键词： Radar Wireless sensor networks Sensors Spaceborne radar Security Radar measurements Mathematical models

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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IEEE International Conference on systems, Man and Cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods Design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning Cybernetics

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Trade execution games in a Markovian environment

arXiv

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arXiv 2024年

作者： Ohnishi, Masamitsu Shimoshimizu, Makoto Faculty of Informatics Yamato University Osaka Suita City564-0082 Japan Center for Mathematical Modeling and Data Science Osaka University Toyonaka City Osaka560-8531 Japan Department of Industrial and Systems Engineering Tokyo University of Science 2641 Yamazaki Noda City Chiba278-8510 Japan

This paper examines a trade execution game for two large traders in a generalized price impact model. We incorporate a stochastic and sequentially dependent factor that exogenously affects the market price into financial markets. Our model accounts for how strategic and environmental uncertainties affect the large traders' execution strategies. We formulate an expected utility maximization problem for two large traders as a Markov game model. Applying the backward induction method of dynamic programming, we provide an explicit closed-form execution strategy at a Markov perfect equilibrium. Our theoretical results reveal that the execution strategy generally lies in a dynamic and non-randomized class;it becomes deterministic if the Markovian environment is also deterministic. In addition, our simulation-based numerical experiments suggest that the execution strategy captures various features observed in financial markets. Copyright © 2024, The Authors. All rights reserved.

关键词： Dynamic programming

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Out-of-Distribution Fault Diagnosis of Industrial Cyber-Physical systems Based on Orthogonal Anchor Clustering With Adaptive Balance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 48-60页

作者： Liu, Ruonan Hu, Puyuan Zhao, Siheng Sun, Zhijian Han, Te Pang, Zhibo Zhang, Weidong Shanghai Jiao Tong University Department of Automation Shanghai200240 China National Key Laboratory of Marine Engine Science and Technology Shanghai201108 China Crossocean of Suzhou Technology Suzhou215121 China Beijing Institute of Technology Center for Energy and Environmental Policy Research School of Management Beijing100081 China ABB Corporate Research Sweden Department of Automation Technology Vasteras722 26 Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm114 28 Sweden Henan University Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Kaifeng475001 China Shanghai Jiaotong University Department of Automation Shanghai200240 China

Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS), ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural networks have demonstrated competitive results for intelligent fault diagnosis, which are usually trained via the historical data of all fault modes. However, in real engineering, it is usually difficult to collect samples and exhaust all failures during the training stage. As a result, out-of-distribution fault diagnosis (OOD-FD) becomes a more realistic problem that requires the methods to not only accurately diagnose the known faults, but also effectively recognize unknown ones. Therefore, a novel orthogonal anchor clustering with focal attention (FA-OAC) is proposed in this paper for OOD-FD. Firstly, an orthogonal anchor clustering (OAC) algorithm is proposed to fix the class center of each fault mode orthogonally and distinguish the known and unknown faults at the class level. Then, because the identifiability of different fault modes changes a lot in OOD-FD, the focal attention mechanism is applied to dynamically adjust the attention to different fault modes according to the distance loss of OAC, thus addressing the identifiability imbalance problem. To verify the effectiveness of the proposed method, different OOD-FD tasks are designed based on two rotating machinery datasets. The experimental results and comparison with state-of-the-art fault diagnosis methods have demonstrated that the proposed method has improved the OOD-FD performance greatly and therefore provides an effective tool in real engineering. © 2023 IEEE.

关键词： Rotating machinery

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Effects of Image Presentation Using a Head-Mounted Display on Muscle and Brain Activity during Swallowing

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World Journal of Neuroscience 2022年第2期12卷 68-81页

作者： Kengo Hoyano Yasuhiro Ogoshi Department of Speech and Hearing Sciences Faculty of Health and Medical Sciences Fukui Health Science University Fukui Japan Department of Human and Artificial Intelligent Systems Graduate School of Engineering University of Fukui Fukui Japan

Introduction: It is well known that humans have an increased sense of taste and consume more food when eating with others. This effect is called social facilitation of eating. We previously reported that self-images also have the effect of social facilitation of eating. In the present study, we investigated the effect of a head-mounted display (HMD) as a means of presenting self-images. Methods: Fourteen healthy adults (7 females and 7 males) were included in the study. The mean age of the participants was 20.4 years. The experimental conditions were as follows: the presentation conditions include the SG condition, in which an image was projected on the smart glasses, and the MT condition, in which an image was projected on the monitor. The stimulation conditions include the self-image condition (Self condition), in which the participant’s own image was projected, and the background image condition (Background condition), in which the background image was projected. Participants were asked to consume green tea jelly three times under the four conditions, which consisted of combinations of the presentation and stimulation conditions. Electromyography (EMG) and electroencephalography (EEG) were used to measure the muscle activity of the suprahyoid muscle group and brain activity, respectively. Results: The EMG of the “SG-Self” condition was significantly higher than that of “SG-Background” and “MT-Background” conditions. The EMG of the “MT-Self” condition was significantly higher than that of the “MT-Background” condition. In the EEG before the start of swallowing, “SG-Self” was significantly lower in the alpha band and higher in the beta band than “MT-Background”. The beta-alpha ratio was significantly higher for “SG-Self” than for “SG-Background” and “MT-Background” and higher for “MT-Self” than for “MT-Background”. Conclusion: These results suggest that self-images influence muscle and brain activities during swallowing, regardless of the presentation conditions, s

关键词： Social Facilitation Swallowing Electroencephalography (EEG) Electromyography (EMG) Diet Modification for Dysphagia

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Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin

Enhancing Sustainable Development Goals Through Future Vapor...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Surendra Maharjan Wenzhao Li Shahryar Fazli Hani Sewilam Hesham El-Askary Computational and Data Sciences Graduate Program Schmid College of Science and Technology Chapman University Orange CA USA Earth Systems Science and Data Solutions Lab Chapman University Orange CA USA The Center for Applied Research on the Environment and Sustainability The American University in Cairo Cairo Egypt Department of Engineering Hydrology RWTH Aachen University Aachen Germany Department of Environmental Sciences Faculty of Science Alexandria University Alexandria Egypt

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 to 2060 under two Shared Socioeconomic Pathways (SSPs), SSP2-4.5 and SSP5-8.5. The study's findings on the implications of rising VPD levels in the Nile River Basin (NRB), particularly under the SSP 5-8.5 scenario, highlight a critical challenge for the region's agricultural productivity and food security. The increased VPD, indicative of drier conditions, leads to a moisture deficit for crops, potentially reducing agricultural yields. This scenario poses a significant threat to food security, as lower crop yields can result in food shortages and higher food prices, adversely affecting vulnerable populations. The study underscores the necessity of integrating VPD insights into agricultural and water resource management strategies to uphold food security against climatic variations in support of the SDGs.

关键词： Productivity Climate change Precipitation Food security Agriculture Rivers Sustainable development

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