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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Sun, Daobo Sun, Kang Qin, Shuo Tang, Bin Meng, Xiangxu College of Computer Science and Technology Harbin Engineering University Harbin China Beijing Institute of Spacecraft System Engineering Beijing China Qingdao Innovation and Development Base of Harbin Engineering University Qingdao China

ISBN: (纸本)9781665410205

Remote sensing image change detection (RSCD) is an active research area in remote sensing. Existing convolutional neural networks (CNN) and Transformer methods operate on images in Euclidean space, limiting flexible perception and interaction among different positions. Recent advancements in various fields have focused on transferring feature processing to non-Euclidean space, allowing for more flexible feature learning. Mapping different locations of high-resolution remote sensing images into non-Euclidean space enables more flexible perception of individual pixels. Motivated by this, we have developed a method solely based on GNN, termed Pure GNN-based Method with the Mutual Information Sensing (PGNet), specifically for detecting changes in remote sensing. In the PGNet framework, Graph Convolutional Networks (GCNs) are employed to derive graph-level characteristics. By aggregating information from neighboring nodes in the graph, we capture richer and more detailed features. Subsequently, by fusing the shallow and deep distributions of local and global features of bi-temporal remote sensing images, we achieve an effective combination of fine-grained and macro-level information. Finally, in order to make explicit semantic perception of bi-temporal images, we propose a Mutual Information Sensing module, which encourages bi-temporal feature pairs to enhance their understanding of each other's semantic information. To confirm the efficacy of PGNet, we carried out a series of tests with advanced techniques across multiple datasets. The outcomes show that our model surpasses existing CNN and Transformer-based methods in precision. © 2024 IEEE.

关键词： Convolutional neural networks

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MPI Allgather Utilizing CXL Shared Memory Pool in Multi-Node Computing systems

MPI Allgather Utilizing CXL Shared Memory Pool in Multi-Node...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Ahn, Hooyoung Kim, Seonyoung Park, Yoomi Han, Woojong Ahn, Shinyoung Tran, Tu Ramesh, Bharath Subramoni, Hari Panda, Dhabaleswar K. Supercomputing System Research Section Electronics and Telecommunications Research Institute Korea Republic of The Ohio State University Department of Computer Science and Engineering United States

ISBN: (纸本)9798350362480

In Artificial Intelligence (AI) and high-performance computing (HPC), growing data and model sizes require distributed processing across multiple nodes due to single-node limitations, increasing inter-node communication. To address these challenges, we propose a novel MPI allgather method leveraging CXL technology, which supports composable architectures and dynamic resource allocation in data centers and HPC systems. Notably, CXL 3.1 facilitates cache coherence among nodes. The proposed allgather method uses the CXL shared memory pool as a communication buffer, outperforming existing algorithms for two reasons: First, CXL provides lower latency than Ethernet and IB, and second, by using the CXL shared memory pool as a shared communication buffer across multiple nodes, it significantly reduces the number of communications. To the best of our knowledge, this work is the first to explore combining MPI collective communication with CXL technology to optimize MPI allgather. Our proposed allgather method significantly reduces communication latency compared to traditional allgather methods by up to 42.14x, with a minimum improvement of 2.91x, as measured using the OSU Micro-Benchmark (OMB), a standard MPI benchmarking suite. © 2024 IEEE.

关键词： Resource allocation

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Deep Learning-based Mortality Prediction of COVID-19 Patients with Cardiovascular Disease 9

Deep Learning-based Mortality Prediction of COVID-19 Patient...

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9th IEEE International Conference on Data science in Cyberspace, DSC 2024

作者： Zheng, Huilin Liang, Yingyi Zhang, Daming Shi, Kai Dong, Luxi Xie, Xiaolan Guilin University of Technology Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin University of Technology College of Computer Science and Engineering Guilin China

ISBN: (纸本)9798350391367

Coronavirus disease 2019 (COVID-19) is one of the most dangerous diseases in recorded human history due to its high contagiousness and rapid dissemination. Moreover, people who already have medical issues like cardiovascular disease (CVD) have a higher risk of getting seriously ill. Therefore, this study proposes a deep learning-based prediction model for the mortality of COVID-19 patients with CVD. The research substances are introduced as follows. First, we obtain the original dataset from the Kaggle website provided by the Mexican government, and extract our experimental data. After that, we develop a deep learning-based prediction model for the mortality of COVID-19 patients with CVD while applying a 5-fold cross-validation approach for the model training and validation. Finally, we evaluate the performance of the proposed model and also compare it with many common machine learning models. In our experimental results, the proposed model achieved higher performance than all of the other models. It facilitates decision-making and provides an accurate mortality prediction for COVID-19 patients with CVD. © 2024 IEEE.

关键词： COVID-19

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A Hybrid Temporal-Magnitude Based Sampling for Event-Based Control 3

A Hybrid Temporal-Magnitude Based Sampling for Event-Based C...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Miguel-Escrig, Oscar Sanchez-Moreno, Jose Romero-Perez, Julio-Ariel Dormido-Bencomo, Sebastian Universitat Jaume I Department of System Engineering and Design Castelló de la Plana Spain Department of Computer Science and Automatic Control Madrid Spain

ISBN: (纸本)9798331540319

In the current industrial environment, which is shifting towards an event-based control prone paradigm, sampling strategies in use must be revisited. Both temporal and magnitude dependent sampling strategies have been demonstrated to be suitable for control systems, reporting benefits in different categories. However, these sampling strategies also present some drawbacks, discussed in this contribution. Aiming to address some of these drawbacks, a new sampling strategy is proposed gathering characteristics of both predecessors. © 2024 IEEE.

关键词： Decentralized control

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Error Dependent Sampling to Reduce Transient Events in Event Based Control 3

Error Dependent Sampling to Reduce Transient Events in Event...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Miguel-Escrig, Oscar Romero-Perez, Julio-Ariel Sanchez-Moreno, Jose Dormido-Bencomo, Sebastian Universitat Jaume I Department of System Engineering and Design Castelló de la Plana Spain Department of Computer Science and Automatic Control Madrid Spain

ISBN: (纸本)9798331540319

One of the objectives of event-based control is the reduction of generated events to perform an appropriate process control. Among the event generation techniques used to this end, those quantifying the error signal can be found more frequently for its simplicity of implementation. However, they entail a drawback in the form of trade-off between event generation and performance. Aiming to reduce the number of events, specifically in the transient response, without degrading the performance, an error dependent sampling scheme is studied in this work. © 2024 IEEE.

关键词： Electromagnetic transients

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Resilience assessment framework toward interdependent bus-rail transit network:Structure,critical components,and coupling mechanism

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Communications in Transportation Research 2023年第1期3卷 118-129页

作者： Bing Liu Xiaoyue Liu Yang Yang Xi Chen Xiaolei Ma School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Civil&Environmental Engineering University of UtahSalt Lake CityUT84112USA School of Computer Science and Engineering Beihang UniversityBeijing100191China Key Laboratory of Intelligent Transportation Technology and System Ministry of EducationBeijing100191China

Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation ***,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal ***,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various ***,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or *** proposed framework is validated via a case study of a BRTN in Beijing,*** indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent ***,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional *** findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.

关键词： Complex network Bus-rail transit network Resilience analysis Interdependent coupling relationship Classification analysis

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Vacancy Modulated Analog Resistive Switching Memory Device Based on Bilayer of Zn@ZnO/ZnO for Neuromorphic Computing 30

Vacancy Modulated Analog Resistive Switching Memory Device B...

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30th IEEE International Conference on Electronics, Circuits and systems, ICECS 2023

作者： Khan, Muhammad Umair Mohammad, Baker Khalifa University System on Chip Center Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350326499

This work proposed a vacancy-modulated analog resistive random-access memory (ReRAM) for neuromorphic computing, utilizing a structure composed of Ag/Zn@ZnO/ZnO/FTO. The resistive switching behavior can be modulated by the movement of oxygen vacancies under positive or negative voltages. This characteristic leads to the desired resistive switching behavior for neuromorphic computing. The Ag/Zn@ZnO/ZnO/FTO based analog ReRAM exhibits several desirable features, including a low operation current, forming-free operation, and self-compliance. The conductance change rate of the device can be adjusted efficiently by modifying the amplitudes and pulse intervals of spike pulses. The device can be used for short-time memory (STM) and long-term memory (LTM) memory operations with good retention time. These characteristics align with the requirements for next-generation ReRAM. The introduction of the Ag/Zn@ZnO/ZnO/FTO-based device structure paves the way for the future development of neuromorphic computing memory applications. © 2023 IEEE.

关键词： Zinc oxide

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Position Measurement Based Slave Torque Feedback Control for Teleoperation systems With Time-Varying Communication Delays

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 388-402页

作者： Xian Yang Jing Yan Changchun Hua Xinping Guan the Institute of Information Science and Engineering Yanshan University the Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004China IEEE the Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China

Bilateral teleoperation system is referred to as a promising technology to extend human actions and intelligence to manipulating objects *** the tracking control of teleoperation systems,velocity measurements are necessary to provide feedback ***,due to hardware technology and cost constraints,the velocity measurements are not always *** addition,the time-varying communication delay makes it challenging to achieve tracking *** paper provides a solution to the issue of real-time tracking for teleoperation systems,subjected to unavailable velocity signals and time-varying communication *** order to estimate the velocity information,immersion and invariance(I&I)technique is employed to develop an exponential stability velocity *** the proposed velocity observer,a linear relationship between position and observation state is constructed,through which the need of solving partial differential and certain integral equations can be ***,the mean value theorem is exploited to separate the observation error terms,and hence,all functions in our observer can be analytically *** the estimated velocity information,a slave-torque feedback control law is presented.A novel Lyapunov-Krasovskii functional is constructed to establish asymptotic tracking *** particular,the relationship between the controller design parameters and the allowable maximum delay values is ***,simulation and experimental results reveal that the proposed velocity observer and controller can guarantee that the observation errors and tracking error converge to zero.

关键词： Asymptotic stability bilateral teleoperation time-varying delay velocity observer

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CFD Simulation of Flight Vehicle Optical Dome and Flow Field Based on Solid-Fluid Coupling Approach 25

CFD Simulation of Flight Vehicle Optical Dome and Flow Field...

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25th IEEE China Conference on system Simulation Technology and its Application, CCSSTA 2024

作者： Li, Jing Wang, Qilong Xu, Liang Wan, Ziming Zhao, Yan Zhao, Xuewen Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin China Beijing Institude of Electronic System Engineering Beijing China

ISBN: (纸本)9798350366600

At high velocity flight, the infrared imaging system encounters significant aero-optical disturbances due to the uneven gas flow around the aircraft's forward section and the elevated temperatures of the optical dome. In the simulation study of aero-optical effects, hydrodynamic calculations of the gas flow field and optical dome are required. This paper examines the utilization of the solid-fluid coupling approach in simulating aero-optical phenomena from the perspective of fluid dynamics computations. This paper undertakes the geometric modelling of the airflow environment and optical dome of a blunt-nose front-window flight vehicle. Utilizing ICEM, the mesh generation for both the gaseous flow domain and the solid optical dome is executed. Subsequently, Fluent software facilitates the performance of hydrodynamic simulations, concurrently extracting vital parameters from both the flow field and the optical dome. The method in this paper can be used in the calculation and analysis of aero-optical effects of high-speed flight vehicles. © 2024 IEEE.

关键词： Flow of gases

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Distributed Hierarchical AI Architecture for Meta-Described Local Dynamic Maps in Autonomous Driving 16

Distributed Hierarchical AI Architecture for Meta-Described ...

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16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Miyata, Hiroshi Arimoto, Kazutami Saitoh, Masatoshi Hayami, Atsushi Mizuno, Hisayoshi Shimazu, Yukihiko Yokogawa, Tomoyuki Technoaccel Networks Corp. Tokyo Office Tokyo Japan Okayama Prefectural University Computer Science and System Engineering Sousya Okayama Japan Toyota Motor Corporation Information and Communication Planning Division Tokyo Japan Okayama Prefectural University Computer Science and System Engneering Sousya Okayama Japan

ISBN: (纸本)9798350377903

In autonomous driving, sharing information among vehicles to enhance safety is an important issue. However, it is not yet clear how each terminal car processes information and how to share it with other cars. Therefore, this paper proposes a distributed hierarchical AI architecture in which each edge distributed terminal of a car or intermediate cloud is equipped with a processing AI that generates metadata and builds them hierarchically. The hierarchical AI consists of multiple AI information processing layers and generates metadata links by concatenating the output of each layer. The hierarchical and spatially distributed nature of information processing allows for a compact digital twin that enables efficient spatiotemporal processing by receiving only the data necessary for that terminal and facilitating the processing necessary for that terminal. As a concrete example, we created software for vehicle front camera image processing for local dynamic maps for autonomous driving, and we evaluated the intensity and processing load of the proposed architecture. In the future, we will continue to study the software and hardware necessary to increase the hierarchy and speed of AI processing. © 2024 IEEE.

关键词： Spatio-temporal data

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