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12th International Conference on Awareness Science and Technology, iCAST 2023

作者： Kokubun, Kota Li, Tianhui Chen, Wenxi Dept. of Computer and Information Systems The University of Aizu Aizu-Wakamatsu Japan Division of Information System The University of Aizu Aizu-Wakamatsu Japan Dept. of Computer Science and Engineering The University of Aizu Aizu-Wakamatsu Japan

ISBN: (纸本)9798350324693

The aim of this study is to investigate the effect of meteorological factors on heart rate variability (HRV) derived from daily electrocardiogram (ECG) data. Daily meteorological data were obtained from the Japan Meteorological Agency’s database. Daily ECG data were measured while bathing for five y ears. T he s ubject w as a h ealthy m ale i n h is fi fties. After collecting ECG data, R-R intervals were calculated to perform HRV analysis in time domain and frequency domain. The evaluation of link between meteorological factors and HRV parameters was realized by utilizing meteorological factors’ importance calculated by Random Forest, and Steel-Dwass significant difference analysis of the values. Additionally, the evaluation was also performed by analyzing the obtained meteorological factors’ importance values using Granger Causality test. In Steel-Dwass test, several significant d ifferences (p © 2023 IEEE.

关键词： Electrocardiograms

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MVKTrans: Multi-View Knowledge Transfer for Robust Multiomics Classification

MVKTrans: Multi-View Knowledge Transfer for Robust Multiomic...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Cong, Shan Sang, Zhiling Liu, Hongwei Luo, Haoran Wang, Xin Liang, Hong Hao, Jie Yao, Xiaohui Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin China Harbin Engineering University Qingdao Innovation and Development Center Qingdao China Chinese University of Hong Kong Department of Surgery Hong Kong Chinese Academy of Medical Sciences Peking Union Medical College Institute of Medical Information Beijing China

ISBN: (纸本)9798350386226

The distinct characteristics of multiomics data, including complex interactions within and across biological layers and disease heterogeneity (e.g., heterogeneity in etiology and clinical symptoms), drive us to develop novel designs to address unique challenges in multiomics prediction. In this paper, we propose the multi-view knowledge transfer learning (MVKTrans) framework, which transfers intra- and inter-omics knowledge in an adaptive manner by reviewing data heterogeneity and suppressing bias transfer, thereby enhancing classification performance. Specifically, we design a graph contrastive module that is trained on unlabeled data to effectively learn and transfer the underlying intra-omics patterns to the supervised task. This unsupervised pretraining promotes learning general and unbiased representations for each modality, regardless of the downstream tasks. In light of the varying discriminative capacities of modalities across different diseases and/or samples, we introduce an adaptive and bi-directional cross-omics distillation module. This module automatically identifies richer modalities and facilitates dynamic knowledge transfer from more informative to less informative omics, thereby enabling a more robust and generalized integration. Extensive experiments on four real biomedical datasets demonstrate the superior performance and robustness of MVKTrans compared to the state-of-theart. Code and data are available at https://***/Yaolabfantastic/MVKTrans. © 2024 IEEE.

关键词： Contrastive Learning

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Designing low-diameter interconnection networks with multi-ported host-switch graphs

Designing low-diameter interconnection networks with multi-p...

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作者： Yasudo, Ryota Nakano, Koji Koibuchi, Michihiro Matsutani, Hiroki Amano, Hideharu Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan Department of Information and Computer Science Keio University Yokohama Japan

A host-switch graph was originally proposed as a graph that represents a network topology of a computer systems with 1-port host computers and (Formula presented.) -port switches. It has been studied from both theoretical and practical aspects in terms of the diameter, the average shortest path length, and the performance of real applications. In recent high-performance computing systems, however, a host computer is connected to multiple switches by using InfiniBand, NVSwitch, or Omni-Path, and consequently they provide high bandwidths. Since a host-switch graph cannot represent such systems, this article extends a host-switch graph so that it can represent such systems. As a result, a host-switch graph can include multi-ported hosts. Furthermore, we propose to use multi-port hosts for reducing the diameter. We show that the diameter minimization is equivalent to solving the degree diameter problem for bipartite graphs of diameter three. Our experimental results show that we can drastically reduce the diameter as well as increasing the bandwidth and improves performance of MPI applications by up to 162% as compared with networks with single-ported hosts. © 2020 John Wiley & Sons, Ltd.

关键词： Graph theory

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The Asymptotics of Difference systems of Sets for Synchronization and Phase Detection

arXiv

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arXiv 2024年

作者： Tsunoda, Yu Fujiwara, Yuichiro Faculty of Engineering Information and Systems University of Tsukuba Japan Division of Mathematics and Informatics Chiba University Japan

We settle the problem of determining the asymptotic behavior of the parameters of optimal difference systems of sets, or DSSes for short, which were originally introduced for computationally efficient frame synchronization under the presence of additive noise. We prove that the lowest achievable redundancy of a DSS asymptotically attains Levenshtein’s lower bound for any alphabet size and relative index, answering the question of Levenshtein posed in 1971. Our proof is probabilistic and gives a linear-time randomized algorithm for constructing asymptotically optimal DSSes with high probability for any alphabet size and information rate. This provides efficient self-synchronizing codes with strong noise resilience. We also point out an application of DSSes to phase detection. Copyright © 2024, The Authors. All rights reserved.

关键词： Synchronization

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Air Target Threat Assessment Based on Graph Convolutional Neural Network 1

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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Yan, Ma Boyan, Lv Lu, Ding Dan, Huang School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai200240 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Electrical Engineering Guangxi University Nanning530004 China Center for aerospace systems engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

In modern air warfare, battlefield commanders need to make decisions based on the assessment of the threat level of enemy targets. However, excessive threat parameters, complex judgment rules and continuous application of flight formations bring great challenges to threat assessment. To this end, a threat assessment method for air targets based on graph convolutional neural networks is proposed in this paper. In this method, six threat features are selected: speed, distance, altitude, radar cross-section(RCS), jamming signal level (JSL) and closest point of approach (CPA). The topology of flight formation is represented by adjacency matrix, which is used to assess the threat degree of air targets in different flight formation. By extracting the feature of threat coefficient and topology structure, the threat level of target in formation can be evaluated. The test results show that the accuracy of this model can reach 96.75%, which is better than the traditional methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolution

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Creating a semi-opened micro-cavity ovary through sacrificial microspheres as an in vitro model for discovering the potential effect of ovarian toxic agents

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Bioactive Materials 2023年第8期26卷 216-230页

作者： Min Ye Yiran Shan Bingchuan Lu Hao Luo Binhan Li Yanmei Zhang Zixuan Wang Yuzhi Guo Liliang Ouyang Jin Gu Zhuo Xiong Ting Zhang Biomanufacturing Center Department of Mechanical EngineeringTsinghua UniversityBeijing100084China Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing Beijing100084China Biomanufacturing and Engineering Living Systems Innovation International Talents Base(111 Base)Beijing100084China MOE Key Laboratory of Bioinformatics BNRIST Bioinformatics DivisionDepartment of AutomationTsinghua UniversityBeijing100084China

The bio-engineered ovary is an essential technology for treating female *** the development of relevant in vitro models could be a critical step in a drug ***,we develop a semi-opened culturing system(SOCS)strategy that maintains a 3D structure of follicles during the *** on the SOCS,we further developed micro-cavity ovary(MCO)with mouse follicles by the microsphere-templated technique,where sacrificial gelatin microspheres were mixed with photo-crosslinkable gelatin methacryloyl(GelMA)to engineer a micro-cavity niche for follicle *** semi-opened MCO could support the follicle growing to the antral stage,secreting hormones,and ovulating cumulus-oocyte complex out of the MCO without extra *** MCO-ovulated oocyte exhibits a highly similar transcriptome to the in vivo counterpart(correlation of 0.97)and can be ***,we found that a high ROS level could affect the cumulus expansion,which may result in anovulation *** damage could be rescued by melatonin,but the end of cumulus expansion was 3h earlier than anticipation,validating that MCO has the potential for investigating ovarian toxic agents in *** provide a novel approach for building an in vitro ovarian model to recapitulate ovarian functions and test chemical toxicity,suggesting it has the potential for clinical research in the future.

关键词： Bio-engineered ovary SOCS Semi-opened MCO Ovarian model Drug study

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Assessing the Effects of Blackhole Attacks on MANET Reliability and Security

Assessing the Effects of Blackhole Attacks on MANET Reliabil...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Fadhil, Saif Aamer Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad10011 Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Mobile Ad Hoc Networks (MANETs) are characterized by some important attributes, including infrastructure, mobile, and dynamic nature, which makes them have vast applications in different areas of computer networks. The black hole attack falls among the strongly criticized security threats within the framework of the MANETs. This deceptive behavior captures data packets from a source destined for the malicious node and then declines them when they are received. This paper comprehensively reviews prior studies done to analyze and mitigate black hole attacks in MANETs. Besides this, we will conduct a comparative analysis of the research above projects. The present paper extends prior work by actually performing the black hole assault simulations in a MANETs environment. This is done with the aid of the NS2 simulator and the Ad Hoc On-Demands Distance Vector (AODV) routing protocol. In this study, the black hole attack is analyzed and the consequences of the attack are assessed in terms of the system performance and security. We analyze crucial parameters like end-to-end latency, PDR, packet drop, and throughput to evaluate the consequences of this assault. From our results derived from the analysis of our simulations, we aim to present substantial points to do with the impacts of blackhole attacks on MANETs. In this way, our goal is to participate in the perpetually evolving efforts aimed at enhancing the security and reliability of such dynamic networks. © 2024 IEEE.

关键词： Mobile ad hoc networks

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On the Cross-Graph Transferability of Dynamic Link Prediction 25

On the Cross-Graph Transferability of Dynamic Link Predictio...

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34th ACM Web Conference, WWW 2025

作者： Pan, Zhiqiang Gao, Chen Cai, Fei Chen, Wanyu Zhang, Xin Chen, Honghui Li, Yong National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China College of Electronic Countermeasures National University of Defense Technology Hefei China Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9798400712746

Dynamic link prediction aims to predict the future links on dynamic graphs, which can be applied to wide scenarios such as recommender systems and social networks on the World Wide Web. Existing methods mainly (1) focus on the in-graph learning, which cannot generalize to graphs unobserved during training;or (2) achieve the cross-graph predictions in a many-many mechanism by training on multiple graphs across various domains, which results in a large computational cost. In this paper, we propose a cross-graph dynamic link predictor named CrossDyG, which achieves the cross-graph transferability in a one-many mechanism which trains on one single source graph and test on different target graphs. Specifically, we provide causal and empirical analysis on the structural bias caused by the graph-specific structural characteristics in cross-graph predictions. Then, we conduct deconfounded training to learn the universal network evolution pattern from one single source graph during training. Finally, we apply the causal intervention to leverage the graph-specific structural characteristics of each target graph during inference. Extensive experiments conducted on three benchmark data of dynamic graphs demonstrate that CrossDyG outperforms the state-of-the-art baselines by up to 11.01% and 17.02% in terms of AP and AUC, respectively. In addition, the improvements are especially significant when training on small source graphs. © 2025 Copyright held by the owner/author(s).

关键词： Social networking (online)

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Self-Guided Autoencoders for Unsupervised Change Detection in Heterogeneous Remote Sensing Images

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2458-2471页

作者： Shi, Jiao Wu, Tiancheng Kai Qin, Alex Lei, Yu Jeon, Gwanggil Northwestern Polytechnical University School of Electronics and Information Xi'an710129 China Northwestern Polytechnical University in Shenzhen Research and Development Institute Shenzhen518057 China Chongqing Innovation Center of Northwestern Polytechnical University Chongqing401135 China Swinburne University of Technology Department of Computer Science and Software Engineering HawthornVIC3122 Australia Incheon National University Department of Embedded Systems Engineering Incheon22012 Korea Republic of

To address the problem of enormous differences in two heterogeneous images, the traditional unsupervised frameworks are most normally realized by converting two images into a common domain with various auxiliary strategies, such as transformation and alignment, which requires extensive calculation and has difficulty balancing the training tasks. To achieve a concise framework, this article proposes self-guided autoencoders (SGAE) for unsupervised change detection (CD) in heterogeneous remote sensing images (RSIs). Unlike traditional methods that aim to narrow the differences of heterogeneous images to highlight the changed information, SGAE forces the flow of identification in formation generated in unlabeled data through self-guided iterations. First, initial unsupervised networks output an elementary change map that will be screened to obtain reliable pseudolabels. The selected pseudolabeled samples will be used as the input of a supervised network to obtain another change map. Then, multiple change maps will be fused to refine the confidence of pseudolabels again, obtaining new fused pseudolabeled samples for the self-guided network, which will be trained with pseudolabeled samples and unlabeled samples. Finally, the above operations will be repeated to continuously optimize the net, which helps itself to extract the discriminative features for classification in self-guided iterations. Experiments compared with several algorithms on four datasets demonstrate the effectiveness and robustness of our method, which can help unsupervised models improve discriminative feature extraction and classification performance with a more flexible learning method. © 2020 IEEE.

关键词： Feature extraction

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Routing Guidance for Emerging Transportation systems with Improved Dynamic Trip Equity

arXiv

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arXiv 2025年

作者： Bai, Ting Li, Anni Xu, Gehui Cassandras, Christos G. Malikopoulos, Andreas A. Information and Decision Science Lab School of Civil & Environmental Engineering Cornell University IthacaNY United States Division of Systems Engineering Center for Information and Systems Engineering Boston University BrooklineMA United States Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom

In this letter, we present a dynamic routing guidance system that optimizes route recommendations for individual vehicles within an emerging transportation system while enhancing travelers’ trip equity. We develop a framework to quantify trip quality and equity in a dynamic travel environment, providing new insights into how routing guidance influences equity in road transportation. Our approach enables real-time routing by incorporating both monitored and anticipated traffic congestion. We provide conditions that ensure achieving perfect trip equity for all travelers in a free-flow network. Finally, simulation studies on 1,000 vehicles traversing an urban road network in Boston demonstrate that our proposed method improves trip equity by approximately 13.3% compared to the shortest-route strategy. In addition, the results reveal that our approach redistributes travel costs across vehicle types through route optimization, contributing to a more equitable transportation system. Copyright © 2025, The Authors. All rights reserved.

关键词： Traffic congestion

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