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5th China Conference on Intelligent Networked Things, CINT 2022

作者： Cai, Xin Xiao, Feng Wei, Bo State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Electrical Engineering Xinjiang University Urumqi830047 China

ISBN: (纸本)9789811989148

This paper presents a resilient event-triggered distributed algorithm for resource allocation of multi-agent systems under denial-of-service (DoS) attacks. A class of time-sequence-based and aperiodic DoS attacks exists in communication networks. A resilient event-triggered communication scheme is designed to determine when agents communicate with neighbors on the network in the presence of DoS attacks. An explicit condition in terms of the frequency and duration of DoS attacks is obtained to ensure the convergence of the designed resilient algorithm to the optimal allocation. Simulation results are given to validate the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Denial-of-service attack

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PID Control with Model-free Adaptive Mechanism for Electromagnetic Scanning Micromirrors

PID Control with Model-free Adaptive Mechanism for Electroma...

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2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2022

作者： Sun, Wanyan Tan, Qingyuan Tan, Yonghong Tianjin Key Laboratory of Intelligent Robotics Nankai University Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin China University of Windsor Dept. of Electrical and Computer Engineering Windsor Canada College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai China

ISBN: (数字)9781665475433

ISBN: (纸本)9781665475433

In this paper, a model-independent adaptive PID control scheme is proposed for the angle control of electromagnetic scanning micromirrors. In this scheme, only using the input and output data of the micromirror, a model-free adaptive mechanism is designed to adjust the PID parameters online to adapt to the change of the micromirror characteristics due to the hysteresis exists in the micromirror. It makes the deflection angle of the micromirror can track the reference trajectory fast and accurately. Finally, the simulation results show that the proposed control method has achieved better control performance than PID control in controlling the deflection angle of the micromirror. © 2022 IEEE.

关键词： Three term control systems

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Covert Communication in Satellite-Terrestrial systems with a Full-Duplex Receiver

Covert Communication in Satellite-Terrestrial Systems with a...

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2024 International Conference on Satellite Internet, SAT-NET 2024

作者： Guo, Zewei Sun, Ranran He, Ji Shen, Yulong Jiang, Xiaohong Future University Hakodate School of Systems Information Science Hakodate041-8655 Japan Hangzhou Institute of Technology Xidian University Hangzhou311200 China Xidian University School of Computer Science and Technology Xi'an710071 China Institute of Systems General Academy of Systems Engineering Academy of Military Sciences Beijing100101 China Xidian University Shaanxi Key Laboratory of Network and System Security Xi'an710071 China

ISBN: (纸本)9798350375176

This paper investigates the covert communication in a satellite-terrestrial system, including a satellite transmitter Alice, a terrestrial full-duplex receiver Bob and a terrestrial warden Willie. To help the covert transmission from Alice, the full-duplex Bob transmits the jamming signal to confuse Willie and also receives the signal from Alice simultaneously. To explore the fundamental covertness in such a system, we first provide theoretical modelings for satellite-terrestrial downlink, and the detection error probability of Willie. Based on these models, we then study the transmit power optimization for covert rate maximization. Finally, we present extensive numerical results to validate our theoretical analysis and to illustrate the impact of various system parameters on the maximum covert rate. © 2024 IEEE.

关键词： Satellite communication systems

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MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5888-5903页

作者： Zhang, Yaning Wang, Tianyi Yu, Zitong Gao, Zan Shen, Linlin Chen, Shengyong Qilu University of Technology Shandong Academy of Sciences Faculty of Computer Science and Technology Jinan 250014 China National University of Singapore School of Computing 21 Lower Kent Ridge Rd 119077 Singapore Great Bay University School of Computing and Information Technology Dongguan 523000 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen 518060 China Qilu University of Technology (Shandong Academy of Sciences) Shandong Artificial Intelligence Institute Jinan 250014 China Tianjin University of Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin 300384 China Shenzhen University Computer Vision Institute College of Computer Science and Software Engineering Shenzhen 518060 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518129 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen 518060 China

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches mainly capture face forgery patterns using image modality, other modalities like fine-grained noises and texts are not fully explored, which limits the generalization capability of the model. In addition, most FFD methods tend to identify facial images generated by GAN, but struggle to detect unseen diffusion-synthesized ones. To address the limitations, we aim to leverage the cutting-edge foundation model, contrastive language-image pre-training (CLIP), to achieve generalizable diffusion face forgery detection (DFFD). In this paper, we propose a novel multi-modal fine-grained CLIP (MFCLIP) model, which mines comprehensive and fine-grained forgery traces across image-noise modalities via language-guided face forgery representation learning, to facilitate the advancement of DFFD. Specifically, we devise a fine-grained language encoder (FLE) that extracts fine global language features from hierarchical text prompts. We design a multi-modal vision encoder (MVE) to capture global image forgery embeddings as well as fine-grained noise forgery patterns extracted from the richest patch, and integrate them to mine general visual forgery traces. Moreover, we build an innovative plug-and-play sample pair attention (SPA) method to emphasize relevant negative pairs and suppress irrelevant ones, allowing cross-modality sample pairs to conduct more flexible alignment. Extensive experiments and visualizations show that our model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. © 2005-2012 IEEE.

关键词： CLIP Diffusion face forgery detection Image-noise fusion Sample pair attention Transformer

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Bioimaging of Dissolvable Microneedle Arrays: Challenges and Opportunities

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Research 2022年第4期2022卷 633-655页

作者： Yanni Wang Gehua Ma Guangzhi Gao Ji Tao Wenzhao Cao Haohao Sun Fengsen Ma Yilong Zhang Yen Wei Mei Tian Laboratory of Biologics and Biomaterials Collge of PharmacyZhejiang University of TechnologyHangzhou 310014China Cllge of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Human Phenome Institute Fudan UniversityShanghai 201203China College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China Life Science Research Center Frontier Crossing InstituteZhejiang University of TechnologyHangzhou 310023China Engineering Research Center of Intelligent Sensing and System Ministry of EducationHangzhou 310023China College of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310023China Department of Chemistry and the Tsinghua Center for Frontier Polymer Research Tsinghua UniversityBeijing 100084China

The emergence of microneedle arrays(MNAs)as a novel,simple,and minimally invasive administration approach largely addresses the challenges of traditional drug *** particular,the dissolvable MNAs act as a promising,multifarious,and well-controlled platform for micro-nanotransport in medical research and cosmetic formulation *** effective delivery mostly depends on the behavior of the MNAs penetrated into the body,and accurate assessment is urgently *** imaging technologies offer high sensitivity and resolution visualization of cross-scale,multidimensional,and multiparameter information,which can be used as an important aid for the evaluation and development of new *** combination of MNA technology and imaging can generate considerable new knowledge in a cost-effective manner with regards to the pharmacokinetics and bioavailability of active substances for the treatment of various *** addition,noninvasive imaging techniques allow rapid,receptive assessment of transdermal penetration and drug deposition in various tissues,which could greatly facilitate the translation of experimental MNAs into clinical *** on the recent promising development of bioimaging,this review is aimed at summarizing the current status,challenges,and future perspective on in vivo assessment of MNA drug delivery by various imaging technologies.

关键词： needle mostly formulation

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An Effective CU Depth Decision Method for HEVC Using Machine Learning

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computer systems Science & engineering 2021年第11期39卷 275-286页

作者： Xuan Sun Pengyu Liu Xiaowei Jia Kebin Jia Shanji Chen Yueying Wu Beijing University of Technology Beijing100124China Beijing Laboratory of Advanced Information Networks Beijing100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124China Department of Computer Science University of PittsburghPittsburgh15260USA School of Physics and Electronic Information Engineering Qinghai Nationalities University810007QinghaiChina

This paper presents an effective machine learning-based depth selection algorithm for CTU(Coding Tree Unit)in HEVC(High Efficiency Video Coding).Existing machine learning methods are limited in their ability in handling the initial depth decision of CU(Coding Unit)and selecting the proper set of input features for the depth selection *** this paper,we first propose a new classification approach for the initial division depth *** particular,we study the correlation of the texture complexity,QPs(quantization parameters)and the depth decision of the CUs to forecast the original partition depth of the current ***,we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs,picture distortion and the *** the found relationships,we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as ***,we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct *** proposed method can significantly improve the efficiency of interframe coding by circumventing the traversing cost of the division *** shows that the mentioned method can reduce the time spent by 34.56%compared to HM-16.9 while keeping the partition depth of the CUs correct.

关键词： HEVC inter-frame coding CU depth

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A Method for Discovering Hidden Patterns of Cybersecurity Knowledge Based on Hierarchical Clustering∗ 6

A Method for Discovering Hidden Patterns of Cybersecurity Kn...

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6th IEEE International Conference on Data Science in Cyberspace, DSC 2021

作者： Ding, Zhaoyun Cao, Deqi Liu, Lina Yu, Donghua Ma, Haoyang Wang, Fei National University Of Defense Technology Key Laboratory Of Information System Engineering Changsha China School Of Electronic And Information Engineering Soochow University Suzhou China Shaoxing University Department Of Computer Science And Engineering Shaoxing China

ISBN: (纸本)9781665418157

The construction of cybersecurity knowledge graphs improves the full-dimensional cognitive ability of cyber threats. However, most of the current research on the cybersecurity knowledge graphs focuses on the one-hop or multi-hop correlation queries of knowledge, while ignoring the hidden patterns in the knowledge graphs. Based on the knowledge graph stated in this paper[1], we propose a method for discovering hidden patterns of cybersecurity knowledge based on hierarchical clustering, using the hacker group features of security technologies in the knowledge graph, calculating the distance between the security technology knowledge in the knowledge graph based on the Phicoefficient, and mining cybersecurity technologies that are often used by hacker groups by employing the ward linkage method of hierarchical clustering. The experimental results show that three similar cybersecurity technologies, namely Peripheral Device Discovery, Data from Removable Media and Junk Data, all of which are aimed at stealing or attacking the externally-connected devices of computers, are used by most hacker groups. © 2021 IEEE.

关键词： Knowledge graph

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Collaborative Segmentation Model for Colonoscopy Ulcers based on Fuzzy Labeling*

Collaborative Segmentation Model for Colonoscopy Ulcers base...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Yanning Lin Jie Chen Ziqian Ding Linxu Chen Le Li Zhongsheng Zhu Zhaoxia Wang Jianqiang Li College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen Children’s Hospital Shenzhen China Gastroenterology Shenzhen Children’s Hospital China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Inflammatory Bowel Disease (IBD) is a global chronic intestinal inflammatory disease, and its incidence rate increases year by year with the progress of economic globalization. Currently, the diagnosis of IBD in children mainly relies on endoscopic examination, but scoring endoscopic images is a challenging issue, especially in distinguishing different types of ulcers. To address this issue, this article designs a mobile application to accelerate data annotation processing and may provide reference for other unlabeled datasets. In the context of image segmentation, blurring labels has become an important issue. Deep learning methods are widely used in medical image segmentation, but their accuracy depends on high-quality annotated data. However, there are low-quality noise areas in the annotated data, and obtaining accurate and high-quality annotations becomes more time-consuming with limited annotation budgets. This article proposes a collaborative training framework to improve learning of noisy pixels. This framework determines the label confidence of an image by calculating the similarity between image pixels and surrounding pixels. Then, two parallel deep networks were constructed for semantic prediction, which aimed to guide each other on pixels that may have noise. By applying consistency in dual network prediction, the semantic information of uncertain pixels is corrected as much as possible. Experimental results have shown that this framework is slightly superior to models trained with pixel level precise labels, thus more effectively utilizing existing annotated data in the case of fuzzy labels.

关键词： Training Image segmentation Accuracy Annotations Biological system modeling Semantics Noise Collaboration Colonoscopy Medical diagnostic imaging

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Analog parallel processor for broadband multifunctional integrated system based on silicon photonic platform

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Light(Science & Applications) 2025年第3期14卷 746-756页

作者： Na Qian Defu Zhou Haowen Shu Ming Zhang Xingjun Wang Daoxin Dai Xiao Deng Weiwen Zou State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBejingChina State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZhejiang UniversityHangzhouChina

Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial ***,broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic ***,we report an analog parallel processor(APP)based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog *** APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel *** photonic analog parallelism,data rate and data volume in each sequence are simultaneously compressed,which mitigates the requirement on each parallel computing ***,the fusion of the outputs from each computing core is equivalent to directly processing broadband *** the proof-of-concept experiment,two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated *** bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is *** wireless communication rate of 8 Gbit/s is also *** the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture,we anticipate that the proposed APP will accelerate the development of powerful optoelectronic processors as critical support for applications such as satellite networks and intelligent driving.

关键词： analog parallel processor sharing hardware platform multifunctional integrated systems establish full cooperation different functionalities analog parallel processor app based silicon photonic platform electronic circuitryherewe broadband signal

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DeepCell: Multiview Representation Learning for Post-Mapping Netlists

arXiv

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arXiv 2025年

作者： Shi, Zhengyuan Ma, Chengyu Zheng, Ziyang Zhou, Lingfeng Pan, Hongyang Jiang, Wentao Yang, Fan Yang, Xiaoyan Chu, Zhufei Xu, Qiang Department of Computer Science and Engineering The Chinese University of Hong Kong Sha Tin Hong Kong Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China School of Computer Science Hangzhou Dianzi University Hangzhou China School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University Shanghai China National Center of Technology Innovation for EDA Nanjing China

Representation learning for post-mapping (PM) netlists is a critical challenge in Electronic Design Automation (EDA), driven by the diverse and complex nature of modern circuit designs. Existing approaches focus on intermediate representations like And-Inverter Graphs (AIGs), limiting their applicability to post-synthesis stages. We introduce DeepCell, a multiview representation learning framework that integrates structural and functional insights from both PM netlists and AIGs to learn rich, generalizable embeddings. At its core, DeepCell employs the novel Mask Circuit Modeling (MCM) mechanism, which refines PM netlist representations in a self-supervised manner using pretrained AIG encoders. DeepCell sets a new benchmark in PM netlist representation, outperforming existing methods in predictive accuracy and reconstruction fidelity. To validate its efficacy, we apply DeepCell to functional engineering Change Orders (ECO), achieving significant reductions in patch generation costs and runtime while improving patch quality. Copyright © 2025, The Authors. All rights reserved.

关键词： Mapping

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