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Pre-ictal causal connectivity reveals the epileptic network characteristics for deep brain stimulation

Neuroscience 2025年 579卷 329-343页

作者： Yifan Wang Tao Yu Yulan Ma Weigang Cui Xueyuan Wang Liankun Ren Yang Li Department of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Beijing Institute of Functional Neurosurgery Department of Functional Neurosurgery Xuanwu Hospital Capital Medical University Beijing 100053 China School of Engineering Medicine Beihang University Beijing 100191 China Department of Neurology Xuanwu Hospital Capital Medical University Beijing 100053 China Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Virtual Reality Technology and Systems Department of Automation Science and Electrical Engineering Beihang University Beijing 100191 China

Deep brain stimulation of anterior nucleus of the thalamus (ANT-DBS) is an effective clinical treatment for drug-resistant focal epilepsy. However, the complex epileptic network characteristics underlying ANT-stimulation effectiveness remain unknown, owing to currently unclear connectivity between ANT and seizure-related cortex in pre-ictal periods. Here, we developed a novel individualized pre-ictal ANT-cortical tripartite connectivity network (PANT-CTCNet), aiming to reveal epileptic network characteristics using intracranial stereo-electroencephalography (sEEG) recordings in five patients with focal epilepsy for 90 trials. Each trial represented a pre-ictal or post-stimulus sEEG duration, which was used to construct the epileptic network. By employing conditional Granger causality, we constructed individualized ANT-cortical connectivity networks and found a common epileptic network centred on ANT closely connected with seizure-related cortex in pre-ictal periods. After ANT stimulation for clinical validation, strengthened pre-ictal connectivity between ANT and epileptogenic zones led to significant decline in the causal intensity of epileptic networks. The PANT-CTCNet can give a quantitative reference for clinical preoperative evaluation of patient suitability for ANT-DBS treatment. These findings regarding epileptic network characteristics provide theoretical basis in the selection of optimal surgical candidates for personalized ANT-DBS.

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LEFV: A Lightweight and Efficient System for Face Verification with Deep Convolution Neural Networks 19

LEFV: A Lightweight and Efficient System for Face Verificati...

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Proceedings of the 3rd International Conference on Video and Image Processing

作者： Ming Liu Ping Zhang Qingbao Li Jinjin Liu Zhifeng Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781450376822

The emergence of deep learning has made great progress in face recognition. With the popularization of embedded devices, deploying the deep model on embedded devices has become a trend. Most high-precision models require lots of computation costs. Therefore, developing a lightweight deep face recognition system running on embedded devices is a hot topic in current research. To achieve high-accuracy real-time performance of an embedded device, we now present a simple and effective face recognition system LEFV, including face detection, face normalization and face recognition. The quantitative experiments on two large-scale challenging datasets, WIDER FACE dataset and IJB-A dataset, show competitive performances on both runtime and accuracy.

关键词： Face Verification Face Detection Deep Convolution Neural Networks Lightweight Model

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Efficient Low-Resolution Face Recognition via Bridge Distillation

arXiv

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arXiv 2024年

作者： Ge, Shiming Zhao, Shengwei Li, Chenyu Zhang, Yu Li, Jia The Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China SenseTime Group Limited 100084 China The State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China The Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China The Peng Cheng Laboratory Shenzhen518055 China

Face recognition in the wild is now advancing towards light-weight models, fast inference speed and resolution-adapted capability. In this paper, we propose a bridge distillation approach to turn a complex face model pretrained on private high-resolution faces into a light-weight one for low-resolution face recognition. In our approach, such a cross-dataset resolution-adapted knowledge transfer problem is solved via two-step distillation. In the first step, we conduct cross-dataset distillation to transfer the prior knowledge from private high-resolution faces to public high-resolution faces and generate compact and discriminative features. In the second step, the resolution-adapted distillation is conducted to further transfer the prior knowledge to synthetic low-resolution faces via multi-task learning. By learning low-resolution face representations and mimicking the adapted high-resolution knowledge, a light-weight student model can be constructed with high efficiency and promising accuracy in recognizing low-resolution faces. Experimental results show that the student model performs impressively in recognizing low-resolution faces with only 0.21M parameters and 0.057MB memory. Meanwhile, its speed reaches up to 14,705, 934 and 763 faces per second on GPU, CPU and mobile phone, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Multi-task learning

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Software Supply Chain Analysis Based on Function Similarity

Software Supply Chain Analysis Based on Function Similarity

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作者： Wenjie Sun Zheng Shan Fudong liu Xingwei Li Meng Qiao Chunyan Zhang State Key Laboratory of Mathematical Engineering and Advanced Computing

The supply of open source and open source components is growing at an alarming rate,while vulnerabilities in open source components are *** supply chain analysis aims to discover third-party components and open source code used in a software,and analyze the software's dependence on *** this paper,we propose a software component analysis method and a known vulnerabilities detecting *** scanning the open source components of the binary file and conducting vulnerability analysis,the known vulnerabilities are *** paper mainly solves the problem of detecting known vulnerabilities in the supply chain of binary *** conducted a case analysis and achieved good results.

关键词： OpenSSL Software Supply Chain Analysis Based on Function Similarity

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Ultra-Fast Mini License Plate Recognition System Based-on Vision Processing Unit 2

Ultra-Fast Mini License Plate Recognition System Based-on Vi...

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2nd International Conference on Big-Data Service and Intelligent Computation, BDSIC 2020

作者： Wang, Junhui Ren, Shuangyin He, Jiezhong Ji, Xiaolan Huang, Diqing College of Computer National University of Defense Technology State Key Laboratory of Mathematical Engineering and Advanced Computing China College of Computer National University of Defense Technology

ISBN: (纸本)9781450388399

As more embedded environments need license plate recognition systems, how to recognize car plates with high speed/accuracy and low energy has become an important and challenging problem. In this paper, we propose a ultra-Fast miNi (FaNi) license plate recognition (LPR) system. The FaNi system are divided into one training sub-system and one inference sub-system. The former are used to get some offline features;then, the latter is deployed online to recognize license numbers with nearly real-time speed. The inference system is comprised of the vision processing unit (VPU) and the display unit. These two parts are both implemented with hardware logic. Experiments show that the FaNi system can obtain high accuracy and high speed with low resource cost. © 2020 ACM.

关键词： Field programmable gate arrays (FPGA)

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NAS Honeypot Technology Based on Attack Chain

NAS Honeypot Technology Based on Attack Chain

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作者： Bing Liu Hui Shu Fei Kang State Key Laboratory of Mathematical Engineering and Advanced Computing

With the wide application of network attached storage(NAS), the security problem is becoming more and more serious, together with the increasingly fierce attacks against NAS devices of different manufacturers. In order to better capture various types of attacks against NAS devices and detect security threats in time, this paper proposes a solution named NAS honeypot,mining the potential security threats through modeling and analyzing the NAS threats. Then a NAS honeypot based on device virtualization technology and depth monitoring and attack induction was designed on the basis of the construction NAS attack chain. Experimental results show that the NAS honeypot can effectively capture, record and analyze network attacks against multi-types NAS devices with a strong guiding effect in mastering popular attack method of NAS devices and alleviating the security threats of NAS.

关键词： NAS Threat modeling Attack chain Honeypot

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Field-tuned magnetic structure and phase diagram of the honeycomb magnet YbCl_(3)

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Science China(Physics,Mechanics & Astronomy) 2021年第3期64卷 84-89页

作者： YiQing Hao HongLiang Wo YiMeng Gu XiaoWen Zhang YiQing Gu ShiYi Zheng Yang Zhao GuangYong Xu Jeffrey WLynn Kenji Nakajima Naoki Murai WenBin Wang Jun Zhao State Key Laboratory of Surface Physics and Department of Physics Fudan UniversityShanghai 200433China NIST Center for Neutron Research National Institute of Standards and TechnologyGaithersburg 20899USA Department of Materials Science and Engineering University of MarylandCollege Park 20742USA J-PARC Center Japan Atomic Energy Agency(JAEA)Ibaraki 319-1195Japan Institute of Nanoelectronic Devices and Quantum Computing Fudan UniversityShanghai 200433China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093China

We report thermodynamic and neutron diffraction measurements on the magnetic ordering properties of the honeycomb lattice magnet YbCl_(3). We find YbCl_(3) exhibits a Ne′el type long-range magnetic order at the wavevector(0, 0, 0) below TN= 600 *** magnetic order is associated with a small sharp peak in heat capacity and most magnetic entropy release occurs above the magnetic ordering temperature. The magnetic moment lies in-plane, parallel to the monoclinic a-axis, whose magnitude mYb= 0.86(3) μBis considerably smaller than the expected fully ordered moment of 2.24 μBfor the doublet crystal-field ground state. The magnetic ordering moment gradually increases with increasing magnetic field perpendicular to the ab-plane, reaching a maximum value of 1.6(2) μBat 4 T, before it is completely suppressed above ~ 9 T. These results indicate the presence of strong quantum fluctuations in YbCl_(3).

关键词： magnetic order neutron diffraction honeycomb lattice

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Research on the Protection Mechanism of Cisco IOS Exploit

Research on the Protection Mechanism of Cisco IOS Exploit

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作者： Jinzhu Wang Ruijie Cai Shengli Liu State Key Laboratory of Mathematical Engineering and Advanced Computing

Cisco IOS is an operating system that runs on Cisco routing and switching *** security is important to the entire *** vulnerability attacks have become one of the main sources of threat to Cisco IOS security,it is necessary to analyze the defense mechanism of IOS against vulnerability *** purpose of this paper is to find out the deficiencies of IOS vulnerability defense mechanism in time and put forward improvement methods and preventive ***,this paper introduces the protection mechanism of Cisco IOS vulnerability,including CheckHeaps,DEP,*** principle of these mechanisms and the idea of vulnerability protection are *** then,after analyzing the shortcomings of these protection mechanisms,the basic idea of bypassing these protection mechanisms is ***,in view of the shortcomings of Cisco IOS vulnerability defense mechanism and the proposed bypass methods,some advices about how to better protect Cisco IOS from vulnerability exploitation are given.

关键词： Research on the Protection Mechanism of Cisco IOS Exploit Cisco IOS

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Thin-film neural networks for optical inverse problem

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Light(advanced Manufacturing) 2021年第4期2卷 23-30页

作者： Lingjie Fan Ang Chen Tongyu Li Jiao Chu Yang Tang Jiajun Wang Maoxiong Zhao Tangyao Shen Minjia Zheng Fang Guan Haiwei Yin Lei Shi Jian Zi State Key Laboratory of Surface Physics Key Laboratory of Micro-and Nano-Photonic Structures(Ministry of Education)and Department of PhysicsFudan UniversityShanghai 200433China Shanghai Engineering Research Center of Optical Metrology for Nano-fabrication(SERCOM) Shanghai 200433China Institute for Nanoelectronic devices and Quantum computing Fudan UniversityShanghai 200438China Collaborative Innovation Center of Advanced Microsstructures Nanjing UniversityNanjing 210093China

The thin-film optical inverse problem has attracted a great deal of attention in science and industry,and is widely applied to optical ***,as the number of layers increases,the time it takes to extract the parameters of thin films drastically ***,we introduce the idea of exploiting the structural similarity of all-optical neural networks and applied it to the optical inverse *** propose thin-film neural networks(TFNNs)to efficiently adjust all the parameters of multilayer thin *** test the performance of TFNNs,we implemented a TFNN algorithm,and a reflectometer at normal incidence was *** on multilayer thin films with 232 layers,it is shown that TFNNs can reduce the time consumed by parameter extraction,which barely increased with the number of layers compared with the conventional *** were also used to design multilayer thin films to mimic the optical response of three types of cone cells in the human *** light passing through these multilayer thin films was then recorded as a colored photo.

关键词： method inverse film

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Arbitrary coherent distributions in a programmable quantum walk

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Physical Review Research 2022年第2期4卷 023042-023042页

作者： Rong Zhang Ran Yang Jian Guo Chang-Wei Sun Yi-Chen Liu Heng Zhou Ping Xu Zhenda Xie Yan-Xiao Gong Shi-Ning Zhu National Laboratory of Solid State Microstructure School of Physics School of Electronic Science and Engineering and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China College of Electronic and Optical Engineering Nanjing University of Posts and Telecommunication Nanjing 210023 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computing National University of Defense Technology Changsha 410073 China

The coherent superposition of position states in a quantum walk (QW) can be precisely engineered towards the desired distributions to meet the need of quantum information applications. The coherent distribution can make full use of quantum parallel in computation and simulation. Particularly, the uniform superposition provides the robust nonlocality, which has wide applications such as the generation of genuine multibit random numbers without postprocessing. We experimentally demonstrate that the rich dynamics featured with arbitrary coherent distributions can be obtained by introducing different sets of the time- and position-dependent operations. Such a QW is realized by a resource-constant and flexible optical circuit, in which the variable operation is executed based on a Sagnac interferometer in an intrinsically stable and precisely controlled way. Our results contribute to the practical realization of quantum-walk-based quantum computation, quantum simulations, and quantum information protocols.

关键词： Quantum control Quantum information architectures & platforms Quantum protocols

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