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Pindel-TD:A Tandem Duplication Detector Based on A Pattern Growth Approach

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Genomics, Proteomics & Bioinformatics 2024年第1期22卷 99-104页

作者： Xiaofei Yang Gaoyang Zheng Peng Jia Songbo Wang Kai Ye School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Center for Mathematical Medical the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China moe key lab for intelligent networks&networks security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Faculty of Science Leiden UniversityLeiden 2311 EZNetherland

Tandem duplication(TD)is a major type of structural variations(SVs)that plays an important role in novel gene formation and human ***,TDs are often missed or incorrectly classified as insertions by most modern SV detection methods due to the lack of specialized operation on TD-related mutational ***,we developed a TD detection module for the Pindel tool,referred to as Pindel-TD,based on a TD-specific pattern growth ***-TD is capable of detecting TDs with a wide size range at single nucleotide *** simulated and real read data from HG002,we demonstrated that Pindel-TD outperforms other leading methods in terms of precision,recall,F1-score,and ***,by applying Pindel-TD to data generated from the K562 cancer cell line,we identified a TD located at the seventh exon of SAGE1,providing an explanation for its high ***-TD is available for non-commercial use at https://***/xjtu-omics/pindel.

关键词： Tandem duplication Pattern growth Short-read sequencing Structural variation SAGE1

The Immense Impact of Reverse Edges on Large Hierarchical networks

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Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang moe Engineering Research Center of Autonomous intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu key laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary moe key laboratory for intelligent networks and Network security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

Graph neural network based approach Che upo to automatically assigning common weakness enumeration identifiers for vulnerabilities

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Cybersecurity 2024年第3期7卷 1-15页

作者： Peng Liu Wenzhe Ye Haiying Duan Xianxian Li Shuyi Zhang Chuanjian Yao Yongnan Li key lab of Education Blockchain and intelligent Technology Ministry of EducationGuangxi Normal UniversityGuilin 541004China School of Software Beihang UniversityBeijing 100000China School of National security People's Public Security University of ChinaBeijing 1000000China Guangxi key lab of Multi-Source Information Mining and security Guangxi Normal UniversityGuilin 541004China

Vulnerability reports are essential for improving software security since they record key information on *** a report,CWE denotes the weakness of the vulnerability and thus helps quickly understand the cause of the ***,CWE assignment is useful for categorizing newly discovered *** this paper,we propose an automatic CwE assignment method with graph neural ***,we prepare a dataset that contains 3394 real world vulnerabilities from Linux,OpenSSL,Wireshark and many other software ***,we extract state-ments with vulnerability syntax features from these vulnerabilities and use program slicing to slice them according to the categories of syntax *** top of slices,we represent these slices with graphs that characterize the data dependency and control dependency between ***,we employ the graph neural networks to learn the hidden information from these graphs and leverage the Siamese network to compute the similarity between vulnerability functions,thereby assigning CWE IDs for these *** experimental results show that the proposed method is effective compared to existing methods.

关键词： Vulnerability categorization CWE Graph representation GNN

Tjong:A transformer‐based Mahjong AI via hierarchical decision‐making and fan backward

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 982-995页

作者： Xiali Li Bo Liu Zhi Wei Zhaoqi Wang Licheng Wu School of Information and Engineering Minzu University of ChinaBeijingChina key laboratory of Ethnic Language intelligent Analysis and security Governance of moe Minzu University of ChinaBeijingChina Department of Computer Science New Jersey Institute of TechnologyNewarkNew JerseyUSA

Mahjong,a complex game with hidden information and sparse rewards,poses significant *** Mahjong AIs require substantial hardware resources and extensive datasets to enhance AI *** authors propose a transformer‐based Mahjong AI(Tjong)via hierarchical decision‐*** utilising self‐attention mechanisms,Tjong effectively captures tile patterns and game dynamics,and it decouples the decision pro-cess into two distinct stages:action decision and tile *** design reduces de-cision complexity ***,a fan backward technique is proposed to address the sparse rewards by allocating reversed rewards for actions based on winning *** consists of 15M parameters and is trained using approximately 0.5 M data over 7 days of supervised learning on a single server with 2 *** action decision achieved an accuracy of 94.63%,while the claim decision attained 98.55%and the discard decision reached 81.51%.In a tournament format,Tjong outperformed AIs(CNN,MLP,RNN,ResNet,VIT),achieving scores up to 230%higher than its ***-more,after 3 days of reinforcement learning training,it ranked within the top 1%on the leaderboard on the Botzone platform.

关键词： decision making deep learning deep neural networks

Optimal coordination of zero carbon building energy systems

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National Science Open 2024年第3期3卷 13-28页

作者： Wangyi Guo Zhanbo Xu Jinhui Liu Yaping Liu Jiang Wu Kun Liu Xiaohong Guan School of Future Technology Xi'an Jiaotong University Ministry of Education key lab for intelligent networks and Network security School of Automation Science and EngineeringXi'an Jiaotong University Center for intelligent and Networked Systems Department of AutomationTNLISTTsinghua University

Optimal scheduling of renewable energy sources and building energy systems serves as a pivotal strategy for achieving zero carbon ***,the coordination of zero carbon building energy systems(ZCBS) is still challenging due to the complicated interactions among multi-energy hybrid storage and the complex coordination between seasonal and daily ***,this study develops a coordination scheduling approach for *** operation model and a seasonal-daily scheduling approach are developed to optimize the operation of hydrogen,geothermal,and water storage *** performance of the developed method is demonstrated using numerical case *** results show that the ZCBS can be achieved by using renewable energy sources with the system flexibility provided by hydrogen,geothermal,and water storage *** is also found that the developed scheduling approach reduces operation costs by more than 43.4%under the same device capacity,compared with existing scheduling approaches.

关键词： zero carbon building energy systems seasonal-daily scheduling multi-energy storage two-stage robust optimization

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反向连边在大型分层网络中的影响（英文）

Engineering 2024年第5期 240-249页

作者：曹浩森胡斌斌莫小雨陈都鑫高建喜袁烨陈关荣 Tamás Vicsek 管晓宏张海涛 moe Engineering Research Center of Autonomous intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology School of Mechanical and Aerospace Engineering Nanyang Technological University Jiangsu key laboratory of Networked Collective Intelligence School of Mathematics Southeast University Department of Computer Science Rensselaer Polytechnic Institute Department of Electronic Engineering City University of Hong Kong Department of Biological Physics E?tv?s University moe key laboratory for intelligent networks and Network security School of Automation Science and Engineering Xi'an Jiaotong University

Hierarchical networks are frequently encountered in animal groups, gene networks, and artificial engineering systems such as multiple robots, unmanned vehicle systems, smart grids, wind farm networks,and so forth. The structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes, such as lagging birds' howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social group. This study reveals that, for most large-scale real hierarchical networks, the majority of the reverse edges do not affect the synchronization process of the entire network; the synchronization process is influenced only by a small part of these reverse edges along specific paths. More surprisingly, a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%. The effect of such edges depends not on the network size but only on the average in-degree of the involved subnetwork. The overwhelming majority of active reverse edges turn out to have some kind of ‘‘bunchingo effect on the information flows of hierarchical networks, which slows down synchronization processes. This finding refines the current understanding of the role of reverse edges in many natural, social, and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these networks. Our study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

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Cyclic-delay time-reversal space-time block codes for single-carrier transmission with frequency-domain decision-feedback equalization

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Science China(Information Sciences) 2011年第9期54卷 1905-1915页

作者： FENG Ang,YIN QinYe & WANG HuiMing moe key laboratory for intelligent networks and Network security,Xi’an Jiaotong University,Xi’an 710049,China moe key laboratory for intelligent networks and Network security Xi’an Jiaotong University Xi’an China

Transmit diversity is an important multiple-input multiple-output (MIMO) approach to improve the transmission reliability;however,it is usually designed with maximum-likelihood *** this paper,we investigate a simple transceiver structure for single-carrier MIMO systems,in which the cyclic-delay time-reversal space-time block code (CDTR-STBC) is employed at the transmitter,and the frequency-domain decision-feedback equalization (FD-DFE) is used at the *** separate the transmit antennas into two groups,and then,encode the groups by STBC and cyclically delay the data streams within each *** processing can mitigate the impact of error-propagation and reduce the signal-to-noise ratio (SNR) loss when FD-DFE is employed,in which SNR is defined as the ratio of the received signal power over the noise power at each receive *** support our proposal,this paper also provides the performance analysis of *** is shown that the proposed scheme can achieve full diversity and full transmission rate for a MIMO system employing arbitrary ***,it has considerable performance improvement over the existing schemes.

关键词： single-carrier frequency-domain equalization cyclic delay space-time block code diversity order

AOD estimation in WSN localization system with synthetic aperture technique

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Science China(Information Sciences) 2012年第10期55卷 2216-2225页

作者： WANG WenJie,YAO BoBin & YIN QinYe moe key lab for intelligent networks and Network security,School of Electronic and Information Engineering,Xi’an Jiaotong University,Xi’an 710049,China moe key lab for intelligent networks and Network security School of Electronic and Information Engineering Xi’an Jiaotong University Xi’an China

Angel of departure(AOD) based distributed localization scheme in wireless sensor networks allows the single antenna sensor node to estimate its own AOD information by an equivalent antenna array for further position ***,the condition that the number of antennas at the multi-antenna agent/anchor node should be larger than the number of multipath signal components(MPCs) constrains its actual *** this paper,we provide a more practical approach to achieve AOD information estimation under multipath *** that the sensor node can not identify the line of sight(LOS) signal component due to the insufficient degree of freedom,which is determined by the above limiting condition,we introduce a synthetic aperture technique with the aid of a fast moving multi-antenna agent/anchor *** operation greatly enlarges the degree of freedom of the equivalent antenna array constructed at sensor node end but without requiring other extra physical antennas equipped at agent/anchor node or sensor node end,which means that it relaxes the limiting ***,the AOD information of LOS signal component can be estimated and extracted successfully in complex multipath *** analysis proves the effectiveness of our proposed synthetic aperture technique and numerical simulations show great performance improvement.

关键词： angle of departure degree of freedom synthetic aperture wireless sensor networks

Survey on rain removal from videos or a single image

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Science China(Information Sciences) 2022年第1期65卷 72-94页

作者： Hong WANG Yichen WU Minghan LI Qian ZHAO Deyu MENG School of Mathematics and Statistics Ministry of Education key lab of intelligent networks and Network security Xi'an Jiaotong University Pazhou lab

Rain can cause performance degradation of outdoor computer vision tasks. Thus, the exploration of rain removal from videos or a single image has drawn considerable attention in the field of image processing. Recently, various deraining methodologies have been proposed. However, no comprehensive survey work has yet been conducted to summarize existing deraining algorithms and quantitatively compare their generalization ability, and especially, no off-the-shelf toolkit exists for accumulating and categorizing recent representative methods for easy performance reproduction and deraining capability evaluation. In this regard, herein, we present a comprehensive overview of existing video and single image deraining methods as well as reproduce and evaluate current state-of-the-art deraining methods. In particular, these approaches are mainly classified into model-and deep-learning-based methods, and more elaborate branches of each method are presented. Inherent abilities, especially generalization performance, of the state-of-the-art methods have been both quantitatively and visually analyzed through thorough experiments conducted on synthetic and real benchmark datasets. Moreover, to facilitate the reproduction of existing deraining methods for general users, we present a comprehensive repository with detailed classification, including direct links to 85 deraining papers, 24 relevant project pages, source codes of 12 and 25 algorithms for video and single image deraining, respectively, 5 and 10 real and synthesized datasets, respectively, and 7 frequently used image quality evaluation metrics, along with the corresponding computation codes. Research limitations worthy of further exploration have also been discussed for future research along this direction.

关键词： rain removal maximum a posterior estimation deep learning generalization performance comprehensive repository