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A regularized magnetotelluric inversion with a minimum support gradient constraint

Earthquake Science 2020年第3期33卷 130-140页

作者： Junjun Zhou Xiangyun Hu Tiaojie Xiao Institute of Geophysics and Geomatics China University of GeosciencesWuhan 430000China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China

Magnetotelluric(MT)inversion is an illposed problem and the standard way to address it is through regularization,by adding a stabilizing functional to the data objective functional in order to obtain a stable *** traditional stabilizing functionals,in which a low-order differential operator is used,yield a smooth solution that may not be appropriate when anomalies occur in block *** some cases the focused imaging of a sharp electrical boundary is *** though various experiments have used stabilizing functionals that are suitable to obtain a clear and sharp boundary,such as the minimum support(MS)and the minimum gradient support(MGS)functionals,there are still some limitations in *** this paper,the minimum support gradient(MSG)is proposed as the stabilizing *** the uniform regularization framework,a regularized inversion with a variety of stabilizing functionals is performed and the inversion results are *** study shows that MSG inversion can not only obtain a clearly focused inversion but also a quite stable and robust one.

关键词： magnetotelluric focus inversion sharp boundary regulafization

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Optimization and parallelization Single Particle Cryo-EM Software RELION with GPU

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2018年第2期55卷 409-417页

作者： Su, Huayou Wen, Wen Li, Dongsheng Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China

Single particle cryo-electron microscopy (cryo-EM) is one of the most important methods of macromolecular structure. RELION (regularized likelihood optimization) is an open-source computer program for the refinement of macromolecular structures by single-particle analysis of cryo-EM data. Due to its easy usage and high quality results, RELION has attracted a lot of attentions from researchers. However, the computation requirement of this program is too huge to solve some large molecular structures with CPU, which harpers the popularization of RELION. In this paper, we characterize the algorithm of RELION and parallelize it with GPU. Firstly, the mathematical theory, computer patterns and performance bottlenecks of RELION are analyzed comprehensively. Then, we optimize the program targeting at fine-grained many-core architecture processor, such as GPU. We propose an efficient multi-level parallel model to utilize the powerful computation capacity of many-core processor. In order to achieve high performance, we reconstruct the data structure for GPU continues memory access. To avoid the limitation of GPU memory size, we implement an adaptive framework. The experimental results show that the proposed GPU based algorithm can achieve good performance. When compared with the CPU implementation, the speedup ratio of the application is more than 36 times, while the speedup ratio of compute-intensive algorithm is about 75X. Moreover, the testing results on multi GPUs show that the GPU based implementation has good scalability. © 2018, Science Press. All right reserved.

关键词： Graphics processing unit

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Research on Integrated Detection of SQL Injection Behavior Based on Text Features and Traffic Features 10th

Research on Integrated Detection of SQL Injection Behavior B...

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10th International Conference on Computer Engineering and Networks, CENet 2020

作者： Li, Ming Liu, Bo Xing, Guangsheng Wang, Xiaodong Wang, Zhihui College of Intelligence Science and Technology National University of Defence Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

ISBN: (纸本)9789811584619

With the rapid development of Internet technology, various network attack methods come out one after the other. SQL injection has become one of the most severe threats to Web applications and seriously threatens various Web application services and users data security. There are both traditional detection methods and emerging methods based on deep learning technology with higher detection accuracy for the detection of SQL injection. However, they are all for detecting a single statement and cannot determine the stage of the attack. To further improve the effect of SQL injection detection, this paper proposes an integrated detection framework for SQL injection behavior based on both text features and traffic features. We propose a SQL-LSTM model based on deep learning technology as the detection model at the text features level. Meanwhile, the features of the data traffic are merged. By this integrated method, the detection effect of SQL injection is further improved. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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High-performance Network Traffic Classification Based on Graph Neural Network 6

High-performance Network Traffic Classification Based on Gra...

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6th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Pang, Bo Fu, Yongquan Ren, Siyuan Jia, Yan Harbin Institute of Technology College of Computer Science and Technology Shenzhen China National University of Defense Technology National Key Laboratory for Parallel and Distributed Processing College of Computer Changsha China Peng Cheng Laboratory Shen Zhen China

ISBN: (纸本)9781665460033

Network traffic classification is crucial for network security and network management and is one of the most important network tasks. Current state-of-the-art traffic classifiers are based on deep learning models to automatically extract features from packet streams. Unfortunately, current approaches fail to effectively combine the structural information of traffic packets with the content features of the packets, resulting in limited classification accuracy. In this paper, we propose a graph neural network model for network traffic classification, which can well perceive the interaction feature of packets in traffic. Firstly, we design a graph structure for packets' flows to hold the interaction information between packets, which embeds both packet contents and sequence relationships into a unified graph. Secondly, we propose a graph neural network framework for graph classification to automatically learn the structural features of the packets' flows together with the packets' features. Extensive evaluation results on real-world traffic data show that the proposed model improves the prediction accuracy of improves the prediction accuracy by 2% to 37% for malicious traffic classification. © 2023 IEEE.

关键词： Graph neural networks

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RiverMapper: Step-wisely Mapping the Surface Rivers on Optical Remote Sensing Images

RiverMapper: Step-wisely Mapping the Surface Rivers on Optic...

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2022 International Conference on Neural Networks, Information, and Communication Engineering, NNICE 2022

作者： Zhang, Peng Pan, Hengyue Yang, Ke Dou, Yong Niu, Xin National Laboratory for Parallel and Distributed Processing National University of Defense Technology 410073 China Artificial Intelligence Research Center National Innovation Institute of Defense Technology BeiJing100850 China

ISBN: (纸本)9781510655171

Accurately mapping the surface rivers is important in ecological environment monitoring and disaster prevention. The development of remote sensing technology and computer vision greatly improves the efficiency of this task. However, there are few methods that map the rivers from an image directly. The existing automatic river mapping methods usually had two successive stages: waterbody extraction and flow-path extraction, where the latter methods were very dependent on the waterbody masks generated by the former methods. Errors in waterbody masks caused breaks and redundancies in the extracted graphs. This paper proposed RiverMapper, which mapped the rivers step-wisely without dividing into two stages. Following the directions and actions predicted by the convolution neural network, RiverMapper walked along the rivers step by step and cropped the fixed-size image patches at each step for segmentation. Final river graphs were constructed by the waterbody mask patches and those tracks generated by RiverMapper. We applied RiverMapper on optical remote sensing images containing the Changjiang River and the Huanghe River. Without the degradation of the performance on waterbody extraction, RiverMapper outperformed other methods in terms of the local topological and geometrical similarity between the predicted and the ground-truth river graphs. © 2022 SPIE.

关键词： Mapping

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An efficient distributed algorithm for constructing delay- and degree-bounded application-level multicast tree

An efficient distributed algorithm for constructing delay- a...

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8th International Symposium on parallel Architectures, Algorithms and Networks, I-SPAN 2005

作者： Feng, Liu Jingshu, Huang Xicheng, Lu Yuxing, Peng National Laboratory for Parallel and Distributed Processing Changsha 410073 China School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907-2035 United States

ISBN: (纸本)0769525091

In this paper we investigate the problem of finding a delay- and degree-bounded maximum sum of nodes application level multicast tree. We then proved the problem is NP-hard, and its relationship with the well-studied degree-bounded minimum maximum-delay multicast tree problem. We propose a distributed algorithm - OverStream, which adopts PPAF heuristic for father node to choose optimal child nodes based on multiple network parameters. Simulation results show that our algorithm is better than OMNI, SpreadIt, HMTP, and Zigzag in general. © 2005 IEEE.

关键词： Algorithms

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CoCache: Multi-layer Multi-path Cooperative Cache Accelerating the Deployment of Large Scale Virtual Machines

CoCache: Multi-layer Multi-path Cooperative Cache Accelerati...

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2014 IEEE 8th International Symposium on Service Oriented System Engineering

作者： Ziyang Li Zhaoning Zhang Huiba Li Yuxing Peng National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China

By analyzing the problems and challenges of virtual machine image store system in cloud computing environment, we present a cooperative persistent cache (CoCache) for virtual disks. CoCache takes advantage of the service ability of the cached nodes by providing virtual image data service for other nodes. CoCache can transfer data between nodes in a P2P pattern, for extending data service ability of the system. CoCache is realized in the kernel space of Linux, can support any kind of VMM. Experiments show that CoCache can effectively reduce the cost during virtual machines read data, and promote the service ability of virtual machine storage system. Layer-aware cache policy is proposed specially for improving cache hit rate in the multi-layer and multipath environment.

关键词： Virtual machining Servers Image storage Cloud computing Computer architecture System performance Cache storage

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Automatic generation of Markov chain usage models from real-time software UML models

Automatic generation of Markov chain usage models from real-...

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International Conference on Quality Software

作者： Jiong Yan Ji Wang Huo-wang Chen National Laboratory for Parallel and Distributed Processing Changsha China

ISBN: (纸本)0769522076

The paper concerns automatic generation of usage models from real-time software UML models. Firstly, we define the reasonably constrained real-time software UML artifacts, which include use case diagrams, timed sequence diagrams and the execution probability of each sequence diagram in its associated use case. Secondly, the paper presents a method that derives the software usage model from the constrained UML artifacts. The method elicits the messages associated with the objects under testing and their occurrence probabilities to generate the usage model of each use case. Timing constraints in sequence diagrams are considered during usage model generation. Then the usage models of use cases are integrated into the software usage model by utilizing the execution sequence relations between use cases. The usage models can be used to generate real-time software statistical test cases and facilitate real-time software statistical testing.

关键词： Unified modeling language Software quality

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A knowledge graph embedding method based on neural network 5

A knowledge graph embedding method based on neural network

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5th IEEE International Conference on Data Science in Cyberspace, DSC 2020

作者： Li, Chenchen Li, Aiping Tu, Hongkui Wang, Ye Wang, Changhai National University of Defense Technology College of Computer ChangSha China National University of Defense Technology College of Computer Science and Technology on Parallel and Distributed Processing Laboratory ChangSha China

ISBN: (数字)9781728195582

ISBN: (纸本)9781728195582

As the basis of many knowledge graph completion tasks, the embedding representation of entities and relations in knowledge graph (KG) is an important task in the fields of Natural Language processing (NLP) and Artificial Intelligence (AI). While most of the existing knowledge graph embedding (KGE) models based on convolutional neural network (CNN) can obtain abundant feature embedding, they may ignore an important fact that the triples in the KG come from the text, as they simply learn about the feature embedding of entities and relations without considering contextual information. Therefore, in this paper, we propose an effective KGE model based on neural network. First of all, we convert the triple (h, r, t) of the KG into a sentence [h r t]. Then, the LSTM neural network is used to learn the long-term dependence of sentences from the input feature vectors. Then, on this basis, the two-layer convolutional neural network with several different filters is used to extract different local features. Finally, the obtained feature vectors are connected together, and the inner product is carried out with the weight vectors to obtain the score of the triple, so as to judge the validity of the given triple. We evaluate our model on two benchmark datasets FB15k-237 and WN18RR, the experimental results show that the model can effectively improve the accuracy of link prediction, achieving better results compared with other baseline models. © 2020 IEEE.

关键词： Knowledge graph

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On path-wise automatic generation of test data for both white-box and black-box testing

On path-wise automatic generation of test data for both whit...

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Asia-Pacific Conference on Software Engineering

作者： Jin-Hui Shan Ji Wang Zhi-Chang Qi National Laboratory for Parallel and Distributed Processing Hunan China

ISBN: (纸本)0769514081

Automatic generation of test data for a given path in a program is an elementary problem in software testing, the difficulty of which lies in how to solve the nonlinear constraint. Gupta et al. (1998) proposed a method, which is referred to as the iterative relaxation method, to address the above problem by linearizing the predicate functions. This paper improves the iterative relaxation method by omitting the constructions of predicate slice and input dependency set, and proves the equivalence of systems of constraints generated by both methods. Since it is not necessary for our method to analyze the dependencies between statements on the path in the course of deriving a system of constraints, our method still works when some statements are only object or executable codes rather than source codes on the path. Therefore, our method can also be used for generating test data for black-box testing and regression testing. We have developed a prototype of a path-wise test data generator whose fundamental algorithm is presented in this paper. The initial experiments with this prototype have shown that our method is practical.

关键词： Automatic testing Iterative methods Input variables Relaxation methods Equations Laboratories Software testing distributed processing Constraint theory Software prototyping

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