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arXiv 2019年

作者： Zhou, Sheng Wang, Guangchao Zhang, Shan Niu, Zhisheng Shen, Xuemin Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing100084 China School of Computer Science and Engineering Beihang Univesity Beijing100191 China State Key Laboratory of Software Development Environment Beijing Key Laboratory of Computer Networks Department of Electrical and Computer Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada

Space-air-ground integrated networks (SAGIN) provide great strengths in extending the capability of ground wireless networks. On the other hand, with rich spectrum and computing resources, the ground networks can also assist space-air networks to accomplish resource-intensive or power-hungry missions, enhancing the capability and sustainability of the space-air networks. Therefore, bi-directional mission offloading can make full use of the advantages of SAGIN and benefits both space-air and ground networks. In this article, we identify the key role of network reconfiguration in coordinating heterogeneous resources in SAGIN, and study how network function virtualization (NFV) and service function chaining (SFC) enable agile mission offloading. A case study validates the performance gain brought by bi-directional mission offloading. Future research issues are outlooked as the bi-directional mission offloading framework opens a new trail in releasing the full potentials of SAGIN. Copyright © 2019, The Authors. All rights reserved.

关键词： Network function virtualization

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Region-wise generative adversarial image inpainting for large missing areas

arXiv

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arXiv 2019年

作者： Ma, Yuqing Liu, Xianglong Bai, Shihao Wang, Lei Liu, Aishan Tao, Dacheng Hancock, Edwin State Key Lab of Software Development Environment Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine UBTECH Sydney Artificial Intelligence Centre School of Information Technologies Faculty of Engineering and Information Technologies University of Sydney DarlingtonNSW2008 Australia Department of Computer Science University of York York United Kingdom

Recently deep neutral networks have achieved promising performance for filling large missing regions in image inpainting tasks. They usually adopted the standard convolutional architecture over the corrupted image, leading to meaningless contents, such as color discrepancy, blur and artifacts. Moreover, most inpainting approaches cannot well handle the large contiguous missing area cases. To address these problems, we propose a generic inpainting framework capable of handling with incomplete images on both contiguous and discontiguous large missing areas, in an adversarial manner. From which, region-wise convolution is deployed in both generator and discriminator to separately handle with the different regions, namely existing regions and missing ones. Moreover, a correlation loss is introduced to capture the non-local correlations between different patches, and thus guides the generator to obtain more information during inference. With the help of our proposed framework, we can restore semantically reasonable and visually realistic images. Extensive experiments on three widely-used datasets for image inpainting tasks have been conducted, and both qualitative and quantitative experimental results demonstrate that the proposed model significantly outperforms the state-of-the-art approaches, both on the large contiguous and discontiguous missing areas. Copyright © 2019, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A survey on formal specification and verification of separation kernels

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Frontiers of computer science 2017年第4期11卷 585-607页

作者： Yongwang ZHAO Zhibin YANG Dianfu MA State Key Laboratory of Software Development Environment (NLSDE) School of Computer Science and Engineering Beihang Univerisity Beijing 100191 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210016 China

Abstract Separation kernels are fundamental software of safety and security-critical systems, which provide their hosted applications with spatial and temporal separation as well as controlled information flows among partitions. The application of separation kernels in critical domain demands the correctness of the kernel by formal verification. To the best of our knowledge, there is no survey paper on this topic. This paper presents an overview of formal specification and verification of separation kernels. We first present the back- ground including the concept of separation kernel and the comparisons among different kernels. Then, we survey the state of the art on this topic since 2000. Finally, we summa- rize research work by detailed comparison and discussion.

关键词： real-time operating systems separation kernel,survey formal specification formal verification

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A hierarchical similarity based job recommendation service framework for university students

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Frontiers of computer science 2017年第5期11卷 912-922页

作者： Rui LIU Wenge RONG Yuanxin OUYANG Zhang XIONG State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China Engineering Research Center of Advanced Computer Application Technology Ministry of Education Beihang University Beijing 100191 China School of Computer Science and Engineering Beihang University Beijing 100191 China

When people want to move to a new job, it is often difficult since there is too much job information availab.e. To select an appropriate job and then submit a resume is tedious. It is particularly difficult for university students since they normally do not have any work experience and also are unfamiliar with the job market. To deal with the informa- tion overload for students during their transition into work, a job recommendation system can be very valuable. In this research, after fully investigating the pros and cons of current job recommendation systems for university students, we propose a student profiling based re-ranking framework. In this system, the students are recommended a list of potential jobs based on those who have graduated and obtained job offers over the past few years. Furthermore, recommended employers are also used as input for job recommendation result re-ranking. Our experimental study on real recruitment data over the past four years has shown this method＇s potential.

关键词： job recommendation students similarity time,re-ranking

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Marshall-Olkin Power-Law Distributions in Length-Frequency of Entities

arXiv

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arXiv 2018年

作者： Zhong, Xiaoshi Yu, Xiang Cambria, Erik Rajapakse, Jagath C. School of Computer Science and Technology Beijing Institute of Technology China State Key Laboratory of Software Development Environment Beihang University China School of Computer Science and Engineering Nanyang Technological University Singapore

Entities involve important concepts with concrete meanings and play important roles in numerous linguistic tasks. Entities have different forms in different linguistic tasks and researchers treat those different forms as different concepts. In this paper, we are curious to know whether there are some common characteristics that connect those different forms of entities. Specifically, we investigate the underlying distributions of entities from different types and different languages, trying to figure out some common characteristics behind those diverse entities. After analyzing twelve datasets about different types of entities and eighteen datasets about entities in different languages, we find that while these entities are dramatically diverse from each other in many aspects, their length-frequencies can be well characterized by a family of Marshall-Olkin power-law (MOPL) distributions. We conduct experiments on those thirty datasets about entities in different types and different languages, and experimental results demonstrate that MOPL models characterize the length-frequencies of entities much better than two state-of-the-art power-law models and an alternative log-normal model. Experimental results also demonstrate that MOPL models are scalab.e to the length-frequency of entities in large-scale real-world datasets. Copyright © 2018, The Authors. All rights reserved.

关键词： Large dataset

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Heuristic Maximum Clique Based Identity Switches Awareness for Tracking

Heuristic Maximum Clique Based Identity Switches Awareness f...

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2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI2018)

作者： Chao Li Di Cui Hao Sheng Jiahui Chen Yang Zhang State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang University Shenzhen Key Laboratory of Data Vitalization Research Institute in ShenzhenBeihang University

Multi-target tracking is a popular research topic in the field of computer vision. Most recent works based on tracking-by-detection paradigm have trouble when dealing with tracking errors(i.e. identity switches) that are caused by overlapping of different pedestrians. In this work, we propose a novel method which is capable to perceive the mismatched tracklets by using an Identity Switch Awareness Algorithm based on iterative maximum clique searching. Besides, we present an optimal method to accelerate the maximum clique searching process to alleviate the cost of computing. Finally, we introduce this algorithm into a network flow tracking method and test the validity of it on five challenging sequences. The results show obvious improvement on MOTA and IDs.

关键词： Multi-target tracking Identity Switches Maximum clique problem

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Context-aware Pedestrian Detection with Salient Region Self-growing in Far-infrared Images

Context-aware Pedestrian Detection with Salient Region Self-...

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2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI2018)

作者： Hao Sheng Meiyuan Liu Yanwei Zheng Yang Liu State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang University Shenzhen Key Laboratory of Data Vitalization Research Institute in ShenzhenBeihang University

In this paper, we present a new framework to detect pedestrians in infrared images. The framework consists of a candidate generation module and a classification module, both of which are implemented based on convolution neural ***, we learned effective segmentation threshold by deep learning methods, and proposed a salient region self-growing algorithm to generate candidates. Besides, we conducted contextaware classification on the candidates to reduce the false positives using cues from the context. We achieved state-of-theart result on a public dataset, which has shown the effectiveness of the proposed method.

关键词： pedestrian detection infrared neural network

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An efficient and fast polarity optimization approach for mixed polarity Reed-Muller logic circuits

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Frontiers of computer science 2017年第4期11卷 728-742页

作者： Zhenxue HE Limin XIAO Fei GU Tongsheng XIA Shubin SU Zhisheng HUO Rong ZHANG Longbing ZHANG Li RUAN Xiang WANG State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computer Science and Engineering Beihang University Beijing 100191 China School of Electronic and Information Engineering Beihang University Beijing 100191 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China National Engineering Research Center for Science & Technology Resources Sharing Service Beijing 100191 China

Although the genetic algorithm has been widely used in the polarity optimization of mixed polarity Reed- Muller （MPRM） logic circuits, few studies have taken into account the polarity conversion sequence. In order to im- prove the efficiency of polarity optimization of MPRM logic circuits, we propose an efficient and fast polarity optimiza- tion approach （FPOA） considering the polarity conversion se- quence. The main idea behind the FPOA is that, firstly, the best polarity conversion sequence of the polarity set wait- ing for evaluation is obtained by using the proposed hybrid genetic algorithm （HGA）; secondly, each of polarity in the polarity set is converted according to the best polarity con- version sequence obtained by HGA. Our proposed FPOA is implemented in C and a comparative analysis has been pre- sented for MCNC benchmark circuits. The experimental re- suits show that for the circuits with more variables, the FPOA is highly effective in improving the efficiency of polarity op- timization of MPRM logic circuits compared with the tradi- tional polarity optimization approach which neglects the po- larity conversion sequence and the improved polarity opti- mization approach with heuristic technique.

关键词： genetic algorithm polarity optimization mixed

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Enhancing constraint based test generation by local search 17

Enhancing constraint based test generation by local search

引用

6th International Conference on software and computer Applications, ICSCA 2017

作者： Lin, Mengxiang Hou, Xiaomei Liu, Rui Ge, Linyan School of Mechanical Engineering and Automation State Key Laboratory of Software Development Environment Beihang University China School of Computer Science and Technology State Key Laboratory of Software Development Environment Beihang University China School of Information Management Wuhan University China

ISBN: (纸本)9781450348577

The core operation of symbolic execution based test data generation is to generate a path constraint in terms of input variables for a selected path. Solutions to the path constraint are test data which will be used to execute the target path. So far, the limitations of constraint solving still prevent its widespread use in practice. Most of the constraint solvers aim at a particular kind of constraint and might have no way to deal with complex path constraints derived in a real-world software application. To tackle the problem, we propose a hybrid solving strategy for path constraints containing multiple kinds of constraints. In particular, the path constraint is converted and divided into two parts that can be solved by different constraint solving techniques. A local search method is combined with a linear constraint solver to solve complex mathematical constraints. We have extended the symbolic execution engine KLEE with our approach and evaluated its effectiveness on a set of mathematical programs. The preliminary evaluation shows that our approach can solve a majority of complex path constraints in the experiments in reasonable time. © 2017 ACM.

关键词： Application programs

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A reinforced hungarian algorithm for task allocation in global software development 29

A reinforced hungarian algorithm for task allocation in glob...

引用

29th International Conference on software engineering and Knowledge engineering, SEKE 2017

作者： Yu, Xiao Wu, Man Jia, Xiangyang Liu, Ye State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China School of Computer Science and Information Engineering HuBei University Wuhan China

ISBN: (纸本)1891706411

The allocation of software development tasks is a critical management activity in distributed development projects. One of the most important problem is to find the lowest-cost way to assign tasks in global software development, which can be solved by Hungarian algorithm. However, the original Hungarian algorithm only assume that a task can only be solved by one development site. The assumption is not agreed with the actual case where a software development task is usually be solved through a collab.ration among several sites. To address such an issue, this paper proposes a reinforced Hungarian algorithm (RHA) for task assignment in global software development. RHA consists of three major stages. First, RHA transforms a n×m cost matrix into two n×n cost matrix by adding (2n-m) virtual development sites. Second, RHA performs the original Hungarian algorithm on the two n×n cost matrix to get the optimal assignment results. Finally, RHA removes the (2n-m) virtual development sites and gets the final optimal assignment result for m tasks. Simulation results indicate that RHA is a viable approach for the task assignment problem in global software development.

关键词： software design

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