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Frontiers in Education (FIE) Conference

作者： W. Eric Wong Linghuan Hu Haoliang Wang Zhenyu Chen Department of Computer Science University of Texas at Dallas USA State Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9781538611753;9781538611746

This Innovative Practice, Work in Progress Paper presents how we improve software testing education via industry sponsored contests. Over the past decades, we have built software to improve our efficiency, reliability, and safety in production, business, daily life, etc. These goals, however, cannot be accomplished if the software is not properly tested. Some universities provide classes to teach students the fundamental knowledge and techniques of software testing. However, these classes often ignore industry practices and can hardly offer real-world testing experiences to students. To address this, we partnered with industry sponsors to design and host several software testing contests along with software testing tutorials. Through the contests and tutorials, we brought real-world testing and tool experience to the students and provided excellent opportunities for them to practice their learned testing techniques to overcome industry testing challenges.

关键词： software software testing Industries Tools computer bugs Education

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CariGAN: Caricature generation through weakly paired adversarial learning

arXiv

引用

arXiv 2018年

作者： Li, Wenbin Xiong, Wei Liao, Haofu Huo, Jing Gao, Yang Luo, Jiebo State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science University of Rochester United States

Caricature generation is an interesting yet challenging task. The primary goal is to generate a plausible caricature with reasonable exaggerations given a face image. Conventional caricature generation approaches mainly use low-level geometric transformations such as image warping to generate exaggerated images, which lack richness and diversity in terms of content and style. The recent progress in generative adversarial networks (GANs) makes it possible to learn an image-to-image transformation from data so as to generate diverse output images. However, directly applying GAN-based models to this task leads to unsatisfactory results due to the large variance in the caricature distribution. Moreover, some models require pixel-wisely paired training data which largely limits their usage scenarios. In this paper, we model caricature generation as a weakly paired image-to-image translation task, and propose Cari-GAN to address these issues. Specifically, to enforce reasonable exaggeration and facial deformation, facial landmarks are adopted as an additional condition to constrain the generated image. Furthermore, an image fusion mechanism is designed to encourage our model to focus on the key facial parts so that more vivid details in these regions can be generated. Finally, a diversity loss is proposed to encourage the model to produce diverse results to help alleviate the "mode collapse" problem of the conventional GAN-based models. Extensive experiments on a large-scale "WebCaricature" dataset show that the proposed CariGAN can generate more plausible caricatures with larger diversity compared with the state-of-the-art models. Copyright © 2018, The Authors. All rights reserved.

关键词： Generative adversarial networks

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B-spline surface fitting to mesh vertices

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science China(Information sciences) 2017年第7期60卷 259-261页

作者： Yang LU Junhai YONG Kanle SHI Hejin GU Ping ZHENG Jean-Claude PAUL School of Software Tsinghua University Department of Computer Science and Technology Tsinghua University Key Laboratory for Information System Security Ministry of Education of China Tsinghua National Laboratory for Information Science and Technology Tsinghua University Department of Research & Development Jiangxi Academy of Science Department of Mathematics and Computer Science Nanchang Normal University

Here we propose a novel method of fitting B-spline surfaces to input mesh *** a mesh model that is difficult to fit with one B-spline surface,we divide it into several patches that form a tree structure(which is called hierarchical splines[1]),and for each patch,we use one B-spline surface for ***,only a few patches are required,and G2continuity can be achieved between the adjacent surfaces.

关键词： B-spline surface fitting to mesh vertices

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Community-aware Photo Quality Evaluation by Deeply Encoding Human Perception

引用

IEEE Transactions on Multimedia 2019年

作者： Wang, Zepeng Li, Ping Zhang, Luming Shao, Ling Department of CSIE Hefei University of Technology Hefei China. School of Computer Science and Technology Hangzhou Dianzi University Hangzhou 310018 China and also with the State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210023 China. College of Computer Sciences Zhejiang University Hangzhou China. Abu Dhabi United Arab Emirates. He is also with the School of Computing Sciences University of East Anglia Norwich UK.

Computational photo quality evaluation is a useful technique in many tasks of computer vision and graphics, $e.g.$, photo retaregeting, 3D rendering, and fashion recommendation. Conventional photo quality models are designed by characterizing pictures from all communities ($e.g.$, “architecture” and “colorful”) indiscriminately, wherein community-specific features are not encoded explicitly. In this work, we develop a new community-aware photo quality evaluation framework. It uncovers the latent community-specific topics by a regularized latent topic model (LTM), and captures human visual quality perception by exploring multiple attributes. More specifically, given massive-scale online photos from multiple communities, a novel ranking algorithm is proposed to measure the visual/semantic attractiveness of regions inside each photo. Meanwhile, three attributes: photo quality scores, weak semantic tags, and inter-region correlations, are seamlessly and collaboratively incorporated during ranking. Subsequently, we construct gaze shifting path (GSP) for each photo by sequentially linking the top-ranking regions from each photo, and an aggregation-based deep CNN calculates the deep representation for each GSP. Based on this, an LTM is proposed to model the GSP distribution from multiple communities in the latent space. To mitigate the overfitting problem caused by communities with very few photos, a regularizer is added into our LTM. Finally, given a test photo, we obtain its deep GSP representation and its quality score is determined by the posterior probability of the regularized LTM. Comprehensive comparative studies on four image sets have shown the competitiveness of our method. Besides, eye tracking experiments demonstrated that our ranking-based GSPs are highly consistent with real human gaze movements. IEEE

关键词： Eye tracking

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An Internet Application-Driven Cache Placement Algorithm for software-Defined Information-Centric Networking

An Internet Application-Driven Cache Placement Algorithm for...

引用

2018 International computers, Signals and Systems Conference, ICOMSSC 2018

作者： Liu, Jing Hu, Ziwei Guo, Jinghong Hao, Hanyong Tsinghua University Department of Computer Science Beijing China Beijing University of Post and Telecommunication State Key Laboratory of Networking and Switching Technology Beijing China Global Energy Interconnection Research Institute Beijing China China State Grid Corporation of China State Grid Laboratory of Electric Power Communication Network Technology Beijing China

ISBN: (纸本)9781538667514

Currently, video has becoming one of the most traffic-intense Internet applications. However, it also causes Internet transmission problems, such as congestion, high delay and bad user experience. Therefore, it is necessary to design a cache mechanism for some popular videos in advance. To address this problem, this paper designs an Internet application-driven algorithm for centralized cache placement of popular videos in software-defined information-centric networking. First, it designs a centralized control architecture and the cache controller and node working mechanism, and then this problem is formulated as an integer programming. Finally, it proposes a greedy algorithm based on a 0-1 multiple knapsack problem to solve the integer programming and sets a performance indicator to evaluate this algorithm. The result shows that the algorithm can achieve desirable performance. © 2018 IEEE.

关键词： Integer programming

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A Bootstrapping Approach to Entity Linkage on the Semantic Web

SSRN

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SSRN 2018年

作者： Hu, Wei Jia, Cunxin National Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Technology Nanjing University China

In the Big Data era, ever-increasing RDF data have reached a scale in billions of entities and brought challenges to the problem of entity linkage on the Semantic Web. Although millions of entities, typically denoted by URIs, have been explicitly linked with owl:sameAs, potentially coreferent ones are still numerous. Existing automatic approaches address this problem mainly from two perspectives: one is via equivalence reasoning, which infers semantically coreferent entities but probably misses many potentials;the other is by similarity computation between property-values of entities, which is not always accurate and do not scale well. In this paper, we introduce a bootstrapping approach by leveraging these two kinds of methods for entity linkage. Given an entity, our approach firstly infers a set of semantically coreferent entities. Then, it iteratively expands this entity set using discriminative property value pairs. The discriminability is learned with a statistical measure, which does not only identify important property-values in the entity set, but also takes matched properties into account. Frequent property combinations are also mined to improve linkage accuracy. We develop an online entity linkage search engine, and show its superior precision and recall by comparing with representative approaches on a large-scale and two benchmark datasets. © 2018, The Authors. All rights reserved.

关键词： Resource Description Framework (RDF)

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JDAS: a software development framework for multidatabases

JDAS: a software development framework for multidatabases

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作者： Xie, Guoqi Chen, Yuekun Liu, Yan Fan, Chunnian Li, Renfa Li, Keqin College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Nanjing University of Information Science and Technology China Department of Computer Science State University of New York New PaltzNY United States

Modern software development for services computing and cloud computing software systems is no longer based on a single database but on existing multidatabases and this convergence needs new software architecture and framework design. Most current popular frameworks are not designed for multidatabases, and many practical problems in development arise. This study designs and implements a software development framework called Java data access service (JDAS) for multidatabases using the object-oriented programming language Java. The JDAS framework solves related problems that arise when other frameworks are employed in practical software development with multidatabases by presenting and introducing design methods. JDAS consists of the modules of the database abstract, object relational mapping, connection pools management, configuration management, data access service, and inversion of control. Results and case study reveal that the JDAS framework effectively reduces development complexity and improves development efficiency of the software systems with multidatabases. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Object oriented programming

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Secure Beamforming Design for MISO SWIPT Systems: An Indirectly Optimized Approach

Secure Beamforming Design for MISO SWIPT Systems: An Indirec...

引用

2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yao Yu Siyu Wang Shumei Liu Lei Guo Zhaolong Ning Shimin Gong Mohammad S. Obaidat School of Computer Science and Engineering Northeastern University Shenyang China Chongqing University of Posts and Telecommunications China State Key Laboratory for Novel Software Technology Nanjing University China School of Intelligent Systems Engineering Sun Yat-sen University China ECE Department Nazarbayev University Astana Kazakhstan College of Computing and Informatics University of Sharjah UAE The King Abdullah II School of Information Technology The University of Jordan Amman Jordan University of Science and Technology Beijing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

By considering the Simultaneous Wireless Information and Power Transfer (SWIPT) schemes, this paper focuses on secure transmission model design in multiple-input-single-output (MISO) channels. In these channels, the channel state information is assumed to be perfect. Our objective is to maximize the worst-case secrecy rate with respect to both potential eavesdroppers and obvious eavesdroppers under the constraints of energy-harvesting and total transmission power. We present an optimization model to indirectly obtain maximum security rate in a single receiver system. Due to the high computational complexity of the solution process caused by the formulated non-convex optimization problem, we propose a novel indirect method to handle this issue. Then, a Semi-Definite Programming (SDP) relaxation method is used to approach the optimal solution. Moreover, we reveal the conditions for ensuring that the above semi-definite relaxation is compact. Simulation results demonstrate that the gained performance in our system is much better than those of the existing competing schemes.

关键词： Receivers Interference Signal to noise ratio Transmitters Optimization Security Communication system security

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Secure keyboards against motion based keystroke inference attack 1

引用

12th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2016

作者： Du, Shaoyong Gao, Yue Hua, Jingyu Zhong, Sheng State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (数字)9783319596082

ISBN: (纸本)9783319596075

Nowadays, attackers seek various covert channels to access the users’ privacy on the mobile devices. Recent research has demonstrated that the built-in motion sensors can be exploited to monitor the users’ screen taps and infer what they have typed. This paper presents several practical and convenient countermeasures against this attack in terms of the soft keyboard. We find that this attack is sensitive to the motion noise of the mobile device and the layout variation of the soft keyboard. We, thus, present two kinds of countermeasures against this attack by introducing vibration noise in sensor readings and dynamics in the keyboard layout, respectively. We implement these countermeasures on Android platform and recruit 20 volunteers to evaluate these countermeasures’ effectiveness and usability on both the smartphones and tablets. The results show that the proposed countermeasures can effectively reduce the attackers’ keystroke inference accuracy without significantly hurting the typing efficiency. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2017.

关键词： computers

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AI-skin: Skin disease recognition based on self-learning and wide data collection through a closed loop framework

arXiv

引用

arXiv 2019年

作者： Chen, Min Zhou, Ping Wu, Di Hu, Long Hassan, Mohammad Mehedi Alamri, Atif School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Big Data Analysis and Processing Guangzhou China Chair of Pervasive and Mobile Computing Information Systems Department College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Chair of Pervasive and Mobile Computing Software Engineering Department CCIS King Saud University Riyadh11543 Saudi Arabia

There are a lot of hidden dangers in the change of human skin conditions, such as the sunburn caused by long-time exposure to ultraviolet radiation, which not only has aesthetic impact causing psychological depression and lack of selfconfidence, but also may even be life-threatening due to skin canceration. Current skin disease researches adopt the auto-classification system for improving the accuracy rate of skin disease classification. However, the excessive dependence on the image sample database is unable to provide individualized diagnosis service for different population groups. To overcome this problem, a medical AI framework based on data width evolution and self-learning is put forward in this paper to provide skin disease medical service meeting the requirement of real time, extendibility and individualization. First, the wide collection of data in the close-loop information flow of user and remote medical data center is discussed. Next, a data set filter algorithm based on information entropy is given, to lighten the load of edge node and meanwhile improve the learning ability of remote cloud analysis model. In addition, the framework provides an external algorithm load module, which can be compatible with the application requirements according to the model selected. Three kinds of deep learning model, i.e. LeNet-5, AlexNet and VGG16, are loaded and compared, which have verified the universality of the algorithm load module. The experiment platform for the proposed real-time, individualized and extensible skin disease recognition system is built. And the system's computation and communication delay under the interaction scenario between tester and remote data center are analyzed. It is demonstrated that the system we put forward is reliable and effective. Copyright © 2019, The Authors. All rights reserved.

关键词： Data acquisition

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