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2017 2nd International Conference on Computer, Network Security and communication Engineering(CNSCE2017)

作者： Bo-wen LIU Nai-jie GU De-he GU School of Computer Science and Technology University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China Anhui Province Key Laboratory of Computing and Communication Software

All kinds of intelligent terminal equipment emerge in endlessly and grow explosively. Typical devices, such as smartphones and tablets, are becoming more and more popular, furthermore, intelligent equipment market share has more than that on PCs. And on mobile devices area, the demand for virtualization technology is gradually increasing. As an important branch of computer technology development, operating system level virtualization is becoming a hot spot of current research due to its low overhead and the advantages of lightweight. In this paper, based on the Android system on mobile devices, implement a prototype which can run multiple virtual system instances on only an Android OS by modifying the namespace mechanism in the Linux kernel to and expand into driver namespace mechanism. In addition, put forward a model called the active-inactive model guaranteeing the process if and only if in the active namespace to operate the device drivers, which was designed and implemented a new scheme of operating system level virtualization.

关键词： Virtualization Android Namespace

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Personalized video emotion tagging through a topic model

Personalized video emotion tagging through a topic model

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shan Wu Shangfei Wang Zhen Gao Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781509041183

The inherent dependencies among video content, personal characteristics, and perceptual emotion are crucial for personalized video emotion tagging, but have not been thoroughly exploited. To address this, we propose a novel topic model to capture such inherent dependencies. We assume that there are several potential human factors, or "topics," that affect the personal characteristics and the personalized emotion responses to videos. During training, the proposed topic model exploits the latent space to model the relationships among personal characteristics, video content and video tagging behaviors. After learning, the proposed model can generate meaningful latent topics, which help personalized video emotion tagging. Efficient learning and inference algorithms of the model are proposed. Experimental results on the CP-QAE-I database demonstrate the effectiveness of the proposed approach in modeling complex relationships among video content, personal characteristics, and perceptual emotion, as well as its good performance in personalized video emotion.

关键词： Video emotion tagging personal characteristics topic model

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Spectroscopy-Based Food Internal Quality Evaluation with XGBoost Algorithm

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Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data, APWeb-WAIM 2018

作者： Li, Lingling Li, Caihong Wu, Yuan Yang, Yi Zhang, Yixuan Zhang, Hairui Wu, Bin Liu, Li Xie, Rong School of Information Science and Engineering Lanzhou University Lanzhou730000 China Silk Road Economic Belt Research Center Lanzhou University Lanzhou730000 China Division of Biological Science University of California at San Diego La Jolla United States Communication and Network Center Lanzhou University Lanzhou730000 China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China School of Software Engineering Chongqing University Chongqing400044 China School of Computer Science Wuhan University Wuhan430072 China

ISBN: (纸本)9783030012977

In this paper, the combination of Near-Infrared (NIR) spectroscopy and a novel forecasting algorithm called XGBoost was proposed for food internal quality evaluation. First, the original NIR spectral data was preprocessed by Savitzky-Golay smoothing method to reduce the influence of noises. Secondly, the preprocessed spectra was submitted to PCA to extract essential information. Finally, the model was established by using the XGBoost algorithm. The performance of the proposed model was examined by comparing with different models including back propagation neural network (BPNN) and support vector regression (SVR). The results showed that the new proposed model outperformed other two models and this XGBoost-based tool was suitable for food internal quality control. © 2018, Springer Nature Switzerland AG.

关键词： Near infrared spectroscopy

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Emotion recognition through integrating EEG and peripheral signals

Emotion recognition through integrating EEG and peripheral s...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yangyang Shu Shangfei Wang Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China 230027

ISBN: (纸本)9781509041183

The inherent dependencies among multiple physiological signals are crucial for multimodal emotion recognition, but have not been thoroughly exploited yet. This paper propose to use restricted Boltzmann machine (RBM) to model such ***, the visible nodes of RBM represent EEG and peripheral physiological signals, and thus the connections between visible nodes and hidden nodes capture the intrinsic relations among multiple physiological signals. The RBM generates new representation from multiple physiological signals. Then, a support vector machine is adopted to recognize users' emotion states from the generated features. Furthermore, we extend the proposed fusion method for incomplete datas, since physiological signals are often corrupted due to artifacts. Specifically, we pre-train the RBM using all the complete data, then we update missing values and RBM parameters to minimize free energy of visible vectors using both complete and incomplete data. Experiments on two benchmark databases demonstrate the effectiveness of the proposed methods.

关键词： multimodal emotion recognition RBM EEG peripheral physiological signal missing data

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A straightforward method to judge the completeness of a polymorphic gate set

arXiv

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arXiv 2017年

作者： Li, Zhifang Luo, Wenjian Yue, Lihua Wang, Xufa School of Computer Science and Technology University of Science and Technology of China Hefei230027 China Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei230027 China

Polymorphic circuits are a special kind of circuits which possess some different build-in functions and these functions are activated by environment parameters, like light and VDD. Some theories have been proposed to guide the design of polymorphic circuits, including the definition of complete polymorphic gate sets and algorithms to judge the completeness of a polymorphic gate set. However, the previous algorithms have to enumerate all the polymorphic signals for judging the completeness of a polymorphic gate set, and it is not easy to be conducted manually. In this paper, a straightforward method is proposed to judge the completeness of a polymorphic gate set. And the correctness of the straightforward method is proved theoretically. Some examples are given to show that the proposed method could be conducted step by step. Its actual computing cost is usually low, and it is suitable for manual operation. Copyright © 2017, The Authors. All rights reserved.

关键词： Timing circuits

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A Dynamic Load Balancing Method of Cloud-Center Based on SDN

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China communications 2016年第2期13卷 130-137页

作者： WANG Yong TAO Xiaoling HE Qian KUANG Yuwen Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology School of Information and Communication Guilin University of Electronic Technology

In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What＇s more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput.

关键词： SDN cloud computing data center dynamic load balancing

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A Hybrid Genetic Algorithm for Vehicle Routing Problems with Dynamic Requests

A Hybrid Genetic Algorithm for Vehicle Routing Problems with...

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IEEE Symposium Series on Computational Intelligence

作者： Ruikang Yi Wenjian Luo Chenyang Bu Xin Lin Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

In this paper, a hybrid Genetic Algorithm (GA) is proposed to solve the Vehicle Routing Problems with Dynamic Requests (VRPDR). The proposed hybrid GA primarily involves the following parts. First, a greedy split is introduced, which is fit for the VRPDR. Second, the adjacent-exchange-based local search is proposed. Third, a novel mutation operator, named the insert mutation, is proposed. The experimental results show that the proposed hybrid GA is effective.

关键词： Dynamic Vehicle Routing Genetic Algorithm Split Algorithm Local Search

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Viewpoint selection for photographing architectures

arXiv

引用

arXiv 2017年

作者： He, Jingwu Wang, Linbo Zhou, Wenzhe Zhang, Hongjie Cui, Xiufen Guo, Yanwen National Key Lab for Novel Software Technology Nanjing University NanJing210023 China MOE Key Laboratory of Intelligent Computing and Signal Processing Institute of Media Computing Anhui University HeFei230039 China Samsung Electronics R&D China

—This paper studies the problem of how to choose good viewpoints for taking photographs of architectures. We achieve this by learning from professional photographs of world famous landmarks that are available on the Internet. Unlike previous efforts devoted to photo quality assessment which mainly rely on 2D image features, we show in this paper combining 2D image features extracted from images with 3D geometric features computed on the 3D models can result in more reliable evaluation of viewpoint quality. Specifically, we collect a set of photographs for each of 15 world famous architectures as well as their 3D models from the Internet. Viewpoint recovery for images is carried out through an image-model registration process, after which a newly proposed viewpoint clustering strategy is exploited to validate users’ viewpoint preferences when photographing landmarks. Finally, we extract a number of 2D and 3D features for each image based on multiple visual and geometric cues and perform viewpoint recommendation by learning from both 2D and 3D features using a specifically designed SVM-2K multi-view learner, achieving superior performance over using solely 2D or 3D features. We show the effectiveness of the proposed approach through extensive experiments. The experiments also demonstrate that our system can be used to recommend viewpoints for rendering textured 3D models of buildings for the use of architectural design, in addition to viewpoint evaluation of photographs and recommendation of viewpoints for photographing architectures in practice. Copyright © 2017, The Authors. All rights reserved.

关键词： Photography

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software Backdoor Analysis Based on Sensitive Flow Tracking and Concolic Execution

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Wuhan University Journal of Natural Sciences 2016年第5期21卷 421-427页

作者： XU Xin WANG Jiajie CHENG Shaoyin ZHANG Tao JIANG Fan School of Computer Science and Technology University of Science and Technology of China Hefei 230027 Anhui China China Information Technology Security Evaluation Center Beijing 100085 China Anhui Province Key Lab of Software in Computing and Communication Hefei 230026 Anhui China

In order to effectively detect and analyze the backdoors this paper introduces a method named Backdoor Analysis based on Sensitive flow tracking and Concolic Execution（BASEC）.BASEC uses sensitive flow tracking to effectively discover backdoor behaviors, such as stealing secret information and injecting evil data into system, with less false negatives. With concolic execution on predetermined path, the backdoor trigger condition can be extracted and analyzed to achieve high accuracy. BASEC has been implemented and experimented on several software backdoor samples widespread on the Internet, and over 90% of them can be detected. Compared with behavior-based and system-call-based detection methods, BASEC relies less on the historical sample collections, and is more effective in detecting software backdoors, especially those injected into software by modifying and recompiling source codes.

关键词： software backdoor detection data flow tracking concolic execution malware detection

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Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues

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The Journal of China Universities of Posts and Telecommunications 2016年第2期23卷 56-65,96页

作者： Kang Kai Wang Cong Luo Tao School of Software Engineering Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts Telecommunications

Vehicular Ad-hoc networks（VANETs） are kinds of mobile Ad-hoc networks（MANETs）, which consist of mobile vehicles with on-board units（OBUs） and roadside units（RSUs）. With the rapid development of computation and communication technologies, peripheral or incremental changes in VANETs evolve into a revolution in process. Cloud computing as a solution has been deployed to satisfy vehicles in VANETs which are expected to require resources（such as computing, storage and networking）. Recently, with special requirements of mobility, location awareness, and low latency, there has been growing interest in research into the role of fog computing in VANETs. The merging of fog computing with VANETs opens an area of possibilities for applications and services on the edge of the cloud computing. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile vehicles in VANET. Mobile vehicles in VANET can also demand services of low-latency and short-distance local connections via fog computing. This paper presents the current state of the research and future perspectives of fog computing in VANETs. Moreover, we discuss the characteristics of fog computing and services based on fog computing platform provided for VANETs. In this paper, some opportunities for challenges and issues are mentioned, related techniques that need to be considered have been discussed in the context of fog computing in VANETs. Finally, we discuss about research directions of potential future work for fog computing in VANETs. Within this article, readers can have a more thorough understanding of fog computing for VANETs and the trends in this domain.

关键词： VANET fog computing cloud computing application vehicular cloud computing

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