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3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016

作者： Zhang, Fuquan Mao, Zijing Ding, Gangyi School of software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States School of software Beijing Institute of TechnologyBeijing 10008 1 China Software Building Beijing Institute of Technology 5 South Zhongguancun Street Haidian Beijing100081 China

ISBN: (纸本)9781450341295

The temperature sensor network in intelligent building classified collection of big data processing has the problem of big data redundancy interference, which results in unable to determine the fixed filter thresholds. This paper proposed Chaos differential disturbance based fuzzy C-means clustering model for big temperature sensing data classification tasks. It requires to analyze temperature sensor in the intelligent building big distributed structure model of data in a database storage system, the big data information flow feature fusion and time series analysis. Based on traditional fuzzy c-means clustering processing, we introduced chaos disturbance to avoid the classification into local convergence and local optimum, and therefore improve the performance of data clustering. The testing results show that our proposed classification method effectively reduces the error rate for classification tasks of temperature data in intelligent building and have achieved the best performance among the existing algorithms. © 2016 ACM.

关键词： Temperature sensors

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Scale and topology preserving SIFT feature hashing 1

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Kang, Chen Zhu, Li Qian, Xueming School of Software Engineering Xi’an Jiaotong University Xi’an710049 China The Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an710049 China School of Electronic and Information Engineering Xi’an Jiaotong University Xi’an710049 China

ISBN: (数字)9783319488967

ISBN: (纸本)9783319488950

Abstract. In recent years, content based image retrieval has been concerned because of practical needs on Internet services, especially methods that can improve retrieving speed and precision. Thus, we propose a hashing scheme called Geometry and Topology Preserving Hashing for content based image retrieval. A training process of hashing function involves both of geometric information and topology information is introduced. Compared with state-of-the-art methods, our method gives better precision in experiment on the Oxford Building dataset. © Springer International Publishing AG 2016.

关键词： Geometry

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TenSR: Multi-dimensional tensor sparse representation

TenSR: Multi-dimensional tensor sparse representation

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2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016

作者： Qi, Na Shi, Yunhui Sun, Xiaoyan Yin, Baocai Beijing Key Laboratory of Multimedia and Intelligent Software Technology College of Metropolitan Transportation Beijing University of Technology China Microsoft Research United States Faculty of Electronic Information and Electrical Engineering Dalian University of Technology China

ISBN: (纸本)9781467388511

The conventional sparse model relies on data representation in the form of vectors. It represents the vector-valued or vectorized one dimensional (1D) version of an signal as a highly sparse linear combination of basis atoms from a large dictionary. The 1D modeling, though simple, ignores the inherent structure and breaks the local correlation inside multidimensional (MD) signals. It also dramatically increases the demand of memory as well as computational resources especially when dealing with high dimensional signals. In this paper, we propose a new sparse model TenSR based on tensor for MD data representation along with the corresponding MD sparse coding and MD dictionary learning algorithms. The proposed TenSR model is able to well approximate the structure in each mode inherent in MD signals with a series of adaptive separable structure dictionaries via dictionary learning. The proposed MD sparse coding algorithm by proximal method further reduces the computational cost significantly. Experimental results with real world MD signals, i.e. 3D Multi-spectral images, show the proposed TenSR greatly reduces both the computational and memory costs with competitive performance in comparison with the state-of-the-art sparse representation methods. We believe our proposed TenSR model is a promising way to empower the sparse representation especially for large scale high order signals.

关键词： One dimensional

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Design and implementation of tourism activity recognition and discovery system 12

Design and implementation of tourism activity recognition an...

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12th World Congress on intelligent Control and Automation, WCICA 2016

作者： Yifan, Yuan Junping, Du Dan, Fan Lee, Jangmyung Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Haidian District Beijing China Department of Electronics Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9781467384148

With the rapid development of technologies, such as cloud computing, big data and so forth, tourism big data has drawn the attention of many scholars. How to make full use of a large amount of raw data from tourism activity, and how to recognize and discover tourism activity quickly, accurately and conveniently from information which is accumulated over a long period have become a new direction of tourism data application. In this paper, text analysis, text classification and other relevant technologies are combined based on text mining. Furthermore, a tourism activity recognition and discovery system is designed and implemented, which has achieved the recognition and discovery of tourism activity from a large amount of information. The research results could contribute to recommending and predicting tourism activity in China. © 2016 IEEE.

关键词： Big data

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A real-time people number detection algorithm of scenic spot based on density center clustering 12

A real-time people number detection algorithm of scenic spot...

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12th World Congress on intelligent Control and Automation, WCICA 2016

作者： Yaomin, Wen Junping, Du Meiyu, Liang Dan, Fan Lee, Jangmyung Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Haidian District Beijing China Department of Electronics Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9781467384148

In recent years, accidents occur frequently because the people number of scenic spots is lack of control. In this paper, a novel real-time people number detection algorithm of scenic spot based on density center clustering (DPBC) is proposed. Taking account of the complexity of the scenic environment, we use the Gauss mixture model (GMM) to suppress the background interference, extract the feature points from the crowd and cluster these feature points by applying a clustering algorithm based on density center. Then we establish a training set and estimate the people number by using the support vector regression model (SVR). We implement the proposed algorithm based on Opencv and use PETS dataset to validate the effectiveness of our proposed algorithm. Experimental results demonstrate that compared with Aibiol algorithm and Conte algorithm, our proposed algorithm improved the accuracy for estimating the people number in a scenic spot. © 2016 IEEE.

关键词： Clustering algorithms

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Grey wolf optimizer (GWO) for Automated Offshore Crane Design

Grey wolf optimizer (GWO) for Automated Offshore Crane Desig...

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IEEE Symposium Series on Computational Intelligence

作者： Ibrahim A. Hameed Robin T. Bye Ottar L. Osen Software and Intelligent Control Engineering Laboratory Faculty of Engineering and Natural Sciences Norwegian University of Science and Technology NTNU in Alesund Postboks 1517 NO-6025 Alesund Norway

ISBN: (纸本)9781509042418

In this paper, a new meta-heuristic optimization algorithm called Grey Wolf Optimizer (GWO) is applied to offshore crane design. An offshore crane is a pedestal-mounted elevating and rotating lifting device used to transfer materials or personnel to or from marine vessels, barges and structures whereby the load can be moved horizontally in one or more directions and vertically. Designing and building offshore cranes is a very complex process. It depends on the configuration of a large set of design parameters and is characterized by increased workability and functionality for the owner and cost effectiveness in the total cost of ownership. In an attempt to reduce time and cost involved in the design process, this paper defines a best set of design parameters and uses GWO for the automatic configuration of this set of parameters in a manner that increases the maximum safe working load of the crane and reduces its total weight. Results are verified by a comparative study with other Evolutionary Algorithms (EAs). Results show that the GWO algorithm is able to provide very competitive results compared to these well-known meta-heuristics.

关键词： virtual prototyping product optimization artificial intelligence design automation software framework

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Proactive Healthcare and an Early Warning Mechanism for Coronary Artery Disease Patients using Internet-of-Thing Devices

Proactive Healthcare and an Early Warning Mechanism for Coro...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Shao-Jie Hsu Shih-Syun Lin Tun-Wen Pai Hamido Fujita Dept. of Computer Science and Engineering National Taiwan Ocean University Keelung Taiwan Intelligent Software Systems Laboratory Iwate Prefectural University Japan

ISBN: (纸本)9781509018987

Ubiquitous Internet environment and matured key technologies of sensing devices provide diversified applications of Internet of Thing (IoT). IoT in intelligent healthcare is one of the major topics for convincing powerful functions of IoT regarding the promotion of national health policies, strategies, and plans. However, according to statistics reports, annual global mortality for cardiovascular diseases remained as high as 29%, of which coronary artery disease (CAD) is accounted for 42%. Unfortunately, almost half of the patients not knowing they are at risk of cardiovascular diseases until serious symptoms occurred. Here, we proposed an early warning system by integrating IoT, big data, and cloud computing technologies which physically linked among personal communication devices of patient/doctor, cloud systems, and hospital medical information systems. The system collects personal heart rate and metabolic equivalent (MET) features from calibrated fitness devices wore by users, and corresponding fitted curves are dynamically calculated and compared to previously trained curve patterns from 213 patients with heart diseases and 124 healthy individuals. The prototype system was already successfully developed and validated by a couple of testing cases with excellent performance. To ensure the robustness of the proposed system, now we are evaluating system reliability and trying to collect more testing samples for further validating effectiveness of the proactive healthcare mechanism.

关键词： proactive healthcare mechanism Internet of medical thing metabolic equivalent(MET) coronary artery disease (CAD)

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Emergency online attention & psychological distance under risk 2

Emergency online attention & psychological distance under ri...

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2nd ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, EM-GIS 2016

作者： Deng, Qing Li, Lihua Liu, Yi Deng, Xiaolong Zhang, Hui Department of Engineering Physics Tsinghua University China Counter-Terrorism College People's Public Security University of China China Public Order School People's Public Security University of China China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781450345804

Risk communication is an effective means of emergency management. Online information plays an important role in risk communication, especially in the Big Data Era. Citizens' psychology to send and receive information determines their online behavior when they face risk. Using the Tianjin Port Explosions as an example, multiple linear regression analysis is used to untangle the relationship between online attention and psychology behavior under risk. Citizens' online attention is estimated by social media data collection from the Sina Weibo. Psychology behavior is quantified by psychological distance which consists of four dimensions: spatial distance, temporal distance, social distance and probability. The regression model is built via SPSS 20.0 and the obtained result is matched with actual situation. It indicates that online attention is negatively correlated to spatial distance, temporal distance and social distance while positively correlated to probability of the event. It also shows that citizens' online attention under risk is positively correlated to their online attention under normal circumstance. Based on the regression model, citizens' attention and response to emergency are easy to be assessed. CCS Concepts Information systems → Data analytics Mathematics of computing → Regression analysis Mathematics of computing → Exploratory data analysis. © 2016 ACM.

关键词： Risk management

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Multi-style video stylization based on texture advection

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Science China(Information Sciences) 2015年第11期58卷 90-102页

作者： TANG Ying ZHANG Yan SHI XiaoYing FAN Jing School of Computer Science and Technology Zhejiang University of Technology Key Laboratory of Visual Media Intelligent Process Technology of Zhejiang Province School of Software Engineering Hangzhou Dianzi University

Artistic video stylization, which is widely used in multimedia entertainment, transforms a given video into different artistic styles. Most of the existing video stylization algorithms can simulate single or limited video artistic styles. Although some algorithms can achieve multi-style video processing, these algorithms are complex and difficult to implement. To solve this problem, we propose a multi-styled video stylization algorithm based on texture advection, where different artistic styles are synthesized and transferred from user-specified texture samples of desired styles. We use the direction field-guided texture synthesis to compute the texture layer that represents the artistic style. Painterly directional video styles are simulated competently by the orientation changes in the synthesized anisotropic textures. There appeared local distorted region of the texture layer during texture advection under the optical flow field. To address this issue, we propose the texture inpaint to synthesize the limited distorted region and make the stylized video temporally coherent. We also accelerate the video stylization by using the CUDA parallel computing framework that parallelly computes the morphological operations used for video abstraction. Finally, we produce stylized videos of multiple artistic styles with satisfactory experimental results, including the styles of oil painting, watercolor painting and stylized lines drawing.

关键词： non-photorealistic rendering video stylization texture synthesis direction field CUDA

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Cryptanalysis of a Completely Anonymous Multi-recipient Signcryption Scheme with Public Verification

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Journal of Donghua University(English Edition) 2015年第2期32卷 240-243页

作者：张波孙涛于代荣 School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Shandong Provincial Key Laboratory of Software Engineering

Anonymity is a very important security objective in network ***,Pang et *** a novel multirecipient signcryption scheme with complete anonymity and claimed that the new concrete scheme was strong existential unforgeability under selective multi-ID,chosen message ***,by giving concrete attacks,named " inside attack" and " outside attack" respectively,we indicate that Pang et al.'s scheme is not secure in their security model.

关键词： recipient private claimed secure giving message signer outside secret chosen

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