Exploring album structure for face recognition in online social networks

In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.     

Present it like it is here: Creating local presence to improve online product experiences

Advanced online product presentation technologies such as virtual mirrors enable consumers to experience products like they are actually present with them in the real world. This study is one of the first to address the mechanism underlying this phenomenon. Inspired by literature on media technology the concept of local presence is put forward and applied to the online consumer behavior domain. A key objective of this paper is to examine whether local presence adds to our understanding of how emerging product presentation formats influence online product experiences. To this end, a laboratory experiment (N = 366) was conducted with product presentation format as a three level (pictures, 360-spin rotation, and virtual mirror) independent variable, allowing for a comparison of the effectiveness of different presentation formats in creating perceptions of local presence. As a second objective, the influence of local presence on perceptions of product tangibility and product likability, two key facets of the online product experience, were assessed. The results, obtained with the use of analysis of variance and partial least squares modeling, show the superiority of the virtual mirror in creating local presence, and demonstrate that local presence is highly predictive of product tangibility and product likability. Theoretical and managerial implications are discussed.     

A stochastic Kaczmarz algorithm for network tomography

We develop a stochastic approximation version of the classical Kaczmarz algorithm that is incremental in nature and takes as input noisy real time data. Our analysis shows that with probability one it mimics the behavior of the original scheme: starting from the same initial point, our algorithm and the corresponding deterministic Kaczmarz algorithm converge to precisely the same point. The motivation for this work comes from network tomography where network parameters are to be estimated based upon end-to-end measurements. Numerical examples via Matlab based simulations demonstrate the efficacy of the algorithm.     

利用电阻探针对石油设备及管道的腐蚀进行监测

从1998年起，国内石油炼制行业开始大量炼制进口高硫原油，油气管道的腐蚀问题受到了重视。介绍了电阻探针腐蚀监测系统的原理及组成。并针对油气管道，实施了在线监测，安装了6组腐蚀电阻探针，分析了测量结果，为今后防腐工作提供了依据。     

Online learning and fusion of orientation appearance models for robust rigid object tracking

We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the Kinect. To combine these two completely different modalities, we propose to use features that do not depend on the data representation: angles. More specifically, our framework combines image gradient orientations as extracted from intensity images with the directions of surface normals computed from dense depth fields. We propose to capture the correlations between the obtained orientation appearance models using a fusion approach motivated by the original Active Appearance Models (AAMs). To incorporate these features in a learning framework, we use a robust kernel based on the Euler representation of angles which does not require off-line training, and can be efficiently implemented online. The robustness of learning from orientation appearance models is presented both theoretically and experimentally in this work. This kernel enables us to cope with gross measurement errors, missing data as well as other typical problems such as illumination changes and occlusions. By combining the proposed models with a particle filter, the proposed framework was used for performing 2D plus 3D rigid object tracking, achieving robust performance in very difficult tracking scenarios including extreme pose variations.     

Research on the measure method of complaint theme influence on online social network

Consumer complaints on online social network quickly become online groups complaints through many people’s aggregation and looking on, interaction and word-of-mouth communication. Therefore, assessing and managing online complain influence has become a new problem for enterprise to listen to and manage online group complaints. This paper analyzed the complaint information feature of consumer group on online social network, from three-dimensional perspective of complaint text’s quality, transmission timeliness and user interaction degree. We built the influence measure model of online complaint theme based on entropy weight model by monitoring and analyzing real-time the static and dynamic properties of complaint information, explored the measure method of complaint theme influence, employed empirical method to verify the validity and provided scientific decision-making tools and methods for enterprise listening to and managing online group complains.     

Public Displays of Play: Studying Online Games in Physical Settings

As research on virtual worlds gains increasing attention in educational, commercial, and military domains, a consideration of how player populations are ‘reassembled’ through social scientific data is a timely matter for communication scholars. This paper describes a large‐scale study of virtual worlds in which participants were recruited at public gaming events, as opposed to through online means, and explores the dynamic relationships between players and contexts of play that this approach makes visible. Challenging conventional approaches to quantitatively driven virtual worlds research, which categorizes players based on their involvement in an online game at a particular point in time, this account demonstrates how players' networked gaming activities are contingent on who they are playing with, where, and when.     

E-life--家居生活视频网设计与实现

E-life--家居生活视频网主要是在和用户充分交流的基础上,实现资源共享,共同建设属于普通大众的现代家居生活视频网站。其立足于现代家居生活,通过对现代家居生活类视频的集合,从而方便用户的检索、浏览和下载。