Scheme for preparation of mulipartite entanglement of atomic ensembles

We describe an experimental scheme of preparing multipartite W class of maximally entangled states between many atomic ensembles. The scheme is based on laser manipulation of atomic ensembles and single-photon detection, and well fits the status of the current experimental technology. In addition, we show one of the applications of the kind of W class states, teleporting an entangled state of atomic ensembles with unknown coefficients to more than one distant parties, either one of which equally likely receives the transmitted state.Comment: 4 pages, 3 figure

Automatic Detection of Public Development Projects in Large Open Source Ecosystems: An Exploratory Study on GitHub

Hosting over 10 million of software projects, GitHub is one of the most important data sources to study behavior of developers and software projects. However, with the increase of the size of open source datasets, the potential threats to mining these datasets have also grown. As the dataset grows, it becomes gradually unrealistic for human to confirm quality of all samples. Some studies have investigated this problem and provided solutions to avoid threats in sample selection, but some of these solutions (e.g., finding development projects) require human intervention. When the amount of data to be processed increases, these semi-automatic solutions become less useful since the effort in need for human intervention is far beyond affordable. To solve this problem, we investigated the GHTorrent dataset and proposed a method to detect public development projects. The results show that our method can effectively improve the sample selection process in two ways: (1) We provide a simple model to automatically select samples (with 0.827 precision and 0.947 recall); (2) We also offer a complex model to help researchers carefully screen samples (with 63.2% less effort than manually confirming all samples, and can achieve 0.926 precision and 0.959 recall).Comment: Accepted by the SEKE2018 Conferenc

Navigation Objects Extraction for Better Content Structure Understanding

Existing works for extracting navigation objects from webpages focus on navigation menus, so as to reveal the information architecture of the site. However, web 2.0 sites such as social networks, e-commerce portals etc. are making the understanding of the content structure in a web site increasingly difficult. Dynamic and personalized elements such as top stories, recommended list in a webpage are vital to the understanding of the dynamic nature of web 2.0 sites. To better understand the content structure in web 2.0 sites, in this paper we propose a new extraction method for navigation objects in a webpage. Our method will extract not only the static navigation menus, but also the dynamic and personalized page-specific navigation lists. Since the navigation objects in a webpage naturally come in blocks, we first cluster hyperlinks into different blocks by exploiting spatial locations of hyperlinks, the hierarchical structure of the DOM-tree and the hyperlink density. Then we identify navigation objects from those blocks using the SVM classifier with novel features such as anchor text lengths etc. Experiments on real-world data sets with webpages from various domains and styles verified the effectiveness of our method.Comment: 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI

Rigid vortices in MgB2

Magnetic relaxation of high-pressure synthesized MgB$_2$ bulks with different thickness is investigated. It is found that the superconducting dia-magnetic moment depends on time in a logarithmic way; the flux-creep activation energy decreases linearly with the current density (as expected by Kim-Anderson model); and the activation energy increases linearly with the thickness of sample when it is thinner than about 1 mm. These features suggest that the vortices in the MgB$_2$ are rather rigid, and the pinning and creep can be well described by Kim-Anderson model.Comment: Typo corrected & reference adde