Search

This study focuses on robust Tomlinson-Harashima precoding transceiver design for multi-cell multiple-input- multiple-output interference channel with statistical channel state information error. The objective is formulated to minimise the maximum per-user mean square error (MSE) with per-transmitter power constraint. Since the problem is not jointly convex, an approximated method is proposed. The authors optimise the receiver matrix to be minimum MSE form as well as derive the optimisation problems of transmitter matrix and feedback matrix to be second-order cone programming, respectively. By use of the results, the three matrices are updated iteratively. The convergence of the proposed method is also proved. Simulation results show that the proposed scheme outperforms the robust linear transceiver in both MSE and bit error ratio. [ABSTRACT FROM AUTHOR]

In conventional schedule-based wireless transmission system, frequent interactions between devices and access networks lead to significant signalling overhead, and thus limit the development of low-latency applications. Contention-based data transmission (CBDT) is widely used as a promising solution to address the above issues. In this study, the authors propose a detection-based retransmission scheme for CBDT to further reduce the delay-outage probability which cannot be avoided due to collision. In this scheme, each device simultaneously monitors the occupied resource blocks during data transmission. When a collision event is detected, the retransmission for this packet is determined without waiting for the acknowledgment message from the receiver. The reliability performance is significantly improved for low-latency applications, since the possible retransmission times for each packet is increased within the limited transmission period. In addition, the impacts of imperfect detection on extra transmission load and packet loss are analysed in detail. The simulation and analytical results demonstrate that the detection-based scheme significantly improves the reliability of CBDT. [ABSTRACT FROM AUTHOR]

In this article, we describe the results of an experiment designed to understand the effects of background information and social interaction on image tagging. The participants in the experiment were asked to tag 12 preselected images of Jewish cultural heritage. The users were partitioned into three groups: the first group saw only the images with no additional information whatsoever, the second group saw the images plus a short, descriptive title, and the third group saw the images, the titles, and the URL of the page in which the image appeared. In the first stage of the experiment, each user tagged the images without seeing the tags provided by the other users. In the second stage, the users saw the tags assigned by others and were encouraged to interact. Results show that after the social interaction phase, the tag sets converged and the popular tags became even more popular. Although in all cases the total number of assigned tags increased after the social interaction phase, the number of distinct tags decreased in most cases. When viewing the image only, in some cases the users were not able to correctly identify what they saw in some of the pictures, but they overcame the initial difficulties after interaction. We conclude from this experiment that social interaction may lead to convergence in tagging and that the “wisdom of the crowds” helps overcome the difficulties due to the lack of information. [ABSTRACT FROM AUTHOR]

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube). [ABSTRACT FROM AUTHOR]

In early 2006, information industry association UKSG commissioned a research report 'to identify the new relationships and information exchange requirements... [necessary] to maximize the benefit of OpenURL linking'. Central to the efficient operation of the OpenURL is the knowledge base, which consists of data supplied by content providers including publishers. The report found that a lack of awareness on the part of many publishers of the OpenURL's capabilities and requirements is impacting the quality and timeliness of the data they provide to populate knowledge bases, and thus undermining the potential of this sophisticated technology. A programme of education and advocacy, particularly among smaller publishers, will be key to improving the efficacy with which OpenURL is currently implemented. The study's findings and suggestions will be taken forward by the KBART (Knowledge Bases And Related Tools) working group co-chaired by UKSG and NISO; this article reviews the initial report and summarizes the planned remit and expected outcomes of the working group. [ABSTRACT FROM AUTHOR]