521,311 research outputs found

    Revisiting h measured on UK LIS and IR academics

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    A brief communication appearing in this journal ranked UK LIS and (some) IR academics by their h-index using data derived from Web of Science. In this brief communication, the same academics were re-ranked, using other popular citation databases. It was found that for academics who publish more in computer science forums, their h was significantly different due to highly cited papers missed by Web of Science; consequently their rank changed substantially. The study was widened to a broader set of UK LIS and IR academics where results showed similar statistically significant differences. A variant of h, hmx, was introduced that allowed a ranking of the academics using all citation databases together

    Complexity of ITL model checking: some well-behaved fragments of the interval logic HS

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    Model checking has been successfully used in many computer science fields, including artificial intelligence, theoretical computer science, and databases. Most of the proposed solutions make use of classical, point-based temporal logics, while little work has been done in the interval temporal logic setting. Recently, a non-elementary model checking algorithm for Halpern and Shoham's modal logic of time intervals HS over finite Kripke structures (under the homogeneity assumption) and an EXPSPACE model checking procedure for two meaningful fragments of it have been proposed. In this paper, we show that more efficient model checking procedures can be developed for some expressive enough fragments of HS

    A Molecular Biology Database Digest

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    Computational Biology or Bioinformatics has been defined as the application of mathematical and Computer Science methods to solving problems in Molecular Biology that require large scale data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential role in Computational Biology research and development. This paper introduces into current Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the integration of Molecular Biology data from different sources. This paper is primarily intended for an audience of computer scientists with a limited background in Biology

    A Survey of the Trends in Facial and Expression Recognition Databases and Methods

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    Automated facial identification and facial expression recognition have been topics of active research over the past few decades. Facial and expression recognition find applications in human-computer interfaces, subject tracking, real-time security surveillance systems and social networking. Several holistic and geometric methods have been developed to identify faces and expressions using public and local facial image databases. In this work we present the evolution in facial image data sets and the methodologies for facial identification and recognition of expressions such as anger, sadness, happiness, disgust, fear and surprise. We observe that most of the earlier methods for facial and expression recognition aimed at improving the recognition rates for facial feature-based methods using static images. However, the recent methodologies have shifted focus towards robust implementation of facial/expression recognition from large image databases that vary with space (gathered from the internet) and time (video recordings). The evolution trends in databases and methodologies for facial and expression recognition can be useful for assessing the next-generation topics that may have applications in security systems or personal identification systems that involve "Quantitative face" assessments.Comment: 16 pages, 4 figures, 3 tables, International Journal of Computer Science and Engineering Survey, October, 201

    Report on the EU-US Workshop on Large Scientific Databases

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    This joint workshop was set up under the auspices of the Joint European Commission/National Science Foundation Strategy Group that met in Budapest in September 1998. The meeting derived from a joint collaboration agreement between the EC and NSF, signed by Dr. George Metakides (Director of Information Technologies for the EC) and Prof. Juris Hartmanis (Director of Computer and Information Science and Engineering at the NSF). Some themes that were identified include: digital libraries human-centered computing and virtual environments large scientific databases, and intelligent implants This report expresses the conclusions and recommendations of the Workshop on Large Scientific Databases, held in Annapolis, Maryland, USA in September 1999. The purpose of the workshop was to develop a report to the funding agencies outlining a possible solicitation to the research community, with emphasis on joint European-US work on Large Scientific Databases. Before the workshop, each participant submitted a position paper (these are available at the web site http://www.cacr.caltech.edu/euus). The results of the position papers, presentations, and group discussion are summarized in this report. There were 12 participants from Europe and 12 from the United States, and they are listed at the end of this report. The last section of this report describes possible funding mechanisms

    Generating Multimedia Components for M-Learning

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    The paper proposes a solution to generate template based multimedia components for instruction and learning available both for computer based applications and for mobile devices. The field of research is situated at the intersection of computer science, mobile tools and e-learning and is generically named mobile learning or M-learning. The research goal is to provide access to computer based training resources from any location and to adapt the training content to the specific features of mobile devices, communication environment, users' preferences and users' knowledge. To become important tools in education field, the technical solutions proposed will follow to use the potential of mobile devices.M-learning, mobile devices, MPEG-21 standard, multimedia databases
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