105,341 research outputs found

    Developing Central Pattern Generator based periodic motions using tactile interaction

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    Controlling robots by Central Pattern Generators (CPGs) is a widespread bio-inspired technique for the realization of robot motions. The numerous parameters of the CPGs, often specialized for a specific task, are usually set by automatic techniques like genetic algorithms or policy gradient. However, using these approaches leaves the users with little control on the resulting motion, which can be modified only by changing the evaluation function. Conversely manually setting each parameter gives the user full control over the motion, but identifying which parameters should be altered to obtain a desired effect is not intuitive and therefore developing motion requires time and effort. We present a system that allows programming the CPG parameters by interacting with the robot and in particular by intuitively touching the robot, giving the user full control on the resulting motion without requiring a direct modification of the parameter values

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Artificial neural network-based storm surge forecast model: Practical application to Sakai Minato, Japan

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    The present study describes a novel way of a systematic and objective selection procedure for the development of an Artificial Neural Network-based storm Surge Forecast Model (ANN-SFM) with the 5, 12 and 24 h-lead times and its application to Sakai Minato area on the Tottori coast, Japan. The selection procedure guides how to determine the superiority of the best performing model in terms of the appropriate combination of unit number in the hidden layer and parameter in the input layer. In the application of ANN-SFM to Sakai Minato, it is found that the best 5 and 12 h-forecast ANN-SFMs are established with the most suitable set of 70 units (the number of hidden neurons) and the input components of surge level, sea level pressure, the depression rate of sea level pressure, longitude, latitude, central atmospheric pressure and highest wind speed. The best 24 h-forecast ANN-SFM is determined with 160 units and the input parameters of surge level, sea level pressure, the depression rate of sea level pressure, longitude and latitude. The proposed method of the selection procedure is able to be adaptable to other coastal locations for the development of the artificial neural network-based storm surge forecast model as establishing the superiority of the most relevant set combining unit numbers and input parameters

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Distributed Vision System For Robot Localisation In Indoor Environment

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    Traditional image-based localisation methods do not work when the robot is moving in an environment whose appear- ance is changing in time. We propose an extension to the classical image-based localisation that uses a Distributed Vision System (DVS) and can work also in highly dynamic environments. The DVS is composed of omnidirectional cameras installed in the environment and can communicate with the robot. The localisation of the robot is achieved by comparing the current image grabbed by the robot with the images grabbed at the same time by the DVS. Finding the DVS’s image most similar to the robot’s image gives a topological localisation of the robot. In this paper, we an- alyze requirements and effectiveness of this approach and we present some preliminary experimental results obtained with the Distributed Vision System

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    The construction of Karen Karnak: The multi-author-function

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    This thesis is situated within the comparatively recent developments of Web 2.0 and the emergence of interactive WikiMedia, and explores the mode of authorship within a Read/Write culture compared to that of a Read/Only tradition. The hypothesis of this study is that the role of the audience has become merged with the author, and as such, represents new functions and attributes, distinct from a more conventional concept of authorship, in which the roles of audience and author are more separate. Read/Write and participatory culture, as defined by this study, is focused on collaboration, and includes the influences of D.I.Y. culture, Open-Source practices and the production of text by multiple authors. Multi-authorship presents a re-thinking of several concepts which support the notion of the individual author, since the focus of multi-authorship is not on attribution and ownership of a finished text, but on the continued malleability of a text. Modes of multi-authorship, demonstrated in the use of the pseudonyms Alan Smithee and Karen Eliot, represent declarative authors whose names signify multiple origins, whilst concurrently indicating a distinct body of work. The function of these names form an important context to this study, since primary research involves the construction of an experimental mode of multi-authorship utilising WikiMedia technology and the interaction of thirty nine participants, who are invited to create a body of work under the collective pseudonym Karen Karnak. The data generated by this experiment is analysed using aspects of Michel Foucault's author-function to identify and determine power structures inherent in the WikiMedia context. The interplay of power structures, including concepts such as identity, ownership and the body of work, affect the resulting mode of authorship and contribute to the construction of Karen Karnak, suggesting further areas of research into the emerging multi-author

    Contribution of Information and Communication Technology (ICT) in Country’S H-Index

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    The aim of this study is to examine the effect of Information and Communication Technology (ICT) development on country’s scientific ranking as measured by H-index. Moreover, this study applies ICT development sub-indices including ICT Use, ICT Access and ICT skill to find the distinct effect of these sub-indices on country’s H-index. To this purpose, required data for the panel of 14 Middle East countries over the period 1995 to 2009 is collected. Findings of the current study show that ICT development increases the H-index of the sample countries. The results also indicate that ICT Use and ICT Skill sub-indices positively contribute to higher H-index but the effect of ICT access on country’s H-index is not clear

    Fully Turbulent Mean Velocity Profile for Purely Viscous non-Newtonian Fluids

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    The characteristic near wall behavior of turbulent flow of purely-viscous non-Newtonian fluids is discussed for both power-law (P.-L.) and Herschel-Bulkley (H.-B.) rheological models. A proper scaling is presented for H.-B. fluids to establish an analogy with power-law fluids with same flow index. To provide reference data for turbulent flow of non-Newtonian fluids, DNS simulations of power-law fluids are conducted in a rectangular channel for a large range of power-law indices (nn = 0.5, 0.69, 0.75, 0.9, 1, 1.2). The DNS data show that the mean velocity profile in the viscous and logarithmic layers follow expressions of the form u+=y+u^{+}=y^{+} and u+=2.5log(y+)+Bnu^{+}=2.5\,log(y^{+})+B_{n} respectively, where BB shows a logarithmic dependency on the flow index.Comparison with some experimental data shows the above formulation to be valid for Reynolds numbers (based on shear velocity) as high as 1000
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