32,886 research outputs found

    Experiences on a motivational learning approach for robotics in undergraduate courses

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    This paper presents an educational experience carried out in robotics undergraduate courses from two different degrees: Computer Science and Industrial Engineering, having students with diverse capabilities and motivations. The experience compares two learning strategies for the practical lessons of such courses: one relies on code snippets in Matlab to cope with typical robotic problems like robot motion, localization, and mapping, while the second strategy opts for using the ROS framework for the development of algorithms facing a competitive challenge, e.g. exploration algorithms. The obtained students’ opinions were instructive, reporting, for example, that although they consider harder to master ROS when compared to Matlab, it might be more useful in their (robotic related) professional careers, which enhanced their disposition to study it. They also considered that the challenge-exercises, in addition to motivate them, helped to develop their skills as engineers to a greater extent than the skeleton-code based ones. These and other conclusions will be useful in posterior courses to boost the interest and motivation of the students.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Identifying Gaps and Setting Priorities for Employment and Training Research

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    The report summarizes recent workforce and employment related research, to identify current gaps in employment and training research and makes recommendations for future research processes and priorities that could better inform policy makers, practitioners, job seekers and employers. The report reviews workforce and related research funded by several federal agencies, including the US Departments of Labor, Education, Agriculture, Health and Human Services, and Housing and Urban Development, the National Science Foundation and other federal entities, as well as research undertaken by regional, state and local workforce agencies and philanthrophic organizations

    Bibliometric Mapping of the Computational Intelligence Field

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    In this paper, a bibliometric study of the computational intelligence field is presented. Bibliometric maps showing the associations between the main concepts in the field are provided for the periods 1996–2000 and 2001–2005. Both the current structure of the field and the evolution of the field over the last decade are analyzed. In addition, a number of emerging areas in the field are identified. It turns out that computational intelligence can best be seen as a field that is structured around four important types of problems, namely control problems, classification problems, regression problems, and optimization problems. Within the computational intelligence field, the neural networks and fuzzy systems subfields are fairly intertwined, whereas the evolutionary computation subfield has a relatively independent position.neural networks;bibliometric mapping;fuzzy systems;bibliometrics;computational intelligence;evolutionary computation

    JISC Research Data MANTRA Project at EDINA, Information Services, University of Edinburgh: Evaluation

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    This document reports on the findings of an evaluation of the Research Data MANTRA project at the University of Edinburgh. The MANTRA project ran from 1 August 2010 to 31 July 2011 and, as part of the JISC Managing Research Data programme's training materials projects, produced training materials in research data management for postgraduate researchers of specific disciplines. This evaluation is intended to provide, after a light-touch review, an impression of the extent to which the project achieved its goals and suggestions for where further work may be useful

    Feature extraction and classification of movie reviews

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    Brain Mechanisms of Persuasion: How "Expert Power" Modulates Memory and Attitudes

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    Human behavior is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as "expert power", is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging (fMRI), we probed the neural processes predicting these behavioral effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behavior, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion.neuroeconomics;social influence;attitude;expertise;persuasion;celebrities;memory encoding

    The Best Answers? Think Twice: Online Detection of Commercial Campaigns in the CQA Forums

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    In an emerging trend, more and more Internet users search for information from Community Question and Answer (CQA) websites, as interactive communication in such websites provides users with a rare feeling of trust. More often than not, end users look for instant help when they browse the CQA websites for the best answers. Hence, it is imperative that they should be warned of any potential commercial campaigns hidden behind the answers. However, existing research focuses more on the quality of answers and does not meet the above need. In this paper, we develop a system that automatically analyzes the hidden patterns of commercial spam and raises alarms instantaneously to end users whenever a potential commercial campaign is detected. Our detection method integrates semantic analysis and posters' track records and utilizes the special features of CQA websites largely different from those in other types of forums such as microblogs or news reports. Our system is adaptive and accommodates new evidence uncovered by the detection algorithms over time. Validated with real-world trace data from a popular Chinese CQA website over a period of three months, our system shows great potential towards adaptive online detection of CQA spams.Comment: 9 pages, 10 figure

    Is Management Interdisciplinary? The Evolution of Management as an Interdisciplinary Field of Research and Education in the Netherlands

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    Management research and education are often characterized as being interdisciplinary. However, most discussions on what interdisciplinarity in management studies means have bogged down in ideological fixations. In this paper we alternatively take a historical perspective and analyze the evolution of the interdisciplinarity concept in management studies during the last decades in the Netherlands. We distinguish between two opposite versions of interdisciplinarity: a synoptic (conceptual) and an instrumental (pragmatic) one. Both versions resulted from different knowledge strategies (boundary-work) of competing and cooperating disciplines. We conclude that in the Netherlands instrumental versions of interdisciplinarity in management research and education prevailed.management science;Interdisciplinarity;disciplinarity;management education;history of management education
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