1,721,688 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Dynamic Markov random fields
No full textIn this talk the author will outline some of the recent work undertaken by the Oxford Brookes Vision Group, a common theme underlying much of the research is to cast vision problems in terms of combinatorial optimization which provides a rich a deep theory for understanding them, with many new and exciting results
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Deep Reinforcement Learning in complex environments
Full text linkDeep Reinforcement Learning (DRL), is becoming a popular and mature framework for learning to solve sequential decision making problems. The application of Deep Neural Networks, flexible and powerful function approximators, towards learning policies has effectively enabled RL to solve applications that were thought to be too difficult: from beating professional human players in hard games such as Go, to becoming the foundation for flexible embodied control. We explore what happens when one attempts to learn policies in environments that present complex dynamics and hard and structured tasks. As these environments provide challenges that lie fundamentally at the forefront what most state-of-the-art Reinforcement Learning methods try to tackle, they provide a general view of existing weaknesses, while also providing opportunities for improving the general framework as well as particular algorithms. Firstly, we study and develop methods for Deep Multi-Agent Reinforcement Learning, a setting in which multiple agents are interacting with an (often complex) environment and each other. The presence of multiple agents breaks some of the key assumptions that provide necessary stability to standard learning methods, creating unique and interesting problems. We test these methods by formulating a multi-agent version of the StarCraft micromanagement problem, an extremely complex real-time control and planning problem based on one of the hardest environments currently available in the literature. Secondly, in a single-agent version of the same problem, we investigate how DRL can be used to develop a set of parameter-efficient differentiable planning modules to solve path-planning tasks with complex environment dynamics and variable map sizes. We show that the modules enable learning to plan when the environment also includes stochastic elements, providing a cost-efficient learning system to build low-level size-invariant planners for a variety of interactive, hard navigation problems. Thirdly, and lastly, we present a novel RL benchmark based on one of the oldest and most complex video games ever developed: the NetHack Learning Environment (NLE). NLE provides an environment that is scalable, rich, and challenging for state-of-the-art RL, while maintaining familiarity with standard grid-worlds, and dramatically decreasing the computational requirements compared to existing environments of similar complexity and scope. We believe that this particular intersection of properties will enable the community to employ a single environment both as a debugging tool for increasingly complicated RL agents, and as a target for the next decade of RL research
Structural and electrochemical analyses of a P2|O3 mixed-phase sodium-ion positive electrode active material
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