1,721,044 research outputs found
Organisms modeling: The question of radial basis function networks
No full textThere exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of systems-theory and artificial neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evaluation of an usual machine learning technique (radial basis function(RBF) networks) in the context of systems and biological reactive organism
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
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
Quantization-based simulation of spiking neurons: theoretical properties and performance analysis
Full text linkIn this work we present an exhaustive analysis of the use of Quantized State Systems (QSS) algorithms for the discrete event simulation of Leaky Integrate and Fire models of spiking neurons. Making use of some properties of these algorithms, we first derive theoretical error bounds for the sub-threshold dynamics as well as estimates of the computational costs as a function of the accuracy settings. Then, we corroborate those results on different simulation experiments, where we also study how these algorithms scale with the size of the network and its connectivity. The results obtained show that the QSS algorithms, without any type of optimisation or specialisation, obtain accurate results with low computational costs even in large networks with a high level of connectivity.Fil: Bergonzi, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Fernandez, Joaquin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Muzy, Alexandre. Centre National de la Recherche Scientifique; FranciaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin
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
Solving credit assignment problems involving different decision making structures
No full textLe problème d'attribution de crédit consiste à attribuer du (dis)crédit aux actions résultant d'un processus de prise de décisions. Dans cette thèse, les processus de prise de décisions sont étudiés sous la forme de structures parallèle et série. Pour la structure parallèle, les processus de prise de décision sont indépendants les uns des autres. Alors pour la structure série, les processus décisionnels sont exécutés dans l'ordre et dépendent éventuellement les uns des autres. La prise en compte de la structure d'un problème d'apprentissage doit permettre une meilleure attribution des crédits, et donc d'apprendre à associer les processus de prise de décision aux actions. Ces structures de prise de décisions sont considérées ici pour des apprentissages multi-agents et par renforcement. Dans un apprentissage multi-agent, on distingue les structures parallèle et série. Dans la structure parallèle, chaque agent interagit avec sa propre machine à sous (ou ensemble d'actions possibles) indépendamment des autres agents, et coopère avec les autres agents pour atteindre un objectif commun. Dans la structure série, deux niveaux de prise de décision sont impliqués : un agent dit leader (au niveau supérieur) et des agents dits followers (au niveau inférieur). L'agent leader attribue chaque agent follower à sa machine à sous. Ensuite, les agents followers choisissent indépendamment un levier. Enfin, nous abordons l'apprentissage d'une tâche comportementale d'un agent dans le contexte de l'apprentissage par renforcement où la récompense est retardée dans le temps et non Markovienne, pour une série de processus décisionnels dépendants. Pour toutes les structures de décision, un algorithme policy-gradient est proposé. La convergence des algorithmes est prouvée, et leurs performances sont évaluées et comparées sur des données artificielles.Credit assignment problem consists of how to assign credit or blame for outcomes of decision-making processes to the actions that could have contributed to those outcomes. In this thesis the decision-making processes are studied in the form of parallel and series structures. In the parallel form, decision-making processes are independent from each others. While in the series form, decision-making processes are taken in order and possibly depend on each others. Leveraging the structure of a learning problem should allow a better credit assignment, thus learning how to map decision-making processes to actions. The decision-making structures are considered here in multi-agent learning and reinforcement learning. In a multi-agent learning, we distinguish the parallel and series structures. In the parallel structure, each agent interacts with its own multi-armed bandit (or set of actions) independently from the other agents, and cooperate to achieve an objective. In the series structure, two levels of decision making are involved: a leader agent (at top level) and follower agents (at bottom level). The leader agent chooses how the agents are distributed over the multi-armed bandits in a one-to-one assignment. Then the follower agents independently select an arm in the multi-armed bandit they are assigned to. Finally, we address a behavioral task learning of one agent in the context of reinforcement learning where the reward is delayed in time and non Markovian, for a series of dependent decision-making processes. For all decision structures, a policy gradient algorithm is proposed. The convergence of the algorithms is proved, and their performances are assessed and compared on several synthetic data sets
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