1,721,063 research outputs found
Sparse Optimal Control for Networked Systems --Understanding by Case Studies
特集号: 「カーシェアリングサービスに対するシステム制御的アプローチ
Rare-event Modeling for Dynamical Systems and Its Applications: Stable Distribution Approach
動的な現象をモデル化する際に,それが内包する確率的不確かさを適切にモデルに組み込むことは重要である.特に近年では,突風による風力発電量の急激な変動など,システムに大きな影響を与えるレアイベントを考慮した不確かさのモデリング・解析手法がますます求められている.動的システムにおける確率的不確かさを表現するのに最も用いられるのは,ガウス型の雑音であり,解析的な扱いやすさという大きな利点をもつ一方で,裾が急速に減衰するガウス分布では外れ値を表現することができない.そこで本稿ではレアイベントモデリングが可能,かつ,動的システムでの解析的扱いやすさを併せもつ,安定分布を利用したモデリング手法を解説する.また本枠組みの応用例として,等価線形化による非線形システム解析,動的システムにおけるプライバシー保護を紹介する.When we model dynamic phenomena, it is important to properly incorporate their probabilistic uncertainty. In particular, there is an increasing need for modeling and analysis methods for rare events that cause severe impact, e.g., extreme wind power fluctuations due to gusts. For the modeling of the stochasticity in dynamical systems, Gaussian noise is often used because of its analytical tractability. However, it cannot represent outliers because of its rapidly decaying tails. In this context, this article introduces a modeling and analysis method using stable distributions. This framework is capable of modeling rare events while retaining the favorable properties equipped with the Gaussian. As applications, we also describe our results on stochastic linearization analysis and privacy protection in dynamical systems
Going Beyond Counting First Authors in Author Co-citation Analysis
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
Variations on the Author
“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
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
Dispelling the Myths Behind First-author Citation Counts
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We 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
Nonlinear model reduction by deep autoencoder of noise response data
In this paper a novel model order reduction method for nonlinear systems is proposed. Differently from existing ones, the proposed method provides a suitable non-linear projection, which we refer to as control-oriented deep autoencoder (CoDA), in an easily implementable manner. This is done by combining noise response data based model reduction, whose control theoretic optimality was recently proven by the author, with stacked autoencoder design via deep learning
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