1,720,958 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
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
Programm der Schroeter'schen Erziehungsschule zu Jena (Elementar- und Realschule) : mit welchem zu der am Dienstag, den 20 März 1877, stattfindenden öffentlichen Prüfung im Namen des Lehrercollegiums ergebenst einladet Dr. Timon Schroeter, Rector. (1876/77)
Full text linkPROGRAMM DER SCHROETER'SCHEN ERZIEHUNGSSCHULE ZU JENA (ELEMENTAR- UND REALSCHULE) : MIT WELCHEM ZU DER AM DIENSTAG, DEN 20 MÄRZ 1877, STATTFINDENDEN ÖFFENTLICHEN PRÜFUNG IM NAMEN DES LEHRERCOLLEGIUMS ERGEBENST EINLADET DR. TIMON SCHROETER, RECTOR.
Programm der Schroeter'schen Erziehungsschule zu Jena (-)
Programm der Schroeter'schen Erziehungsschule zu Jena (Elementar- und Realschule) : mit welchem zu der am Dienstag, den 20 März 1877, stattfindenden öffentlichen Prüfung im Namen des Lehrercollegiums ergebenst einladet Dr. Timon Schroeter, Rector. (1876/77) (1)
Cover (1)
Titelblatt (6)
Einleitung (8)
Lehrverfassung der Elementar- und Realschule (10)
Statistische Nachrichten (14)
Nachrichten aus dem Schulleben (15)
Lehrmittel / Oeffentliche Prüfungen und Festlichkeiten (16
Maschinelles Lernen zur Entwicklung von Medikamenten
No full textIn dieser Dissertation werden sieben Studien vorgestellt, die sich mit der Entwicklung prädiktiver Modelle zur Anwendung in der Wirkstoffsuchforschung beschäftigen. Es wurden drei neue Algorithmen entwickelt um die Genauigkeit von Vorhersagen zu erhöhen, einzelne Vorhersagen zu erklären sowie Hinweise zur Optimierung von Molekülen zu gewinnen. Konkret wurden Modelle für die folgenden Eigenschaften chemischer Verbindungen entwickelt: Metabolische Stabilität, Ames Mutagenität, Wasserlöslichkeit, Verteilungskoeffizienten, Cytochrom P450 Inhibition, PPAR-gamma Bindung und den hERG-Ionenkanal Blockade Effekt. Aus Sicht des maschinellen Lernens ist die Chemoinformatik ein Anwendungsfeld mit vielen Herausforderungen, nicht nur, weil keine bis heute entwickelte Repräsentation chemischer Moleküle deren dynamischen dreidimensionalen Charakter adäquat beschreibt, sondern auch, weil in typischen Anwendungsfällen fundamentale Annahmen verletzt werden, die den meisten Algorithmen des maschinellen Lernens zu Grunde liegen. Weder werden Trainings- und Testdaten ideal identisch verteilt aus der gleichen Wahrscheinlichkeitsverteilung gezogen, noch sind die bedingten Wahrscheinlichkeiten für die Labels (gemessenen Eigenschaften) bei gegebenen Features (Deskriptoren) für Trainings- und Testdaten gleich. Darüber hinaus zeigen alle Eigenschaften, die Molekulare Erkennung beinhalten, extreme Sprünge, sog. Activity Cliffs. Um der Tatsache gerecht zu werden, dass, unabhängig vom verwendeten Lernalgorithmus, eine große Zahl von Testverbindungen nicht akkurat vorhergesagt werden können, wurden Gauß-Prozess Modelle in die Chemoinformatik eingeführt, denn deren prädiktive Varianzen können direkt als Schätzung der Zuverlässigkeit der Vorhersage interpretiert werden. Der praktische Nutzen dieses Vorgehens wurde in Studien zu Verteilungskoeffizienten, Wasserlöslichkeit und der Metabolischen Stabilität gezeigt. Es wurden zwei verschiedene Algorithmen entwickelt, um Vorhersagen (ggf. auch nicht-linearer) maschineller Lernmodelle zu erklären. Die erste Methode erklärt Vorhersagen durch Visualisierung der relevantesten Objekte (Moleküle) aus der Trainingsmenge des Modells. Für alle Verfahren des maschinellen Lernens, für die das verallgemeinerte Representer Theorem gilt, kann man den normierten Beitrag jedes Trainingsobjekts zur Vorhersage analytisch berechnen. In einer Fallstudie zur Ames Mutagenität wurde gezeigt, dass, durch Anpassung der Kernweite von Gauß-Kernen, Gauß-Prozess Klassifikationsmodelle erzeugt werden können, deren Vorhersagen jeweils nahezu vollständig durch eine kleine Zahl von Trainingsobjekten determiniert werden. Diese führen zu intuitiv verständlichen Visualisierungen, die auch aus chemischer Sicht überzeugen. Der zweite Algorithmus verwendet lokale Gradienten der Vorhersage um die lokal wichtigsten Features (Deskriptoren) zu ermitteln. Für Gauß-Prozesse können die lokalen Gradienten analytisch ermittelt werden. In einer Fallstudie zur Ames Mutagenität wurden sowohl Toxikophore als auch Detoxikophore korrekt identifiziert und selbst eine lokale Besonderheit im chemischen Raum (das untypische Verhalten der Steroide) wurde erkannt. Obwohl Wirkstoffdesign die ursprüngliche Motivation und das erste Anwendungsfeld für die neuen Algorithmen zum Erklären individueller Vorhersagen waren, lassen sich beide resultierenden Algorithmen auf eine große Vielfalt von Fragestellungen übertragen. In jedem Bereich, in dem Menschen dabei unterstützt werden sollen, Entscheidungen zu fällen, können Erklärungen von Modellvorhersagen wertvoll sein.This thesis presents seven studies about constructing predictive models for application in drug discovery and drug design. Three new algorithms have been developed to improve the accuracy of predictions, explain individual predictions and elicit hints for compound optimization. More specifically, predictive models for the following properties of chemical compounds have been developed: Metabolic Stability, Ames Mutagenicity, Aqueous Solubility, Partition Coefficients, Cytochrome P450 Inhibition, PPAR gamma binding and the hERG Channel Blockade Effect. From the point of view of machine learning, chemoinformatics is a very challenging field of endeavor, not only because as of today, no existing representation adequately captures the dynamical three dimensional nature of chemical molecules, but also because in typical drug discovery applications, fundamental assumptions common to most machine learning algorithms are severely violated. Neither are training and test data sampled ideally identically distributed from the same underlying probability density, nor is the conditional distribution of labels (measurements) given the input features (descriptors) the same in training and test data. Lastly, all properties concerned with molecular recognition can exhibit sudden extreme changes, so called activity cliffs. To cope with the fact that, regardless of the learning algorithm employed, many predictions for test compounds may not be correct, Gaussian Process models have been introduced into the field of chemoinformatics, because their predictive variances can directly serve as individual confidence estimates. The practical usefulness of predictive variances has been established in studies on Partition Coefficients, Aqueous Solubility and Metabolic Stability. Two separate algorithms for explaining individual predictions of (possibly non-linear) machine learning models are presented. The first method explains predictions by the means of visualizing relevant objects (molecules) from the training set of the model. For all machine learning methods covered by the generalized representer theorem, one can calculate the normalized contribution of each training data point analytically. In a case study on Ames Mutagenicity, it was found that by tuning the width-parameter of radial basis function kernels, Gaussian Process Classification models can be obtained where the prediction for each test compound is almost completely determined by very few training compounds, leading to intuitively understandable visualizations that were found to be convincing from a chemists point of view. The second algorithm utilizes local gradients of the model's predictions to obtain the locally most relevant features. In case of Gaussian Process models, local gradients can be calculated analytically. In a case study on Ames Mutagenicity, toxicophores and detoxicophores were identified correctly and even local peculiarities in chemical space (the extraordinary behavior of steroids) was discovered. While drug design served as the original motivation and testbed for developing algorithms for explaining individual predictions, both new methods can be applied to a wide range of modeling tasks. Wherever human experts are to be supported in making decisions, explanations of predictions will be valuable
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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