306,314 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Nouvelles espagnoles de Miguel de Cervantes
No full textSign.: A-D, A-B, C, A-C, D, A-C, D, A-DCada parte ten portadilla e pax. propiaPort. con grav. xilAs il son xilLa bohemienne , nouvelle premiere ; L'amant libéral, nouvelle seconde ; Theodosie Etleocadie, nouvelle troisieme ; Le falous d'estrémadure, nouvelle quatrieme ; L'espagnole angloise, nouvelle cinquieme ; le sot curreux, nouvelle sixiem
A SIMULATION APPROACH TO THE VALUATION OF CAPITAL BUDGETING PROJECTS INCORPORATING A DEFER OPTION
No full textTechniques applied to determine the value of derivatives have been recently exported in the field of investment valuation. This paper aims to provide some light to the use of a new technique in the investment valuation literature, aiming to take into account the value of flexibility. This technique, designed by Longstaff and Schwartz, combines Monte Carlo simulation and the Ordinary Least Squares in order to value American-style derivatives with different specifications. We show that this method can easily be incorporated to value capital budgeting projects in the framework of the real options theory and provides coherent results from an economic point of view. We do this by estimating the value of several cases of an investment project that incorporates an option to defer the initial investment or layout through time. We estimate these values by using the Ox programming language. Algunas técnicas aplicadas para determinar el valor de derivados han sidorecientemente exportadas en el campo de la valoración de inversiones. Este trabajo tienecomo objetivo clarificar el uso de una nueva técnica dentro de la literatura de valoraciónde inversiones, teniendo en cuenta el valor de flexibilidad. Esta técnica, diseñada porLongstaff y Schwartz, combina la simulación de Monte Carlo y los Mínimos CuadradosOrdinarios con el objetivo de valorar derivados de tipo americano con distintasespecificaciones. En este trabajo demostramos que este método puede ser fácilmenteincorporado para valorar proyectos de inversión en el marco de la teoría de opcionesreales y muestra resultados coherentes desde el punto de vista económico. Lo hacemosestimando el valor de distintos casos de un proyecto de inversión que incorpora unaopción de posponer la inversión inicial en el tiempo. Estimamos estos valores usando ellenguaje de programación Ox.Least Squares Monte Carlo, opción de espera, movimiento geométrico Browniano, proyecto de inversión. Least Squares Monte Carlo, defer option, geometric Brownian motion, investment project.
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
La France ne meurt pas ! ! : ode patriotique / de Paul Defer
No full textAppartient à l’ensemble documentaire : LangRous1Avec mode text
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems
No full textLearn-to-Defer is a paradigm that enables learning algorithms to work not in isolation but as a team with human experts. In this paradigm, we permit the system to defer a subset of its tasks to the expert. Although there are currently systems that follow this paradigm and are designed to optimize the accuracy of the final human-AI team, the general methodology for developing such systems under a set of constraints (e.g., algorithmic fairness, expert intervention budget, defer of anomaly, etc.) remains largely unexplored. In this paper, using a -dimensional generalization to the fundamental lemma of Neyman and Pearson (d-GNP), we obtain the Bayes optimal solution for learn-to-defer systems under various constraints. Furthermore, we design a generalizable algorithm to estimate that solution and apply this algorithm to the COMPAS and ACSIncome datasets. Our algorithm shows improvements in terms of constraint violation over a set of baselines
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