1,720,953 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Rainfal - runoff simulation with machine learning methods
No full textThe conversion of precipitation to runoff is considered one of the most important research areas in the science of hydrology. The rainfall-runoff modelling provides considerable information about the hydrologic behavior of a watershed and given the probability of appearance of flood events which usually caused from extreme weather phenomena. The watershed management and the planning of hydraulic technical infrastructure depends on water influx, losses and final discharges. The main water influx in the watershed comes from precipitation (rainfall and snowfall) and the losses include infiltration, evapotranspiration and interception. Finally the remaining water from the difference between influx and losses is the water discharge. The complexity of the rainfall-runoff relationship and the numerous parameters it involves make it difficult to determine a mathematical function that will describe precisely the final runoff. Artificial intelligence and machine learning methods have the important advantage that they can approach the hydrological phenomena without requiring the exact knowledge of the physical parameters that affect the rainfall-runoff relationship. The fact that these methods have the ability to determine a relationship between inputs and target data makes them powerful computational tools for the simulation of complex water processes such as the transformation of precipitation to runoff. In the present dissertation four models were developed for the rainfall-runoff simulation, each one using a different machine learning approach. More specifically the author has developed models of artificial neural networks, Bayesian neural networks, support vector regression models and ensemble methods (Boosting and Bagging). We make a special mention to the Boosting learning algorithm, which was developed in order to be adaptable to the special characteristics of the meteorological and hydrological data, providing accurate predictions both of normal and extreme runoff values. This particular model named HydroBAL which is the initialism for “Hydrologic Boosting ALgorithm”. The models were applied to three watersheds for which data of precipitation and runoff were available. The application of the models showed that all of them simulate efficiently the rainfall-runoff relationship and their differences are minor. An important aspect of the models is their considerable accuracy in forecasting the extreme values. These values rarely appear in the time series data (inputs-targets) and diverge from the normal data range, so their prediction is very difficult. However these values are important because they are directly connected to flood events. Finally the effectiveness of these models at all levels of runoff simulation and forecasting create positive expectations for their generalization applicability.Το υδρολογικό φαινόμενο του μετασχηματισμού των κατακρημνίσεων σε απορροή αποτελεί ένα από τα σημαντικότερα πεδία έρευνας στην επιστήμη της υδρολογίας. Η μοντελοποίηση της σχέσης βροχόπτωσης-απορροής παρέχει αξιόλογες πληροφορίες για την υδρολογική συμπεριφορά μίας λεκάνης απορροής και την πιθανότητα εμφάνισης πλημμυρικών γεγονότων που προκαλούνται συνήθως από ακραία καιρικά φαινόμενα. Η διαχείριση των νερών σε επίπεδο λεκάνης απορροής και ο σχεδιασμός υδραυλικών τεχνικών έργων στηρίζονται στις εισροές, απώλειες και τελικές εκροές νερού, δηλαδή στις κατακρημνίσεις, στις απώλειες που δημιουργούνται από τη διήθηση, εξατμισοδιαπνοή και υδατοσυγκράτηση και τελικά στο νερό που απομένει και απορρέει. Η πολυπλοκότητα του φαινομένου και ο μεγάλος αριθμός παραμέτρων από τους οποίους επηρεάζεται καθιστούν δύσκολη την εύρεση μίας μαθηματικής συνάρτησης που να προσδιορίζει με ακρίβεια την τελική απορροή. Οι μέθοδοι τεχνητής νοημοσύνης και μηχανικής μάθησης έχουν το τεράστιο πλεονέκτημα της προσέγγισης υδρολογικών φαινομένων, όπως η σχέση βροχόπτωσης-απορροής, χωρίς να είναι απαραίτητη η γνώση των φυσικών παραμέτρων που την επηρεάζουν. Η ικανότητά τους να δημιουργούν μία σχέση μεταξύ δεδομένων εισόδων και στόχων τα καθιστά πανίσχυρα υπολογιστικά εργαλεία για την προσομοίωση των πολύπλοκων διεργασιών του νερού, όπως ο μετασχηματισμός των κατακρημνίσεων σε απορροή. Στην παρούσα ερευνητική εργασία αναπτύχθηκαν μοντέλα για την προσομοίωση της σχέσης βροχόπτωσης-απορροής που εντάσσονται σε τέσσερις διαφορετικές προσεγγίσεις μηχανικής μάθησης. Ειδικότερα δημιουργήθηκαν μοντέλα τεχνητών νευρωνικών δικτύων, Bayesian νευρωνικών δικτύων, παλινδρόμησης των μηχανών διανυσμάτων υποστήριξης και συνδυαστικών αλγορίθμων μάθησης (Boosting και Bagging). Ειδική αναφορά πρέπει να γίνει σε ένα μοντέλο συνδυαστικού αλγόριθμου μάθησης Boosting το οποίο κατασκευάστηκε με σκοπό να προσαρμόζεται στις ιδιαιτερότητες των μετεωρολογικών και υδρολογικών δεδομένων παρέχοντας τη μέγιστη δυνατή ακρίβεια πρόβλεψης κανονικών και ακραίων τιμών απορροής ταυτόχρονα. Για το συγκεκριμένο μοντέλο προτάθηκε η ονομασία HydroBAL που αποτελεί το ακρωνύμιο της έκφρασης «Hydrologic Boosting ALgorithm». Ως πεδίο εφαρμογής των μοντέλων επιλέχθηκαν τρεις λεκάνες απορροής, για τις οποίες υπήρχαν διαθέσιμα στοιχεία κατακρημνίσεων και απορροών. Η εφαρμογή των μοντέλων κατέδειξε τη μεγάλη αποτελεσματικότητα τους στην προσομοίωση του υδρολογικού φαινομένου και οι μεταξύ τους διαφορές διαπιστώθηκε ότι είναι πολύ μικρές. Αξιοσημείωτη είναι η καλή συμπεριφορά των μοντέλων στις πολύ ακραίες τιμές, οι οποίες παρατηρούνται σποραδικά στις χρονοσειρές των προτύπων εισόδων-στόχων και αποκλίνουν από το σύνηθες εύρος τιμών των δεδομένων με αποτέλεσμα η πρόβλεψη τους να είναι δύσκολη. Η σημαντικότητα του γεγονότος έγκειται στο ότι οι ακραίες τιμές είναι αυτές που δίνουν τα πλημμυρικά γεγονότα. Τελικά η αποτελεσματικότητα των μοντέλων σε όλα τα επίπεδα προσομοίωσης και πρόβλεψης της απορροής δημιουργεί θετικές προοπτικές για τη γενικευμένη εφαρμογή τους
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
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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