1,720,964 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
Representación simplificada de señales unidimensionales y bidimensionales para la extracción de información real
No full textEsta tesis se enmarcó en los proyectos de investigación “Segmentación, análisis y detección de objetos y texturas en imágenes y secuencias de videos” desarrollados en el Laboratorio de Procesamiento Digital de Imágenes del Instituto de Investigaciones Científicas y Tecnológicas en Electrónica (ICyTE), dependiente de la Facultad de Ingeniería de la Universidad Nacional de Mar del Plata y de CONICET y en el proyecto de investigación y desarrollo “ Desarrollo de sistemas y algoritmos para la extracción de conocimiento aplicado a sensores inteligentes” de la Facultad Regional Del Neuquén, Universidad Tecnológica Nacional.
Esta tesis propone una forma distinta de representar la información embebida en una señal. La idea principal de la representación propuesta se basa en la unión de trayectorias simplificadas manteniendo la estructura intrínseca de la señal. Esta representación genera una estructura que minimiza la información redundante presente en la señal, facilitando los procesos de extracción de conocimiento. La redundancia, no solo enlentece los procesos subsiguientes, sino que además genera confusión, “ruido’, para el entendimiento deseado.
Dado que la señal es representada por una secuencia de segmentos de funciones, escaladas, dilatadas o contraídas que convergen a la señal, el comportamiento macroscópico de ella es rápidamente inferido observando la secuencia y las características de los segmentos. Para lograr aplicaciones reales de extracción de conocimiento es necesario procesar la señal y estos procesos, en general intensivos en computo, atentan en contra de las aplicaciones en tiempo real. Esta situación conflictiva es resuelta mediante la eliminación en tiempo real de muestras de la señal cuyo valor pueda ser inferido de su entorno cercano. En el marco de esta tesis llamaremos tiempo real cada vez que se obtenga información deseada de manera tal que no introduzca demoras significativas en la obtención de la función objetivo.
Los algoritmos propuestos en esta tesis logran este objetivo de una manera simple y eficaz. Simple porque a partir de la observación de como la señal se aparta de un comportamiento lineal se infieren las trayectorias simplificadas, empleando operaciones lógicas y aritméticas. La redundancia se elimina en el proceso de adquisición de la señal.
Es importante puntualizar que el objetivo de la tesis no es comprimir la señal, sino que conservar la estructura informativa de la señal minimizando la redundancia para facilitar los procesos de inferencia de conocimiento.
La estructura propuesta para la representación de la señal ha demostrado una eficiente inferencia de conocimiento como se puedo comprobar en las aplicaciones abordadas, las cuales han sido y están siendo implementadas en sistemas embebidos para lograr aplicaciones reales.
Mail de los autores Gustavo Monte Fil: Monte, Gustavo. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentin
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
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
Smart Sensor Efficient Signal Processing for Earthquake Early Detection
No full textThis paper presents a new method for earthquake early warning alert that uses a smart sampling technique that expose the signal information in a way that it is simpler to infer knowledge. The objective is to estimate, from the first few seconds of the P wave, if the incoming earthquake is destructive or not. The proposed method is described and compared to conventional approaches. Performance results for real seismic data are shown highlighting the results for earthquakes of different magnitudes. Preliminary results are excellent for inferring damage based on the approach of a single seismic station
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
An enhanced Smart Sampling algorithm based on Deep Learning
No full textThe spread of Wireless Sensor Networks, driven mainly by the increasing use of pervasive sensors in everyday reality, according to the IoT concept, is bringing to light increasing issues in terms of energy consumption and bandwidth occupancies for the transmission of acquired data. In this regard, researchers and standards committees, especially that of the IEEE 21451 standard, have focused their efforts on Smart Sampling methods to reduce the number of samples acquired and then transmitted over the network adaptively based on the dynamics of the measured signal. This work aims to employ new techniques based on deep learning, especially LSTM autoencoders, to predict certain signal time windows to turn off the acquisition and transmission system, delegating the full signal computation to a central processing unit. Thus, the objective was to evaluate the accuracy and timeliness of the method to replace the classical Real-Time Segmentation algorithm proposed by the IEEE 21451 standard. The results obtained on three types of signals were satisfactory, clearing the way for implementation in smart data acquisition systems
- …
