1,720,995 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
ENHANCING THE PERFORMANCE OF VISIBLE LED LIGHTS BASED INDOOR POSITIONING SYSTEM USING MACHINE LEARNING
No full textRecently, visible light positioning (VLP) applications have attracted a great deal of research attention because of the extremely high positioning accuracy that this system can provide. VLP continues to emerge as a leading candidate in the field of indoor positioning because of its advantages of accuracy, cost effectiveness, and simplicity even though it faces some difficulties, including multipath reflection, light interference between Light Emitting Diode (LED) lights, and noises from sunlight and artificial light sources. The main target of this thesis is to gradually develop VLP systems from simulation to experiment by building and improving machine learning (ML) algorithms as well as solving some inherent limitations of the LED-based VLP system. To minimize the computational time when applying ML algorithms, the novel adoption of dual-function ML is employed. These algorithms have a common feature that contains two functions: classification and regression. The division of the experimental testbed into specific areas by classification function significantly reduces the execution time for the positioning process. On the other hand, the regression function of the proposed dual-function ML algorithms plays an important role in estimating and improving the positioning accuracy. To solve the multipath reflection effects, a combination of random forest and K-nearest neighbor (KNN) algorithms is used to improve the positioning accuracy at the areas outside the center where the appearance of noise due to reflection is a serious problem. In addition to simulation, an improved algorithm of KNN, namely weighted optimum KNN (WOKNN), is applied to the real model to prove the feasibility and practicality of the proposed VLP system. The results show that, the proposed solution enhances the positioning accuracy to the millimeter level. During the implementation of the WOKNN algorithm, the fact is that the number of initially labeled fingerprints greatly affects the positioning performance. The more the offline fingerprints the system has, the more accurate the system achieves. It is an obstacle to leverage the fingerprinting method in larger spaces. To eliminate this weakness, the Ada-XCoReg algorithm is suggested. This is a combination of co-training semi-regression learning and adaptive boosting algorithms. The experimental results show that a mean positioning error of approximately 6 cm is achieved although the number of labeled fingerprints is reduced by roughly 90 percent. By applying this approach, a high positioning accuracy is maintained while the number of fingerprints became more feasible for real applications.Docto
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
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
Control of a Quadrotor Using a Smart Self-Tuning Fuzzy PID Controller
No full textThis paper deals with the modelling, simulation-based controller design and path planning of a four rotor helicopter known as a quadrotor. All the drags, aerodynamic, coriolis and gyroscopic effect are neglected. A Newton-Euler formulation is used to derive the mathematical model. A smart self-tuning fuzzy PID controller based on an EKF algorithm is proposed for the attitude and position control of the quadrotor. The PID gains are tuned using a self-tuning fuzzy algorithm. The self-tuning of fuzzy parameters is achieved based on an EKF algorithm. A smart selection technique and exclusive tuning of active fuzzy parameters is proposed to reduce the computational time. Dijkstra's algorithm is used for path planning in a closed and known environment filled with obstacles and/or boundaries. The Dijkstra algorithm helps avoid obstacle and find the shortest route from a given initial position to the final position
Machine Learning in Indoor Visible Light Positioning Systems: A Review
No full textDeveloping a wireless indoor positioning system with high accuracy, reliability, and reasonable cost has been the focus of many researchers. Recent studies have shown that visible-light-based positioning (VLP) systems have better positioning accuracy than radio-frequency-based systems. A notable highlight of those research articles is their combination of VLP and machine learning (ML) to improve the positioning performance in both two-dimensional and three-dimensional spaces. In this paper, in addition to describing VLP systems and well-known positioning algorithms, we analyze, evaluate, and summarize the ML techniques that have been applied recently. We break these into four categories: supervised learning, unsupervised learning, reinforcement, and deep learning. We also provide deep discussion of articles published during the past five years in terms of their proposed algorithm, space (2D/3D), experimental method (simulation/experiment), positioning accuracy, type of collected data, type of optical receiver, and number of transmitters
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