1,720,954 research outputs found
Reinforcement Learning for charging scheduling in a renewable powered Battery Swapping Station
Full text linkBattery Swap (BS) technology represents a promising solution to overcome the main obstacles to a widespread adoption of electric vehicles (EVs) in a urban environment, like the limited range of EVs and the long battery charging time. Furthermore, with respect to traditional charging stations, it offers higher flexibility in dynamically managing the EV electricity demand to prevent the risk of power grid overload. Nevertheless, proper scheduling of the battery charge process is crucial to offer effective e-mobility services, trading off cost, Quality of Service and feasibility constraints. In this paper we consider a renewable powered multi-socket Battery Swapping Station (BSS) and design two algorithms based on Approximate Dynamic Programming (ADP) and Reinforcement Learning (RL) to dynamically adapt the scheduling of the battery charging process to the stochastic nature of the system. Both approaches are proved to be effective in remarkably enhancing the service quality in terms of increased capability to satisfy the customer demand for EV battery charging, at a lower cost with respect to benchmark approaches, with RL outperforming ADP under any budget constraint. In particular, under RL the probability of not satisfying the EV demand can be decreased by up to more than 40% with respect to benchmark approaches, and a significant cost reduction of almost 20% can be achieved, jointly with a greener system operation. Furthermore, our results show that a fine tuning of hyper-parameters is fundamental to properly trade off cost and Quality of Service constraints according to varying business needs. Finally, we analyse how the proposed strategies may affect the battery health due to their impact on battery degradation, hence influencing the BSS management cost
A low-cost automatic people-counting system at bus stops using Wi-Fi probe requests and deep learning
Full text linkCounting people is an important part of people-centric applications, and the increase in the number of IoT devices has allowed the collection of huge amounts of data to facilitate people counting. The present study seeks to provide a novel, low-cost, automatic people-counting system for use at bus stops, featuring a sniffing device that can capture Wi-Fi probe requests, and overcoming the problem of Media Access Control (MAC) randomization us-ing deep learning. To make manual data collection considerably easier, a “People Counter” app was designed to collect ground truth data in order to train the model with higher accuracy. A user-friendly, operating system-independent dashboard was created to display the most relevant metrics. A two-step methodological approach was followed comprising device choice and data collection; data analysis and algorithm development. For the data analysis, three different approaches were tested, and among these a deep-learning approach using Convolutional Recurrent Neural Network (CRNN) with Long Short-term Memory (LSTM) architecture produced the best re-sults. The optimal deep learning model predicted the number of people at the stop with a mean absolute error of around1.2 persons, which can be considered a good preliminary result considering that the experiment was done in a very complex open environment. People-counting systems at bus stops can sup-port better bus scheduling, improve the boarding and alighting time of pas-sengers, and aid the planning of integrated multi-modal transport system networks
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
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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