1,721,500 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
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
Optimization methods for developing electric vehicle charging strategies
Full text linkElectric vehicles (EVs) are considered to be a crucial and proactive player in the future for transport electrification, energy transition, and emission reduction, as promoted by policy-makers, relevant industries, and the academia. EV charging would account for a non-negligible share in the future electricity demand. The integration of EV brings both challenges and opportunities to the electricity system, mainly from their charging profiles. When EV charging behaviors are uncontrolled, their potentially high charging rate and synchronous charging patterns may result in the bottleneck of the grid capacity and the shortage of generation ramping capacity. However, the promising load shifting potential of EVs can alleviate these problems and even bring additional flexibilities to the demand side for further applications, such as peak shaving and the integration of renewable energy.
To grasp these opportunities, novel controlled charging strategies should be developed to help integrate electric vehicles into energy systems. However, corresponding methods in current literature often have customized assumptions or settings so that they might not be practically or widely applied. Furthermore, the attention of literature is more paid to explaining the results of the methods or making consequent policy recommendations, but not sufficiently paid to demonstrating the methods themselves. The lack of the latter might undermine the credibility of the work and hinder readers’ understanding. Therefore, this thesis serves as a methodological framework in response to the fundamental and universal challenges in developing charging strategies for integrating EV into energy systems. The discussions aim to raise readers’ awareness of the essential but often unnoticed concerns in model development and hopefully would enlighten future researchers into this topic.
Specifically, this cumulative thesis comprises four papers and analyzes the research topic from two perspectives. With Paper A and Paper B, the micro perspective of the thesis is more applied and focuses on the successful implementation of charging scheduling solutions for each EV individually. Paper A proposes a two-stage scenario-based stochastic linear programming model to schedule EV charging behaviors and considers the uncertainties from future EVs. The model is calculated in a rolling window fashion with updated parameters. Scenario generation for future EVs is simulated by inhomogeneous Markov chains, and scenario reduction is achieved by a fast forward selection method to reduce the computational burden. The objective function is formulated as variance minimization so that the model can be flexibly implemented for various applications. Paper B applies the model proposed in Paper A to investigate how the generation of a wind turbine could be correlated with the EV controlled charging demand. An empirical controlled charging strategy is designed for comparison where EVs would charge as much as possible when wind generation is sufficient or would postpone charging otherwise. Although these two controlled charging strategies perform similarly in terms of wind energy utilization, the solutions from the proposed model could additionally alleviate the volatility of wind energy generation by matching the EV charging curve to the electricity generation profile.
With Paper C and Paper D, the macro perspective of the thesis is more explorative and investigates how EVs as a whole would contribute to energy transition or emission reduction. Paper C investigates the greenhouse gas emissions of EVs under different charging strategies in Europe in 2050. Methodologically, the paper proposes an EV module that enables different EV controlled charging strategies to be endogenously determined by energy system models. The paper concludes that EVs would contribute to a 36% emission reduction on the European level even under an uncontrolled charging strategy. Unidirectional and bidirectional controlled charging strategies could further reduce emissions by 4% and 11%, respectively, compared with the original level. As a follow-up study of Paper C, Paper D develops, demonstrates, improves, and compares three different types of EV aggregation methods for integrating an EV module into energy system models. The analysis and demonstration of these methods are achieved by having a simplified energy system model as a testbed and the results from the individual EV modeling method as the benchmark. As different EV aggregation methods share the same data set as for the individual EV modeling method, the disturbance from parameters is minimized, and the influence from mathematical formulations is highlighted. These EV aggregation methods are compared from multiple aspects
Decision-making under uncertainty in short-term electricity markets
Full text linkIn the course of the energy transition, the share of electricity generation from renewable energy sources in Germany has increased significantly in recent years and will continue to rise. Particularly fluctuating renewables like wind and solar bring more uncertainty and volatility to the electricity system. As markets determine the unit commitment in systems with self-dispatch, many changes have been made to the design of electricity markets to meet the new challenges. Thereby, a trend towards real-time can be observed. Short-term electricity markets are becoming more important and are seen as suitable for efficient resource allocation. Therefore, it is inevitable for market participants to develop strategies for trading electricity and flexibility in these segments.
The research conducted in this thesis aims to enable better decisions in short-term electricity markets. To achieve this, a multitude of quantitative methods is developed and applied: (a) forecasting methods based on econometrics and machine learning, (b) methods for stochastic modeling of time series, (c) scenario generation and reduction methods, as well as (d) stochastic programming methods. Most significantly, two- and three-stage stochastic optimization problems are formulated to derive optimal trading decisions and unit commitment in the context of short-term electricity markets. The problem formulations adequately account for the sequential structure, the characteristics and the technical requirements of the different market segments, as well as the available information regarding uncertain generation volumes and prices. The thesis contains three case studies focusing on the German electricity markets.
Results confirm that, based on appropriate representations of the uncertainty of market prices and renewable generation, the optimization approaches allow to derive sound trading strategies across multiple revenue streams, with which market participants can effectively balance the inevitable trade-off between expected profit and associated risk. By considering coherent risk metrics and flexibly adaptable risk attitudes, the trading strategies allow to substantially reduce risk with only moderate expected profit losses. These results are significant, as improving trading decisions that determine the allocation of resources in the electricity system plays a key role in coping with the uncertainty from renewables and hence contributes to the ultimate success of the energy transition
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
Auswirkungen von strategischem Bietverhalten auf die Marktpreise am deutschen Day-Ahead-Spotmarkt und an den Regelleistungsauktionen
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