1,721,087 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
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
Management of environmental damage and impacts in green spaces in urban environments: survey of the factors leading to degradation
No full textCom o desenvolvimento dos grandes centros urbanos nos últimos anos, a importância de áreas verdes no planejamento urbano tornou-se cada vez mais necessária, devido a sua capacidade de minimizar os efeitos das perdas de funcionalidades ecológicas e ofertar aos habitantes maior conexão com a natureza, proporcionando saúde e bem-estar. Contudo, devido ao crescimento exacerbado de grandes centros urbanos as áreas verdes encontram-se em constante degradação. No contexto da gestão ambiental, estudos para determinar quais os danos e impactos ambientais que afetam mais significativamente a capacidade das praças urbanas em promover serviços adaptativos ecossistêmicos podem auxiliar a compreensão das principais causas do estágio de degradação em que as praças se encontram. Dessa forma, o objetivo deste trabalho é os danos e impactos ambientais que afetam a capacidade de uma praça urbana prover serviços ecossistêmicos, levando a um estágio degradação. Para tal, houve a identificação dos principais Serviços Ecossistêmicos e Danos com o auxílio da metodologia de Redes de Interação de Sorensen. Em seguida os impactos ambientais negativos tiveram a sua significância calculada através de uma Matriz que integra critérios da metodologia RIAM de Pastakia e da Matriz GUT. Assim houve a compreensão dos principais danos ambientais que levam um espaço público a um estágio de degradação.With the development of large urban centers in recent years, the importance of green areas in urban planning has become increasingly necessary, due to their ability to minimize the effects of loss of ecological functionality and offer inhabitants a greater connection with nature, providing health and well-being. However, due to the exacerbated growth of large urban centers, green areas are in constant degradation. In the context of environmental management, studies to determine which damages and environmental impacts most significantly affect the ability of urban squares to promote adaptive ecosystem services can help to understand the main causes of the stage of degradation in which squares are found. Thus, the objective of this work is the damage and environmental impacts that affect the capacity of an urban square to provide ecosystem services, leading to a degradation stage. To this end, the main Ecosystem Services and Damages were identified with the help of Sorensen's Interaction Networks methodology. Then, the negative environmental impacts had their significance calculated using a Matrix that integrates criteria from Pastakia's RIAM methodology and the GUT Matrix. Thus, there was an understanding of the main environmental damages that lead a public space to a stage of degradation.Não recebi financiament
Detecção de ataques DDoS em ambientes SDN/NFV utilizando algoritmos de aprendizagem de máquina não supervisionados em fluxos de dados
Get PDFAccording to data from the Cisco Visual Networking Index (VNI), which aims to make a realistic
forecast based on various levels and real data sources, it is estimated that the total number of DDoS
attacks on a global level will reach 14.5 million by 2022. For this reason, it is essential to protect
yourself from DDoS attacks. Thus, there is a need for new protection techniques to be developed.
In addition, solutions need to take into account performance and scalability requirements. In
addition, environments based on the SDN/NFV architecture allow network administrators to
detect and react to DDoS attacks more efficiently. This is because network control is centralized
and software-based traffic analysis capabilities can be developed. This dissertation analyzes
the efficiency and effectiveness of using unsupervised machine learning algorithms that work
with the data flow strategy in the detection of DDoS type attacks in SDN/NFV environments,
through a comparative analysis. First, a Systematic Literature Mapping was carried out, which
served as a basis for the realization of a first experiment. Then, a Systematic Literature Review
was carried out, and works that used unsupervised machine learning to detect DDoS attacks
and that worked with the data flow strategy were included, as this characteristic is inherent to
the environment. SDN/NFV. Thus, the chosen algorithms were: BIRCH, Mini-batch k-means,
Clustream, StreamKM++, DenStream, and D-Stream. After that, a platform was set up to run
the experiment, as well as a dataset was developed. After performing the tests, a qualitative and
quantitative analysis of the results was performed. The qualitative analysis aimed to compare
how effective the algorithms are in detecting DDoS attacks and the quantitative analysis aimed
to compare the efficiency, in this case, the processing speed of the algorithms in this detection.
The results obtained show that the algorithms BIRCH, Mini-batch k-means, Clustream, and
StreamKM++ obtained accuracy around 99%, while DenStream and D-Stream reached accuracy
around 79%. The shortest total execution time was for the D-Stream algorithm, while the longest
time was for StreamKM++. Because of this, the algorithms that stood out were D-Stream and
Mini-batch k-means, since that was the fastest algorithm, and this one obtained an accuracy
25.18% higher than D-Stream.Segundo dados do Cisco Visual Networking Index (VNI), que visa realizar uma previsão realista
baseada em vários níveis e fontes de dados reais, estima-se que o número total de ataques DDoS a
nível global chegue a 14,5 milhões até 2022. Por esse motivo, fica evidente que é imprescindível
se proteger de ataques do tipo DDoS. Dessa forma, há necessidade de que novas técnicas de
proteção sejam desenvolvidas. Além disso, é preciso que as soluções levem em consideração
os requisitos de desempenho e escalabilidade. Aliado a isso, ambientes baseados na arquitetura
SDN/NFV permitem que os administradores de rede detectem e reajam aos ataques DDoS
com mais eficiência. Isso porque o controle da rede é centralizado e é possível desenvolver
recursos de análise de tráfego baseados em software. Esta dissertação analisa a eficiência e
efetividade da utilização de algoritmos de aprendizagem de máquina não supervisionados que
trabalham com a estratégia de fluxo de dados na detecção de ataques do tipo DDoS em ambientes
SDN/NFV, por meio de uma análise comparativa. Primeiramente, foi realizado um Mapeamento
Sistemático da Literatura, o qual serviu de embasamento para a realização de um primeiro
experimento. Em seguida, foi realizada uma Revisão Sistemática da Literatura e foram incluídos
os trabalhos que utilizassem aprendizagem de máquina não supervisionada na detecção de
ataques DDoS e que trabalhassem com a estratégia de fluxo de dados, pois, essa característica
é inerente ao ambiente SDN/NFV. Dessa maneira, os algoritmos escolhidos foram: BIRCH,
Mini-batch k-means, Clustream, StreamKM++, DenStream e D-Stream. Após isso, foi montada
uma plataforma para a execução do experimento, assim como foi desenvolvido um dataset para
ser utilizado. Após a realização dos testes, foi realizada uma análise qualitativa e quantitativa
sobre os resultados. A análise qualitativa objetivou comparar o quão efetivo são os algoritmos
na detecção de ataques DDoS e a análise quantitativa visa comparar a eficiência, neste caso, a
velocidade de processamento dos algoritmos nessa detecção. Os resultados obtidos mostram os
algoritmos BIRCH, Mini-batch k-means, Clustream e StreamKM++ obtiveram acurácias em
torno de 99%, enquanto DenStream e D-Stream alcançaram acurárias em torno de 79%. O menor
tempo total de execução foi do algoritmo D-Stream, enquanto o maior tempo foi do StreamKM++.
Em vista disso, os algoritmos que se destacaram foram D-Stream e Mini-batch k-means, já que
aquele foi o algoritmo mais rápido e este obteve uma acurácia 25,18% maior que D-Stream.São Cristóvã
Impacts of cryptocurrency mining on electricity consumption and the environment
No full textAtualmente grandes tecnologias possibilitam uma nova era digital no âmbito financeiro após a revolucionária criação das Criptomoedas, uma moeda sem lastro e extremamente volátil, onde há diversas áreas de utilização e trazendo benefícios e malefícios, tanto para a sociedade quanto para o planeta. Diante disso, serão apresentados dados de consumo de energia do que chamam de Mineração de Criptomoedas, será também relacionado com o consumo de algumas cidades brasileiras e ao fim, haverá uma comparação do consumo de energia elétrica gerado em pontos de mineração com estas cidades, além de informar qual é o impacto causado no quesito ambiental.Currently, major technologies enable a new digital era in the financial realm following the revolutionary creation of cryptocurrencies, a currency without backing and extremely volatile, with various areas of application and bringing both benefits and drawbacks, both for society and the planet. In light of this, data on the energy consumption of what is called Cryptocurrency Mining will be presented, also related to the consumption of some Brazilian cities, and, in the end, there will be a comparison of the electricity consumption generated in mining points and these cities, as well as information on the environmental impact caused
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