1,720,954 research outputs found
Employing Artificial Intelligence to Reduce the Phenomenon of Administrative and Financial Corruption in Iraq
Administrative and financial corruption is considered one of the serious scourges that have greatly increased in recent decades in many developing societies. In Iraq, it appeared clearly in all public institutions, which led to a clear decline in domestic and foreign investment operations throughout the country, especially after the American occupation in 2003. Its effects were reflected in various aspects of life. Therefore, the research aims to employ artificial intelligence to enhance administrative practices and improve the performance of government organizations, reducing corruption and promoting transparency and integrity. This research is based on the hypothesis that administrative and financial corruption can be reduced using artificial intelligence in Iraq. Whereas analyzing data and taking advantage of modern technologies can enhance transparency and accountability, the most important conclusion reached by the research is the limited use of intelligence. Artificial intelligence in Iraq is due to several challenges that it faces, and its backwardness in this aspect. Finally, the research provides recommendations, the most important of which is that interest in artificial intelligence and its employment is one of the important aspects of reducing administrative and financial corruption in Iraq
The Impact of Artificial Intelligence on Economic Development in Iraq
The research aims to determine the extent of the impact of artificial intelligence on economic development, and the research is based on the basic hypothesis of the extent and nature of the impact that artificial intelligence can contribute to economic development. Through answering questions like: What is artificial intelligence? What are the most important mechanisms by which artificial intelligence affects development? Has artificial intelligence had a positive or negative impact on economic development? The research has shown that artificial intelligence technology has a significant impact on production, employment, employment structure, marketing services, investment, consumption, agriculture, and other sectors. It also restructures the economy, as it enters as a factor of production - the specificity of artificial intelligence - and from here the relationship between artificial intelligence and economic development differs when artificial intelligence is viewed as a complementary factor of production. As is the case in developed countries, it can be viewed as a factor of production that has a substitution effect, as it negatively affects workers and exposes them to the risk of unemployment, as is expected in developing countries. The research reached a set of conclusions, perhaps the most prominent of which is the great similarity between human intelligence and artificial intelligence techniques, with its enormous ability to learn, analyze big data, and make decisions. All of this affected the process of accelerating the entry of technology into markets in the form of products without any assistance from the human factor. Artificial intelligence was unique in changing some economic concepts. This is due to the predictive ability of artificial intelligence, which enabled it to predict both demand and supply, and determine prices proactively. That is, making demand and supply more individual, making different markets more consistent; Because of its ability to process a huge amount of information; which makes rational expectations theory more valid
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
We 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
We 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.
Author-wise bibliometric analysis based on entropy.</p
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