1,720,956 research outputs found
Road traffic accident analysis using machine learning techniques for Soshanguve, Pretoria
Get PDFMSc (Computer Science), North-West University, Mafikeng CampusRoad traffic accidents (RTAs) in South Africa reached the highest road death toll in 2017, in spite of road safety campaigns and initiatives. "Ongoing campaigns are simply not sufficient", said a representative from the South African Automobile Association (AA). RTA data is usually collected at accident scenes and those who collect this data lack sufficient knowledge and skill to translate the data into knowledge that can be used to gain a better understanding of the root causes and factors associated with the occurrence of an accident. The South African literature on RTAs has shown a limitation in using advanced methods such as machine learning, to extract insight from RTA data or trace patterns and trends that are associated with the occurrence of an accident. In this work, machine learning methods were deployed to study the relationships that exist in data that is captured on South African Accident Report (AR) forms. An AR form is a form that is completed for all RTAs that occur on a public road where a motor vehicle was involved [1]. In order to increase the data, distances to the nearest places of interest such as bars, malls, schools, restaurants, and buildings were extracted through a geospatial database and added to the AR data. The reason behind this was to determine if distances to the nearest places of interest have an impact on the injury severity of drivers in RTAs. First, the main characteristics in the data were summarized by performing the exploratory data analysis. Upon completion of the exploratory data analysis, it was found that truck license holders particularly code C1, used light vehicles such as motor cars, in comparison to heavy motor vehicles. The results from the exploratory data analysis also revealed that these drivers sustained the most severe injuries in RTAs, different from light motor vehicle drivers. In South Africa, duty licenses are granted with various codes that indicate the kind of vehicle that may be used with that duty license; the codes are shown in Appendix A. It should also be noted that the tests for each license code are conducted differently using different vehicles. For example, when testing for a heavy duty license code C1, the test is conducted on a vehicle with a Gross vehicle mass (GVM) of 3500 kg and less than 16000 kg, and when testing for a light motor vehicle duty license code B, the test is conducted on a vehicle with a GVM of ≤ 3500 kg. To determine if truck licenses code C1 and the distances to the nearest places of interests such as malls, bars, schools, restaurants, and buildings have a high importance on the injury severity of drivers in RTA, three classifiers were created by using parametric and non-parametric machine learning algorithms namely; Multivariate Logistic Regression (MLR) and the Extreme Gradient Boosting Tree (XGBoost), where XGBoost outran MLR. The first classifier was created using the extracted distance features and the target class (injury severity), the second classifier was created using the initial data that is collected on AR forms and the third classifier was created by integrating engineered distance features and data that is collected on AR forms. This model achieved an accuracy of 83.14%±3.34 %, and a precision, recall, and an F1 score of 82.83%±3.18 %, 82.66 %±3.16 %, and 82.35%±3.25 %, respectively. Also, the most significant predictors of injury severity of drivers in RTAs were found to be truck licenses code C1, light motor duty license code EB, vehicle type (motor car or station wagon), single vehicle: overturned accident type, vehicle maneuver and the distance to the closest building. There are several mitigation strategies that can arise as a result of confirming whether or not the distances to the nearest places of interest, or if the kind of duty license that a motorist has have a high importance on injury severity. For example, if the type of duty license and the distances to the nearest places of interest have a significant impact on the level of injury in RTAs, than it may be useful to explore how adjusting the current status quo will improve safety on the road which states that motorists with heavy duty licenses are allowed to use light motor vehicles. Moreover, if closest places of interests also play a role in the injury severity of drivers in RTAs, this information can direct policymakers to areas of high accident occurrences and proactive measures can then be taken such as to create a road safety awareness down the affected line i.e, N1, N14; allocate more funds to improve the road, ensure that medical services are close by to provide optimal treatment of rehabilitation following the injury such as effective first aid and appropriate care, and also increase traffic personnel in the affected area. The study also searched for frequent attributes that co-exist in the incidence of a RTA by applying the association rule mining technique. Before searching for frequent items that co-exist in the data, the clustering was performed as a preliminary step. This resulted into having two clusters and the support, confidence, and lift of the rules found in the first cluster were 0.21, 0.71 and 2.05 respectively. Similary, the support, confidence, and lift of the rules found in the second cluster were 0.22, 0.71 and 2.35 respectively.Master
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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