1,721,160 research outputs found
Feature engineering techniques to classify cause of death from forensic autopsy reports / Ghulam Mujtaba
Full text linkForensic autopsy focuses on revealing the cause of death (CoD) by examining a dead body. This process is performed by medical pathologists during the investigation of criminal and civil law cases. In forensic autopsy, pathologists examine corpses externally and anatomically to collect autopsy findings. Moreover, these experts collect the history of the deceased and death scene-related information from the deceased’s relatives and eyewitnesses. Afterward, the pathologists determine the CoD through their expert knowledge while correlating the current autopsy findings with previous autopsy reports. Therefore, determining the CoD from autopsy findings is laborious, time consuming, and subject to inconsistencies associated with any labor-intensive process. Hence, automated text classification (ATC) techniques must be employed to overcome the aforementioned issues in determining the CoD. This study aimed to employ ATC techniques to classify the CoD from forensic autopsy reports. In the ATC technique, feature engineering is a highly important step because the success or failure of any ATC model is heavily dependent on the quality of the features used in the classification task. In ATC, the traditional feature engineering techniques include bag of words (BoW) and n-gram. This study argues that BoW and its variant techniques are inadequate in determining the CoD from forensic autopsy reports because these techniques ignore word-order, word-context, and word-level synonymy and polysemy. To overcome the aforementioned issues of BoW and its variant techniques, this study aimed to achieve the following four main objectives. First, this work intended to investigate the existing feature engineering techniques to classify free-text clinical reports, including forensic autopsy reports. Second, this study aimed to develop semi-automated expert-driven feature engineering to overcome the issue of word-level synonymy and polysemy. Third, this research sought to propose a fully automated conceptual graph-based feature engineering technique to address issues in word-order and word-context. Finally, this work intended to evaluate the proposed techniques by comparing their performances with existing baseline techniques. For the experimental evaluation, forensic autopsy reports of 16 different CoDs were obtained from a very large hospital in Kuala Lumpur, Malaysia. These reports were preprocessed by applying various text preprocessing techniques. The discriminative features were then extracted from the preprocessed reports through the proposed feature engineering techniques and formed numeric master feature vectors. These master feature vectors were fed as input to six machine learning algorithms to construct and evaluate the classification models. Furthermore, to show the effectiveness of the proposed techniques, this study compared their performances with five state-of-the-art baseline feature engineering techniques. Experimental results showed that the proposed techniques outperformed the traditional BoW and its variant techniques. Moreover, support vector machines and random forest algorithms outperformed the four other algorithms. The proposed techniques are feasible and practical in determining the CoD from forensic autopsy reports and can assist pathologists to accurately and rapidly determine the CoD from autopsy findings. Finally, the proposed techniques are generally applicable to other kinds of free-text clinical reports
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
Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic
No full textIn this study, we present the evidence of dramatic changes in the structure and time-varying patterns of volatility connectedness across equities and major commodities (oil, gold, silver and natural gas) in the US economy before and during the COVID-19 outbreak. We utilize high frequency 5-min trading data of most actively traded US ETFs to construct the volatility connectedness network. We compute the intraday volatility estimates using MCS-GARCH model and then employ Diebold and Yilmaz (2012) spillover index approach to approximate volatility spillovers between the financial markets. Our main findings showcase significant impact of COVID-19 pandemic on the volatility linkages of financial markets as the volatility connectedness among the different assets peaked during the outbreak. Other findings and implications of the study are further discussed
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
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