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Response Surface Modeling and Optimization to Elucidate the Differential Effects of Demographic Characteristics on HIV Prevalence in South Africa
No full textComputers and Industrial Engineering 42, Cape Town, South Africa, 16-18 July 2012In this study, a Central Composite Face Centered (CCF) design was employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa. The demographic characteristics studied for each pregnant mother attending an antenatal clinic in South Africa, were mother's age, partner's age, mother's level of education and parity. HIV status of an antenatal clinic attendee was found to be highly sensitive to changes in pregnant woman's age and partner's age, using the 2007 South African annual antenatal HIV and syphilis seroprevalence data. Individually the pregnant woman's level of education and parity had no significant effect on the HIV status. However, the latter two demographic characteristics exhibited significant effects on the HIV status of antenatal clinic attendees in two way interactions with other demographic characteristics. Using HIV as the optimization objective, the following summary statistics were obtained, R2 = 0.99 and two-factor interactions (2FI) model F-value of 63.77. The model F-value of 63.77 implied the 2FI model was significant and there was only a 0.01% chance this model value could occur due to noise. The model 'Lack of Fit' value of 0.01 implied that the 'Lack of Fit' was not significant relative to the pure error and thus there was a 99.88% chance that this 'Lack of Fit' F-value could occur due to noise. An adeq. precision value of 25 was obtained, suggesting that this 2FI model could be used to navigate the design space. A 3D response surface plot indicated that the highest rate of HIV positive individuals was obtainable at the highest age of the pregnant women and lowest age of their partners.http://dx.doi.org/10.1109/ASONAM.2012.149http://conferences.sun.ac.za/index.php/cie/cie-42/paper/view/252http://conferences.sun.ac.za/index.php/cie/cie-4
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
Response Surface Modeling and Optimization to Elucidate the Differential Effects of Demographic Characteristics on HIV Prevalence in South Africa
No full textIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)In this study, a Central Composite Face Centered (CCF) design was employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa. The demographic characteristics studied for each pregnant mother attending an antenatal clinic in South Africa, were mother's age, partner's age, mother's level of education and parity. HIV status of an antenatal clinic attendee was found to be highly sensitive to changes in pregnant woman's age and partner's age, using the 2007 South African annual antenatal HIV and syphilis seroprevalence data. Individually the pregnant woman's level of education and parity had no significant effect on the HIV status. However, the latter two demographic characteristics exhibited significant effects on the HIV status of antenatal clinic attendees in two way interactions with other demographic characteristics. Using HIV as the optimization objective, the following summary statistics were obtained, R2 = 0.99 and two-factor interactions (2FI) model F-value of 63.77. The model F-value of 63.77 implied the 2FI model was significant and there was only a 0.01% chance this model value could occur due to noise. The model 'Lack of Fit' value of 0.01 implied that the 'Lack of Fit' was not significant relative to the pure error and thus there was a 99.88% chance that this 'Lack of Fit' F-value could occur due to noise. An adeq. precision value of 25 was obtained, suggesting that this 2FI model could be used to navigate the design space. A 3D response surface plot indicated that the highest rate of HIV positive individuals was obtainable at the highest age of the pregnant women and lowest age of their partners.http://dx.doi.org/10.1109/ASONAM.2012.149http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6425658http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=642312
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
Development and validation of an HIV risk scorecard model
No full textIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Niagara Falls, Canada, 25-28 August 2013This research paper covers the development of an HIV risk scorecard using SAS Enterprise MinerTM. The HIV risk scorecard was developed using the 2007 South African annual antenatal HIV and syphilis seroprevalence data. Antenatal data contains various demographic characteristics for each pregnant woman, such as pregnant woman's age, male sexual partner's age, race, level of education, gravidity, parity, HIV and syphilis status. The purpose of this research was to use a scorecard to rank the effects of the demographic characteristics on influencing an individual's risk of acquiring an HIV infection, not the probability of being sick. The project encompassed the selection of the data sample, classing, selection of demographic characteristics, fitting of a regression model, generation of weights-of-evidence (WOE), calculation of information values (IVs), creation and validation of an HIV risk scorecard. The educational level and syphilis status of the pregnant women produced information values below 0.05 and were rejected from inclusion in the final HIV risk scorecard. Based on their respective information values, the following four demographic characteristics of the pregnant women were found to be of medium predictive strength and thus included in the final HIV risk scorecard; age, age of male sexual partner, gravidity and parity. The age of the pregnant woman had the highest information value and Gini coefficient. The HIV risk scorecard showed that the risk of contracting an HIV infection increased gradually up to the age of 30 years for females and 34 years old for their male sexual partners. Thereafter, the risk decreased gradually towards the age of 45.http://www.ieee.org/conferences_events/index.htmlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=677971
Comparative study of an HIV risk scorecard and regression models to rank effects of demographic characteristics on risk of aquiring an HIV infection
No full textIEEE international conference on bioinformatics and biomedicine (BIBM2013), Shanghai, China, 18-21 December 2013This research paper covers the development of an HIV risk scorecard using SAS Enterprise MinerTM. The HIV risk scorecard was developed using the 2007 South African annual antenatal HIV and syphilis seroprevalence data. Limited comparisons are made with a more recent 2010 antenatal database. Antenatal data contains various demographic characteristics for each pregnant woman, such as pregnant woman’s age, male sexual partner’s age, population group, level of education, gravidity, parity, HIV and syphilis status. The purpose of this research was to use a scorecard to rank the effects of the demographic characteristics on influencing a pregnant woman’s risk of acquiring an HIV infection. The project encompassed the selection of the data sample, classing, selection of demographic characteristics, fitting of a regression model, generation of weights-of-evidence (WOE), calculation of information values (IVs), creation and validation of an HIV risk scorecard. The educational level and syphilis status of the pregnant women produced information values below 0.05 and were rejected from inclusion in the final HIV risk scorecard. Based on their respective information values, the following four demographic characteristics of the pregnant women were found to be of medium predictive strength and thus included in the final HIV risk scorecard; pregnant woman’s age, age of male sexual partner, gravidity and parity. The age of the pregnant woman had the highest information value and Gini coefficient. The final objective of this research was to demonstrate that a binned variable HIV risk scorecard can provide as much risk ranking as any other regression based model.http://bibm2013.tongji.edu.cn/http://dx.doi.org/10.1109/BIBM.2013.6732736http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=673273
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
Comparative study of neural networks and design of experiments to the classification of HIV status
Get PDFThis research addresses the novel application of design of experiment, artificial neural net-works and logistic regression to study the effect of demographic characteristics on the risk of acquiring HIV infection among the antenatal clinic attendees in South Africa. The annual antenatal HIV survey is the only major national indicator for HIV prevalence in South Africa. This is a vital technique to understand the changes in the HIV epidemic over time. The annual antenatal clinic data contains the following demographic characteristics for each pregnant woman; age (herein called mother's age), partner's age (herein father's age), population group (race), level of education, gravidity (number of pregnancies), parity (number of children born), HIV and syphilis status. This project applied a screening design of experiment technique to rank the effects of individual demographic characteristics on the risk of acquiring an HIV infection. There are a various screening design techniques such as fractional or full factorial and Plackett-Burman designs. In this work, a two-level fractional factorial design was selected for the purposes of screening. In addition to screening designs, this project employed response surface methodologies (RSM) to estimate interaction and quadratic effects of demographic characteristics using a central composite face-centered and a Box-Behnken design. Furthermore, this research presents the novel application of multi-layer perceptron’s (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees. A review report was produced to study the application of neural networks to modelling HIV/AIDS around the world. The latter report is important to enhance our understanding of the extent to which neural networks have been applied to study the HIV/AIDS pandemic. Finally, a binary logistic regression technique was employed to benchmark the results obtained by the design of experiments and neural networks methodologies. The two-level fractional factorial design demonstrated that HIV prevalence was highly sensitive to changes in the mother's age (15-55 years) and level of her education (Grades 0-13). The central composite face centered and Box-Behnken designs employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa, demonstrated that HIV status of an antenatal clinic attendee was highly sensitive to changes in pregnant mother's age and her educational level. In addition, the interaction of the mother's age with other demographic characteristics was also found to be an important determinant of the risk of acquiring an HIV infection. Furthermore, the central composite face centered and Box-Behnken designs illustrated that, individual-ally the pregnant mother's parity and her partner's age had no marked effect on her HIV status. However, the pregnant woman’s parity and her male partner’s age did show marked effects on her HIV status in “two way interactions with other demographic characteristics”. The multilayer perceptron (MLP) sensitivity test also showed that the age of the pregnant woman had the greatest effect on the risk of acquiring an HIV infection, while her gravidity and syphilis status had the lowest effects. The outcome of the MLP modelling produced the same results obtained by the screening and response surface methodologies. The binary logistic regression technique was compared with a Box-Behnken design to further elucidate the differential effects of demographic characteristics on the risk of acquiring HIV amongst pregnant women. The two methodologies indicated that the age of the pregnant woman and her level of education had the most profound effects on her risk of acquiring an HIV infection. To facilitate the comparison of the performance of the classifiers used in this study, a receiver operating characteristics (ROC) curve was applied. Theoretically, an ROC analysis provides tools to select optimal models and to discard suboptimal ones independent from the cost context or the classification distribution. SAS Enterprise MinerTM was employed to develop the required receiver-of-characteristics (ROC) curves. To validate the results obtained by the above classification methodologies, a credit scoring add-on in SAS Enterprise MinerTM was used to build binary target scorecards comprised of HIV positive and negative datasets for probability determination. The process involved grouping variables using weights-of-evidence (WOE), prior to performing a logistic regression to produce predicted probabilities. The process of creating bins for the scorecard enables the study of the inherent relationship between demographic characteristics and an in-dividual’s HIV status. This technique increases the understanding of the risk ranking ability of the scorecard method, while offering an added advantage of being predictive.Master
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
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