With increased pressures from governmental and insurance agencies, today's physician devotes less time to patient care and more time to administration. To alleviate this problem, Biological & Popular Culture, Inc. (Biopop) proposed the building of partnerships with healthcare professionals to provide high-quality, cost-effective medical care in a physician network setting. To assist Biopop in evaluating potential operating procedures, a discrete-event simulation model has been constructed. The model is built in an object-oriented, visual manner utilizing the Visual Simulation Environment (VSE). The model examines both internal Biopop operations and external clinic operations. The research presented herein describes the design of the simulation model and details the analysis of the clinical environment. A methodology for determining appropriate staffing and physical resources in a clinical environment is presented. This methodology takes advantage of several simulation-based statistical techniques, including batch means; fractional factorial design; and simultaneous ranking, selection, and multiple comparisons. An explanation of the experimental design is provided and results of the experimentation are presented. Based upon the experimental results, conclusions are drawn and recommendations are made for an appropriate staffing and facility size for a two-physician family practice healthcare clinic. / Master of Science

Opsomming Daar bestaan 'n behoefte aan 'n objektiewe maatstaf om die gehalte van akademiese publikasies te bepaal en te vergelyk. Hierdie navorsing het die invloed of reaksie wat deur 'n publikasie gegenereer is uit verwysingsdata bepaal. Daar is van 'n iteratiewe algoritme gebruik gemaak wat gewigte aan verwysings toeken. In die Internetomgewing word hierdie benadering reeds met groot sukses toegepas deur onder andere die PageRank-algoritme van die Google soekenjin. Hierdie en ander algoritmes in die Internetomgewing is bestudeer om 'n algoritme vir akademiese artikels te ontwerp. Daar is op 'n variasie van die PageRank-algoritme besluit wat 'n Invloedwaarde bepaal. Die algoritme is op gevallestudies getoets. Die empiriese studie dui daarop dat hierdie variasie spesialisnavorsers se intu¨ıtiewe gevoel beter weergee as net die blote tel van verwysings. Abstract Ranking of journals are often used as an indicator of quality, and is extensively used as a mechanism for determining promotion and funding. This research studied ways of extracting the impact, or influence, of a journal from citation data, using an iterative process that allocates a weight to the source of a citation. After evaluating and discussing the characteristics that influence quality and importance of research with specialist researchers, a measure called the Influence factor was introduced, emulating the PageRankalgorithm used by Google to rank web pages. The Influence factor can be seen as a measure of the reaction that was generated by a publication, based on the number of scientists who read and cited itA good correlation between the rankings produced by the Influence factor and that given by specialist researchers were found. / Mathematical Sciences / M.Sc. (Operasionele Navorsing)

Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Citation analysis is an important tool in the academic community. It can aid universities, funding bodies, and individual researchers to evaluate scientific work and direct resources appropriately. With the rapid growth of the scientific enterprise and the increase of online libraries that include citation analysis tools, the need for a systematic evaluation of these tools becomes more important. The research presented in this study deals with scientific research output, i.e., articles and citations, and how they can be used in bibliometrics to measure academic success. More specifically, this research analyses algorithms that rank academic entities such as articles, authors and journals to address the question of how well these algorithms can identify important and high-impact entities. A consistent mathematical formulation is developed on the basis of a categorisation of bibliometric measures such as the h-index, the Impact Factor for journals, and ranking algorithms based on Google’s PageRank. Furthermore, the theoretical properties of each algorithm are laid out. The ranking algorithms and bibliometric methods are computed on the Microsoft Academic Search citation database which contains 40 million papers and over 260 million citations that span across multiple academic disciplines. We evaluate the ranking algorithms by using a large test data set of papers and authors that won renowned prizes at numerous Computer Science conferences. The results show that using citation counts is, in general, the best ranking metric. However, for certain tasks, such as ranking important papers or identifying high-impact authors, algorithms based on PageRank perform better. As a secondary outcome of this research, publication trends across academic disciplines are analysed to show changes in publication behaviour over time and differences in publication patterns between disciplines. / AFRIKAANSE OPSOMMING: Sitasiesanalise is ’n belangrike instrument in die akademiese omgewing. Dit kan universiteite, befondsingsliggams en individuele navorsers help om wetenskaplike werk te evalueer en hulpbronne toepaslik toe te ken. Met die vinnige groei van wetenskaplike uitsette en die toename in aanlynbiblioteke wat sitasieanalise insluit, word die behoefte aan ’n sistematiese evaluering van hierdie gereedskap al hoe belangriker. Die navorsing in hierdie studie handel oor die uitsette van wetenskaplike navorsing, dit wil sê, artikels en sitasies, en hoe hulle gebruik kan word in bibliometriese studies om akademiese sukses te meet. Om meer spesifiek te wees, hierdie navorsing analiseer algoritmes wat akademiese entiteite soos artikels, outeers en journale gradeer. Dit wys hoe doeltreffend hierdie algoritmes belangrike en hoë-impak entiteite kan identifiseer. ’n Breedvoerige wiskundige formulering word ontwikkel uit ’n versameling van bibliometriese metodes soos byvoorbeeld die h-indeks, die Impak Faktor vir journaale en die rang-algoritmes gebaseer op Google se PageRank. Verder word die teoretiese eienskappe van elke algoritme uitgelê. Die rang-algoritmes en bibliometriese metodes gebruik die sitasiedatabasis van Microsoft Academic Search vir berekeninge. Dit bevat 40 miljoen artikels en meer as 260 miljoen sitasies, wat oor verskeie akademiese dissiplines strek. Ons gebruik ’n groot stel toetsdata van dokumente en outeers wat bekende pryse op talle rekenaarwetenskaplike konferensies gewen het om die rang-algoritmes te evalueer. Die resultate toon dat die gebruik van sitasietellings, in die algemeen, die beste rangmetode is. Vir sekere take, soos die gradeering van belangrike artikels, of die identifisering van hoë-impak outeers, presteer algoritmes wat op PageRank gebaseer is egter beter. ’n Sekondêre resultaat van hierdie navorsing is die ontleding van publikasie tendense in verskeie akademiese dissiplines om sodoende veranderinge in publikasie gedrag oor tyd aan te toon en ook die verskille in publikasie patrone uit verskillende dissiplines uit te wys.

National soccer teams are currently ranked by soccer's governing body, the Federation Internationale de Football Association (FIFA). Although the system used by FIFA is thorough, taking into account many different factors, many of the weights used in the system's calculations are somewhat arbitrary. It is investigated here how the use of a statistical model might better compare the teams for ranking purposes. By treating each game played as a pairwise comparison experiment and by using the Bradley-Terry model as a starting point some suitable models are presented. A key component of the final model introduced here its ability to differentiate between friendly matches and competitive matches when determining the impact of a match on a teams ranking. Posterior distributions of the rating parameters are obtained, and the rankings and results obtained from each model are compared to FIFA's rankings and each other.

Analyzing ranking data is an essential component in a wide range of important applications including web-search and recommendation systems. Rankings are difficult to visualize or model due to the computational difficulties associated with the large number of items. On the other hand, partial or incomplete rankings induce more difficulties since approaches that adapt well to typical types of rankings cannot apply generally to all types. While analyzing ranking data has a long history in statistics, construction of an efficient framework to analyze incomplete ranking data (with or without ties) is currently an open problem. This thesis addresses the problem of scalability for visualizing and modeling partial incomplete rankings. In particular, we propose a distance measure for top-k rankings with the following three properties: (1) metric, (2) emphasis on top ranks, and (3) computational efficiency. Given the distance measure, the data can be projected into a low dimensional continuous vector space via multi-dimensional scaling (MDS) for easy visualization. We further propose a non-parametric model for estimating distributions of partial incomplete rankings. For the non-parametric estimator, we use a triangular kernel that is a direct analogue of the Euclidean triangular kernel. The computational difficulties for large n are simplified using combinatorial properties and generating functions associated with symmetric groups. We show that our estimator is computational efficient for rankings of arbitrary incompleteness and tie structure. Moreover, we propose an efficient learning algorithm to construct a preference elicitation system from partial incomplete rankings, which can be used to solve the cold-start problems in ranking recommendations. The proposed approaches are examined in experiments with real search engine and movie recommendation data.

Opsomming Daar bestaan 'n behoefte aan 'n objektiewe maatstaf om die gehalte van akademiese publikasies te bepaal en te vergelyk. Hierdie navorsing het die invloed of reaksie wat deur 'n publikasie gegenereer is uit verwysingsdata bepaal. Daar is van 'n iteratiewe algoritme gebruik gemaak wat gewigte aan verwysings toeken. In die Internetomgewing word hierdie benadering reeds met groot sukses toegepas deur onder andere die PageRank-algoritme van die Google soekenjin. Hierdie en ander algoritmes in die Internetomgewing is bestudeer om 'n algoritme vir akademiese artikels te ontwerp. Daar is op 'n variasie van die PageRank-algoritme besluit wat 'n Invloedwaarde bepaal. Die algoritme is op gevallestudies getoets. Die empiriese studie dui daarop dat hierdie variasie spesialisnavorsers se intu¨ıtiewe gevoel beter weergee as net die blote tel van verwysings. Abstract Ranking of journals are often used as an indicator of quality, and is extensively used as a mechanism for determining promotion and funding. This research studied ways of extracting the impact, or influence, of a journal from citation data, using an iterative process that allocates a weight to the source of a citation. After evaluating and discussing the characteristics that influence quality and importance of research with specialist researchers, a measure called the Influence factor was introduced, emulating the PageRankalgorithm used by Google to rank web pages. The Influence factor can be seen as a measure of the reaction that was generated by a publication, based on the number of scientists who read and cited itA good correlation between the rankings produced by the Influence factor and that given by specialist researchers were found. / Mathematical Sciences / M.Sc. (Operasionele Navorsing)

<p>With the large number of Android apps available in app stores such as Google Play, it has become increasingly challenging to choose among the apps. The users generally select the apps based on the ratings and reviews of other users, or the recommendations from the app store. But it is very important to take the security into consideration while choosing an app with the increasing security and privacy concerns with mobile apps. This thesis proposes different ranking schemes for Android apps based on security apps evaluated from the static code analysis tools that are available. It proposes the ranking schemes based on the categories of evidences reported by the tools, based on the frequency of each category, and based on the severity of each evidence. The evidences are gathered, and rankings are generated based on the theory of Subjective Logic. In addition to these ranking schemes, the tools are themselves evaluated against the Ghera benchmark. Finally, this work proposes two additional schemes to combine the evidences from difference tools to provide a combined ranking.</p>

Text in Afrikaans / Weens die veeleisende aard van sorggewing aan VIGS-weeskinders, bevind die sorggewers hulle dikwels in 'n posisie waar hulle self sorg en ondersteuning nodig het. Die vraag het begin ontstaan op watter manier hierdie sorggewers ondersteun kan word. Dit het duidelik geword dat die kerk vanuit hul sosiale verantwoordelikheid sorg en ondersteuning aan die sorggewers kan bied. Sorggewers van een instansie wat aan die navorsingsreis deelgeneem het, het inderdaad nie genoeg sorg en ondersteuning van die kerk ontvang nie. Hierdie gebrek aan ondersteuning het 'n direkte invloed op die sorggewers se hantering van sorggewingseise. Sorggewers van die ander twee deelnemende instansies ontvang genoeg ondersteuning van lidmate, en dit maak 'n groot verskil aan hoe sorggewingspanning beleef word. In hierdie studie is daar krities gekyk na wyses waarop die kerk betrokke is en verder kan betrokke raak by die sorggewers van VIGSweeskinders. / Philosophy, Practical & Systematic Theology / M.Th. (Praktiese Teologie)

In this thesis, we present and analyze three algorithms that are designed to make computer simulation more efficient, valid, and/or applicable. The first algorithm uses simulation cloning to enhance efficiency in transient simulation. Traditional simulation cloning is a technique that shares some parts of the simulation results when simulating different scenarios. We apply this idea to transient simulation, where multiple replications are required to achieve statistical validity. Computational savings are achieved by sharing some parts of the simulation results among several replications. We improve the algorithm by inducing negative correlation to compensate for the (undesirable) positive correlation introduced by sharing some parts of the simulation. Then we identify how many replications should share the same data, and provide numerical results to analyze the performance of our approach. The second algorithm chooses a set of best systems when there are multiple candidate systems and multiple objectives. We provide three different formulations of correct selection of the Pareto optimal set, where a system is Pareto optimal if it is not inferior in all objectives compared to other competing systems. Then we present our Pareto selection algorithm and prove its validity for all three formulations. Finally, we provide numerical results aimed at understanding how well our algorithm performs in various settings. Finally, we discuss the estimation of input distributions when theoretical distributions do not provide a good fit to existing data. Our approach is to use a quasi-empirical distribution, which is a mixture of an empirical distribution and a distribution for the right tail. We describe an existing approach that involves an exponential tail distribution, and adapt the approach to incorporate a Pareto tail distribution and to use a different cutoff point between the empirical and tail distributions. Then, to measure the impact, we simulate a stable M/G/1 queue with a known inter-arrival and unknown service time distributions, and estimate the mean and tail probabilities of the waiting time in queue using the different approaches. The results suggest that if we know that the system is stable, and suspect that the tail of the service time distribution is not exponential, then a quasi-empirical distribution with a Pareto tail works well, but with a lower bound imposed on the tail index.

Text in Afrikaans / Weens die veeleisende aard van sorggewing aan VIGS-weeskinders, bevind die sorggewers hulle dikwels in 'n posisie waar hulle self sorg en ondersteuning nodig het. Die vraag het begin ontstaan op watter manier hierdie sorggewers ondersteun kan word. Dit het duidelik geword dat die kerk vanuit hul sosiale verantwoordelikheid sorg en ondersteuning aan die sorggewers kan bied. Sorggewers van een instansie wat aan die navorsingsreis deelgeneem het, het inderdaad nie genoeg sorg en ondersteuning van die kerk ontvang nie. Hierdie gebrek aan ondersteuning het 'n direkte invloed op die sorggewers se hantering van sorggewingseise. Sorggewers van die ander twee deelnemende instansies ontvang genoeg ondersteuning van lidmate, en dit maak 'n groot verskil aan hoe sorggewingspanning beleef word. In hierdie studie is daar krities gekyk na wyses waarop die kerk betrokke is en verder kan betrokke raak by die sorggewers van VIGSweeskinders. / Philosophy, Practical and Systematic Theology / M.Th. (Praktiese Teologie)