Maintaining and operating manual main distribution frames is labour-intensive. As a result, Automated Main Distribution Frames (AMDFs) have been developed to alleviate the task of maintaining subscriber loops. Commercial AMDFs are currently employed in telephone exchanges in some parts of the world. However, the most significant factors limiting their widespread adoption are costeffective scalability and reliability. Therefore, an impelling incentive is provided to create a simulation framework in order to explore typical implementations and scenarios. Such a framework will allow the evaluation and optimisation of a design in terms of both internal and external redundancies. One of the approaches to improve system performance, such as system reliability, is to allocate the optimal redundancy to all or some components in a system. Redundancy at the system or component levels can be implemented in one of two schemes: parallel redundancy or standby redundancy. It is also possible to mix these schemes for various components. Moreover, the redundant elements may or may not be of the same type. If all the redundant elements are of different types, the redundancy optimisation model is implemented with component mixing. Conversely, if all the redundant components are identical, the model is implemented without component mixing. The developed framework can be used both to develop new AMDF architectures and to evaluate existing AMDF architectures in terms of expected lifetimes, reliability and service availability. Two simulation models are presented. The first simulation model is concerned with optimising central office equipment within a telephone exchange and entails an environment of clients utilising services. Currently, such a model does not exist. The second model is a mathematical model incorporating stochastic simulation and a hybrid intelligent evolutionary algorithm to solve redundancy allocation problems. For the first model, the optimal partitioning of the model is determined to speed up the simulation run efficiently. For the second model, the hybrid intelligent algorithm is used to solve the redundancy allocation problem under various constraints. Finally, a candidate concept design of an AMDF is presented and evaluated with both simulation models. / Dissertation (MEng)--University of Pretoria, 2013. / gm2014 / Electrical, Electronic and Computer Engineering / unrestricted

„Nun sag, wie hast du’s mit der Messung im Labor?“ So oder ähnlich lautet die sich anhand dieser Arbeit ergebende Gretchenfrage bezüglich biomechanischer Auswertungen und Studien des Laufsports, welche unter Laborbedingungen durchgeführt werden. Hierbei wird angenommen, dass eine Messung im Labor eine valide experimentelle Operationalisierung des Ausdauerlaufens darstellt. Aufgrund der räumlichen Begrenzung kann lediglich eine vergleichsweise geringe Anzahl an einzelnen Versuchen aufgezeichnet werden. Für die statistische Auswertung werden dann zumeist einzelne Parameter der Zeitreihen berechnet, welche wiederum zusammengefasst durch Mittelwerte den Probanden repräsentieren müssen. Bei der Verwendung von diskreten Parametern reduziert sich die aufgenommene Information der Zeitreihe dabei erheblich. Damit einhergehend muss die Frage geklärt werden, ob die Variabilität eines Probanden anhand diskreter Werte oder anhand der gesamten Kurve Beachtung finden muss. Des Weiteren stellt sich die Frage inwieweit das arithmetische Mittel über eine große Anzahl an Versuchen als die den Probanden repräsentierende Kennzahl verwendet und dessen Variabilität mittels einer endlichen Anzahl an Wiederholungen charakterisiert werden kann. Für die Untersuchungen wurden zunächst zwei Studien durchgeführt, wobei die Aufzeichnung von Bodenreaktionskräften und der Winkelgeschwindigkeit bei 100 Läufen an je zwei Messtagen im Labor erfolgte. Die statistischen Auswertungen umfassen sowohl die Betrachtung der Konvergenz von Folgen kumulierter Mittelwerte, Standardabweichungen und Root Mean Square Errors für diskrete Parameter und die gesamten aufgezeichneten Signale der Bodenreaktionskräfte und Winkelgeschwindigkeit als auch die Untersuchung von Prädiktionsbändern. Zudem wurden unterschiedliche Algorithmen zur Bestimmung der minimalen Anzahl an aufzuzeichnenden Versuchen entwickelt. Diese beinhalten nichtlineare Regressionsmodelle für die Anpassung der kumulierten Fläche der Prädiktionsbänder gesamter Kurven und die Analyse der Differenzen aufeinanderfolgender Standardabweichungskurven. Zusammenfassend geht aus dieser Arbeit hervor, dass die postulierte ausreichende und stabile Charakterisierung eines Probanden anhand des arithmetischen Mittels sowie der vollständigen und soliden Beschreibung der Variabilität für diskrete Parameter nicht nachgewiesen werden konnte. Für gesamte Kurven ergab sich ein anderes Bild. Die Probanden konnten anhand der mittleren vertikalen Bodenreaktionskräfte sowie der Bodenreaktionskräfte in anterior-posterior Richtung stabil und ausreichend charakterisiert werden. Für die Bodenreaktionskräfte in mediolateraler Richtung und die Kurve der Winkelgeschwindigkeit wurde dies nicht bestätigt. Die Möglichkeit der Charakterisierung der Variabilität eines Probanden konnte zudem verifiziert werden. Durch Beibehaltung der ursprünglichen Messprozedur ist die Wahrscheinlichkeit sehr hoch, dass der begangene Fehler den Ausgang der statistischen Auswertung beeinflusst und damit Eigenschaften der vorliegenden Grundgesamtheit unter Umständen falsch widerspiegelt. Von einer Verwendung des Mittelwertes diskreter Parameter sollte daher abgesehen werden. Der Fehler sowie dessen unbekanntes Ausmaß sind zum Teil unkontrollierbar und dessen Auswirkungen auf weitere biomechanische Kenngrößen nicht überprüfbar. Die Annahme, dass eine Labormessung als valide experimentelle Operationalisierung des Ausdauerlaufens angesehen werden kann, ist damit hinfällig. Es ist zukünftig notwendig, die Erforschung neuer Aufnahme- und Auswerteprozeduren, die alternative Verwendung gesamter Kurven und die Entwicklung neuer Testverfahren zu forcieren.

Multilevel Random Pulse Width Modulation (RPWM) schemes have drawn increasing attention in the past few years. Multilevel topologies provide high voltage and high power capabilities and random PWM schemes offer reduction in discrete harmonics spectral. This dissertation provides a generalized theory and analysis methods of the standard five-level Weighted RPWM (WRPWM). Equations have been derived to analyze the spectral performance and average switching frequency of the WRPWM output waveform using statistical approach. A modified WRPWM scheme has been proposed. The modified WRPWM scheme is then analyzed with the equations derived from the same approach. The analyzed theoretical spectrum of the standard five-level WRPWM is then compared with the three-level WRPWM scheme and the conventional carrier based PWM scheme. A scaled laboratory prototype diode clamping five-level inverter has been built for verification of the standard and the proposed modified WRPWM schemes. It can be seen that the experimental measurements and the theoretical analyzed results are all in good agreement. Results show the two five-level WRPWM schemes offers significant improvements on the spectrum content than the conventional carrier based PWM scheme. It was found that the five-level WRPWM schemes have successfully suppress the magnitude of third harmonic below 5% of the magnitude of fundamental component and even less for the higher order harmonic components. Research contributions made by the dissertation are: - The proposed modified multilevel WRPWM scheme which utilizing the switching decision redundancy of multilevel inverter to manipulate the harmonic content of the output signal. - The derived mathematical equations of the standard and modified five-level WRPWM scheme for analytical purposes. / Dissertation (MEng (Electrical Engineering))--University of Pretoria, 2005. / Electrical, Electronic and Computer Engineering / unrestricted

<p>No Fault Founds (NFFs) are an expensive problem faced by the airline industry. The underlying cause of NFFs are a major focus of research work in the field, but the dearth of consistent data is a roadblock faced by many decision makers. An important risk factor identified is the occurrence rate of NFFs.</p><p>This research work aims to help decision makers in the Airline Maintenance, Repair and Overhaul teams, when faced with recurring NFFs, to make a choice based on value derived from the system and risk preference of the decision maker under uncertainty. The value of the aircraft fleet is laid out using Net Present Value at every decision point along the system life cycle while accounting for the uncertainty in the failure rate information. Two extreme decisions are considered for the decision maker to choose between: rebooting the system every time a failure occurs and results in an NFF which allows for it to recur while reducing uncertainty of the failure rate; or eliminating the failure mode which assumes that the failure does not recur and therefore completely removes the uncertainty. Both decisions have their associated uncertain costs that affect the NPV calculated. We use a Monte Carlo approach to estimate the expected profit from deciding to eliminate the failure mode. We make use of Expected Utility Theory to account for the risk preference of a decision maker under uncertainty and build an Expected Utility Maximizing decision framework.</p>To conclude we give some guidance to interpret the results and understand what factors influence the optimal decision. We conclude that not accounting for uncertainty in estimating a failure rate for the future along with uncertainty in NFF costs can lead to an undesirable decision. If the decision maker waits too long to gather more information and reduce uncertainty, then rebooting the system for the remaining life could be more worthwhile than spending the large amount of money to Eliminate a failure mode. Finally, we conclude that, despite uncertainties in information of occurrence rates and costs of NFFs, an Expected Utility maximizing decision between the two options considered – Reboot and Eliminate – is possible given the available information.

In recent years, the Buy Now Pay Later (BNPL) consumer credit industry associated with e-commerce has been rapidly emerging as an alternative to credit cards and traditional consumer credit products. In parallel, the regulation IFRS 9 was introduced in 2018 requiring creditors to become more proactive in forecasting their Expected Credit Losses and include the impact of macroeconomic factors. This study evaluates several methods of supervised statistical learning to model the Probability of Default (PD) for BNPL credit contracts. Furthermore, the study analyzes to what extent macroeconomic factors impact the prediction under the requirements in IFRS 9 and was carried out as a case study with the Swedish fintech firm Klarna. The results suggest that XGBoost produces the highest predictive power measured in Precision-Recall and ROC Area Under Curve, with ROC values between 0.80 and 0.91 in three modeled scenarios. Moreover, the inclusion of macroeconomic variables generally improves the Precision-Recall Area Under Curve. Real GDP growth, housing prices, and unemployment rate are frequently among the most important macroeconomic factors. The findings are in line with previous research on similar industries and contribute to the literature on PD modeling in the BNPL industry, where limited previous research was identified. / De senaste åren har Buy Now Pay Later (BNPL) snabbt vuxit fram som ett alternativ till kreditkort och traditionella kreditprodukter, i synnerhet inom e-handel. Dessutom introducerades 2018 det nya regelverket IFRS 9, vilket kräver att banker och andra kreditgivare ska bli mer framåtblickande i modelleringen av sina förväntade kreditförluster, samt ta hänsyn till effekter från makroekonomiska faktorer. I denna studie utvärderas flera metoder inom statistisk inlärning för att modellera Probability of Default (PD), sannolikheten att en kreditförlust inträffar, för BNPL-kreditkontrakt. Dessutom analyseras i vilken utsträckning makroekonomiska faktorer påverkar modellernas prediktiva förmågor enligt kraven i IFRS 9. Studien genomfördes som en fallstudie med det svenska fintechföretaget Klarna. Resultaten tyder på att XGBoost har den största prediktionsförmågan mätt i Precision-Recall och ROC Area Under Curve, med ROC-värden mellan 0.80 och 0.91 i tre scenarier. Inkludering av makroekonomiska variabler förbättrar generellt PR-Area Under Curve. Real BNP-tillväxt, bostadspriser och arbetslöshet återfinns frekvent bland de viktigaste makroekonomiska faktorerna. Resultaten är i linje med tidigare forskning inom liknande branscher och bidrar till litteraturen om att modellera PD i BNPL-branschen där begränsad tidigare forskning hittades.

The thesis contains 3 repairable systems and 2 replacement systems: First a repairable system is considered with Markovian deterioration and imperfect repair, carried out at fixed times. We look for optimal strategies under certain conditions. Two optimality criteria are considered: expected discounted cost and long-run average cost. Conditions are found under which the optimal policy is a control-limit policy as used by Derman or Ross. We explicitly explain how to derive this optimal policy; numerical examples are given, too. The special case of unbounded cost is also studied. With the first model the state space is numerable but with the second it is not. With the fourth model the system occurs a shock process and is only inspected after such a shock. Models 3 and 5 are replacement systems with Morkovian deterioration and finite state space {0,...,N}. A system in state N is considered to be in a very serious situation. Hence there is the condition, e.g. stipulated by law, that the percentage of all replaced machines in state N in the group of all replaced machines may not be larger than 100 epsilon for a fixed epsilon in [0,1]. We prove that a generalized control limit policy maximizes the expected running time of a machine and we explain explicitly how to derive this optimal policy. Illustrated numerical examples are given.

Contrary to popular belief, we can’t all be winners. Suppose 6 people compete in a chess tournament in which all pairs of players compete directly and no ties are allowed; i.e., 6 people compete in a ‘round robin tournament’. Each player is assigned a ‘score’, namely the number of games they won, and the ‘score sequence’ of the tournament is a list of the players’ scores. Determining whether a given potential score sequence actually is a score sequence proves to be difficult. For instance, (0, 0, 3, 3, 3, 6) is not feasible because two players cannot both have score 0. Neither is the sequence (1, 1, 1, 4, 4, 4) because the sum of the scores is 16, but only 15 games are played among 6 players. This so called ‘tournament score sequence problem’ (TSSP) was solved in 1953 by the mathematical sociologist H. G. Landau. His work inspired the investigation of round robin tournaments as directed graphs. We study a modification in which the TSSP is cast as a system of inequalities whose solutions form a polytope η-dimensional space. This relaxation allows us to investigate the possibility of fractional scores. If, in a ‘round-robin’-ish tournament, Players A and B play each other 3 times, and Player A wins 2 of the 3 games, we can record this interaction as a 2/3 score for Player A and a 1/3 score for Player B. This generalization greatly impacts the nature of possible score sequences. We will also entertain an interpretation of these fractional scores as probabilities predicting the outcome of a true round robin tournament. The intersection of digraph theory, polyhedral combinatorics, and linear programming is a relatively new branch of graph theory. These results pioneer research in this field.

This study aims to investigate the rationalization behind young adults' decision on whether or not they want children. The goal is to help contribute to previous studies on how reproductive mindsets differ based on whether or not a person wants children. This is a qualitative study rooted in interviews with eleven women and one man all aged 19 to 31 years of age. The theories used to analyze the results are concentrating on the terms expected lifeline, biological destiny, self-fulfillment, active mothering and intense mothering.  The results of this study show that the personal definitions of "success" in life do not differ drastically based on the desire to have children. Additionally, the informants all had similar expectations of what was "needed" from life,  in a financial sense, to achieve desired living conditions before having children. What did matter was what a person found self-fulfilling and their self-image in determining their desire for children. The results also show that the informants had experienced similar interactions with the pressures of societal norms on expected lifeline and that they worry about not living up to the notion of what a good parent is like.

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We derive and test a series of profitability factors for cross-section of expected returns on Japanese and Chinese equity markets. We find gross profitability predicts returns and significant both on Japanese and Chinese equity markets. We test these factors using Fama-MacBeth regression and find gross profitability and value portfolios perform better in Japan, size and gross profitability portfolios perform better in China. Then we create new three-factor model based on the result of 5*5 portfolios, which capture value and gross profitability premium in Japan, and, size and gross profitability premium in China. And the new models' GRS test performs better than Fama-French-three-factor model at the 5% significance level. / 博士(文化情報学) / Doctor of Culture and Information Science / 同志社大学 / Doshisha University