Electro-hydraulic proportional flow valves are widely used in hydraulic industry. There are several different structures and working principles. However, flow valves based on the existing principles usually have some shortcomings such as the complexity of the system and additional energy losses. A concept for a two-stage poppet flow valve with pilot pressure drop – pilot spool opening compensation is presented, and the linear relationship between the pilot stage and main stage, the semi-empirical flow equation are used in the electronic flow controller. To achieve the accurate control of the outlet flow, the actual input voltage of the pilot spool valve is regulated according to the actual pilot pressure drop, the desired flow rate and the given input voltage. The results show that the pilot pressure drop – pilot spool opening compensation method is feasible, and the proposed proportional flow control valve with this compensation method has a good static and dynamic performance.

For both randomized clinical trials and prospective cohort studies, the Cox regression model is a powerful tool for evaluating the effect of a treatment or an explanatory variable on time-to-event outcome. This method assumes proportional hazards over time. Systematic approaches to efficiently evaluate non-proportionality and to model data in the presence of non-proportionality are investigated. Six graphical methods are assessed to verify the proportional hazards assumption based on characteristics of the survival function, cumulative hazard, or the feature of residuals. Their performances are empirically evaluated with simulations by checking their ability to be consistent and sensitive in detecting proportionality or non-proportionality. Two-sample data are generated in three scenarios of proportional hazards and five types of alternatives (that is, non-proportionality). The usefulness of these graphical assessment methods depends on the event rate and type of non-proportionality. Three numerical (statistical testing) methods are compared via simulation studies to investigate the proportional hazards assumption. In evaluating data for proportionality versus non-proportionality, the goal is to test a non-zero slope in a regression of the variable or its residuals on a specific function of time, or a Kolmogorov-type supremum test. Our simulation results show that statistical test performance is affected by the number of events, event rate, and degree of divergence of non-proportionality for a given hazards scenario. Determining which test will be used in practice depends on the specific situation under investigation. Both graphical and numerical approaches have benefits and costs, but they are complementary to each other. Several approaches to model and summarize non-proportionality data are presented, including non-parametric measurements and testing, semi-parametric models, and a parametric approach. Some illustrative examples using simulated data and real data are also presented. In summary, we present a systemic approach using both graphical and numerical methods to identify non-proportionality, and to provide numerous modeling strategies when proportionality is violated in time-to-event data.

This report presents the work carried out aiming towardsdistributed control of electric drives through a networkcommunication medium with temporal constraints, i.e, Ethernet.A general analysis on time delayed systems is carried out,using state space representation of systems in the discretetime domain. The effect of input time delays is identified andis used in the preceding controller designs. The main hardwareapplication focused in this study is a Brushless DC servomotor, whose speed control loop is closed via a 10 MbpsSwitched Ethernet network. The speed control loop, which isapproximately a decade slower than the current control loop, isopened and interfaced to the network at the sensor/actuatornode. It is closed at the speed controller end at another nodein the same local area network (LAN) forming a distributedcontrol system (DCS). The Proportional Integral (PI) classical controller designtechnique with ample changes in parameter tuning suitable fortime delayed systems is used. Then the standard Smith Predictoris tested, modified with the algebraic design techniqueCoefficient Diagram Method (CDM), which increases the systemdegrees of freedom. Constant control delay is assumed in thelatter designs despite the slight stochastic nature in thetiming data observations. Hence the poor transient performanceof the system is the price for the robustness inherited to thespeed controllers at the design stage. The controllability andobservability of the DCS may be lost, depending on the range inwhich the control delay is varying. However a state feedbackcontroller deploying on-line delay data, obtained by means ofsynchronizing the sensor node and controller node systemclocks, results in an effective compensation scheme for thenetwork induced delays. Hence the full state feedbackcontroller makes he distributed system transient performanceacceptable for servo applications with the help of poleplacement controller design. Further, speed synchronizing controllers have been designedsuch that a speed fluctuation caused by a mechanical loadtorque disturbance on one motor is followed effectively by anyother specified motor in the distributed control network with aminimum tracking or synchronizing error. This type ofperformance is often demanded in many industrial applicationssuch as printing, paper, bagging, pick and place and materialcutting. <b>Keywords:</b>Brushless DC Motor, Control Delay, DistributedMotion Control Systems, Proportional Integral Controller, SmithPredictor, Speed Synchronization, State Feedback Controller,Stochastic Systems, Switched-Ethernet, Synchronizing Error,Time Delayed Systems, Tracking Error / NR 20140805

Ratio is one of the key mathematics concepts included in the South African Mathematics curriculum. It is applied in other topics of the Grade 7 curriculum, including geometry, functions and relationships, algebra, similarity and congruency. The aim of this qualitative research study was to explore the difficulties that learners experience in learning ratio. The primary research question for the study was: What is Grade 7 learners’ knowledge of ratio? This research question was answered through the following secondary research questions: How do learners solve problems involving ratio? What is learners’ conceptual knowledge of ratio? And what learning difficulties do learners experience when learning about ratio? The study was informed by Kilpatrick, Swafford and Findell’s (2001) five strands of mathematical proficiency; however, the focus was on conceptual and procedural knowledge of ratio. The interpretivist paradigm and the single exploratory case study design were used to gain insight into the learning of ratio. Data was collected from Grade 7 learners (23 of the 35 learners originally sampled) through a self-developed test that followed the prescripts of the Grade 7 Mathematics curriculum in South Africa and through semi-structured interviews. The test scripts were analysed using the Atlas.tiTM windows coding system and the results were used to construct questions for the semi-structured interviews. The interviews were used to corroborate data emerging from the test. The results of the study indicated that Grade 7 learners can do simple and routine manipulations of ratio as well as non-proportional ratio problems but struggle to solve problems that require multiplicative thinking and proportional reasoning skills. Although there could be other factors contributing to learners’ struggle to tackle proportional ratio problems requiring multiplication and proportional reasoning, a lack of conceptual knowledge seemed to contribute significantly. / Dissertation (MEd)--University of Pretoria, 2020. / Science, Mathematics and Technology Education / MEd / Unrestricted

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Premarital fertility, that is, childbearing before first marriage, is an important yet under researched demographic topic in sub-Saharan Africa. In Zimbabwe, the distinction by marital status in fertility research is hardly drawn. Hence, a gap exists in the knowledge of premarital fertility levels. This research aims to investigate levels of, and factors associated with, premarital fertility since the onset of Zimbabwe's fertility transition in the mid-1980s. The research employed direct fertility estimation techniques to effectively compare premarital, marital, and overall fertility trends between 1988 and 2015. Cox proportional-hazards regression and forest plot analyses were then used to explain changes in factors associated with the timing of premarital first births over the same period. Data quality assessments were carried out using the method of cohortperiod fertility rates to provide explanations for any erratic results. The results showed that premarital fertility was constant and moderate, with an average of 0.7 children per woman, between 1988 and 2015. While most premarital first births consistently occurred to younger women, from 2005 onwards, they increased among women aged above 24 years and decreased among adolescents. An increase in age, commencing sexual activity after adolescence, and improved socio-economic status including level of education decreased the relative risk of having a premarital first birth. However, delaying marriage past young womanhood, history of contraceptive use, Ndebele ethnicity, and residence in regions other than Manicaland and Masvingo, especially Ndebele dominated regions, increased the same risk by 465.0%, 45.5%, 136.0% and up to 135.0% respectively. The stagnation of premarital fertility between 1988 and 2015 while both marital and overall fertility first declined and then stalled indicates that there is insufficient evidence to suggest that premarital fertility had contributed to the stall of fertility decline in Zimbabwe from the mid-1990s. The timing of premarital first births since the start of the fertility transition in the 1980s has had a strong ethnic and cultural bias. Due to evidence of the effect of migrancy and tourism on premarital fertility in border and tourism towns, an extension into the theory of migrant premarital sexual behaviour to detail the risk of premarital fertility among border town residents who interact with but are neither migrants nor tourists is recommended.

Nous proposons dans cette thèse d'exploiter la Modulation Hiérarchique (MH) dans un système OFDMA avec et sans utilisation des relais en vue d'améliorer d'avantage la capacité du système en tirant profit de la diversité d'utilisateurs. MH permet de transmettre un flux supplémentaire à un utilisateur de bonnes conditions radio sur une sous-porteuse initialement allouée à un utilisateur de mauvaises conditions radio. Ceci est différent des techniques classiques d’allocation de ressources proposées dans la littérature qui respectent une orthogonalité parfaite lors de l'allocation : une sous-porteuse est allouée à un seul utilisateur et aucun autre utilisateur ne pourra l'utiliser en même temps. Dans la littérature, la plupart des travaux qui se sont intéressés à l'utilisation de la MH se sont concentrés seulement sur les performances en termes de couche basse avec un nombre fixe d'utilisateurs dans le système correspondant à une configuration statique. Toutefois, cette configuration ne reflète pas la dynamicité du nombre d'utilisateurs dans un tel système, où les utilisateurs arrivent selon une loi aléatoire et partent après avoir fini leurs services. Dans cette thèse, nous exposons l'étude des performances de l'utilisation de la MH avec des configurations dynamiques d'utilisateurs correspondant à une étude au niveau flux. Cela nous permet d'évaluer les performances en termes de nouvelles métriques à savoir le temps moyen de transfert et la probabilité de blocage qui sont importantes pour l'utilisateur et pour l'opérateur. / We investigate, in this thesis, the use of Hierarchical Modulation (HM), a physical layer technique that enables to exploit multiuser diversity, for resource allocation in OFDMA-based systems with and without use of relaying, so as to improve the system capacity. HM allows the sharing of the resources, namely subcarriers and power, between users of different radio conditions by sending an additional stream to a user with good radio conditions on a subcarrier that was initially allocated to carry an original stream to a user with lower radio conditions. And this, without affecting the original user's rate nor the total amount of power assigned to the shared subcarrier. In the literature, most of the works that consider the use of HM focus solely on the physical layer performance, notably in terms of the bit error rate. And this for a static user scenario,i.e., with a fixed number of users in the system, each with an infinite service duration. This configuration however does not reflect the real system behavior where the number of users is dynamic, i.e., the users come to the system at random time epochs and leave it after a finite duration, corresponding to the completion of their services. The study of the system at the flow-level, as opposed to the packet level, for a dynamic user configuration, enables us to investigate the realistic relationship between capacity and demand and to quantify several system-level performance metrics, such as mean transfer times and blocking rates, which are meaningful both to the user and the network operator/provider.

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This paper develops a Bayesian ordinal regression model for the maladaptive subscales of the Inventory for Client and Agency Planning (ICAP). Because the maladaptive behavior section of the ICAP contains ordinal data, current analysis strategies combine all the subscales into three indices, making the data more interval in nature. Regular MANOVA tools are subsequently used to create a regression model for these indices. This paper uses ordinal regression to analyze each original scale separately. The sample consists of applicants for aid from Utah's Division of Services for Persons with Disabilities. Each applicant fills out the Scales of Independent Behavior"”Revised (SIB-R) portion of the ICAP that measures eight different maladaptive behaviors. This project models the frequency and severity of each of these eight problem behaviors with separate ordinal regression models. Gender, ethnicity, primary disability, and mental retardation are used as explanatory variables to calculate the odds ratios for a higher maladaptive behavior score in each model. This type of analysis provides a useful tool to any researcher using the ICAP to measure maladaptive behavior.

The advancement in data acquiring technology continues to see survival data sets with many covariates. This has posed a new challenge for researchers in identifying important covariates for inference and prediction for a time-to-event response variable. In this dissertation, common Cox proportional hazards model selection techniques and a random survival forest technique were compared using five performance criteria measures. These performance measures were concordance index, integrated area under the curve, and , and R2 . To carry out this exercise, a multicentre clinical trial data set was used. A simulation study was also implemented for this comparison. To develop a Cox proportional model, a training dataset of 75% of the observations was used and the model selection techniques were implemented to select covariates. Full Cox PH models containing all covariates were also incorporated for analysis for both the clinical trial data set and simulations. The clinical trial data set showed that the full model and forward selection technique performed better with the performance metrics employed, though they do not reduce the complexity of the model as much as the Lasso technique does. The simulation studies also showed that the full model performed better than the other techniques, with the Lasso technique overpenalising the model from the simulation with the smaller data set and many covariates. AIC and BIC were less effective in computation than the rest of the variable selection techniques, but effectively reduced model complexity than their counterparts for the simulations. The integrated area under the curve was the performance metric of choice for choosing the final model for analysis on the real data set. This performance metric gave more efficient outcomes unlike the other metrics on all selection techniques. This dissertation hence showed that variable selection techniques differ according to the study design of the research as well as the performance measure used. Hence, to have a good model, it is important to not use a model selection technique in isolation. There is therefore need for further research and publish techniques that work generally well for different study designs to make the process shorter for most researchers.