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A thesis submitted to the Wits School of Education, Faculty of Humanities, in accordance with the requirements for the degree of Doctor of Philosophy at the University of the Witwatersrand. January 2019 / The study investigated the ways in which principals and other school leaders navigated issues of multiple deprivation to achieve high academic performance. The study was grounded in the theoretical framework of the University of Chicago Consortium on Chicago School Research (Bryk, Sebring, Allensworth, Easton, & Luppescu, 2010), which proposes five essential supports (5 Essentials) for successful schools. The framework was the lens used to understand whether or not successful school leaders implemented these five essentials supports in response to their learners’ battle with multiple deprivation. The main research question of the study is: what can we learn about school improvement from the leadership practices of successful school leaders in primary schools educating learners afflicted by multiple deprivation in Soweto? Interviews were conducted with two principals, three School Management Team (SMT) members, and three educators. Using thematic content analysis, recurrent themes emerged including stakeholders involvement, policy, academic support, progress monitoring, collaborative teachers, teacher quality, team building, parental involvement, and distributed leadership. In the South African context, this study expands the 5 Essentials framework through a contribution toward the emergence of a model of leadership practices of successful school leaders educating learners afflicted by multiple deprivation in primary township schools. In this model, the four core leadership practice with related themes, explain the leadership practices that underpin learner achievement. The core leadership practices and themes includes: (1) safety practices: stakeholder involvement and policy; (2) instructional practices: collaborative teachers; 3 (3) teacher quality and team building academic practices: academic support and progress monitoring; and (4) family engagement practices: parental Involvement (Biological or Proxy) / MT 2019

Any product sold is expected to be reliable and available when the customer wants to operate it. Companies that produce large capital products (LCP), such as rockets, satellites, or large gas turbines to generate electrical energy, tend to shy away from extending their testing and validation method above the requirements by law, mainly due to the very high costs of each additional test and the uncertain return on investment. This research shows that today’s state of the art validation methods for LCP, required by law, or suggested in literature, and adapted by these industries, are not capable of capturing all significant failure modes (or even enough failure modes), with the consequence that the subsequently sold commercial product will still experience failures with significant effects on product reliability, and subsequently on the companies’ bottom line earnings projections. The research determines the type of data (significant variables) necessary to correlate a company’s validation policy to product failures after commercialization, and predicts the financial impact of the current validation policy on the company’s profitability. An optimized validation plan and testing policy is suggested, and its impact on a company’s profitability is demonstrated through simulation. A generic methodology is derived and its viability is illustrated using a specific product and a dynamic model developed with data available to the researcher. The generic method can be applied by any company to develop its own model for optimizing product reliability prior to market introduction. iv

One of two project reports. Part A can be found at: http://hdl.handle.net/11375/18452 / No abstract was provided. / Thesis / Master of Engineering (ME)

<p> This thesis contributes significantly to the advancement of the response sensitivity analysis with time-domain electromagnetic (EM) solvers. The proposed self-adjoint sensitivity approaches achieve unprecedented computational efficiency. The response Jacobians are computed as a simple post-process of the field solution and the approaches can be applied with any commercial time-domain solver. The proposed sensitivity solvers are a breakthrough in the sensitivity analysis of high-frequency structures since they can be implemented as standalone software or plugin for EM simulators. The goal is to aid the solution of microwave design and inverse problems.</p> <p> The sensitivity information is crucial in engineering problems such as gradient-based optimization, yield and tolerance analyses. However, due to the lack of robust algorithms, commercial EM simulators provide only specific engineering responses not their sensitivities (or derivatives with respect to certain system parameters). The sensitivities are typically obtained by response-level finite difference (FD) approximations or parameter sweeps. For each design parameter of interest, at least one additional full-wave analysis is performed. Such approaches can easily become prohibitively slow when the number of design parameters is large.</p> <p> However, no extra system analysis is needed with the self-adjoint sensitivity analysis methods. Both the responses and their Jacobian are obtained through a single system analysis. In this thesis, two self-adjoint sensitivity solvers are introduced. They are based on a self-adjoint formulation which eliminates the need to perform adjoint system analysis. The first sensitivity solver is based on a self-adjoint formula which operates on the time waveforms of the field solution. Three different approaches associated with this sensitivity solver have been presented. The first approach adopts the staggered grid of the finite-difference time-domain (FDTD) simulation. We refer it as the original self-adjoint approach. The second approach is the efficient coarse-grid approach. It uses a coarse independent FD grid whose step size can be many times larger than that of the FDTD simulation. The third approach is the accurate central-node approach. It uses a central-node grid whose field components are collocated in the center of the traditional Yee cell.</p> <p> The second self-adjoint sensitivity solver is based on a spectral sensitivity formula which operates on the spectral components of the E-field instead of its time waveforms. This is a memory efficient wideband sensitivity solver. It overcomes the drawback associated with our first sensitivity solver whose memory requirements may become excessive when the number of the perturbation grid points is very large. The spectral approach reduces the memory requirements roughly from Gigabytes to Megabytes. The focus of this approach is on microwave imaging applications where our first sensitivity solver is inapplicable due to the excessive memory requirements. The proposed sensitivity solver is also well suited for microwave design problems.</p> <p> The proposed self-adjoint sensitivity solvers in this thesis are verified by numerous examples. They are milestones in sensitivity analysis because they have finally made EM simulation-based optimization feasible.</p> / Thesis / Doctor of Philosophy (PhD)

Thesis: Sc. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 1979 / Vita. / Includes bibliographical references. / by George Brian Kenney. / Sc. D. / Sc. D. Massachusetts Institute of Technology, Department of Materials Science and Engineering

In current bridge practice, all tension members in a truss bridge are identified as fracture critical members which implies that a collapse is expected to occur once a member of this type fails. However, there are several examples which show that bridges have remained standing and shown little distress even after a fracture critical member was completely damaged. Due to the high inspection cost for fracture critical members, it would be beneficial to remove fracture critical designation from some tension members. This could be achieved via considering system redundancy. Since there is no clear guidance in existing codified provisions for assessing system redundancy, this research is undertaken to develop simplified analysis techniques to evaluate system redundancy in truss bridges. The proposed system redundancy analysis in this research starts with the identification of the most critical main truss members whose failure may significantly affect the system redundancy. The system redundancy is then measured by the remaining load capacity of a damaged bridge after losing one of the critical members. The bridge load capacity is checked using 3D models with nonlinear features that can capture the progression of yielding and buckling in a bridge system. The modeling techniques are validated through the case studies of the I-35W Bridge and one test span of the Milton-Madison Bridge. Reasonable correlations are demonstrated between the models and the measured data for these two bridges both in an undamaged and in a damaged state. The feasibility of the proposed methodology for system redundancy evaluation is examined by applying the methodology blindly to two other simple truss bridges. The application shows that the proposed methodology can efficiently measure the system redundancy. To improve the system redundancy, this research also proposes sample retrofit strategies for the four example bridges. / Ph. D.

Systems are developed to fulfill certain requirements. Several system design configurations usually can fulfill the technical requirements, but at different equivalent life-cycle costs. The problem is how to manipulate and evaluate different system configurations so that the required system effectiveness can be achieved at a minimum equivalent cost. It is also important to have a good definition of all the major consequences of each design configuration. For each alternative configuration considered, it is useful to know the number of units to deploy, the inventory and other logistic requirements, as well as the sensitivity of the system to changes in input variable values. An intelligent relational database management system is defined to solve the problem described. Table structures are defined to maintain the required data elements and algorithms are constructed to manipulate the data to provide the necessary information. The methodology is as follows: Customer requirements are analyzed in functional terms. Feasible design alternatives are considered and defined as system design configurations. The reliability characteristics of each system configuration are determined, initially from a system-level allocation, and later determined from test and evaluation data. A maintenance analysis is conducted to determine the inventory requirements (using reliability data) and the other logistic requirements for each design configuration. A vector of effectiveness measures can be developed for each customer, depending on objectives, constraints, and risks. These effectiveness measures, consisting of a combination of performance and cost measures, are used to aid in objectively deciding which alternative is preferred. Relationships are defined between the user requirements, the reliability and maintainability of the system, the number of units deployed, the inventory level, and other logistic characteristics of the system. A heuristic procedure is developed to interactively manipulate these parameters to obtain a good solution to the problem with technical performance and cost measures as criteria. Although it is not guaranteed that the optimal solution will be found, a feasible solution close to the optimal will be found. Eventually the user will have, at any time, the ability to change the value of any parameter modeled. The impact on the total system will subsequently be made visible. / Master of Science

In this thesis, a presentation of a new canonical representation of multi-input multi-output systems is given. The new characterization covers the full range of practical situations in linear systems according to the structural properties and model of the perturbations which are known. Its direct link to ARMA processes as well as to classical state space representation ls also given. The importance of the new representation lies in the fact that all unknown parameters and state variables appear linearly multiplied by either external variables (inputs and outputs) that appear in the data record, or by matrices that are only composed of zeroes and ones. This property enables us to perform a joint state and parameters estimation. Moreover, if the noises are gaussian and their statistics are known, an on-line algorithm that involves a standard discrete-time time-varying Kalman filter is proposed and used successfully in the estimation of unknown parameters for simulated examples. / Master of Science

This dissertation presents a new method of simultaneous parameter and state estimation for linear, stochastic, discrete—time, multiple-input, multiple-output (MIMO) (B systems. This new method is called pseudo-Iinear identification (PLID), and extends an earlier method to the more general case where system input and output measurements are corrupted by noise. PLID can be applied to completely observable, completely controllable systems with known structure (i.e., known observability indexes) and unknown parameters. No assumptions on pole and zero locations are required; and no assumptions on relative degree are required, except that the system transfer functions must be strictly proper. Under standard gaussian assumptions on the various noises, for time-invariant systems in the class described above, it is proved that PLID is the optimal estimator (in the mean-square-error sense) of the states and the parameters, conditioned on the output measurements. It is also proved, under a reasonable assumption of persistent excitation, that the PLID parameter estimates converge a.e. to the true parameter values of the unknown system. For deterministic systems, it is proved that PLID exactly identifies the states and parameters in the minimum possible time, so0called deadbeat identification. The proof brings out an interesting relation between the estimate error propagation and the observability matrix of the time-varying extended system (the extended system incorporates the unknown parameters into the state vector). This relation gives rise to an intuitively appealing notion of persistent excitation. Some results of system identification simulations are presented. Several different cases are simulated, including a two-input, two-output system with non-minimum-phase zeros, and an unstable system. A comparison of PLID with the widely used extended Kalman filter is presented for a single-input, single-output system with near cancellation of a pole-zero pair. Results are also presented from simulations of the adaptive control of an unstable. two-input, two-output system In these simulations, PLID is used in a se1f—tuning regulator to identify the parameters needed to compute the feedback gain matrix, and (simultaneously) to estimate the system states, for the state feedback / Ph. D.