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This paper attempts to evaluate Training for Trainers (T4T) as an aid for developing healthy and sustained church planting movements (CPMs). The thesis is that Training for Trainers (T4T) can enable and sustain (by the Spirit’s power) healthy church planting movements because a discipleship process is built into the methodology that develops believers in their personal and communal growth and equips them to repeat the process with other individuals they reach. The very format of the T4T process provides a context for developing disciples inwardly and training disciples to minister outwardly. The T4T process continues over the course of months and years to systematically move believers through the essential stages of sustained church planting movements: Bridges in conversations with the lost from non-spiritual topics to the gospel in order to find those God is preparing (knowing whom to talk to and how to start) • Reproducible evangelism methods that are effective in the local context and can be learned by any new believer • Reproducible discipleship that addresses both short-term and long-term spiritual growth in a manner appropriate to the local worldview and able to be passed on by a new believer • Reproducible church models appropriate to the local context and able to be led and passed on by new believers • Leadership development and multiplication patterns that develop leaders rapidly in the context of ministry and enable the number of leaders to keep pace with the number of new churches. T4T moves each new generation of disciples (trainers) and churches through this process because it casts vision for and gives loving accountability for disciples to truly become trainers of others. It does this primarily through a three-thirds training process. T4T is training for trainers who will train trainers who will train trainers. T4T attempts to initiate movements of God in which at least four generations of new disciples and churches emerge. This paper evaluates T4T is based on case studies, survey instruments and biblical principles and then offers recommendations for CPM practitioners. / Christian Spirituality, Church History and Missiology / D. Th. (Missiology)

M.Sc., Faculty of Science, University of the Witwatersrand, 2011 / Studies have shown that text-to-speech systems need detailed prosodic models of a language in order to ideally sound natural to native speakers of the language. A text-to-speech system developed for Sesotho needs to have tone implemented in it since Sesotho is a tonal language which uses pitch variations to distinguish lexical and/or grammatical meaning. In order to implement tone for a language such as Sesotho, it is necessary for a tone modeling algorithm to receive as input the tone labels of the syllables of a word. This allows the algorithm to predict the appropriate intonation of the word. The aim of our study is to improve a basic tone labeling algorithm that predicts tone labels using three Sesotho tonal rules. The application of this algorithm is restricted to polysyllabic verb stems. The research study involves implementing an extended tone labeling algorithm that implements four additional Sesotho tonal rules and extends its application to all the other parts of speech. The results of our study show that the extended tone labeling algorithm significantly improves the basic algorithm by increasing the number of matched tone labels. Furthermore, our study provides the basic step to tone modeling for languages such as Sesotho which do not mark tone labels in orthography.

This paper explores the historical progression of the technological development of records and radio and its impact on popular music. It also includes the production technologies that create recorded music, the development of records, cassettes and CDs, and areas of reproduction that have an association with popular music including the sound technologies of radio, film, television, background music, and the juke-box. This paper is not a cultural or social study, but is primarily an historical account of media technology in music production and delivery. Certain social and cultural consequences and issues are included as background and sidebars to the primary topic. The technology of live performance has been omitted because it alone represents a body of material large enough for an entire paper. Western society now travels through a sea of music emanating from countless hidden sources. Such music delivery systems provide a continuous musical score for most people's personal histories. Sound, fragments of sound, and the very processes by which sound is created and manipulated have become products and commodities. The technology has allowed anyone to participate in the creation and hearing of music. This paper traces the history of the various technologies that, in so many respects, have provided a catalyst for that which is created, and the means by which music is listened to in the 20th Century. With rare exception, each new invention, delivery system, or process has had both supporters as well as detractors. Throughout this paper, both the positive as well as the negative effects of these developments will be explored. / Master of Arts (Hons)

The basic philosophy of Functional Data Analysis (FDA) is to think of the observed data functions as elements of a possibly infinite-dimensional function space. Most of the current research topics on FDA focus on advancing theoretical tools and extending existing multivariate techniques to accommodate the infinite-dimensional nature of data. This dissertation reports contributions on both fronts, where a unifying inverse regression theory for both the multivariate setting (Li 1991) and functional data from a Reproducing Kernel Hilbert Space (RKHS) prospective is developed. We proposed a functional multiple-index model which models a real response variable as a function of a few predictor variables called indices. These indices are random elements of the Hilbert space spanned by a second order stochastic process and they constitute the so-called Effective Dimensional Reduction Space (EDRS). To conduct inference on the EDRS, we discovered a fundamental result which reveals the geometrical association between the EDRS and the RKHS of the process. Two inverse regression procedures, a “slicing” approach and a kernel approach, were introduced to estimate the counterpart of the EDRS in the RKHS. Further the estimate of the EDRS was achieved via the transformation from the RKHS to the original Hilbert space. To construct an asymptotic theory, we introduced an isometric mapping from the empirical RKHS to the theoretical RKHS, which can be used to measure the distance between the estimator and the target. Some general computational issues of FDA were discussed, which led to the smoothed versions of the functional inverse regression methods. Simulation studies were performed to evaluate the performance of the inference procedures and applications to biological and chemometrical data analysis were illustrated.

This thesis proposes new analysis tools for simulation models in the presence of data. To achieve a representation close to reality, simulation models are typically endowed with a set of inputs, termed parameters, that represent several controllable, stochastic or unknown components of the system. Because these models often utilize computationally expensive procedures, even modern supercomputers require a nontrivial amount of time, money, and energy to run for complex systems. Existing statistical frameworks avoid repeated evaluations of deterministic models through an emulator, constructed by conducting an experiment on the code. In high dimensional scenarios, the traditional framework for emulator-based analysis can fail due to the computational burden of inference. This thesis proposes a new class of experiments where inference from half a million observations is possible in seconds versus the days required for the traditional technique. In a case study presented in this thesis, the parameter of interest is a function as opposed to a scalar or a set of scalars, meaning the problem exists in the high dimensional regime. This work develops a new modeling strategy to nonparametrically study the functional parameter using Bayesian inference. Stochastic simulations are also investigated in the thesis. I describe the development of emulators through a framework termed quantile kriging, which allows for non-parametric representations of the stochastic behavior of the output whereas previous work has focused on normally distributed outputs. Furthermore, this work studied asymptotic properties of this methodology that yielded practical insights. Under certain regulatory conditions, there is the following result: By using an experiment that has the appropriate ratio of replications to sets of different inputs, we can achieve an optimal rate of convergence. Additionally, this method provided the basic tool for the study of defect patterns and a case study is explored.

"...music is an art that exists in point of time." Aaron Copland, What to Listen for in Music / Few definitions are adequate to describe music, but a "point of time" is a concept with which people are familiar. When musicians give concerts they try to create these points in a context, which allows the audience to observe each moment by itself. Concert practice has developed to define the edges of musical points, guided by cues such as clapping, pauses, and concert program notes. / This masters thesis investigates how to analyze concert recordings of Western music and their program notes to produce segments which best fit the boundaries of musical points. Modern segmentation techniques are reviewed and a new method specific to concert recordings is examined.