Students enrolled for the Network Systems III module at the Vaal University of Technology are experiencing problems with passing this module. Many of them fail due to the fact that they do not understand the subnet masking part of it. In an attempt to increase the students' pass rate, this study will make additional study material available to them, complying with their learning style preferences. This material will be available as elearning material on the Internet. The usage and success of elearning material implies a holistic approach towards learning styles. Learning styles consist of different interrelated learning elements. This study will make use of an action research approach comprising four phases. In the first phase, different learning styles are diagnosed by means of a literature study. The information obtained is applied to compile an interpretive questionnaire for completion by students. This questionnaire will enable the researcher to do an empirical study with regard to their learning preferences. The data obtained from the questionnaires will be analysed and information obtained will be applied to make additional module related elearning material available on the Internet. During the second phase, results obtained from the empirical investigation will be used to develop elearning material on subnetting, while also addressing the identified learning styles of participants. The elearning material is provided on the Moodle learning management system, enabling students to use it according to their own preferences. In the third phase, the success of the intervention on the elearning material is investigated. In this phase, the activities of students using the elearning material are analysed and tests and examination results processed to determine whether there is any correlation between time spent on elearning material and these results. The usage of elearning material is tested by means of an interpretive questionnaire to the students. The last part of the action research approach deals with the question of whether the research was conducted successfully. A second iteration of the process proved the results to be satisfactory. The elearning material was positively received by students participating in the research, while a growing interest in this material was noticed from the last semester in 2007 to the first semester in 2008. / Thesis (M.Sc. (Computer Science))--North-West University, Potchefstroom Campus, 2011.

A statistical downscaling approach based on multiple linear-regression is used to investigate the predictability of land surface winds over the Canadian prairies and Ontario. This study's model downscales mid-tropospheric predictors (wind components and speed, temperature, and geopotential height) from reanalysis products to predict historical wind observations at thirty-one airport-based weather surface stations in Canada. The model's performance is assessed as a function of: season; geographic location; averaging timescale of the wind statistics; and wind regime, as defined by how variable the vector wind is relative to its mean amplitude. Despite large differences in predictability characteristics between sites, several systematic results are observed. Consistent with recent studies, a strong anisotropy of predictability for vector quantities is observed, while some components are generally well predicted, others have no predictability. The predictability of mean quantities is greater on shorter averaging timescales. In general, the predictability of the surface wind speeds over the Canadian prairies and Ontario is poor; as is the predictability of sub-averaging timescale variability. These results and the relative predictability of vector and scalar wind quantities are interpreted with theoretically- and empirically-derived wind speed sensitivities to the resolved and unresolved variability in the vector winds. At most sites, and on longer averaging timescales, the scalar wind quantities are found to be highly sensitive to unresolved variability in the vector winds. These results demonstrate limitations to the statistical downscaling of wind speed and suggest that deterministic models which resolve the short-timescale variability may be necessary for successful predictions. / Graduate

Nanometer-scale silicon shows extraordinary electronic and optical properties that are not available for bulk silicon, and many investigations toward applications in optoelectronic devices are being pursued. Silicon nanoparticle films made from solution are a promising candidate for low-cost solar cells. However, controlling the properties of silicon nanoparticles is quite a challenge, in particular shape and size distribution, which effect device performance. At present, none of the solar cells made from silicon nanoparticle films have an efficiency exceeding the efficiency of those based on crystalline silicon. To address the challenge of controlling silicon nanoparticle properties, both theoretical and experimental investigations are needed. In this thesis, we investigate silicon nanoparticle properties via quantum mechanical modeling of silicon nanoparticles and synthesis of silicon nanoparticle films via colloidal grinding. Silicon nanoparticles with shapes including cubic, rectangular, ellipsoidal and flat disk are modeled using semi-empirical methods and configuration interaction. Their electronic properties with different surface passivation were also studied. The results showed that silicon nanoparticles with hydrogen passivation have higher HOMOLUMO gaps, and also the HOMO-LUMO gap depends on the size and the shape of the particle. In contrast, silicon nanoparticles with oxygen passivation have a lower HOMO-LUMO gap. Raman spectroscopy calculation of silicon nanoparticles show peak shift and asymmetric broadening similar to what has been observed in experiment. Silicon nanoparticle synthesis via colloidal grinding was demonstrated as a straightforward and inexpensive approach for thin film solar cells. Data analysis of silicon particles via SEM images demonstrated that colloidal grinding is effective in reducing the Si particle size to sub-micron in a short grinding time. Further increases in grinding time, followed by filtration demonstrated a narrowing of the Si particle size and size-distribution to an average size of 70 nm. Raman spectroscopy and EDS data demonstrated that the Si nanoparticles contain oxygen due to exposure to air during grinding. I-V characterization of the milled Si nanoparticles showed an ohmic behaviour with low current at low biases then Schottky diode behaviour or a symmetric curve at large biases. / Graduate / 0794 / 0544 / zahraalbu@hotmail.com

The primary task of this paper is to test the interactive relations between tax rates at municipality level. We include 96 municipalities between the years 2006 to 2013.   The relations are estimated by panel data instrumental variable estimation method with fixed effect for overcoming the possible specific error of simultaneity. In addition, we choose a set of control variables to strength our analysis. The main findings of this study suggest, one percent tax cut in the neighboring municipality leads to a 0,62 percent decrease in the tax in the home municipality ceteris paribus. This result is in line with theory and is similar to findings in previous studies such as Edmark and Åhgren (2008).

This thesis describes the analysis of over 1300 spelling and typing errors. It introduces and describes many empirical rules which these errors obey and shows that a vast majority of errors are variations on some 3000 basic forms. It also describes and tests an intelligent, knowledge based spelling error correction algorithm based on the above work. Using the Shorter Oxford English dictionary it correctly identifies over 90% of typical spelling errors and over 80% of all spelling errors, where the correct word is in the dictionary. The methodology used is as follows: An error form is compared with each word in that small portion of the dictionary likely to contain the intended word, but examination of improbable words is rapidly abandoned using heuristic rules. Any differences between the dictionary word and the error form are compared with the basic forms. Any dictionary word which differs from the error form only by one or two basic forms is transferred to a separate list. The program then acts as an expert system where each of the basic forms is a production or rule with a subjective Bayesian probability. A choice is made from the list by calculating the Bayesian probability for each word in the separate list. An interactive spelling error corrector using the concepts and methods developed here is operating on the Bradford University Cyber 170/720 Computer, and was used to correct this thesis. The corrector also runs on VAX and Prime computers.

This article aims at the statistical assessment of time series with large fluctuations in short time, which are assumed to stem from a continuous process perturbed by a Lévy process exhibiting a heavy tail behavior. We propose an easily implementable procedure to estimate efficiently the statistical difference between the noisy behavior of the data and a given reference jump measure in terms of so-called coupling distances. After a short introduction to Lévy processes and coupling distances we recall basic statistical approximation results and derive rates of convergence. In the sequel the procedure is elaborated in detail in an abstract setting and eventually applied in a case study to simulated and paleoclimate data. It indicates the dominant presence of a non-stable heavy-tailed jump Lévy component for some tail index greater than 2.

Fyra analysander intervjuades om deras upplevelser av den psykoanalytiska situationen. Materialet analyserades med hjälp av EPP (empirical phenomenological psychologial) -metoden. Resultatet beskriver fenomenets meningsstruktur som en helhet och visar på den psykoanalytiska situationens generella kännetecken: den psykoanalytiska situationen som något svårfångat, som ett upprepat omprövande, som ett arbete, den präglas av konflikter och motstånd, en upplösning av tid och rum, ett möte med analytikern, ett rum för självutforskande och avslutningsvis, identitetsskapande självreflektion. Resultatet visar att upplevelsen av den psykoanalytiska situationen är något upplösande som bryter med den vanliga livsvärldsupplevelsen. Den är något irrationellt svårfångat. Resultaten visar också hur upplevelsen präglas av relationen till analytikern, hur den möter motstånd och konflikt. Avslutningsvis hur det formas något nytt genom ett prövande och utforskande meningsskapande.

This thesis presents research to build and evaluate embedding of a textual form of state machines into high-level programming languages. The work entailed adding state machine syntax and code generation to the Umple model-oriented programming technology. The added concepts include states, transitions, actions, and composite states as found in the Unified Modeling Language (UML). This approach allows software developers to take advantage of the modeling abstractions in their textual environments, without sacrificing the value added of visual modeling. Our efforts in developing state machines in Umple followed a test-driven approach to ensure high quality and usability of the technology. We have also developed a syntax-directed editor for Umple, similar to those available to other high-level programming languages. We conducted a grounded theory study of Umple users and used the findings iteratively to guide our experimental development. Finally, we conducted a controlled experiment to evaluate the effectiveness of our approach. By enhancing the code to be almost as expressive as the model, we further support model-code duality; the notion that both model and code are two faces for the same coin. Systems can be and should be equally-well specified textually and diagrammatically. Such duality will benefit both modelers and coders alike. Our work suggests that code enhanced with state machine modeling abstractions is semantically equivalent to visual state machine models. The flow of the thesis is as follows; the research hypothesis and questions are presented in “Chapter 1: Introduction”. The background is explored in “Chapter 2: Background”. “Chapter 3: Syntax and semantics of simple state machines” and “Chapter 4: Syntax and semantics of composite state machines” investigate simple and composite state machines in Umple, respectively. “Chapter 5: Implementation of composite state machines” presents the approach we adopt for the implementation of composite state machines that avoids explosion of the amount of generated code. From this point on, the thesis presents empirical work. A grounded theory study is presented in “Chapter 6: A Grounded theory study of Umple”, followed by a controlled experiment in “Chapter 7: Experimentation”. These two chapters constitute our validation and evaluation of Umple research. Related and future work is presented in “Chapter 8: Related work”.

Learning from data, especially ‘Big Data’, is becoming increasingly popular under names such as Data Mining, Data Science, Machine Learning, Statistical Learning and High Dimensional Data Analysis. In this dissertation we propose a new related field, which we call ‘United Nonparametric Data Science’ - applied statistics with “just in time” theory. It integrates the practice of traditional and novel statistical methods for nonparametric exploratory data modeling, and it is applicable to teaching introductory statistics courses that are closer to modern frontiers of scientific research. Our framework includes small data analysis (combining traditional and modern nonparametric statistical inference), big and high dimensional data analysis (by statistical modeling methods that extend our unified framework for small data analysis). The first part of the dissertation (Chapters 2 and 3) has been oriented by the goal of developing a new theoretical foundation to unify many cultures of statistical science and statistical learning methods using mid-distribution function, custom made orthonormal score function, comparison density, copula density, LP moments and comoments. It is also examined how this elegant theory yields solution to many important applied problems. In the second part (Chapter 4) we extend the traditional empirical likelihood (EL), a versatile tool for nonparametric inference, in the high dimensional context. We introduce a modified version of the EL method that is computationally simpler and applicable to a large class of “large p small n” problems, allowing p to grow faster than n. This is an important step in generalizing the EL in high dimensions beyond the p ≤ n threshold where the standard EL and its existing variants fail. We also present detailed theoretical study of the proposed method.

This dissertation addresses the topic of manufacturing network strategies, with a particular focus on the plant perspective. Research on manufacturing networks aims at contributing decision support on how to set up and how to coordinate factories that act in a global setting. Manufacturing networks are networks consisting of wholly owned plant, as opposed to supply chains management where also plants belonging to other organisations are considered. Research on the role of the plant in manufacturing networks can help to gain insights in how the network works and how to achieve network-related competitive advantages. Over the last two decades there has been a trend in increased globalisation and when companies expand beyond their home markets there is a leap in complexity that needs to be handled. A survey of Swedish plants shows that a large majority of medium and large sized plants are part in some kind of manufacturing network, making research on such networks highly relevant. The overall objective of this dissertation is to investigate how factories fit into the network in terms of roles, strategic autonomy and market configurations. Much research has either focused on networks as a whole, often assuming similar or identical plants, or the focus has been on plant internal decision. This research addresses the borderland between plant and network. This dissertation addresses two research objectives. The first is to investigate the relationship between networks and plants roles with particular focus on Swedish based networks and plants and the second is to test and further develop the theory on plant roles. The empirical data that was used in the dissertation was the product of a mail survey and a case study at a manufacturer of heat exchangers. The survey was sent to 563 Swedish factories and included information on competitive priorities, processes, plant roles, performance, suppliers, risk as well as general product and company information. Using focus groups, the case company was followed from the start of the project in January 2006. Following the case company during five years gave the opportunity to study networks in transformation. The research contributed to several insights to the area of plant roles and manufacturing networks as well as to practitioners in manufacturing. Internal and external suppliers are handled differently in terms of selection criteria, which indicates different roles in the network. Detailed exploration of individual site competences has lead to an improved model based on competence themes and links between the plant level and the network level have been established. Additionally we contribute to the manufacturing strategy process area by investigating and suggesting a model for strategic decision autonomy in manufacturing networks. The results are aimed at providing guidance for decision making in manufacturing networks as well as providing an improved foundation for further research in the area.