Thesis (Ph. D.)--University of Iowa, 2007. / Supervisor: Charles H. Whiteman. Includes bibliographical references (leaves 134-137).

Thesis (Ph. D.)--University of Oregon, 2006. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 152-158). Also available for download via the World Wide Web; free to University of Oregon users.

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Internet and network security forms an interesting and topical, yet challenging and developing research domain. In this domain, a taxonomy of information security technologies is identified. This taxonomy is divided into two mainline entities, namely proactive and reactive information security technologies. This thesis is specifically concerned with proactive information security technologies, the focus being on a specific proactive information security technology – vulnerability scanning. Vulnerability scanning is implemented by vulnerability scanner (VS) products. VS products are used proactively to conduct vulnerability scans to identify vulnerabilities so that they can be rectified before they can be exploited by hackers. However, there are currently many problems with state-of-the-art VS products. For example, a vulnerability scan is time-consuming and a vast number of system resources are occupied, leading to the degradation of network and system performance. Furthermore, VS products lack the intelligence that is required to deal with new vulnerabilities that appear like clockwork. Current VS products also differ extensively in the way that they can detect vulnerabilities, as well as in the number of vulnerabilities that they can detect. These problems motivated the researcher to create a model for vulnerability forecasting (VF). The uniqueness of the VF model lies in its holistic approach to addressing these problems while maintaining its end goal – that of being able to do a vulnerability forecast of how vulnerabilities will occur in the near future. Such a vulnerability forecast would, therefore, enable an organisation to use it proactively as part of a risk management scheme. Furthermore, in order to demonstrate the feasibility of implementing the proposed model, a report on the development of a prototype for vulnerability forecasting is included. Rather than reinventing the wheel, the prototype incorporates the use of current state-of-the-art VS products in its VF process. This is advantageous in the sense that the prototype is independent of a specific VS product. It is because of the latter that a standardisation technique had to be used to refer to vulnerabilities in the same way since different VS products do not refer to and detect similar vulnerabilities in the same way. This standardisation technique introduced in this thesis is known as harmonising vulnerability categories. This thesis contributes to the understanding of vulnerability scanning techniques and how vulnerability scanning can be utilised more effectively by doing vulnerability forecasting. The thesis also paves the way for numerous potential future research projects in the domain of Internet and network security. / Prof. J.H.P. Eloff

M.Tech / This study is an investigation into current local and international fashion forecasting approaches and procedures, as well as to discover whether intuition has relevance in the forecasting process. South African fashion is currently in the process of transformation; discovering and establishing a fashion identity, after decades of unquestioningly following international fashion trends (Chang, 2005:20; Cohen, 2005:27; Levin, 2005a: 75-78). The emergence of local fashion/trend forecasting practices in recent years is part of this transformation process. An underlying assumption of this study is that South African fashion will continue to develop, resulting in an increasing demand for fashion forecasting in the country. As there are currently no guidelines available, the study aims to provide insight into a way forward for this practice in South Africa. The study is grounded within a qualitative research paradigm, and the research design and data collection methods have accordingly been selected. The chosen research design falls largely within the framework of an ethnographic study. A comprehensive analysis of existing literature was conducted in order to provide a theoretical grounding to the study and to acquire a global perspective on forecasting procedures. This was followed by semi-structured interviews to obtain primary data from a South African perspective. The participants were purposely selected according to set criteria. The first criteria for selection required the participants to be leading role-players in their particular fields. Secondly, individuals who are trend forecasters by profession, as well as those who may use forecasting material in their businesses. Thirdly, the sample of participants represents specified sectors within the South African fashion/lifestyle industries. Namely, editors at leading trend magazines, in-house trend forecasters/analysts at leading fashion retailers, designers and independent trend analysts/forecasters. In order to construct the findings of the study qualitative content analysis was used as the method for data analysis. Through this process, the descriptions of the participants were interpreted to establish commonalities in practice, so as to identify viable threads of relevance regarding trend forecasting within a South African context. The research findings narrate the participants’ experiences within the field of trend/fashion forecasting, their knowledge frameworks being key to the study (Henning, van Rensburg & Smit, 2004:19). It is evident from the findings that the practice of fashion forecasting in South Africa is at an early stage of development and therefore at present, limited procedural IV structures seem to be in place. The findings further indicate that intuition indeed plays a significant role in the forecasting process, and is often associated with insightful trend/fashion forecasting. South African fashion, although facing several challenges, is perceived to have enormous potential for growth and to be a successful international marketing commodity in the future. In order for the practice of fashion forecasting to be successful in the country, though, it needs to be approached with insight and integrity, and with a true intention to add value.

With businesses operating in an environment of uncertainty, questions were raised around the role of rolling forecasts in this environment and how the current financial processes have changed as a result of the uncertainty. There are currently debates regarding the role of budgeting and other planning methods, one of which is rolling forecasts. One school of thought believes that budgets are no longer relevant in current times and should be replaced with newer methods, whereas the second school of thought believes that budgets are still current and relevant. Having experienced a global financial crisis, the current time can be described as one of uncertainty. Banks were one of the industries hardest hit by this crisis. This research investigates whether the financial planning processes in banks has changed to align itself with an environment of uncertainty. It further explores whether banks have adopted rolling forecasts in their planning processes. Data was collected using expert interviews. The sample included 8 respondents across 3 different banks. The data was then analysed using content analysis. The outcome allowed for visibility into the changes made by banks in their financial planning processes. Insights into the reasons why rolling forecasts were not used was also obtained. Uncertainty in the environment resulted in banks making changes to their financial planning processes. It also emerged that none of the respondents use rolling forecasts. However some of the respondents use forecasting models which are based on some principles of rolling forecast. This research contributes to the budgeting and planning discipline. It contributes by exploring how the budget process is changing to align itself with the changing environment. It also contributes by providing insights into why rolling forecasts are not adopted. / Dissertation (MBA)--University of Pretoria, 2010. / Gordon Institute of Business Science (GIBS) / unrestricted

Energy is of concern for governments and economies all over the world. As conventional methods of energy production are facing the prospect of depleting fossil fuel reserves, economies are facing energy risks. With this tension, various threats arise in terms of energy supply security. A shift from intensive fossil fuel consumption to alternative energy consumption combined with the calculated use of fossil fuels needs to be implemented. Using the energy radiated from the sun and converted to electricity through photovoltaic energy conversion is one of the alternative and renewable sources to address the limited fossil fuel dilemma. South Africa receives an abundance of sunlight irradiance, but limited knowledge of the implementation and possible energy yield of photovoltaic energy production in South Africa is available. Photovoltaic energy yield knowledge is vital in applications for farms, rural areas and remote transmitting devices where the construction of electricity grids are not cost effective. In this study various meteorological and energy parameters about photovoltaics were captured in Port Elizabeth (South Africa) and analyzed, with data being recorded every few seconds. A model for mean daily photovoltaic power output was developed and the relationships between the independent variables analyzed. A model was developed that can forecast mean daily photovoltaic power output using only temperature derived variables and time. The mean daily photovoltaic power model can then easily be used to forecast daily photovoltaic energy output using the number of sunlight seconds in a given day.

The research assesses the value of forecast information in operating a hydro-electric project with a storage reservoir. The benefits are the increased hydro power production, when forecasts are available. The value of short term forecasts is determined by comparing results obtained with the use of one month ahead perfect predictions to those obtained without forecasts but a knowledge of the statistics of the possible flows. The benefits with perfect forecasts provide an upper limit to the benefits which could be obtained with actual less than perfect forecasts. The effects of generating capacity and flow patterns are also discussed. The operation of a hypothetical but typical project is modelled using stochastic dynamic programming. A simple model of streamflow is formulated based on the historical statistics ( means and deviations). The conclusions are: The inflow forecasts can improve the operational efficiency of the reservoir considerably because of the reduction in forecasting uncertainty. The maximum release constraints affect the additional expected values. The benefits from the forecasts increase as the discharge limits reduce. Flow predictions in the high flow season are most valuable when the runoff in that time period dominates the annual flow pattern. However flow predictions at other times of the year also have value. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Expert computer programs have recently emerged from research on artificial intelligence as a practical problem-solving tool. An expert system is a knowledge-based program that imitates the problem-solving behaviour of a human expert to solve complex real-world problems. While conventional programs organize knowledge on two levels: data and program, most expert programs organize knowledge on three levels: data, knowledge base, and control. Thus, what distinguishes such a system from conventional programs is that in most expert systems the problem solving model is treated as a separate entity rather than appearing only implicitly as part of the coding of the program. The purpose of this thesis is twofold. First, it is intended to demonstrate how domain-specific problem-solving knowledge may be represented in computer memory by using the frame representation technique. Secondly, it is intended to simulate a typical flood estimation situation, from the point-of-view of an expert engineer. A frame network was developed to represent, in data structures, the declarative, procedural, and heuristic knowledge necessary for solving a typical flow estimation problem. The control strategy of this computer-based consultant (FLOOD ADVISOR) relies on the concept that reasoning is dominated by a recognition process which is used to compare new instances of a given phenomena to the stereotyped conceptual framework used in understanding that phenomena. The primary purpose of the FLOOD ADVISOR is to provide interactive advice about the flow estimation technique most suitable to one of five generalized real-world situations. These generalizations are based primarily on the type and quantity of the data and resources available to the engineer. They are used to demonstrate how problem solving knowledge may be used to interactively assist the engineer in making difficult decisions. The expertise represented in this prototype system is far from complete and the recommended solution procedures for each generalized case are in their infancy. However, modifications may be easily implemented as the domain-specific expert knowledge becomes available. It is concluded that over the long term, this type of approach for building problem-solving models of the real world are computationally cheaper and easier to develop and maintain than conventional computer programs. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Design flood estimates have traditionally been based on records of past events. However, there is a need for a method of estimating peak flows without these records. The Estimated Parameter Flood Forecasting Model (EPFFM) has been developed to provide such a method for small water resource projects based on a 200 year or less design flood. This "user friendly" computer model calculates the expected peak flow and its standard deviation from low, probable, and high estimates of thirteen user supplied parameters. These parameters describe physical characteristics of the drainage basin, infiltration rates, and rainstorm characteristics. The standard deviation provides a measure of reliability and is used to produce an 80% confidence interval on peak flows. The thesis briefly reviews existing flow estimation techniques and then describes the development of EPFFM. This includes descriptions of the Chicago method of rainfall hyetograph synthesis, Horton's infiltration equation, inflow by time-area method, Muskingum routing equation, and an approximate method of estimating the variance of multivariate equations since these are all used by EPFFM to model the physical and mathematical processes involved. Two examples are included to demonstrate EPFFM's ability to estimate a confidence interval, and compare these with recorded peak flows. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate