This diploma thesis has two aims. The first one is exploration of "Grid/Group Theory" as it was presented by its author Mary Douglas in "Cultural Bias" (1978). According to this theory the thinking in the idiom of witchcraft is a product of an perception of specific social structure by an individual. The crux of this thesis should be comparation of social structure of few African societies with their cosmologies according to the empirical materials. It should proof the validation of the theory and also show some dificulties which the student must face during the application. The second aim is description of witchcraft and sorcery phenomenon and attempt to determine its essence or function for society.

Approved for public release; distribution in unlimited. / The Army is undergoing a major realignment in accordance with the Joint Vision 2010/2020 transformation to establish an enterprise command that is the single authority to operate and manage the Army Enterprise Information Infrastructure (Infrastructure). However, there are a number of critical network management issues that the Army will have to overcome before attaining the full capabilities to manage the full spectrum of Army networks at the enterprise level. The Army network environment consists of an excessive number of heterogeneous applications, systems, and network architectures that are incompatible. There are a number of legacy systems and proprietary platforms. Most of the NM architectures in the Army are based on traditional centralized NM approaches such as the Simple Network Management Protocol (SNMP). Although SNMP is the most pervasive protocol, it lacks the scalability, reliability, flexibility and adaptability necessary to effectively support an enterprise network as large and complex as the Army. Attempting to scale these technologies to this magnitude can be extremely difficult and very costly. This thesis makes the argument that intelligent-agent-based technologies are a leading solution, among the other current technologies, to achieve the Army's enterprise network management goals. / Major, United States Army

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Scoglio / The science of complex networks has significantly advanced in the last decade and has provided valuable insights into the properties of real world systems by evaluating their structure and construction. Several phenomena occurring in real technological and social systems can be studied, evaluated, quantified, and remedied with the help of network science. The electric power grid is one such real technological system that can be studied through the science of complex networks. The electric grid consists of three basic sub-systems: Generation, Transmission, and Distribution. The transmission sub-system is of particular interest in this work because its mesh-like structure offers challenging problems to complex networks researchers. Cascading dynamics of power grids is one of the problems that can be studied through complex networks. The North American Electric Reliability Corporation (NERC) defines a cascading failure as the uncontrolled successive loss of system elements triggered by an incident at any location. In this dissertation, we primarily discuss the dynamics of cascading failures in the power transmission grid, from a complex networks perspective, and propose possible solutions for mitigating their effects. We evaluate the grid dynamics for two specific scenarios, load growth and random fluctuations in the grid, to study the behavior of the grid under critical conditions. Further, we propose three mitigation strategies for reducing the damage caused by cascading failures. The first strategy is intentional islanding in the power transmission grid. The aim of this method is to intentionally split the grid into two or more separate self- sustaining components such that the initial failure is isolated and the separated components can function independently, with minimum load shedding. The second mitigation strategy involves controlled placement of distributed generation (DG) in the transmission system in order to enhance robustness of the grid. The third strategy requires the addition of a link in the transmission grid by reduction of the average spectral distance, utilizing the Ybus matrix of the grid and a novel algorithm. Through this dissertation, we aim to successfully cover the gap present in the complex networks domain, with respect to the vulnerability analysis of power grid networks.

Doctor of Philosophy / Department of Geography / Douglas G. Goodin / Jesse A. Poland / Kevin Price / Wheat breeders are in a race for genetic gain to secure the future nutritional needs of a growing population. Multiple barriers exist in the acceleration of crop improvement. Emerging technologies are reducing these obstacles. Advances in genotyping technologies have significantly decreased the cost of characterizing the genetic make-up of candidate breeding lines. However, this is just part of the equation. Field-based phenotyping informs a breeder’s decision as to which lines move forward in the breeding cycle. This has long been the most expensive and time-consuming, though most critical, aspect of breeding. The grand challenge remains in connecting genetic variants to observed phenotypes followed by predicting phenotypes based on the genetic composition of lines or cultivars. In this context, the current study was undertaken to investigate the utility of UAS in assessment field trials in wheat breeding programs. The major objective was to integrate remotely sensed data with geospatial analysis for high throughput phenotyping of large wheat breeding nurseries. The initial step was to develop and validate a semi-automated high-throughput phenotyping pipeline using a low-cost UAS and NIR camera, image processing, and radiometric calibration to build orthomosaic imagery and 3D models. The relationship between plot-level data (vegetation indices and height) extracted from UAS imagery and manual measurements were examined and found to have a high correlation. Data derived from UAS imagery performed as well as manual measurements while exponentially increasing the amount of data available. The high-resolution, high-temporal HTP data extracted from this pipeline offered the opportunity to develop a within season grain yield prediction model. Due to the variety in genotypes and environmental conditions, breeding trials are inherently spatial in nature and vary non-randomly across the field. This makes geographically weighted regression models a good choice as a geospatial prediction model. Finally, with the addition of georeferenced and spatial data integral in HTP and imagery, we were able to reduce the environmental effect from the data and increase the accuracy of UAS plot-level data. The models developed through this research, when combined with genotyping technologies, increase the volume, accuracy, and reliability of phenotypic data to better inform breeder selections. This increased accuracy with evaluating and predicting grain yield will help breeders to rapidly identify and advance the most promising candidate wheat varieties.

The need for a robust system architecture to support software development is well known. In enterprise software development, this must be realized in a multi-tier environment for deployment to a software framework. Many popular integrated development environment (IDE) tools for component-based frameworks push multi-tier partitioning by assisting developers with convenient code generation tools and software deployment tools which package the code. However, if components are not packaged wisely, modifying and adding components becomes difficult and expensive. To help manage change, vertical partitioning can be applied to compartmentalize components according to function and role, resulting in a grid partitioning. This thesis is to advocate a design methodology that enforces vertical partitioning on top of the horizontal multitier partitioning, and to provide guidelines that document the grid partitioning realization in enterprise software development processes as applied in the J2EE framework.

We have developed a new approach to annotate the uncertainty information of geospatial data. This framework is composed of a geospatial platform and the data with uncertainty. The framework supports geospatial sources such as Geography Markup Language (GML) with uncertainty information. The purpose of this framework is to integrate the uncertainty information of data from the application users and thereby ease the development of processing uncertainty information of geospatial data. Having well organized data and using this framework, the end-users can store the uncertainty information on the current geospatial data structure. For example, a GIS user can share the error information for environmental and geospatial data to others. We have also reported the enhanced geographic information system function.

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository. In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using JMX, we implemented a package that attempts to assist programming for AC features including socket management, logging, and recovery of distributed computation. In the experiments, we have not only realized the powerful Java capabilities that are unknown to many educators, we also illustrated the feasibility of learning AC in senior computer science courses.

Eruptive events on the Sun have an impact on immediate cosmic surround- ings of the Earth. Through induction of electric current also affect Earthbound structures such as the electric power distribution networks. Inspired by recent studies we investigate the correlation between the disturbances recorded by the Czech electric-power distributors with the geomagnetic activity represented by the K index. We found that in the case of the datasets recording the disturbances on the power lines with the high and very high voltage levels and disturbances on elec- trical substations, there was a statistically significant increase of failure rates in the periods of maxima of geomagnetic activity compared to the adjacent minima of activity. There are hints that the disturbances are more pronounced shortly after the maxima than shortly before the maxima of activity. Our results provide hints that the geomagnetically induced currents may af- fect the power-grid equipment even in the mid-latitude country in the middle of Europe. A follow-up study that includes the modelling of geomagnetically induced currents is needed to confirm our findings. The second part of our research includes modelling of geoelectric field using one-minute geomagnetic measurements from Intermagnet database. We applied this model to the long-term...

All financial institutions that provide options to counterparties will in most cases get involved withMonte Carlo simulations. Options with a payoff function that depends on asset’s value at differenttime points over its lifespan are so called path dependent options. This path dependency impli-cates that there exists no parametric solution and the price must hence be estimated, it is hereMonte Carlo methods come into the picture. The problem though with this fundamental optionpricing method is the computational time. Prices fluctuate continuously on the open market withrespect to different risk factors and since it’s impossible to re-evaluate the option for all shifts dueto its computing intensive nature, estimations of the option price must be used. Estimating theprice from known points will of course never produce the same result as a full re-evaluation but anestimation method that produces reliable results and greatly reduces computing time is desirable.This thesis will evaluate different approaches and try to minimize the estimation error with respectto a certain number of risk factors.This is the background for our master thesis at Swedbank. The goal is to create multiple estima-tion methods and compare them to Swedbank’s current estimation model. By doing this we couldpotentially provide Swedbank with improvement ideas regarding some of its option products andrisk measurements. This thesis is primarily based on two estimation methods that estimate optionprices with respect to two variable risk factors, the value of the underlying assets and volatility.The first method is a grid that uses a second order Taylor expansion and the sensitivities delta,gamma and vega. The other method uses a grid of pre-simulated option prices for different shiftsin risk factors. The interpolation technique that is used in this method is calledPiecewise CubicHermiteinterpolation. The methods (or referred to as approaches in the report) are implementedto handle a relative change of 50 percent in the underlying asset’s index value, which is the firstrisk factor. Concerning the second risk factor, volatility, both methods estimate prices for a 50percent relative downward change and an upward change of 400 percent from the initial volatility.Should there emerge even more extreme market conditions both methods use linear extrapolationto estimate a new option price.

Stand-alone or micro off-grid systems can be used to electrify remote areas when it is not economically justifiable to connect to the power grid. In Sweden there are several flood gates that are used to regulate the water level in hydropower dams, these dams are not always easily accessible. Furthermore, some flood gates are not electrified making the adjustment of the water level complicated and time consuming. An off-grid solution could be used to electrify the water level adjustment and this report aims to identify one remote dam, owned by the company VB Kraft, that could be electrified by implementing an off-grid solution. The report will also investigate which off-grid solution that is most applicable concerning maintenance demand, technical and economic aspects. Sensors for monitoring the status of the dam will also be identified which are required to preserve dam security. The chosen off-grid solution will be simulated on a yearly basis and the most appropriate size of the components will be specified. The report has been conducted by collecting material from the company, a literature study and by interviews and email conversations. Calculations have been performed by using MATLAB and Excel. The data is based on measurements from the Swedish Meteorological and Hydrological Institute. The result revealed that Lilla Ursen, a remote dam in Dalarnas county, is maneuvered often and therefore this study will investigate electrification of this dam. Out of the four alternatives (small wind, hydro and hydrokinetic power and PV), PV was considered the most suitable in an off-grid system combined with a lead-acid battery. Sensors considered important for dam security are water level and flow monitoring, position indicator for the flood gate, camera monitoring and a temperature sensor. It also important with a logger and transmitter. The battery is protected with a charge controller. A series of sensitivity analysis have been conducted and the result showed a large variation concerning the battery capacity and the modules area and peak power. For Lilla Ursen it is recommended with a PV module of 30 Wp and a lead-acid battery with a capacity of 280 Ah.