<p>This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices.</p>

<p>Diss. (sammanfattning) Umeå : Umeå universitet, 1990, härtill 5 uppsatser.</p> / digitalisering@umu.se

We eat foods not nutrients. What is more, we eat them in combinations. Consequently, capturing our complex food habits is likely an advantage in nutrition research. The overall aim of this doctoral thesis was therefore to investigate dietary patterns in the Swedish population –nutrient intakes, nutritional biomarkers and health aspects. Prostate cancer is the most common cancer among men in the developed world. However, the impact of dietary factors on disease risk is largely unknown. In Study I we investigated the association between a Mediterranean- and a Low-carbohydrate-high-protein dietary pattern and prostate cancer risk, in a cohort of elderly Swedish men. The latter (but not the former) was associated, inversely, with prostate cancer risk when taking validity in food records into account. Diet is one of our main exposure routes to environmental contaminants. Hence, such exposure could act as a mediating factor in the relation between diet and health. In Study II we investigated the association between; a Mediterranean- and a Low-carbohydrate-high-protein dietary pattern, as well as the official dietary recommendations, and circulating levels of environmental contaminants, in an elderly Swedish population. The first two patterns were positively related to levels of both persistent organic pollutants and heavy metals, whilst the dietary recommendations were inversely associated to dioxin and lead. Finally, although dietary patterns are likely to influence health, little is known about current dietary patterns in Sweden. In Study III we used a data-reduction method to identify dietary patterns in a nationwide sample of the Swedish population. Two major patterns were derived; a Healthy pattern of foods generally considered healthy (e.g. vegetables, fruits, fish and vegetable-oils) and a Swedish traditional pattern (with e.g. meats, potatoes, sauces, non-Keyhole milk-products, sweet-bakery products and margarine). Derived patterns were associated to population characteristics and the Healthy dietary pattern was inversely associated to anthropometric variables in Study IV. Dietary characteristics of the patterns were well reflected in correlations to nutrient intake and (to a lesser extent) in nutritional biomarkers. In conclusion dietary patterns for overall health should be considered, as well as other lifestyle-factors, when interpreting results in nutrition epidemiology and establishing dietary recommendations.

The impact of spatial characteristics on the dynamics of urban development is a topic of great interest in urban studies. The interaction between the residents and the spatial characteristics is of particular interest in the context of urban models where some of the most famous urban models have been based on the process of individual settlements in some specific parts of cities.This research investigates the dynamism of urban development modeled by Cellular Automata and Multi-Agent System. The urban development, in this study embraces urban renewal and residential mobility. It corresponds to the residential mobility of households, attracted by residential and centrality comfort; these comforts are crystallized in some areas and residences of Strasbourg. The diversity and quality of these comforts become criteria for residential choice in a way that the households seek for proximity to these comforts.The Cellular Automata in this study, models the spatial characteristics of urban spatial units and they are identified by some inherent attributes that are equal to the comfort in residences and urban areas. The Multi- Agent System represent a system in which the population of the city interact between them and between them and the city; the agents delegate the socio-professional classes of households. During the spatiotemporal change, the aspiration of households forms the socio-spatio-temporal development of the city.

The budding yeast Saccharomyces cerevisiae has been an invaluable model organism in contributing to the current understanding of cellular biology, owing mainly to its highly tractable genetic system and the completion of its genome sequencing in 1996. Indeed, these bolstered the development of novel methods that have provided great insights into genetic and protein networks in human cells. With the large collection of datasets, S. cerevisiae also became an ideal platform for investigating the mechanism of action of novel compounds. The first part of my thesis uses a validated chemogenomic assay to investigate the mechanism of action of structurally related novel DNA-damaging agents, delineating valuable structure-activity relationship in the process. The second part describes the development of a method that uses drug-induced wild-type growth dynamic to characterize novel compounds, which, in combination with the chemogenomic assay, may complement existing high throughput screening experiments to improve the current drug development process.

Fluoride in drinking water can lead to a crippling disease called fluorosis. As there is no cure for fluorosis, prevention is the only means of controlling the disease and research into fluoride remediation is critical. This work begins by providing a new approach to assessing fluoride remediation strategies using a combination of groundwater chemistry, saturation indices, and multivariate statistics based on the results of a large groundwater survey performed in a fluoride-contaminated region of India. From the Indian groundwater study, it was noted that one technique recommended for defluoridation involved using hydrous ferric oxide (HFO) as a solid phase sorbent for fluoride. This prompted investigation of bacteriogenic iron oxides (BIOS), a biogenic form of HFO, as a means of approaching bioremediation of fluoride. Batch sorption experiments at ionic strengths ranging from 0.001 to 0.1 M KNO3 and time course kinetic studies with BIOS and synthetic HFO were conducted to ascertain total sorption capacities (ST), sorption constants (Ks), and orders of reaction (n), as well as forward (kf) and reverse (kr) rate constants. Microcosm titration experiments were also conducted with BIOS and HFO in natural spring water from a groundwater discharge zone to evaluate fluoride sorption under field conditions. This thesis contributes significant, new information regarding the interaction between fluoride and BIOS, advancing knowledge of fluoride remediation and covering new ground in the uncharted field of fluoride bioremediation.

The budding yeast Saccharomyces cerevisiae has been an invaluable model organism in contributing to the current understanding of cellular biology, owing mainly to its highly tractable genetic system and the completion of its genome sequencing in 1996. Indeed, these bolstered the development of novel methods that have provided great insights into genetic and protein networks in human cells. With the large collection of datasets, S. cerevisiae also became an ideal platform for investigating the mechanism of action of novel compounds. The first part of my thesis uses a validated chemogenomic assay to investigate the mechanism of action of structurally related novel DNA-damaging agents, delineating valuable structure-activity relationship in the process. The second part describes the development of a method that uses drug-induced wild-type growth dynamic to characterize novel compounds, which, in combination with the chemogenomic assay, may complement existing high throughput screening experiments to improve the current drug development process.

Robust, non-intrusive human eye detection problem has been a fundamental and challenging problem for computer vision area. Not only it is a problem of its own, it can be used to ease the problem of finding the locations of other facial features for recognition tasks and human-computer interaction purposes as well. Many previous works have the capability of determining the locations of the human eyes but the main task in this thesis is not only a vision system with eye detection capability / Our aim is to design a real-time, robust, scale-invariant eye tracker system with human eye movement indication property using the movements of eye pupil. Our eye tracker algorithm is implemented using the Continuously Adaptive Mean Shift (CAMSHIFT) algorithm proposed by Bradski and the EigenFace method proposed by Turk &amp / Pentland. Previous works for scale invariant object detection using Eigenface method are mostly dependent on limited number of user predefined scales which causes speed problems / so in order to avoid this problem an adaptive eigenface method using the information extracted from CAMSHIFT algorithm is implemented to have a fast and scale invariant eye tracking. First of all / human face in the input image captured by the camera is detected using the CAMSHIFT algorithm which tracks the outline of an irregular shaped object that may change size and shape during the tracking process based on the color of the object. Face area is passed through a number of preprocessing steps such as color space conversion and thresholding to obtain better results during the eye search process. After these preprocessing steps, search areas for left and right eyes are determined using the geometrical properties of the human face and in order to locate each eye indivually the training images are resized by the width information supplied by the CAMSHIFT algortihm. Search regions for left and right eyes are individually passed to the eye detection algortihm to determine the exact locations of each eye. After the detection of eyes, eye areas are individually passed to the pupil detection and eye area detection algorithms which are based on the Active Contours method to indicate the pupil and eye area. Finally, by comparing the geometrical locations of pupil with the eye area, human gaze information is extracted. As a result of this thesis a software named &ldquo / TrackEye&rdquo / with an user interface having indicators for the location of eye areas and pupils, various output screens for human computer interaction and controls for allowing to test the effects of color space conversions and thresholding types during object tracking has been built.

由績效觀點，品質(適質)與成本(適量)，在概念上是完全一致的。因此，績效的管理，應以品質與成本作為其目標達成與否的衡量標準。本研究以績效觀點來解決公司面臨到品質與成本的兩難的問題。隨著電子產品的功能多樣化，發熱問題卻接踵而來，發熱密度的不斷提昇，對於散熱設計的需求也越來越受到重視。本研究以電源轉換器為對象，其目前已設計完成且已通過美國UL安規認證，但因為其溫升及其變異很大，因此降低電源轉換器的溫升及其變異是一急需解決的問題，以期能找出穩健於不可控因子，使產品變異小且各零件溫升與損失均能降至最低的最適外部零件組合。透過了田口與實驗設計的方法規劃及進行實驗並收集數據。引用加權SN比(multi-response S/N ratio)的方法，分別透過(1)管制圖法及(2)資料包絡法的CCR保證領域法(指CCR-AR模型)來決定加權SN比的權數，以決定可控因子及其水準值。對矩陣實驗的數據利用MTS ( M a h a l o n o b I s － Taguchi System)來篩選研究問題中較重要的特性變數，再針對篩選結果中較重要的特性變數的數據分別利用(1)倒傳遞類神經網路結合資料包絡法及(2)資料包絡法結合主成份分析法兩種分析方法，得到外殼鑽孔形狀與矽膠片大小的最佳因子組合。由改善後的確認實驗結果得知，雖然平均溫升下降的程度不大，然而大部份量測點的溫升標準差都顯著變小了，因此本研究在降低該電源轉換器溫升變異的效果顯著。

Performance engineers face the major challenge in modeling and simulation for the after-market power system due to system degradation and measurement errors. Currently, the majority in power generation industries utilizes the deterministic data matching method to calibrate the model and cascade system degradation, which causes significant calibration uncertainty and also the risk of providing performance guarantees. In this research work, a maximum-likelihood based simultaneous data reconciliation and model calibration (SDRMC) is used for power system modeling and simulation. By replacing the current deterministic data matching with SDRMC one can reduce the calibration uncertainty and mitigate the error propagation to the performance simulation. A modeling and simulation environment for a complex power system with certain degradation has been developed. In this environment multiple data sets are imported when carrying out simultaneous data reconciliation and model calibration. Calibration uncertainties are estimated through error analyses and populated to performance simulation by using principle of error propagation. System degradation is then quantified by performance comparison between the calibrated model and its expected new & clean status. To mitigate smearing effects caused by gross errors, gross error detection (GED) is carried out in two stages. The first stage is a screening stage, in which serious gross errors are eliminated in advance. The GED techniques used in the screening stage are based on multivariate data analysis (MDA), including multivariate data visualization and principle component analysis (PCA). Subtle gross errors are treated at the second stage, in which the serial bias compensation or robust M-estimator is engaged. To achieve a better efficiency in the combined scheme of the least squares based data reconciliation and the GED technique based on hypotheses testing, the Levenberg-Marquardt (LM) algorithm is utilized as the optimizer. To reduce the computation time and stabilize the problem solving for a complex power system such as a combined cycle power plant, meta-modeling using the response surface equation (RSE) and system/process decomposition are incorporated with the simultaneous scheme of SDRMC. The goal of this research work is to reduce the calibration uncertainties and, thus, the risks of providing performance guarantees arisen from uncertainties in performance simulation.