Thesis (M.Sc. (Geography)) -- University of Limpopo, 2020 / This work aimed at assessing the implications of involving local communities in biodiversity conservation in Blouberg Nature Reserve (BNR) in Limpopo Province, South Africa. To achieve this objective, firstly biodiversity status before and after involving local communities in conservation initiatives was assessed using multi-temporal medium-resolution Landsat series data and species diversity indices. The results showed that there were significant variations (α = 0.05) in tree species diversity in BNR for before and after involving local communities. For example, tree species diversity was low after involving communities particularly for the years 1996 and 2019. Secondly, benefits and costs of involving local communities in biodiversity conservation as well as their investigate views, perceptions and attitudes BNR management were assessed. The study demonstrated local communities do not obtain sufficient benefits or incur numerous costs from the nature reserve. Despite this, there was considerable support for biodiversity conservation (84.2%) since household respondents still held positive attitudes towards biodiversity conservation in the reserve. For, example most of them indicated that they would report illegal activities to the authorities. However, despite lack of participation by the majority of the household respondents (89.6%) in biodiversity conservation, they demonstrated understanding of the relevance of nature conservation. In contrary, the BNR Manager stated that the local communities received benefits in the form of fuel-wood for special occasions such as funerals and bush meat sold at treasury approved tariffs during culling. However, illegal activities like poaching are still experienced in the nature reserve. Thus, the study underscores the relevance the integrating satellite data and qualitative information in assessing the ecological condition of PAs. Such information can help in biodiversity monitoring and decision-making on conservation of biodiversity. Keywords: biodiversity conservation; community-based natural resource management approach; ecological status; mapping; satellite data; spatial characterisation; species diversity; statistical analysis.

The diploma thesis deals with the application of statistical methods in assessing selected indicators of the company ABC, Ltd. This work is divided into three parts. The first part explains the terms related to financial indicators, macroeconomic indicators, regression and correlation analysis and also, this part of the work explains the matters of time series. The second part contains an analysis of the current state. Individual analyses of indicators and their predictions are performed in it. Also, there is a research concerning the influence of macroeconomic indicators on the financial performance of ABC, Ltd. In The last part of this diploma thesis, changes are proposed that should lead to the improvement of the current situation of the company.

This master‘s thesis deals with the performance evaluation AGROMORAVIA, a.s. using of classic, modern and statistical methods and subsequent formulation of own designs and their benefits to improve company performance. Based on the analysis results are compared with a competitor. In addition, selected economic indicators are subjected to statistical analysis and the result is a prediction of future development, from which derives valuable information that serves the proposals for improving the current situation of the company in the coming years. Analyses are performed for the period 2006 to 2012.

Abstract Master’s thesis about „Assessing of the financial situation of a company using time series” focuses on a detailed assessment of the economic situation of the state-owned enterprise DIAMO between years 2005–2014. The theoretical part describes methods and indicators of strategic, financial and statistical analyses, which are in the next chapter sequentially applied on the analysed company. The content of the final chapter introduce proposals of elimination of the risk areas of the state-owned enterprise, while the greatest emphasis will be applied on the issue of rising shares of receivables and liabilities to total assets and ensuring positive economic result in corporate profit. The main object of this master’s thesis is assessing financial efficiency of state-owned enterprise DIAMO, afterward identifying risk areas and introducing possible precautions, which will lead to overall greater economic health of the enterprise itself.

The thesis is focused on testing of the cutting tools for machining on five axis machine tools and possibility of implementation of designed experiments in this area. The theoretical section focuses attention on analysis of specific features during five axis machining, including chip cross section and particularity of tool testing under high speed cutting conditions with consideration of dynamic stability of cutting tools. In the thesis force loading of the tool is discussed as well as its measurement process, considering force development caused by tool wear and data analysis. Description of designed experiment and its application to the area of tool testing is included as well. All theoretical predictions are followed by experimental verifying by extensive number of experimental tests, including evaluation of cutting tool condition, influence of hard coatings on cutting power of the tools, etc. For each of testing conditions are designed specific methods of processing of gathered data as well as evaluation of power of the cutting tools. Gathered data were processed by means of statistical evaluation and by statistical methods of designed experiments. The thesis contains also the extensive number of records and analysis, documented by means of light microscopy as well as electron microscopy.

Ces dernières années, la technologie RFID (identification par radiofréquence) s’est fortement développée dans de nombreuses applications industrielles parmi lesquelles les secteurs de l’aéronautique et l’automobile où il y a une forte demande en systèmes d’auto-identification fonctionnant dans des environnements difficiles. Dans ce contexte, l'objectif de ces travaux de thèse est d'étudier les effets du stockage thermique sur la fiabilité des tags RFID UHF passifs. Pour ce faire nous avons adopté une méthodologie homogène contribuant de façon significative à atteindre nos objectifs. La première étape de cette méthodologie consistait à choisir le tag à tester, deux types de tags Web et Tageos provenant de deux fabricants différents ont été soumis à des tests de vieillissement accélérés sous différentes températures. La deuxième étape était de définir les paramètres des tests de vieillissement et de caractériser les tags vieillis. À l'aide d'un banc de mesure dédié, la puissance réfléchie par l’ensemble des tags vieillis est mesurée après chaque phase de vieillissement en fonction de la distance entre l’antenne du tag et celle du lecteur RFID. La puissance réfléchie diminue considérablement après chaque phase de vieillissement avec différentes dynamiques de dégradation pour tous les tags vieillis. Cette dynamique de dégradation dépend du type de tag testé et de la température de test. La dernière étape de la méthodologie comportait l’analyse statistique et physique de défaillance, des différences claires dans les modes, les mécanismes et les temps de défaillance entre les tags Web et Tageos ont été observées. L’analyse physique de défaillance par microscopie optique et MEB a révélé des fissures dans les conducteurs métalliques de l'antenne pour une partie des tags vieillis, cependant pour l’autre partie des tags, aucune défaillance de l'antenne n'a été observée. Des déformations au niveau de la matrice polymère de l'ACP ont été révélées, ce qui a modifié l'adaptation d'impédance entre le RFIC et l'antenne. Des simulations en utilisant le logiciel de modélisation multi-physique COMSOL a été mise en place dans le but de reproduire les mécanismes de défaillances révélés expérimentalement soit au niveau de l’antenne ou de la RFIC. Ces travaux de thèse ont démontré l'importance d'étudier les effets du stockage en haute température sur la fiabilité des tags RFID passifs. Les défaillances sont apparues plus rapidement et les tests ont coûté considérablement moins onéreux par rapport aux autres types de tests de vieillissement accélérés. / Nowadays, RFID has strongly developed in many industrial applications, including the aeronautics and automotive sectors, where there is a strong demand for auto-identification systems operating in severe environments. In this context, the objective of this thesis is to study the effects of thermal storage on the reliability of passive UHF RFID tags. To achieve this, we adopted a consistent methodology. The first step of this methodology was to choose the tag under test. Two types of tags Web and Tageos from two different manufacturers are aged under high temperatures. The second step was to define the parameters of the aging tests and to characterize the aged tags. Using a dedicated measurement bench, the reflected power is measured after each aging phase for all tested tags to determine the power loss caused by the high temperature storage. Reflected power decrease significantly after each aging phase with different dynamics of degradation for all aged tags. This dynamics of degradation depends on the temperature test and the type of tag. The final step involved statistical and physical failure analysis. Clear differences about modes, mechanisms and failure times between Web and Tageos tags have been observed, it seems that Tageos tags are more reliable than Web tags. Failure analysis of the samples, using an optical microscope and SEM, has revealed, cracks in the antenna metallic conductors on a part of the aged tags. In another part of the tags, no failures in the antenna have been seen, but clear deformations at the polymer matrix of the ACP have been observed, thus changing the impedance matching between the RFIC and the antenna. Simulations using the COMSOL multiphysics software have been implemented in order to reproduce the experimental failure mechanisms. This thesis work has demonstrated the importance of studying the effects of high temperature storage on the reliability of passive RFID tags. Failures appeared faster and tests cost considerably less than other types of accelerated aging tests.

The number of experimentally resolved protein structures in the Protein Data Bank has been growing fast in the last 20 years, which motivates the develop- ment of many computational tools for protein-ligand binding sites prediction. Binding sites prediction from protein 3D structure has many important applica- tions; it is an essential step in the complex process of rational drug design, it helps to infer the side-effects of drugs, it provides insight into proteins biological functions and it is helpful in many other fields, such as protein-ligand docking and molecular dynamics. As far as we know, there has not been a study that would systematically investigate general properties of known ligand binding sites on a large scale. In this thesis, we examine these properties using existing experimen- tal and predicted residue-level annotations of protein sequence and structure. We present an automated pipeline for statistical analysis of these annotations, based on hypothesis testing and effect size estimation. It is implemented in Python and it is easily extensible by user-defined annotations. The usage is demonstrated on 33 existing annotations and 4 different datasets. The practical significance of the results is tested with P2Rank prediction method. We hope that the results as well as the pipeline...

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In the area of online analytical processing (OLAP), the concept of multidimensional databases is receiving much popularity. Thus, a couple of different multidimensional data models were proposed from the research as well as from the commercial product side, each emphasizing different perspectives. However, very little work has been done investigating guidelines for good schema design within such a multidimensional data model. Based on a logical reconstruction of multidimensional schema design, this paper proposes two multidimensional normal forms. These normal forms define modeling constraints for summary attributes describing the cells within a multidimensional data cube and constraints to model complex dimensional structures appropriately. Multidimensional schemas compliant to these normal forms do not only ensure the validity of analytical computations on the multidimensional database, but also favor an efficient physical database design.

The purpose of this master thesis is to develop a model to estimate the carbon intensity, i.e the carbon emission relative to economic activity, of publicly traded companies which do not report their carbon emissions. By using statistical and machine learning models, the core of this thesis is to develop and compare different methods and models with regard to accuracy, robustness, and explanatory value when estimating carbon intensity. Both discrete variables, such as the region and sector the company is operating in, and continuous variables, such as revenue and capital expenditures, are used in the estimation. Six methods were compared, two statistically derived and four machine learning methods. The thesis consists of three parts: data preparation, model implementation, and model comparison. The comparison indicates that boosted decision tree is both the most accurate and robust model. Lastly, the strengths and weaknesses of the methodology is discussed, as well as the suitability and legitimacy of the boosted decision tree when estimating carbon intensity. / Syftet med denna masteruppsats är att utveckla en modell som uppskattar koldioxidsintensiteten, det vill säga koldioxidutsläppen i förhållande till ekonomisk aktivitet, hos publika bolag som inte rapporterar sina koldioxidutsläpp. Med hjälp av statistiska och maskininlärningsmodeller kommer stommen i uppsatsen vara att utveckla och jämföra olika metoder och modeller utifrån träffsäkerhet, robusthet och förklaringsvärde vid uppskattning av koldioxidintensitet. Både diskreta och kontinuerliga variabler används vid uppskattningen, till exempel region och sektor som företaget är verksam i, samt omsättning och kapitalinvesteringar. Sex stycken metoder jämfördes, två statistiskt härledda och fyra maskininlärningsmetoder. Arbetet består av tre delar; förberedelse av data, modellutveckling och modelljämförelse, där jämförelsen indikerar att boosted decision tree är den modell som är både mest träffsäker och robust. Slutligen diskuteras styrkor och svagheter med metodiken, samt lämpligheten och tillförlitligheten med att använda ett boosted decision tree för att uppskatta koldioxidintensitet.