Using data from temporary and permanent sample plots various functions describing different stand parameter relationships were developed for P. patula growing at Sao Hill, Southern Tanzania. The functions include equations for: a Weibull diameter distribution, a single tree diameter increment, stand basal area, mortality, and height/diameter relationship. Also site index curves based on a Chapman-Richards equation were constructed, and a compatible taper/volume estimation system was developed. The functions were integrated into a micro-computer model SIMUL in BASIC language. The model is capable of estimating saw-log and pulp-log volumes for different spacings and thinning regimes. Inputs to the model are: initial and simulation ages, stocking/ha, stand mean and standard deviation of diameter at breast height (dbh), basal area/ha, site, dominant height, and minimum diameters and lengths of saw-logs and pulplogs. The output gives yearly values/ha for; stocking, total volume, total basal area/ha, means for dbh, height and tree volume, mortality number and volume/ha, and volumes of saw-logs and pulplogs as out-turn from subsequent thinnings and the final clearfelling. Validation with independent data showed that the model works satisfactorily. Experimental runs at different levels of spacing and thinning regimes suggested that the current thinning schedule at Sao Hill is too heavy and results in loss in total volume. The highest utilizable volumes (mainly saw logs) may be obtained by using the current spacing of 2.7 x 2.7m followed by one thinning at the age of about 11 years to leave about 1100 stems/ha, with a rotation age of 25 years. This treatment is also justified economically giving the highest present value at an interest rate of 3%. The current rotation age 15 years (unthinned) for the production of pulp wood only is ideal to produce the required dimensions (10-20 cm diameter) of pulp logs. SIMUL is recommended for use at Sao Hill and the technique may be adopted for other plantation species in Tanzania with new parameter estimates for the equations.

Title: GIMPLE Model Checker Author: Ondrej Krč-Jediný Department: Department of Distributed and Dependable Systems Supervisor: RNDr. Ondřej Šerý Ph.D. Supervisor's e-mail address: Ondrej.Sery@mff.cuni.cz The goal of the thesis is a prototype implementation of explicit-state model checker of C - an advanced tool for finding errors in programs. This tool ex- plores all possible paths of program execution as well as all thread interleavings. It is based on GIMPLE - output of front-end of GCC compiler, which is the input language for GMC. The thesis is based on the previous work 'Memory represen- tation for GIMPLE Model Checker', that implements work with memory for this tool. Since it is based on GIMPLE, it makes it possible to verify systems directly in C. In addition, it is easily extensible to other languages supported by GCC. Keywords: model checking, GIMPLE, GCC, C 1

This thesis is concerned with developing methodologies that enable existing models to be effectively reused. Results of this thesis are presented in the framework of Quantitative Structural-Activity Relationship (QSAR) models, but their application is much more general. QSAR models relate chemical structures with their biological, chemical or environmental activity. There are many applications that offer an environment to build and store predictive models. Unfortunately, they do not provide advanced functionalities that allow for efficient model selection and for interpretation of model predictions for new data. This thesis aims to address these issues and proposes methodologies for dealing with three research problems: model governance (management), model identification (selection), and interpretation of model predictions. The combination of these methodologies can be employed to build more efficient systems for model reuse in QSAR modelling and other areas. The first part of this study investigates toxicity data and model formats and reviews some of the existing toxicity systems in the context of model development and reuse. Based on the findings of this review and the principles of data governance, a novel concept of model governance is defined. Model governance comprises model representation and model governance processes. These processes are designed and presented in the context of model management. As an application, minimum information requirements and an XML representation for QSAR models are proposed. Once a collection of validated, accepted and well annotated models is available within a model governance framework, they can be applied for new data. It may happen that there is more than one model available for the same endpoint. Which one to chose? The second part of this thesis proposes a theoretical framework and algorithms that enable automated identification of the most reliable model for new data from the collection of existing models. The main idea is based on partitioning of the search space into groups and assigning a single model to each group. The construction of this partitioning is difficult because it is a bi-criteria problem. The main contribution in this part is the application of Pareto points for the search space partition. The proposed methodology is applied to three endpoints in chemoinformatics and predictive toxicology. After having identified a model for the new data, we would like to know how the model obtained its prediction and how trustworthy it is. An interpretation of model predictions is straightforward for linear models thanks to the availability of model parameters and their statistical significance. For non linear models this information can be hidden inside the model structure. This thesis proposes an approach for interpretation of a random forest classification model. This approach allows for the determination of the influence (called feature contribution) of each variable on the model prediction for an individual data. In this part, there are three methods proposed that allow analysis of feature contributions. Such analysis might lead to the discovery of new patterns that represent a standard behaviour of the model and allow additional assessment of the model reliability for new data. The application of these methods to two standard benchmark datasets from the UCI machine learning repository shows a great potential of this methodology. The algorithm for calculating feature contributions has been implemented and is available as an R package called rfFC.

One of the most common pairs of co-occurring psychological disorders in children and adolescents is anxiety and depression. This high frequency of co-occurrence has led to research examining the structure of anxiety and depression, specifically the shared and unique aspects of these syndromes. The tripartite model accounts for the overlap between the disorders by suggesting that they are related because they share the feature of negative affect or general psychological distress. The model further proposes that they can be differentiated by their unique features of physiological hyperarousal (anxiety) and low positive affect (depression). Factor analytic research has shown that anxious symptoms and depressive symptoms can be structurally distinguished and research on the tripartite model has suggested their conceptual distinction. However, research has not shown that anxiety and depression cluster as distinct symptoms in samples of youth. The current study used cluster analysis to examine the grouping of individuals based on their levels of anxiety and depression. It was hypothesized that four groups would emerge-- anxiety only, depression only, comorbid anxiety and depression, and low/no symptoms. Further analyses using the tripartite model variables provided support of the accurate classification of individuals and this model was shown to be a useful tool in differentiating anxious symptoms from depressive symptoms. Exploratory analyses regarding developmental differences in the structure of anxiety and depression provided mixed support.

Abstract A modified thermal spike model initially proposed to account for defect formation in metals within the high heavy ion energy regime is adapted for describing the sputtering of Bi thin films under MeV Kr ions. Surface temperature profiles for both the electronic and atomic subsystems have been carefully evaluated versus the radial distance and time with introducing appropriate values of the Bi target electronic stopping power for multi-charged Kr15+ heavy ions as well as different target physical proprieties like specific heats and thermal conductivities. Then, the total sputtering yields of the irradiated Bi thin films have been determined from a spatiotemporal integration of the local atomic evaporation rate. Besides, an expected non negligible contribution of elastic nuclear collisions to the Bi target sputtering yields and ion-induced surface effects has also been considered in our calculation. Finally, the latter thermal spike model allowed us to derive numerical sputtering yields in satisfactorily agreement with existing experimental data both over the low and high heavy ion energy regions, respectively, dominated by elastic nuclear collisions and inelastic electronic collisions, in particular with our data taken recently for Bi thin films irradiated by 27.5 MeV Kr15+ heavy ions. An overall consistency of our model calculation with the predictions of sputtering yield theoretical models within the target nuclear stopping power regime was also pointed out.

Nowadays, managing business performance is becoming a relatively difficult and complex process for managers since it is undertaking major change both in research and practice. With the growing global interest in Business intelligence (BI), it has also been identified as an important role for small and medium-sized enterprises (SMEs) to satisfy their customer’s needs by analyzing through BI system. However, the limited financial resource and lack of human capital are becoming the constraint for SMEs to invest in Business Intelligence system; as well the return of their investment in BI system is still being considerable for SMEs to invest in the system. This study proposes an innovative approach for assessing and prioritizing the use of BI, which can help SME owners to prioritize their customer’s needs and communicate with their stakeholder by using Kano model. This paper is prepared in a way to define and convey the idea of Kano Model and its application to aspiring organizations.

This diploma thesis deals with the question of simulation models. It is divided into the theoretical and practical part. The aim of the opening part, in which the fundamental theory is defined, is to familiarize the readers with the ideas and advantages which simulation models can offer. In its practical part the work already focuses on the particular simulation project which should point out the possibilities of utilization of these models in practice. The subject of this project is the simulation of the course of the cultural event in the O2 Arena stadium. The main goal of this project is creation of the authentic simulation model which would on the basis of the later analysis enable the elimination or optimalization of the predefined major problems that are connected with organizing big cultural events in this arena.

This project has three parts. The first part is to use the efficient frontier and find the tangency portfolio to form our optimal portfolio. We built our portfolio using the Interactive Brokers software and rebalanced every week for 4 holding periods to see the relationship between our projected returns and actual market returns. In the second part we considered the Capital Asset Pricing Model (CAPM) and ran linear regressions on the stocks we chose in the first part of the project. This process is based on our idea of finding the systematic risk in each stock to improve our stock choosing ability. In the last part we introduce the concept of factor models and add more factors into our original CAPM model. Via a back-testing method, we test the reasonability of our factors and give advice to further improve our portfolio optimization project.

Faculty of Science; School of Computational and Applied Maths; MSC Thesis / The assumption of constant volatility as an input parameter into the Black-Scholes option pricing formula is deemed primitive and highly erroneous when one considers the terminal distribution of the log-returns of the underlying process. To account for the `fat tails' of the distribution, we consider both local and stochastic volatility option pricing models. Each class of models, the former being a special case of the latter, gives rise to a parametrization of the skew, which may or may not re°ect the correct dynamics of the skew. We investigate a select few from each class and derive the results presented in the corresponding papers. We select one from each class, namely the implied trinomial tree (Derman, Kani & Chriss 1996) and the SABR model (Hagan, Kumar, Lesniewski & Woodward 2002), and calibrate to the implied skew for SAFEX futures. We also obtain prices for both vanilla and exotic equity index options and compare the two approaches.

The aim of this study is to identify teachers’ professional opinion of SchoolSoft, a learning platform that is used in all public schools on Gotland, Sweden. Qualitative group interviews with a total of twelve teachers, together with the results of a questionnaire that the participating teachers filled in provided the data for this study. The participating teachers all worked in Swedish grundskolan(compulsory primary- and lower secondary school). The teachers’ opinions of Schoolsoft were identified by subjecting the data to a content analysis.    The results of this study show that the teachers who participated in the study used only a handful of the many available functions of SchoolSoft. They explained that whilst there are some useful functions of the software there exist a plethora of issues, primarily pertaining to its lacking ease of use. Using the Technology Acceptance model, the relationship between perceived ease of use and perceived usefulness can explain the teachers’ overwhelmingly negative opinion of SchoolSoft. Furthermore, it became apparent that only one of the twelve teachers had received any formal training in the usage of SchoolSoft, despite the fact that all teachers on Gotland are required to use it. This fact is likely associated with the teachers critique of the software’s ease of use. An analysis of the teachers’ usage of SchoolSoft through the Innovation-Decision Model shows that the teachers who participated in this study, being long term users of the learning platform and therefore having already progressed through the preceding stages of the model, were all in the conformation phase. The majority of whom indicating that they would neither like to increase their usage of SchoolSoft or continue using it to the same degree.    When questioned if the compulsory usage SchoolSoft affects their freedom to structure their teaching in the way they see fit (Swedish: friutrymme) the teachers responded that it does not. They plan their lessons however they want regardless. They did however indicate that as a result their transparency towards their students’ parents is limited because the teachers are not always able to publish their lesson plans on the learning platform.