The study of RNA-binding proteins has recently increased in importance due to discoveries of their larger role in cellular processes. One study currently conducted at Umeå University involves constructing a model that will be able to improve our knowledge about T-cells by explaining how these cells work in different diseases. But before this model can become a reality, Umeå Univerity needs to investigate the relation between RNA and RNA-binding proteins and find proteins of which highly contribute to the activity of the RNA-binding proteins. To do so, they have decided to use four penalized regression Machine Learning models to analyse protein sequences from CD4 cells. These models consist of a ridge penalized model, an elastic net model, a neural network model, and a Bayesian model. The results show that the models have a number of RNA-binding protein sequences in common which they list as highly decisive in their predictions.

The diploma thesis deals with multivariate statistical methods and their environmental applications. The theoretical part is devoted to selected methods of linear regression analysis, method of principal components and the model of classical and robust factor analysis is also described. In the practical part of thesis, the main emission sources of PM1 aerosols in summer and winter period in Brno and Šlapanice are determined by using the classical factor analysis. The main aerosol emission sources in summer and winter in Šlapanice are also identified by using the robust factor analysis. Furthermore, the prediction of concentrations of PM1 aerosols in summer and winter period in Brno and Šlapanice is performed by using the linear regression model.

The thesis deals on the theory of partial wetting of a wall, whereby a relation between the velocity of a droplet moving along an inclined plane and time is derived. There are explained basic definitions coherent to the theory of partial wetting. According to divergence of a normal vector of the droplet surface, there is developed a technique for mathematical evaluation of the component of dynamic adhesive force. Within the scope of diploma paper, there was an experimental measurement performed, whereat a velocities of droplets of various volumes and at different inclination angles on four analyzed surfaces were determined. By using non-linear regression, unknown parameters such as the adhesion coefficient, the component of a dynamic adhesive force, initial and terminal velocity of a droplet were evaluated from the experiment results. Within the thesis there was performed a simulation of droplet motion on an inclined plane in ANSYS Fluent. Conclusion includes an assessment and a comparison of results obtained, and new procedures that may be helpful at further research of descending droplet.

The aim of this work is to determine the performance and description of the cooling circle in the cooling tower. In order to do that there was applied the linear regression approach in order to create structural empirical model of the cooling tower. The data obtained was analysed through QC expert software, which, if correct data applied, identifies suitable model for specific tower. The models created will be used for diagnostics of the cooling circles and as a comparison tool with other cooling towers in the future. Thus, the findings of this thesis are polynoms, which in thic technological setup characterise the models of the cooling towers.

Basic way how to identify a device in computer network is by MAC address and IP address. Main goal of this work is to create an application capable of clear identification of devices in computer network regardless change of their MAC address or IP address. This is done by exploiting tiny deviations in hardware clock known as clock skew. They appear in every clock based on quartz oscillator. Using clock skew is beneficial, because there is no need of any changes in fingerprinted device nor their cooperation. Accessing these values is done by capturing packets with timestamps included. Application of this method is very wide, for example computer forensics, tracking the device using different access points or counting devices behind router with NAT.

Orientador: Rodrigo Braga Moruzzi / Resumo: A falha humana é um evento indesejado para os engenheiros, e a população que se vê refém destes empreendimentos, (visto os diversos incidentes que ocorrem no Brasil) por fatores como omissão de informações, medições equivocadas ou mesmo erros técnicos, passam despercebidos durante as vistorias. Na área de Saneamento, em se tratando de esgoto sanitário, os riscos não são menores e também devem ser evitados considerando o número de doenças que são proliferadas por falhas no saneamento de esgoto. A partir deste pressuposto, a presente pesquisa visou desenvolver um modelo preditor, usando ferramentas matemáticas que viabilizassem identificar e corrigir erros técnicos no registro e medições realizadas em parâmetros físicos, químicos e biológicos de dois reatores UASB da Estação Candeia da cidade de Bauru- SP. Para isto, após uma revisão sobre a tecnologia de reatores UASB e de estudos probabilísticos baseados no conceito de confiabilidade aplicado a ETEs (Estações de Tratamento de Esgotos), definiu-se, por meio de análise de regressão, um modelo multilinear, acoplado a um algoritmo de otimização, capaz de prever e corrigir parâmetros de entrada e saídas (inconsistentes ou ausentes) no registro do monitoramento da estação referentes ao tratamento de reatores UASB. Com este procedimento matemático, através de uma análise estatística conceitual de confiabilidade do sistema, foi possível corrigir dados e estimar informações de parâmetros ausentes, em 22% das coletas de medidas e regis... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Human failure is an unwanted event for engineers, and the population that is hostage to these endeavors, (due to the various incidents that occur in Brazil) due to factors such as omission of information, wrong measurements or even technical errors, go unnoticed during surveys. . In the Sanitation area, when it comes to sanitary sewage, the risks are no less and should also be avoided considering the number of diseases that are proliferated by sewage sanitation failures. From this assumption, the present research aimed to develop a predictor model, using mathematical tools that could identify and correct technical errors in the recording and measurements performed on physical, chemical and biological parameters of two UASB reactors at Candeia Station of Bauru- SP. For this, after a review of UASB reactor technology and probabilistic studies based on the concept of reliability applied to sewage treatment plants (SEP), a multilinear model coupled to a optimization algorithm, capable of predicting and correcting input and output parameters (inconsistent or absent) in the station monitoring register for the treatment of UASB reactors. With this mathematical procedure, through a conceptual statistical analysis of system reliability, it was possible to correct data and estimate missing parameter information in 22% of the measurement collections and records in the technical reports that were made available for this study. / Mestre

Autor práce: Bc. Tomáš Kolomazník Název práce: Bariéry dalšího vzdělávání nezaměstnaných z hlediska věku ohrožených na trhu práce Abstract The thesis "Barriers to continuing education of the unemployed in the age groups endangered in the labor market" examines the barriers to continuing education in unemployed groups of age 15-25 and 50-64 in the Czech Republic, both of which are often referred to as disadvantaged in the labor market. These age groups are characterized by a low rate of participation in continuing education, while having very specific needs and problems. The aim of this work is to identify the most frequent barriers in the education of the above-mentioned groups, to find out the differences between them and to explore their sociodemographic predictors. For the statistical analysis, data from the Kooperace research conducted by the Fund of Further Education was used. The first chapter defines the concepts of adult education, disadvantaged groups in labor market and introduces different concepts of barriers to education. Furthermore, the most important surveys of adult education in the Czech Republic are presented. In the methodological chapter, seven barrier dimensions have been examined, such as lack of self- confidence, insufficient relevance of adult education supply, lack of time, low...

Geographically, Pakistan is in the western part of south Asia at about 24-37 °N latitudes and62-75 °E longitudes. Livestock and agriculture are two major sectors in Pakistan and play animportant role in the country economy.The tick infestation in livestock is not only devastating for animals and their products but alsobecome the cause of transmission of pathogens into humans. Crimean Congo fever (CCHF) isa viral tick-borne fatal disease. The dissemination of ticks and amplification of Crimean Congofever (CCHF) pathogen throughout the tick-animals-tick cycle, increases risk of transmissionto humans many times. In Pakistan, cases are reported in all areas, particularly those areaswhich lie on the border to CCHF endemic countries. There is a high prevalence of CCHF inboth Baluchistan and Khyber Pakhtunkhwa regions. Baluchistan is bordering with Afghanistanand Iran and Khyber Pakhtunkhwa with Afghanistan. Linear regression analysis revealed apositive significant association of high level of CCHF cases in livestock, with camels, goatsand sheep. The literacy rate is negatively significantly corelated with the numbers of cases.Statistical analysis of border effect revealed a high positive significant correlation of CCHFprevalence in areas near to borders. Both Baluchistan and Khyber Pakhtunkhwa (KPK) haslow literacy rate than other regions of Pakistan. Islamabad (capital city) has a higher literacyrate than all other regions but there is still a high CCHF prevalence. This is not only becauseof high population density but people from other regions, particularly from Baluchistan andKPK come here for animals selling or to seeking medical facilities in the large city hospitals.The study gives a proof that illiteracy and borders are the major respondent factors in theCCHF incidences and prevalence in an area. There is a need to raise awareness about ticksand tick-borne disease in the public and establishment of monitoring system across the bordersto prevent the spread of CCHF virus.

This thesis provides an introduction to methods for handling missing data. A thorough review of earlier methods and the development of the field of missing data is provided. The thesis present the methods suggested in today’s literature, multiple imputation and maximum likelihood estimation. A simulation study is performed to see if there are circumstances in small samples when any of the two methods are to be preferred. To show the importance of handling missing data, multiple imputation and maximum likelihood are compared to listwise deletion. The results from the simulation study does not show any crucial differences between multiple imputation and maximum likelihood when it comes to point estimates. Some differences are seen in the estimation of the confidence intervals, talking in favour of multiple imputation. The difference is decreasing with an increasing sample size and more studies are needed to draw definite conclusions. Further, the results shows that listwise deletion lead to biased estimations under a missing at random mechanism. The methods are also applied to a real dataset, the Swedish enrollment registry, to show how the methods work in a practical application.

In the highly competitive environment that companies find themselves in today, it is key to have a well-functioning supply chain. For manufacturing companies, having a good supply chain is dependent on having a functioning production planning. The production planning tries to fulfill the demand while considering the resources available. This is complicated by the uncertainties that exist, such as the uncertainty in demand, in manufacturing and in supply. Several methods and models have been created to deal with production planning under uncertainty, but they often overlook the complexity in the supply uncertainty, by considering it as a stochastic uncertainty. To improve these models, a prediction based on earlier data regarding the supplier or item could be used to see when the delivery is likely to arrive. This study looked to compare different predictive models to see which one could best be suited for this purpose. Historic data regarding earlier deliveries was gathered from a large international manufacturing company and was preprocessed before used in the models. The target value that the models were to predict was the actual delivery time from the supplier. The data was then tested with the following four regression models in Python: Linear regression, ridge regression, Lasso and Elastic net. The results were calculated by cross-validation and presented in the form of the mean absolute error together with the standard deviation. The results showed that the Elastic net was the overall best performing model, and that the linear regression performed worst.