In this work, two different problems are addressed. In the first part, the problem of synthesizing a set of stabilizing controllers for unknown multivariable systems using direct data is analyzed. This is a model free approach to control design and uses only the frequency domain data of the system. It is a perfect complement to modern and post modern methods that begin the control design with a system model. A three step method, involving sequential design, search for stability boundaries and stability check is proposed. It is shown through examples that a complete set of stabilizing controllers of the chosen form can be obtained for the class of linear stable multivariable systems. The complexity of the proposed method is invariant with respect to the order of the system and increases with the increase in the number of input channels of the given multivariable system. The second part of the work deals with the problem of identification of model uncertainties and the effect of unwanted exogenous inputs acting on a discrete time multivariable system using its output information. A disturbance model is introduced which accounts for the system model uncertainties and the effect of unwanted exogenous inputs acting on the system. The frequency content of the exogenous signals is assumed to be known. A linear dynamical model of the disturbance is assumed with an input that has the same frequency content as that of the exogenous input signal. The extended model of the system is then subjected to Kalman filtering and the disturbance states estimates are used to obtain a least squares estimate of the disturbance model parameters. The proposed approach is applied to a linear multivariable system perturbed by an exogenous signal of known frequency content and the results obtained depict the efficacy of the proposed approach.

This thesis deals with solvency and bankruptcy models usage evaluation and their matual comparison. The first part of the thesis describes solvency and bankruptcy models like Kralicek Quick Test, Solvency Index, Rudolf Doucha Balance Analysis, Grünwald Solvency Model, D-score, Aspect Ratio Global, Altman's Model, Taffler's Model, Springate Model, Zmijewski Model and individual Indexes of credibility. The aim of the thesis is to compare the ability of individual models to predict bankruptcy and indentify the powers which influence the results. Constituent aim is the susceptibility analysis of the presented models and proposal of suitable model for a specific field.

The goal of this thesis is to apply selected methods of fundamental analysis on selected stock sample and to assess in what way fundamental analysis methods' application can be used for determining future stock values. For this purpose, dividend discount models, profit models and cash flow models are employed. For dividend models it is namely Gordon's model, two-tier dividend discount model and H-model, as for profit models methods based on P/E ratio and regarding cash flow models Free Cash Flow to Equity model was chosen. The selection is done with respect to "popularity" of these models within investment theory and practice. Models were applied on companies from American capital market from neutral as well as cyclical sectors. For neutral sector, pharmaceutical company Pfizer, telecom Verizon and producer of nonalcoholic beverages Coca-Cola were picked. As for cyclical sectors, I have chosen Bank of America and industrial goods producer General Electric.

The work deals with competencies, competency model and with developing a project for the creation and implementation in selected company.

The research hopes to provide a deeper understanding of the leading countries in the Central Eastern Europe (CEE) region from a culture sensitive marketing perspective. The aim of this work is to provide a pilot study upon which more critical national culture studies are to be introduced.The purpose of this dissertation is four-fold: 1) To discuss the proper methodology for the research; 2) to replicate the original study in order to suggest the values for the Czech Republic, Poland and Slovakia; 3) to introduce the marketing application theoretical framework for the original study, and 4) to translate the results to marketing scholars and practitioners.

Disertační práce se zabývá modelováním dispersních materiálů metodou konečných prvků v časové oblasti. V práci jsem navrhl matematický model zahrnující dispersní modely a aplikoval jsem na něj metodu konečných prvků. Pozornost jsem věnoval třem nejvíce používaným dispersním modelům. Jedná se o Debyeho model, Lorentzův model a Drudův model. Dále jsem se zabýval technikami implementace těchto dispersních modelů. Techniky jsem zabudoval do metody konečných prvků. Navíc jsem vyvinul novou metodu založenou na technice digitální filtrace. Funkčnost vyvinutých metod a technik jsem ověřil na řadě testovacích příkladů. Diskutoval jsem dosažené výsledky a navrhuji jejich možná vylepšení.

Title: Joint Models for Longitudinal and Time-to-Event Data Author: Jana Vorlíčková Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Arnošt Komárek, Ph.D., Department of Probability and Mathematical Statistics Abstract: The joint model of longitudinal data and time-to-event data creates a framework to analyze longitudinal and survival outcomes simultaneously. A commonly used approach is an interconnection of the linear mixed effects model and the Cox model through a latent variable. Two special examples of this model are presented, namely, a joint model with shared random effects and a joint latent class model. In the thesis we focus on the joint latent class model. This model assumes an existence of latent classes in the population that we are not able to observe. Consequently, it is assumed that the longitudinal part and the survival part of the model are independent within one class. The main intention of this work is to transfer the model to the Bayesian framework and to discuss an estimation procedure of parameters using a Bayesian statistic. It consists of a definition of the model in the Bayesian framework, a discussion of prior distributions and the derivation of the full conditional distributions for all parameters of the model. The model's ability to...

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Mypes (Micro and small companies) play an important role in the economy of a country, since they contribute 24% to Peru's GDP, besides being a generator of employment and business development. In this context, the Mypes of footwear continue to have exponential growth, this due to the result of their operations that are carried out with these companies on a daily basis. Therefore, it is necessary to have qualitative and quantitative data of the reality that these present in your business environment. To identify the level of maturity there are several methods, which provide necessary criteria to identify and qualify the processes that exist within the Mypes.

On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1. / Master of Science

Les logiciels multi-partis sont des applications distribuées sur le web qui mettent en oeuvre des fonctions collaboratives. Ces applications sont les principales cibles des attaquants qui exploitent des vulnérabilités logicielles dans le cadre d'activités malveillantes. Récemment, un type moins connu de vulnérabilité, les anomalies logiques, a attiré l'attention des chercheurs. Sur la base d'informations tirées de la documentation des applications, il est possible d'appliquer deux techniques de test: la vérification du modèle, autrement appelé ``model checking'', et les tests de sécurité de type ``boîte noire''. Le champs d'application du model checking ne prend pas en suffisamment en compte les implémentations actuelles, tandis que les tests de type boîte noire ne sont pas assez sophistiqués pour découvrir les vulnérabilités logique. Dans cette thèse, nous présentons deux techniques d'analyse modernes visant à résoudre les inconvénients de l'état de l'art. Pour commencer, nous présentons la vérification de deux protocoles de sécurité utilisant la technique du model checking. Ensuite, nous nous concentrons sur l'extension du model checking pour soutenir les tests automatisés d'implémentations. La seconde technique consiste en une analyse boîte noire qui combine l'inférence du modèle, l'extraction du processus et du flot de donnée, ainsi qu'une génération de tests basés sur les modèles d'attaque d'une application. En conclusion, nous discutons de l'application de techniques développées au cours de cette thèse sur des applications issues d'un contexte industrielle. / Multi-party business applications are distributed computer programs implementing collaborative business functions. These applications are one of the main target of attackers who exploit vulnerabilities in order to perform malicious activities. The most prevalent classes of vulnerabilities are the consequence of insufficient validation of the user-provided input. However, the less-known class of logic vulnerabilities recently attracted the attention of researcher. According to the availability of software documentation, two testing techniques can be used: design verification via model checking, and black-box security testing. However, the former offers no support to test real implementations and the latter lacks the sophistication to detect logic flaws. In this thesis, we present two novel security testing techniques to detect logic flaws in multi-party business applicatons that tackle the shortcomings of the existing techniques. First, we present the verification via model checking of two security protocols. We then address the challenge of extending the results of the model checker to automatically test protocol implementations. Second, we present a novel black-box security testing technique that combines model inference, extraction of workflow and data flow patterns, and an attack pattern-based test case generation algorithm. Finally, we discuss the application of the technique developed in this thesis in an industrial setting. We used these techniques to discover previously-unknown design errors in SAML SSO and OpenID protocols, and ten logic vulnerabilities in eCommerce applications allowing an attacker to pay less or shop for free.