O presente trabalho teve como objetivo entender os fatores que facilitam a utilização de sistemas de Business Intelligence em empresas de serviços. Para isso utilizou um modelo EXPECTATION-CONFIRMATION THEORY (ECT) adaptado para avaliar o que favorece a aceitação do sistema, além dos constructos do modelo original proposto por Bhattacherjee (2001b): Confirmação, Satisfação, Utilidade Percebida, Intenção Comportamental de Uso e Continuidade de Uso; foram incluídos três constructos no modelo adaptado: Hábito, Qualidade da Informação e Estratégia Direcionada pela Tecnologia. Após a validação de um questionário do tipo survey por especialistas, o instrumento foi enviado para usuários de Sistemas de BI e obteve 81 respondentes funcionários de empresas de serviços. As conclusões apontam que a maior parte das hipóteses foi confirmada, exceto o efeito moderador do Hábito na Continuidade de Uso e a influência da Estratégia Direcionada pela Tecnologia. Podem-se destacar as contribuições acadêmicas e gerenciais deste trabalho. Como contribuição acadêmica, destacam-se: a construção do referencial teórico sobre Business Intelligence, Big Data, Aceitação de Tecnologia, Estratégia e Empresas de Serviços; e o entendimento sobre a relação dos fatores que influenciam a aceitação de um sistema de BI no mercado brasileiro de serviços. Na implicação gerencial, ressalta-se a conclusão que o fato de a estratégia da empresa ser direcionada pela tecnologia não afetar positivamente a utilidade percebida do sistema de BI, isto pode ser um indício que, independentemente de como o empregado identifica a estratégia da empresa, ele percebe o valor do sistema de BI, o que indica que a ferramenta é útil não apenas para cenários de empresas tecnológicas. O trabalho permitirá diversos desdobramentos e análises alternativas, por seu ineditismo e detalhamentos obtidos sobre os aspectos teóricos selecionados. / The objective of this study was to understand the factors that facilitate the use of Business Intelligence systems in Service companies. To do this, it used an EXPECTATION-CONFIRMATION THEORY (ECT) model adapted to evaluate what helps the acceptance of the system, besides the constructs of the original model proposed by Bhattacherjee (2001b): Confirmation, Satisfaction, Perceived Utility, Behavioral Intention of Use and Continuity of Use; three constructs were included in the adapted model: Habit, Information Quality and Technology Driven Strategy. After the validation of a survey questionnaire by specialists, the instrument was sent to users of BI Systems and obtained 81 respondents from service companies. The conclusions indicate that most of the hypotheses were confirmed, except for the moderating effect of the Habit in Continuity of Use and the influence of the Technology Driven Strategy. It is possible to emphasize the academic and managerial contributions of this work. As an academic contribution, the construction of the theoretical reference on Business Intelligence, Big Data, Acceptance of Technology, Strategy and Service Companies; and the understanding of the relationship between the factors that influence the acceptance of a BI system in the Brazilian services market. In the managerial implication, the conclusion is that the fact that the company\'s strategy is driven by the technology does not positively affect the perceived utility of the BI system, this may be an indication that, regardless of how the employee identifies the company\'s strategy, it realizes the value of the BI system, which indicates that the tool is useful not only for technology companies. The work will allow many developments and alternative analyzes, for its originality and details obtained on selected theoretical aspects.

This is a report about machine learning in the field of computer science. The problem handled is prediction of energy consumption in district heating systems. Prediction of energy consumption in district heating systems is a delicate problem because of the social behaviours, weather and distribution time that has to be accounted for. One algorithm is introduced and three different experiments are made to determine if the algorithm is useful. The results from the experiments were good. This report differs in approach to the problem then other reports found in this field. The difference is that this report tries to handle social behaviours and looks at a decentralized view of the problem instead of centralized. / Denna rapport är om maskininlärning och hur mna kan använda en maskinlärningsalgoritm för att förutspå konsumption i fjärrvärmenät. Rapporten skiljer sig markant i synsätt jämt emot andra rapporter i ämnet genom att den tittar även på de sociala faktorerna.

For underwater robotics there exists severe constraints regarding wireless bandwidth in the kilobits range. This makes a centralised approach to high-level mission management possibly less than ideal due to inherent delays and possible temporary incompleteness in data during decision making. This thesis aims to propose, implement (in ROS) and test a distributed approach. An auction based method for task assignment was being used, as well as a Pagerank based approach that models a trust based hierarchy between autonomous agents inferred from information exchange, in order to enforce decision conformity. Simulations where carried out using UWsim and a custom made bandwidth limiter for ROS. It was concluded that the Pagerank based algorithm managed to uphold conformity and solve conflicts during network slowdown but did not always lead to the correct decisions being enforced.

The thesis deals with emotional intelligence and coping strategies for paramedics. The theoretical part provides information on the emotional intelligence of its models and measurement capabilities. It is then discussed strategies of coping with stress on its historical and theoretical approaches and the types of strategies and also about the methods by which we discover the use of a specific coping style. It is also described the characteristics of paramedic profession, qualification requirements for the exercise of the profession, as well as competence and personal characteristics of rescuers. The aim of the empirical part is quantitatively map a degree of emotional intelligence of paramedics, preference coping styles in this population and mutual respect between the two variables.

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Game playing is a relatively interesting task in the field of artificial intelligence in these days. The master thesis deals with general artificial intelligence which is capable of playing selected simple games based on information that is also avai- lable to the human player. Our selected games are 2048, Mario, racing simulator TORCS and Alhambra. All the information acquired by artificial intelligence is provided by games through an interface, therefore none of the models uses visual input. We use evolutionary approaches such as evolutionary algorithms, evolutio- nary strategy CMA and differential evolution applied to different types of neural networks. We are also dealing with deep reinforcement learning. We test these approaches and compare their results. 1

How shall a business adapt its management control systems when learning machines enter the arena? Will the control system continue to focus on humans aspects and continue to consider a learning machine to be an automation tool as any other historically programmed computer? Learning machines introduces productivity capabilities that achieve very high levels of efficiency and quality. A learning machine can sort through large amounts of data and make conclusions difficult by a human mind. However, as learning machines become even more complex systems, they introduce an uncertainty not previously considered by automation tools. The algorithms can make their own associations, and the automation engineer will no longer know exactly how a learning machine produces its outcome. What is the motive for a learning machine’s decision? A learning machine in this context becomes more human-like compared to the older generation of automation computers. This thesis concludes that most contemporary Management Control System principles are relevant when deploying machine learning, but some are not. A Management Control System must in contradiction to a historically programmed computer, consider multiple human-like aspects while controlling a deployed learning machine. These conclusions are based on empirical data from web-articles, TED-talks, literature and questionnaires directed to contemporary companies using machine learning within their organizations.

Tato práce zkoumá možnosti využití aplikací Webu 2.0 v současné marketingové praxi která je vystavena neustálým vlivům změn, kdy koncoví zákazníci získávají stále větší vyjednávací sílu a jsou stále více odolnější vůči tradičním způsobům masové komunikace. Cílem teoretické části je popis a definování pojmu Webu 2.0 dle údajů ze sekundárních zdrojů, vysvětlení obecného rámce Webu 2.0. Dále zde popisuji i jednotlivé aplikace, které spadají pod kategorii Web 2.0 ? blogy, online komunity, wikis, podcasting, mash-upy a widgets. V praktické části pak zkoumám popsané aplikace z hlediska praktického využití. U každé aplikace uvádím příklady z praxe, výhody a nevýhody spojené s jejich použitím a stanovuji doporučení na jejich nejplepší využití. V závěru této části se též poohlížím po příkladech z české praxe a hodnotím ji v porovnání s praxí zahraniční.

The first aim of this thesis is map the Microsoft development tools for business intelligence systems. This goal devide the tools for develop BI into two groups: tools for traditional BI systems and tools for self-service BI systems. The second aim of this thesis is a critical evaluation of approaches based on the criteria and scenarios focuse on selected business areas. This thesis answers the question if some of the approaches is a better solution for business intelligence systems, or whether one approach is more suitable for business intelligence solutions to some business areas.

Abstract This diploma thesis treats about the latest technologies in the field of self-service BI from Microsoft Corporation. The main goal of this work is to analyze the Microsoft self-service BI solutions, to describe the benefits and advantages of this technology and to show examples with real data in Microsoft self-services BI tools. To achieve the goal, the internet resources, recommended literature, and the software applications PowerPivot and PowerView (Excel 2013) are59 used. In its first part this thesis describes the basic characteristics and technology of classical BI solutions. The second part examines the actual self-service BI solution and its usability. And then analyzes the advantages and benefits compared to conventional technologies. Finally, in its last section describes self-service BI solutions, the DAX language used in PowerPivot and shows example reports with real data from banking sector. The key benefit of this diploma is the verification of the usability and advantages of self-service BI by using Microsoft self-service BI products and tools.