The aim of this work is to design an Artificial Intelligence for Sector 66, which is a board game based on Quoridor. In Sector 66 there is a possibility to use spells and fields with some special effects. The Artificial Intelligence is based on Monte Carlo Tree Search. It can be used for 2 to 4 players. The Artificial Intelligence introduced in this work can work with the high branching factor of Quoridor/Sector 66 Game and can also handle unknown elements represented by user defined plug-ins. The game and the Artificial Intelligence has been developed using .NET Framework, XNA and C#. Powered by TCPDF (www.tcpdf.org)

This master’s thesis is focused on description of e-learning by electronic form of teaching as a way of modern education. In theoretical part various forms, possibilities and basic structures of electronic education systems are described. It presents thorough analyses of positives and negatives of e-learning, both, from a technical perspective as well as from social point of view. In the second part of this thesis, the reader becomes familiar with e-learning system AI Tools used by UAMT FEEC VUT in Brno to support the teaching of basics of artificial intelligence. Furthermore, the work deals with the creation of three plug-in modules for this computer programme. These modules are programmed in C# and pursue matters of informed and uninformed state space search, and issues of forward and backward chaining used in expert systems. In conclusion, the results of theoretical and practical work are evaluated

Cílem diplomové práce je návrh a implementace Business Intelligence v malé firmě, jako je personální agentura zabývající se poskytováním ?TEMPORARY HELP?. Požadavky na aplikaci BI jsou koncipovány na základě metodiky Balanced Scorecard. Teoretická část: popis základních principů a nástrojů konceptů BSC a BI včetně definování jejich vzájemného vztahu a specifických nároků daných užitím v malé firmě. Praktická část: ověření získaných poznatků z teoretické části práce v personální agentuře. V rámci BSC byly definovány konkrétní strategické cíle s měřítky a stanoveny strategické akce. Vybrané strategické cíle jsou sledovány vytvořenou BI aplikací v prostředí MS SQL 2000 a MS OFFICE XP.

Many managers of Puerto Rican corporations have not been able to assist employees in their recovery from the devastation left by Hurricane Maria. This lack of assistance has resulted in high employee attrition rates, low productivity, anxiety, isolation, anguish, despair, panic attacks, and depression. Scholarly literature lacks research on emotional intelligence and learning in corporate, postdisaster contexts; both capacities may mitigate employee stress due to the uncertainty inherent in postdisaster conditions and motivate employees to persevere in the face of adversity. The purpose of this quantitative study was to assess the relationship between employee learning, emotional intelligence, and organizational performance. The theoretical framework applied was human capital theory. The research questions focused on how employee learning and emotional intelligence are related to organizational performance. The sample was 90 full-time employees of multinational corporations in Puerto Rico. Data were collected through SurveyMonkey using the Workplace Learning Scale, the Trait Meta-Mood Scale, and the Organizational Performance Scale. Regression analysis was used to analyze the data, and both employee learning and emotional intelligence were found to have a statistically significant positive relationship with organizational performance (β = .563, p = .000; β = .348, p = .000). To more fully capture participants' thoughts and feelings, a mixed methodology is recommended for future research. The results of this study could assist human resources managers in their selection of training that enables employees to gain the skills needed to support business continuity and personal welfare in postdisaster environments.

ABSTRACT The Relationships among Demographic Variables, Intelligences, Critical Thinking, and Emotional Intelligence of Junior High School Students. The main purpose of the study was to explore the relationships among demographic variables, intelligences, critical thinking, and emotional intelligence (EQ) of Junior High School Students. The participants included 547 students (293 males and 254 females) coming from five junior high schools in Tainan and Kaohsiung City. The instruments employed in this study were the subscales of intrapersonal intelligence and interpersonal intelligence from the Multiple Intelligences Scale, The Test of Critical Thinking Skills for Primary and Secondary School Students (TCTS-PS), The Questionnaire of Dispositions Toward Critical Thinking, and The Self-Report Scale of Children¡¦s Emotional Thinking. The Self-Report Scale of Children¡¦s Emotional Thinking comprised two subscales¡Xthe intrapersonal and the interpersonal intelligence of emotion. The employed methods included Descriptive Statistics, t-test, ANOVA, MANOVA, Cannon Correlation Analysis, and Discriminate Analysis. The main findings of this study were as follows: 1. The students¡¦ development of intrapersonal and interpersonal intelligence, critical-thinking skills, critical-thinking dispositions, and emotional intelligence were above the average. 2. The females outperformed the males in both the intrapersonal and interpersonal intelligence of emotion. 3. There were no significant differences on the EQ scores among the three grade levels. 4. The higher educational level the students¡¦ parents had, the better the students¡¦ EQ were. 5. There was a significant canonical correlation between the two kinds of intelligences and the eight factors of EQ. 6. There was a significant canonical correlation between the independent variable set and the eight factors of emotional intelligence. The independent variable set included gender, grades, the parents¡¦ educational level, intrapersonal intelligence, interpersonal intelligences, critical-thinking skills, and critical-thinking dispositions 7. The level of students¡¦ EQ could be effectively predicted by their critical-thinking skills and critical-thinking dispositions. Among the three levels of EQ, the middle level was predicted with the highest accuracy. The finding revealed that high critical-thinking skills and high critical-thinking dispositions required at least an average level of EQ. Therefore, critical-thinking is essential to EQ. Finally, some suggestions for instruction and further research were proposed.

Business intelligence system for SB market.

This thesis describes new evolutionary artificial intelligence methods suitable for solving complex tasks. These include planning, optimization, decision, prediction and other problems. All of these are tasks which an intelligent human being can quickly learn to solve, yet they cannot be solved by machines in reasonable time. For this type of problems usually no analytical method or algorithm exists. These challenges represent the domain for artificial intelligence. This work concentrates on evolutionary methods of artificial intelligence based on genetic algorithms. Specifically grammatical evolution and differnetial evolution are described. The first part of this thesis describes the principles of genetic algorithms especially those used in grammatical evolution. Later the grammatical evolution method is described. Grammatical evolution is a genetic algorithm extended with a context-free grammar processor. This enables it to generate structured strings in an arbitrary language defined by a regular or context-free grammar. Second part of this work focuses on description of a generic computational system, which enables user-friendly control of grammatical evolution. The architecture of the system is thoroughly described. It composes of a computation service, database server and completely separated user interface. Also the problems solved using this system are described. These include symbolic regression, classification and generation of combinatorial logic circuits. All of these tasks were solved using the described implementation.

This dissertation thesis deals with the prediction and optimization of real data using artificial neural networks methods in decision-making. Usage of artificial neural networks includes finding of various suitable types, topologies and learning algorithms of artificial neural networks to solve prediction of real-world data sets. Optimization solutions in the context of work focused on neural networks used in topology optimization learning algorithms and neural networks own calculation. The first part is a summary of current trends in applications development and the utilization of artificial neural networks. The review of the literature is the selection of the most common models of artificial neural networks for prediction of real data needs. Subsequently, the implementation of the defined application of artificial neural networks in support of decision-making process is made. On the basis of determining the value of the decision making process are defined methods for prediction of real data using classical methods. As classical methods are considered methods of statistical prediction models for time series. After that, the methods of artificial neural networks and their application on prediction task are described. In the next part, experiments involving the choice of type, topology, learning algorithms and optimization possibilities of artificial neural networks is tested on real-world data sets. The implementation presents the prediction of selected real-world economic values; namely a set of household expenditures and goods transport is used. Results obtained with artificial neural networks are compared with real value of the index and also with selected models of statistical time series prediction results.

This work describes contemporary methods for sound data classification and their application on sound recordings. This work deals with the selection of sound signal characteristics appropriate for concrete classification criteria followed by the exploration of proper types of artificial neural networks for this task. Different topologies and learnings algorithms of chosen neural networks are proposed and their performance in this classification is compared. Results compared are discussed and the best solution for sound data classificaton based on the content of recordings is chosen. This work also includes the chosen algorithms implementation into the software solution of my own.

This thesis deals with the concept of emotional intelligence and its interactions with drama in education. Summarises knowledge of the theories of emotions and uses them to pedagogical work with a view of developing emotional intelligence. The work is divided into four chapters. In the first chapter, entitled Emotional Intelligence, explains technical terms and concepts of emotional intelligence, the next chapter is the theory of emotions and their relation to drama education, the third chapter is the theory of emotions and the last chapter describes a specific design and implementation of educational program. In addition to specific topics and situations leading to emotional development the thesis also provides specific experience and evaluation of teaching experiment.