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Development of selected small towns with using available support programmes
VOPELKOVÁ, Marcela
The aim of thesis ,,Development of selected small towns with using available support programmes" is to evaluate the present situation of selected small tors and a proposal for their further development by using available support programmes. The theoretical part of the thesis is focused on explanation of all concepts of these small towns and the practical part includes a analysis of received subsidies and their total evaluation and other potential projects for the development of selected towns with using available support programmes.
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Web Application Development with Spring Framework
Nizamov, Kirill ; Pecinovský, Rudolf (advisor) ; Šlajchrt, Zbyněk (referee)
The thesis is concerned with a comparison between a Java framework called Spring and Grails, Zend, Nette, NodeJS, Play, Symfony, OpenXava frameworks described in the theses of Odehnal [1], Kočárek [2], Kadlec [3], Dočkal [4], Šimon [5]. The thesis consists of two parts. The theoretical part introduces the Spring ecosystem and its individual modules to the reader. This part also outlines trends and estimates Spring position and popularity among other Java frameworks. The practical part focuses on web application development based on the criteria defined in the Odehnal's thesis [1]. The sample application shows the style of development in the Spring framework and its functionality and capabilities. Based on the gained experience during the sample application development, Spring is next compared to the other frameworks mentioned earlier and included into the previous comparison. The comparison criteria are specified in the Odehnal's thesis [1] and consist of 4 areas. First of all, there is a basic framework differences comparison. Next, there is an architecture comparison. The third area involves a comparison of work with the framework which also contains both objective criteria and personal estimation. The last part is dedicated to a comparison related to framework support, available literature and overall popularity. The result of this thesis is a comparison of 8 frameworks including the created sample application, which should help the readers when selecting one of the them and should make it easier to orientate in the world of web frameworks.
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Řízení IS/ICT se zaměřením na sourcing služeb informačního systému
Šebesta, Michal ; Voříšek, Jiří (advisor) ; Havlíček, Zdeněk (referee) ; Příklenk, Oldřich (referee) ; Král, Jaroslav (referee)
Research on outsourcing has been around for several decades, while recent evolution in the information systems discipline towards ICT service commoditization significantly changes the context of decision-making. Services that are available on-demand via the Internet allow organizations implementing functions they demand in a fraction of time. This trend represents a chance for organizations seeking to use advanced ICT services without a need of major investments. Problem is the current lack of guidelines and tools for managing ICT services and their outsourcing. Given the trends on the ICT service market, it is expected that much of the IT management in the future will encompass the ICT services and utilize service-level structures. Methods currently available are either too broad or encompass only small part of the whole problem. Ad-hoc or unsound decisions in this area might cause major complications in terms of quality, usability, integration, and consequently influence total cost of organizational IT. Organizations need to either revise existing models or propose and implement completely new models to manage their IS/ICT. This thesis deals with the management of IS/ICT with focus on the ICT services outsourcing. It discusses available sourcing models in the literature and links them to the various interconnected areas. Based on these areas, it presents an integrated view on IT outsourcing strategies. Most importantly the thesis proposes an original concept for decision-making about outsourcing of ICT services named the SOURCER framework. This approach utilizes the presented outsourcing strategies, and introduces a complex methodology and decision-making criteria that will assist organizations with selection of ICT services in order to maintain and manage a most suitable ICT service portfolio. The decision-making is based on four essential viewpoints: function, costs, time, and quality. These viewpoints are discussed, individually analyzed, and serve as a basis for further research. The whole framework is developed and validated according to Design Science Research Methodology (DSRM). Individual components are evaluated using a survey among a group of selected IT managers. Proof of concept is then established by a case study on framework use in a real organization. This case study covers strategy specification, business--IT alignment, specifying service architecture and its interconnections, outsourcing, and management of the ICT service portfolio.
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Clustering and regression analysis of micro panel data
Sobíšek, Lukáš ; Pecáková, Iva (advisor) ; Komárek, Arnošt (referee) ; Brabec, Marek (referee)
The main purpose of panel studies is to analyze changes in values of studied variables over time. In micro panel research, a large number of elements are periodically observed within the relatively short time period of just a few years. Moreover, the number of repeated measurements is small. This dissertation deals with contemporary approaches to the regression and the clustering analysis of micro panel data. One of the approaches to the micro panel analysis is to use multivariate statistical models originally designed for crosssectional data and modify them in order to take into account the within-subject correlation. The thesis summarizes available tools for the regression analysis of micro panel data. The known and currently used linear mixed effects models for a normally distributed dependent variable are recapitulated. Besides that, new approaches for analysis of a response variable with other than normal distribution are presented. These approaches include the generalized marginal linear model, the generalized linear mixed effects model and the Bayesian modelling approach. In addition to describing the aforementioned models, the paper also includes a brief overview of their implementation in the R software. The difficulty with the regression models adjusted for micro panel data is the ambiguity of their parameters estimation. This thesis proposes a way to improve the estimations through the cluster analysis. For this reason, the thesis also contains a description of methods of the cluster analysis of micro panel data. Because supply of the methods is limited, the main goal of this paper is to devise its own two-step approach for clustering micro panel data. In the first step, the panel data are transformed into a static form using a set of proposed characteristics of dynamics. These characteristics represent different features of time course of the observed variables. In the second step, the elements are clustered by conventional spatial clustering techniques (agglomerative clustering and the C-means partitioning). The clustering is based on a dissimilarity matrix of the values of clustering variables calculated in the first step. Another goal of this paper is to find out whether the suggested procedure leads to an improvement in quality of the regression models for this type of data. By means of a simulation study, the procedure drafted herein is compared to the procedure applied in the kml package of the R software, as well as to the clustering characteristics proposed by Urso (2004). The simulation study demonstrated better results of the proposed combination of clustering variables as compared to the other combinations currently used. A corresponding script written in the R-language represents another benefit of this paper. It is available on the attached CD and it can be used for analyses of readers own micro panel data.
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Míry podobnosti pro nominální data v hierarchickém shlukování
Šulc, Zdeněk ; Řezanková, Hana (advisor) ; Šimůnek, Milan (referee) ; Žambochová, Marta (referee)
This dissertation thesis deals with similarity measures for nominal data in hierarchical clustering, which can cope with variables with more than two categories, and which aspire to replace the simple matching approach standardly used in this area. These similarity measures take into account additional characteristics of a dataset, such as frequency distribution of categories or number of categories of a given variable. The thesis recognizes three main aims. The first one is an examination and clustering performance evaluation of selected similarity measures for nominal data in hierarchical clustering of objects and variables. To achieve this goal, four experiments dealing both with the object and variable clustering were performed. They examine the clustering quality of the examined similarity measures for nominal data in comparison with the commonly used similarity measures using a binary transformation, and moreover, with several alternative methods for nominal data clustering. The comparison and evaluation are performed on real and generated datasets. Outputs of these experiments lead to knowledge, which similarity measures can generally be used, which ones perform well in a particular situation, and which ones are not recommended to use for an object or variable clustering. The second aim is to propose a theory-based similarity measure, evaluate its properties, and compare it with the other examined similarity measures. Based on this aim, two novel similarity measures, Variable Entropy and Variable Mutability are proposed; especially, the former one performs very well in datasets with a lower number of variables. The third aim of this thesis is to provide a convenient software implementation based on the examined similarity measures for nominal data, which covers the whole clustering process from a computation of a proximity matrix to evaluation of resulting clusters. This goal was also achieved by creating the nomclust package for the software R, which covers this issue, and which is freely available.
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Usage of unstructured data in Business Intelligence
Rakhmanova, Malika ; Šperková, Lucie (advisor) ; Karkošková, Soňa (referee)
The aim of the thesis is to identify the main trends that are occurring in the market of Business Intelligence and related to unstructured data, to describe the possibilities for integrating unstructured data, to clarify what the impact on the company have the results that can be obtained using these solutions and how generally incorporate an analysis of unstructured data into BI. Another aim is to show the current situation of processing unstructured data on the example of BI system. The thesis is divided into several parts. First part is describing of the Business Intelligence area and the basic components of Business Intelligence, as well as identifying market trends. Then, there is the next part: separating the data into structured and unstructured. Here is the part about how you can access and analyse unstructured data and what is their place in BI systems. This is the end of a block of unstructured data and the beginning of a description of the enhanced version of BI. Finally, the current market situation and BI tools, which include unstructured data, are introduced. This section provides an overview of how BI tools approach to analyse unstructured data. Existed literature, professional and freely available Internet resources are used for writing the work. The purpose is to serve as a source of information for quickly orienting in the current situation, to serve as a guide to the world of BI solutions and to show potential users what are the options and functionality of these BI solutions.
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Comparison of Business Intelligence implementation using open source solutions for middle size companies
Schmidt, Róbert ; Maryška, Miloš (advisor) ; Sládek, Pavel (referee)
The main goal of master thesis is to analyze and propose possible low cost Business Intelligence solution with open source technologies and comparison of available tools for implementation in middle size company. We compare Pentaho and Jaspersoft tools implemented on local hardware and cloud environment with Microsoft Azure services. The theoretical part focuses mainly on understanding the business intelligence and its architecture, because architecture is an important part of the work. Actual tools are designed as stand alone modules for specific activities in the business intelligence lifecycle. Low cost tools are often connected with open source technologies and cloud computing. This part of the work contains explanation of these terms and their advantages and disadvantages for our chosen target group of companies. The analytical part includes defined parameters by which it is conducted analysis of tools and their comparison. Business Intelligence solutions are divided according to arcitectural layers. The evaluation criteria are divided into financial, technical and user category. In conclusion, chosen tools are compared and evaluated. The main contribution of this thesis is comparison of open source business intelligence tools for implementation in middle size company. According to the EU directive, middle size company does not exceed 250 employees or profit is less than 50 million euros. The reader can compare the different solutions and their pitfalls or shortcomings that could be critical for the implementation.
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Development of internal management information system in Dolphin Consulting, s.r.o.
Církovský, Tomáš ; Maryška, Miloš (advisor) ; Kasl, Tomas (referee)
Main goal of this master thesis is to create Management Information System for company Dolphin consulting, s.r.o. based on technologies available within its infrastructure. Next goal is conduct preliminary verification of the created Management Information System. Generally, the Management Information System is created in accordance with resources including but not limited to Business Intelligence, Management Information Systems literature and experiences of the author. The most important assets of this thesis are creating of the system for Dolphin consulting, s.r.o. and initial verification of created system for its further development and highlight issues that arise. This master thesis is divided into two logical parts. The first part is purely theoretical and describes the issues of data warehousing according to Kimball and Inmon, OLAP Cubes and Management Information Systems. Practical part of thesis describes implementation of Business Intelligence tools as a part of created Management Information System in company Dolphin consulting, s.r.o. At the end of this part is the above stated preliminary verification of the Management Information System with list of recommendations for improving the system.
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Possibilities of Big Data use for Competitive Intelligence
Verníček, Marek ; Molnár, Zdeněk (advisor) ; Šperková, Lucie (referee)
The main purpose of this thesis is to investigate the use of Big Data for the methods and procedures of Competitive Intelligence. Among the goals of the work is a toolkit for small and large businesses which is supposed to support their work with the whole process of Big Data work. Another goal is to design an effective solution of processing Big Data to gain a competitive advantage in business. The theoretical part of the work processes available scientific literature in the Czech Republic and abroad as well as describes the current state of Competitive Intelligence, and Big Data as one of its possible sources. Subsequently, the work deals with the characteristics of Big Data, the differences from working with common data, the need for a thorough preparation and Big Data applicability for the methods of Competitive Intelligence. The practical part is focused on analysis of Big Data tools available in the market with regard to the whole process from data collection to the analysis report preparation and integration of the entire solution into an automated state. The outcome of this part is the Big Data software toolkit for small and large businesses based on their budget. The final part of the work is devoted to the classification of the most promising business areas, which can benefit from the use of Big Data the most in order to gain competitive advantages and proposes the most effective solution of working with Big Data. Among other benefits of this work are expansion of the range of resources for Competitive Intelligence and in-depth analysis of possibilities of Big Data usage, designed to help professionals make use of this hitherto untapped potential to improve market position, gain new customers and strengthen the existing user base.
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Satisfaction of women in labour with nursing care during childbirth.
KLÍMOVÁ, Magdaléna
This dissertation investigates the level of satisfaction among expectant mothers with the care services provided during childbirth. Satisfaction reflects a subjective perception of an expectant mother in meeting her needs during childbirth. The feeling of satisfaction is very personal, however, evaluation of the care provided needs to be determined and not ignored. It is important for expectant mothers that the health care professionals present as empathic, friendly, co-operative, and tactful.Theoretical part was developed from evidence-based literature and available findings related to this problematic. There is a description of a childbirth process including a midwife's role during the individual stages of childbirth and options for pain management. Other chapters focus on midwife's approach toward an expectant mother and factors which influence the level of satisfaction during childbirth. Dissertation's aim was to determine whether the expectant mothers were more satisfied in smaller maternity departments, and to evaluate the way a midwife may influence the mother's satisfaction. There were two hypotheses stated and verified by a statistical testing. Hypothesis No. 1: Expectant mothers are more satisfied in smaller maternity departments than larger ones. Hypothesis No. 2: The level of satisfaction is influenced by midwife's empathic approach. Practical part focused mainly on a midwife's approach toward expectant mother. A quantitative research was implemented in form of questionnaires. The research sample constituted of expectant mothers from four postpartum departments in the Czech Republic. In total the sample included 215 expectant mothers, 109 from smaller facilities and 106 from larger maternity departments. In terms of the overall level of satisfaction with their midwife during the childbirth process, 89% of expectant mothers from smaller maternity departments and 83% of expectant mothers from larger departments stated they were satisfied. Conversely, 11% of respondents from smaller facilities and 17% of respondents from larger facilities were dissatisfied. Based on research analysis comparing the level of satisfaction of expectant mothers from smaller and larger maternity departments the hypothesis no. 1 "Expectant mothers are more satisfied in smaller maternity departments than the larger ones" did not show as statistically significant and was rejected. Nonetheless, the questionnaire responses clearly showed that empathic approach of a midwife influenced expectant mother's satisfaction. Statistical testing demonstrated a significant correlation between an expectant mother's satisfaction and empathic approach of a midwife. The second hypothesis "The level of satisfaction is influenced by midwife's empathic approach" was accepted.The research findings may serve as a guiding material for the midwives in order to provide a high quality care to expectant mothers during the childbirth process. They may also be utilised by future midwives who are in undergraduate preparation for the profession, or those professionals who contribute in any way during the childbirth process. Additionally, the research findings may be presented at conferences designated for midwives.
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