The dissertation analyses the situation of brownfields in the region of Vysočina, Czech Republic, assesses the state of brownfields and outlines possible future development. The work contains of seven chapters and is directed at three basic stages. The contents of the first stage is identification and character of environmental limits. The second stage is the analysis of negative features and burdens causing a direct health threat in the monitored area. The third, final stage of this work is a sociological survey focused on perception and evaluation of brownfield sites by local community in this area. The output of these analysises are tables and graphical diagrams, which summarize the data obtained in the research.

The thesis focuses on the changes in teachers´ attitudes towards assessment and classification of primary school pupils as brought about by the requirements for pupils?assessment in accordance with the Framework Education Programme for Elementary Education (RVP ZV). In the theoretical part of the thesis, with the help of specialized literature, I described the types and forms of the assessment and classification used at primary schools as well as the criteria and rules for the assessment of pupils. In the inquiry part I compared approaches of teachers towards assessment and classification used at primary schools and attempted to compare the approaches of ungraded schools to those of fully organized schools. Moreover, I focused on teachers of foreign languages and their approaches to assessment.

Master of Science / Department of Computing and Information Sciences / Doina Caragea / Social media affects our daily lives. It is one of the first sources for finding breaking news. In particular, Twitter is one of the popular social media platforms, with around 330 million monthly users. From local events such as Fake Patty's Day to across the world happenings - Twitter gets there first. During a disaster, tweets can be used to post warnings, status of available medical and food supply, emergency personnel, and updates. Users were practically tweeting about the Hurricane Sandy, despite lack of network during the storm. Analysis of these tweets can help monitor the disaster, plan and manage the crisis, and aid in research. In this research, we use the publicly available tweets posted during several disasters and identify the relevant tweets. As the languages in the datasets are different, Bing translation API has been used to detect and translate the tweets. The translations are then, used as training datasets for supervised machine learning algorithms. Supervised learning is the process of learning from a labeled training dataset. This learned classifier can then be used to predict the correct output for any valid input. When trained to more observations, the algorithm improves its predictive performance.

This diploma thesis deals with taxonomy independent methods for classification of metagenomic signals, aquired by a MinION sequencer. It describes the formation and character of metagenomic data and already existing methods of metagenomic data classification and their development. This thesis also evaluates an impact of the third generation sequencing techniques in the world of metagenomics and further specialises on the function of the Oxford Nanopore MinION sequencing device. Lastly, a custom method for metagenomic data classification, based on data obtained from a MinION sequencer, is proposed and compared with an already existing method of classification.

Four studies were included in this doctoral dissertation aiming to investigatehow habilitation professionals perceive the ICF-CY in clinical work and to identify everyday life situations specific for children and youth aged 0-17 years. The ICF-CY was the conceptual framework and since the research was conducted on as well as with the ICF-CY, the use of the classification runs like a thread through all the work. The design was primarily qualitative and included descriptive and comparative content analyses. Study I was longitudinal, aiming to explore how an implementation of the ICF-CY in Swedish habilitation services was perceived. Studies II-IV were interrelated, aiming to explore children’s most common everyday life situations. Content in measures of participation, professionals’ perspectives, and external data on parents’ perspectives were linked to the ICF-CY and compared. Mixed methods design bridged the Studies III-IV. Results in Study I indicated that knowledge on the ICF-CY enhanced professionals’ awareness of families’ views of child functioning and pointed to the need for ICF-CY based assessment and intervention methods focusing on child participation in life situations. A first important issue in this respect was to identify everyday life situations. Two sets of ten everyday life situations related to the ICF-CY component Activities and Participation, chapters d3-d9, were compiled and adopted for younger and older children respectively, establishing a difference in context specificity depending on maturity and growing autonomy. Furthermore, key constructs in the ICFCY model were discussed, additional ICF-CY linking rules were presented and suggestions for revisions of the ICF linking rules and the ICF-CY were listed. As the sample of everyday life situations reflects the perspectives of adults, further research has to add the perspective of children and youth. The identified everyday life situations will be the basis for the development of code sets included in a screening tool intended for self- or proxy- report of participation from early childhood through adolescence.

This thesis is focused on issues of a real, military and industrial brownfield. There is explained the term ''brownfield'' in the first part of this thesis and then there are described types, classifications, methods of mapping, opportunities of revitalization and their financing. The second part is focused on a real, industrial and military brownfield in the South-Bohemian region, his history and a potential utilization in the years to come.

In its theoretical part, the (Diploma) Thesis "New Exploitation Concept of the Picked Brownfields in Southern Bohemia District" concerns brownfield issues, defines the terms and describes their classifiaction from diferent points of view. Next the Thesis defines procedures of identification and mapping of brownfields. My work indicates authorities dealing with the topics, revitalization possibilities and possibilities of investment in particular investment intents. Applied part of the Thesis aims at one chosen property in South Bohemia District, describes history and today's condition and possibilities of their future use.

Cette thèse porte sur la fonction de détection d'obstacles dans le domaine ferroviaire à partir de la vision par ordinateur. Il s'agit d'assurer une perception de l'environnement situé à l'avant du train afin de détecter et d'évaluer les distances des obstacles situés sur la voie.Nous avons donc proposé un module détection de rails à partir des images à niveaux de gris, pour déterminer une zone libre d'obstacles à l'avant du train. Cette détection est basée dans l'algorithme de RANSAC et une estimation de la voie par un polynôme de degré 2. Elle s'est montrée robuste à notre base de données et a permis de détecter les rails à des distances supérieures à la distance d'arrêt. Aussi, un algorithme d'étalonnage des caméras installées dans le train a été proposé à partir de la morphologie de la voie.Comme support de la reconnaissance de rails, nous présentons un module de détection et classification des appareils de voie basé dans le descripteur HOG extrait des images IPM (Inverse Perspective Mapping). Un classifieur SVM (Support Vector Machines) binaire a été utilisé pour la détection et un SVM multi-classe pour différencier les appareils de voie existants sur la ligne.Après avoir élaboré le module de détection des rails, nous avons implémenté un détecteur de trains. À partir d'un échantillon des images de trains de la ligne en question et des images négatives comme des voitures ou des bus, nous avons créé une base de données d'obstacles pour trouver un descripteur robuste qui arrive à décrire la forme des trains et permet à un classifieur SVM de discriminer les images et détecter les trains. Par la suite, ce classifieur est utilisé par le système global pour déterminer la présence d'un train au-delà de la détection de la voie. À la distance maximale de détection, un rectangle de la taille d'un train est extrait de l'image pour vérifier la présence d'un train. Ces rectangles font l'objet d'une classification au moyen de descripteurs globaux de type HOG et une structure SVM binaire.Cette étude permettra non seulement de déboucher sur des applications concrètes, mais surtout d'évaluer la maturité des technologies de traitements d'images pour réaliser des fonctions sûres appliquées aux systèmes ferroviaires. / This thesis deals with obstacle detection in a railway setting using computer vision. The main task is to provide perception of the environment in front ofthe train using an optical sensor to detect and evaluate distances to obstacles along the track path.We present a module for detecting rails from grayscale images to determine an obstacle-free zone in front of the train. This detection is based on the RANSACalgorithm and fitting the track to a second degree polynomial. The method has shown itself robust to our dataset and allows detecting the rails at distancesgreater than the emergency stopping distance. In addition, a method for calibrating the cameras installed on the train is proposed based on the morphology ofthe track.To supplement rail detection, we present a new module for detecting and classifying junctions based on the HOG descriptor extracted from InversePerspective Mapping (IPM) images. A Support Vector Machines (SVM) binary classifier was used for detection and a multi-class SVM for distinguishing ofjunctions along the rails.In the sequel, a train detector was implemented. Using a set of images of trains found on the studied line and negative images such as cars or buses, we havecreated a database of obstacles to find a robust descriptor which is able to model the form of trains and allows a SVM classifier to distinguish images anddetect trains. Next this classifier is used by the overall system to determine the presence of a train in addition to detecting rails. At the maximum detectiondistance, a train-sized rectangle is extracted from the image in order to confirm the presence of a train. These rectangles are classified by means of HOG-typeglobal descriptors and a binary SVM structure.In addition to its applications to concrete problems, this study permits to evaluate the maturity of image processing technologies forfail-safe railway systems.

This thesis describes searching for high-risk clusters of portals in the Ingress game by using data mining techniques. The work contains background for descibed problematics and methods and experiments used to search for theese information.

Online store customers generate vast amounts of product and service information through reviews, which are an important source of feedback. This thesis deals with the creation of a system for the analysis of product and shop reviews in the czech language. It describes the current methods of sentiment analysis and builds on current solutions. The resulting system implements automatic data download and their indexing, subsequently sentiment analysis together with text summary in the form of clustering of similar sentences based on vector representation of the text. A graphical user interface in the form of a web page is also included. A review data set with a total of more than six million reviews was created during the semester along with an interface for easy data export.