This diploma thesis deals with the preventive assessment of the landscape character of the cadastral territory of Rabštejn nad Střelou. The evaluated area extends into the Nature Park and there is a small specially protected area called Střela Nature Reserve. The research area outside of the natural wealth is also rich in historical buildings. The research part has the focus on the analysis of the landscape of Rabštejn nad Střelou. The territory has been assessed on the basis of identified natural, cultural and historical features and values of landscape character. For each of the traits, its significance, expression and value were determined. For the cadastral area the degree of preservation of the landscape character, its aesthetic value and the degree of protection were determined. On the basis of the analysis, specific proposals for increasing the value of the landscape character were set.

My diploma work deals with problems and evaluation of landscape character in chosen places in Novohradské Mountains. At first there was created a basic characteristic of the evaluated places on the basis of data from historical, geographical and statistical sources. These places were chosen according to their archive accessability, especially with the aid of contemporary photos. Consequently a proper field research was realized which was concentrated on the analysis beforehand determined criteria of the evaluation. Together with this searching there was executed also evaluation of aesthetical incidence. As well this evaluation was realized according to beforehand determined criteria. The main aim of my paper is to catch given places from the view of the extant archive materials and to explore the changes in landscape from the consequent comparison of original and newly created pictures from these places.

The paper deals with organizational identity in relation to organizational strategy. Based on the reserch questionnaire, the values inventory and the interview it was found that the strategy of the organization Lesostavby Třeboň, a. s. is in accordance with organizational identity further external identity orientation is coincident with internal identity orientation and this orientation is perceived by managers and technical-economic workers in the same way. The information obtained was summarized in tables and bar graphs, including the resulting recommendations for the company Lesostavby Třeboň, a. s.

The purpose of this study was to examine the prevalence of character strengths that high school students reported to develop while participating in choir. I created the Character Strengths in Choir Scale (CSCS) to explore the degree to which students believed they exercised 18 character strengths. Local choir students in the pilot study (n = 44) and the main study (n = 114) completed the CSCS and revealed that gratitude, teamwork, and honesty were among the most prevalent strengths while bravery, creativity, and spirituality were among the least prevalent strengths. Student responses were also investigated by subgroups according to gender and years of experience. Results indicated that there were statistically significant differences for the ranking of various character strengths in each subgroup. Aggregately, high school choir students viewed themselves as above average on all assessed strengths.

Master of Music / School of Music, Theatre, and Dance / Patricia Thompson / This Master’s Report is in the form of extended program notes on works performed on a graduate recital for a mezzo-soprano. The notes include biographical information, and a literary and historical exploration of the piece selected, to discuss the overall theme of the feminine character as she appears in contrasting works. Translations of the texts are included in the body of the text. The pieces discussed are Debussy’s Trois Chansons de Bilitis, Rossini’s “Cruda Sorte!...Già so per practica” from L’Italiana in Algeri, selections from Wolf’s Spaniches Liederbuch, Massenet’s “Va! Laisse couler mes larmes” from Werther, Lori Laitman’s Daughters, Handel’s “In gentle murmurs will I mourn” from Jephtha, and Granados’s La maja dolorosa No. 1, 2, and 3. The graduate recital was given in partial fulfillment of the requirements for the Master of Music degree in vocal performance on March 29th, 2015 performed in All Faiths Chapel at Kansas State University. It featured the piano talents of Amanda Arrington, with the aid of Jillian Emerson on cello, Janice McGregor on violin, and Christopher Gugel on flute.

This thesis examines the interpretation and application of the Criminal Justice Act 2003 (UK), Part 11 Chapter 1, which came into force on 15 December 2004. Part 11 Chapter 1 concerns evidence of bad character, a concept approximately comparable with common law similar fact evidence, in relation to all parties who may be connected with a criminal trial. The admission and use of similar fact evidence has often been the subject of controversy, and the significant changes made by the CJA 2003 have attracted their own body of support and criticism. The nine chapters of this thesis attempt an in-depth study into the impact of the legislation on the robustness and effectiveness of the criminal trial, and consider whether the criminal trial is suited to the level of exposure of bad character now facilitated by the CJA. In particular, the thesis focuses upon the key provisions governing the uses of bad character evidence of the defendant: the seven gateways set out in s 101 of the CJA. The operation of those gateways and their accompanying explanatory provisions is examined through a combination of engagement with the Law Commission’s Report 273 (which preceded the enactment of the legislation), the range of Court of Appeal cases dealing with the legislation, and academic commentary. It was foreshadowed by commentators and early case law that the new provisions might not be easy to interpret or apply, and subsequent cases have borne out this prediction. An analysis of the bad character provisions suggests that, even though the CJA was intended to provide clarity in regulation, it has itself led to confusion in some important respects. Certain central terms lack definition, and some provisions have unintended consequences. The case law reflects this in its frequent, often brief, and sometimes inconsistent analysis of the specific parts of the legislation, which can make it difficult to determine the defendant’s guilt or innocence in a precise and scrupulous manner.

Understanding and synthesizing locomotion of humans and animals will have far-reaching impacts in computer animation, robotic and biomechanics. However, due to the complexity of the neuromuscular control and physical interactions with the environment, computationally modeling these seemingly effortless locomotion imposes a grand challenge for scientists, engineers and artists. The focus of this thesis is to present a set of computational tools, which can simulate the physical environment and optimize the control strategy, to automatically synthesize locomotion for humans and animals. We first present computational tools to study swimming motions for a wide variety of aquatic animals. This method first builds a simulation of two-way interaction between fluid and an articulated rigid body system. It then searches for the most energy efficient way to swim for a given body shape in the simulated hydrodynamic environment. Next, we present an algorithm that can synthesize locomotion of soft body animals that do not have skeleton support. We combine a finite element simulation with a muscle model that is inspired by muscular hydrostat in nature. We then formulate a quadratic program with complementarity condition (QPCC) to optimize the muscle contraction and contact forces that can lead to meaningful locomotion. We develop an efficient QPCC solver that solves a challenging optimization problem at the presence of discontinuous contact events. We also present algorithms to model human locomotion with a passive mechanical device: riding a bicycle in this case. We apply a powerful reinforcement learning algorithm, which can search for both the parametrization and the parameters of a control policy, to enable a virtual human character to perform bicycle stunts in a physically simulated environment. Finally, we explore the possibility to use the computational tools that are developed for computer animation to control a real robot. We develop a simulation calibration technique which reduces the discrepancy between the simulated results and the performance of the robot in the real environments. For certain motion planning tasks, this method can transfer the controllers optimized for a virtual character in a simulation to a robot that operates in a real environment.

Η χρήση του Twitter από ολοένα και περισσότερους ανθρώπους έχει ως συνέπεια την παραγωγή μεγάλου όγκου «υποκειμενικών» δεδομένων. Η ανάγκη για εξεύρεση τυχόν πολύτιμης κρυμμένης πληροφορίας σε αυτά τα δεδομένα, έδωσε ώθηση στην ανάπτυξη ενός νέου πεδίου έρευνας, του Sentiment Analysis, που έχει ως αντικείμενο τον εντοπισμό του συναισθήματος ενός χρήστη (ή μιας ομάδας χρηστών) ως προς κάποιο θέμα. Οι παραδοσιακοί αλγόριθμοι και μέθοδοι εντοπισμού συναισθήματος στηρίζονται στην λεκτική ανάλυση φράσεων ή προτάσεων σε «επίσημα» κείμενα και καλούνται word based approaches. Ωστόσο, το μικρό μέγεθος των κειμένων του Twitter, σε συνδυασμό με την χαλαρότητα της χρησιμοποιούμενης γλώσσας (από πλευράς χρηστών), δεν επιτρέπει την αποτελεσματική χρήση αυτών των τεχνικών. Για τον λόγο αυτό, προτιμάται η χρήση τεχνικών που βασίζονται σε χαρακτήρες (αντί για λέξεις) και καλούνται character based approaches. Στόχος της διπλωματικής εργασίας είναι η εφαρμογή της character based μεθόδου στην ανάλυση tweets πολιτικού περιεχομένου. Συγκεκριμένα, χρησιμοποιήθηκαν δεδομένα από την πολιτική σκηνή των Η.Π.Α., με σκοπό να εντοπιστεί η προτίμηση ενός χρήστη ως προς το Ρεπουμπλικανικό ή το Δημοκρατικό κόμμα μέσω σχετικών tweets. Για την ανάλυση χρησιμοποιήθηκε επιβλεπόμενη μάθηση με την βοήθεια του Naive Bayes ταξινομητή. Αρχικά, συλλέχθηκε ένα σύνολο από 7904 tweets, προερχόμενα από τους επίσημους λογαριασμούς Twitter 48 γερουσιαστών. Το σύνολο αυτό χωρίσθηκε σε δυο επιμέρους σύνολα, το σύνολο εκπαίδευσης και το σύνολο ελέγχου, ελέγχοντας για κάθε μια από τις δυο μεθόδους ανάλυσης (την word based και character based μέθοδο) την ακρίβεια της ταξινόμησης. Από τα πειράματα πρόεκυψε πως η character based μέθοδος ταξινομεί τα tweets με μεγαλύτερη ακρίβεια. Στην συνέχεια συλλέξαμε δυο νέα σύνολα έλεγχου, ένα από τον επίσημο λογαριασμό Twitter του Ρεπουμπλικανικού κόμματος και ένα από τον επίσημο λογαριασμό Twitter του Δημοκρατικού κόμματος. Αυτή την φορά, ως σύνολο εκπαίδευσης χρησιμοποιήθηκε ολόκληρο το αρχικό σύνολο από τα tweets των γερουσιαστών και ελέγχθηκε η ακρίβεια ταξινόμησης για την character based μέθοδο στα δυο νέα σύνολα ελέγχου. Αν και στην περίπτωση του Democratic Twitter account τα αποτελέσματα μπορούν να χαρακτηριστούν ως «ικανοποιητικά», μιας και η ακρίβεια της ταξινόμησης πλησίασε το 80%, για την περίπτωση του Republican Twitter account κάτι τέτοιο δεν ισχύει. Για το λόγο αυτό, προχωρήσαμε σε μια πιο διεξοδική μελέτη της δομής και του περιεχομένου αυτών tweets. Από την ανάλυση προέκυψαν ορισμένα ενδιαφέροντα αποτελέσματα για την προέλευση των χαμηλών ποσοστών στην ακρίβεια ταξινόμησης. Συγκεκριμένα, πρόεκυψε πως στην πλειοψηφία των tweets που έγιναν από τους Ρεπουμπλικάνους γερουσιαστές, δεν περιέχονταν κάποια προσωπική τους άποψη. Ήταν απλά μια αναφορά σε κάποιο άρθρο ή video που είδαν στον διαδίκτυο. Άρα, η πλειοψηφία των tweets αυτών περιέχουν «αντικειμενική» αντί για «υποκειμενική» πληροφορία. Συνεπώς, δεν είναι δυνατόν να εξαχθούν τα χαρακτηριστικά εκείνα που θα βοηθήσουν στον εντοπισμό της πολικότητας των χρηστών. / As more people enter the “social web”, social media platforms are becoming an increasingly valuable source of subjective information. The large volume of social media content available requires automatic techniques in order to process and extract any valuable information. This need recently gave rise to the field of Sentiment Analysis, also known as Opinion Mining. The goal of sentiment analysis is to identify the position of a user (or a group of users – a crowd), with respect to a particular issue or topic. Existing sentiment analysis systems aim at extracting patterns mainly from formal documents with respect to a particular language (most techniques concern English). They either search for discriminative series of words or use dictionaries that assess the meaning and sentiment of specific words and phrases. The limited size of Twitter posts in conjunction with the non-standard vocabulary and shortened words (used by its users) inserts a great deal of noise, making word based approaches ineffective. For all of the above reasons, a new approach was recommended in the literature. This new approach is not based on the study of words but rather on the study of consecutive character sequences (namely character-based approaches). In this work, we demonstrate the superiority of the character based approach over the word based one in determining political sentiment. We argue that this approach can be used in order to efficiently determine the political preference (e.g. Republican or Democrat) of voters or to identify the importance that particular issues have on particular voters. This type of feedback can be useful in the organization of political campaigns or policies. We created a corpus consisting of 7904 tweets, collected from the Twitter accounts of 48 U.S. senators. This corpus was then separated into two sets, the training set and the test set, in order to measure for each method (word and character based) the accuracy of the classification. From the experiments it was found that the character based method classified the tweets with greater accuracy. In the next test, we used two new test sets, one from the official Twitter account of the Republican Party and one from the official Twitter account of the Democratic Party. The main difference, with respect to the previous test, was the use of the total set of tweets collected from the senators’ Twitter accounts as a training set and the use of the tweets from the official Twitter accounts of each party as a test set. Even though from the official Democrat Twitter account, 80% of the tweets were correctly classified as Democrat, for the official Republican Twitter account this is not the case (56.7% accuracy). This was found to be partly because the majority of the Republican account tweets were references to online articles or videos and not the personal opinions or views of the users. In other words, such tweets cannot be characterized as personal (subjective), in order to classify the respective user as leaning towards one party or the other, but rather should be considered as objective.

published_or_final_version / History / Doctoral / Doctor of Philosophy

published_or_final_version / Psychology / Doctoral / Doctor of Philosophy