Ever since we entered the digital communication era, the ease of information sharing through the internet has encouraged online literature searching. With this comes the potential risk of a rise in academic misconduct and intellectual property theft. As concerns over plagiarism grow, more attention has been directed towards automatic plagiarism detection. This is a computational approach which assists humans in judging whether pieces of texts are plagiarised. However, most existing plagiarism detection approaches are limited to super cial, brute-force stringmatching techniques. If the text has undergone substantial semantic and syntactic changes, string-matching approaches do not perform well. In order to identify such changes, linguistic techniques which are able to perform a deeper analysis of the text are needed. To date, very limited research has been conducted on the topic of utilising linguistic techniques in plagiarism detection. This thesis provides novel perspectives on plagiarism detection and plagiarism direction identi cation tasks. The hypothesis is that original texts and rewritten texts exhibit signi cant but measurable di erences, and that these di erences can be captured through statistical and linguistic indicators. To investigate this hypothesis, four main research objectives are de ned. First, a novel framework for plagiarism detection is proposed. It involves the use of Natural Language Processing techniques, rather than only relying on the vii traditional string-matching approaches. The objective is to investigate and evaluate the in uence of text pre-processing, and statistical, shallow and deep linguistic techniques using a corpus-based approach. This is achieved by evaluating the techniques in two main experimental settings. Second, the role of machine learning in this novel framework is investigated. The objective is to determine whether the application of machine learning in the plagiarism detection task is helpful. This is achieved by comparing a thresholdsetting approach against a supervised machine learning classi er. Third, the prospect of applying the proposed framework in a large-scale scenario is explored. The objective is to investigate the scalability of the proposed framework and algorithms. This is achieved by experimenting with a large-scale corpus in three stages. The rst two stages are based on longer text lengths and the nal stage is based on segments of texts. Finally, the plagiarism direction identi cation problem is explored as supervised machine learning classi cation and ranking tasks. Statistical and linguistic features are investigated individually or in various combinations. The objective is to introduce a new perspective on the traditional brute-force pair-wise comparison of texts. Instead of comparing original texts against rewritten texts, features are drawn based on traits of texts to build a pattern for original and rewritten texts. Thus, the classi cation or ranking task is to t a piece of text into a pattern. The framework is tested by empirical experiments, and the results from initial experiments show that deep linguistic analysis contributes to solving the problems we address in this thesis. Further experiments show that combining shallow and viii deep techniques helps improve the classi cation of plagiarised texts by reducing the number of false negatives. In addition, the experiment on plagiarism direction detection shows that rewritten texts can be identi ed by statistical and linguistic traits. The conclusions of this study o er ideas for further research directions and potential applications to tackle the challenges that lie ahead in detecting text reuse.

Large variations in writing styles and difficulties in segmenting cursive words are the main reasons for handwritten cursive words recognition for being such a challenging task. An Indian postal document reading system based on a segmentation-free context based stochastic model is presented. The originality of the work resides on a combination of high-level perceptual features with the low-level pixel information considered by the former model and a pruning strategy in the Viterbi decoding to reduce the recognition time. While the low-level information can be easily extracted from the analyzed form, the discriminative power of such information has some limits as describes the shape with less precision. For that reason, we have considered in the framework of an analytical approach, using an implicit segmentation, the implant of high-level information reduced to a lower level. This enrichment can be perceived as a weight at pixel level, assigning an importance to each analyzed pixel based on their perceptual properties. The challenge is to combine the different type of features considering a certain dependence between them. To reduce the decoding time in the Viterbi search, a cumulative threshold mechanism is proposed in a flat lexicon representation. Instead of using a trie representation where the common prefix parts are shared we propose a threshold mechanism in the flat lexicon where based just on a partial Viterbi analysis, we can prune a model and stop the further processing. The cumulative thresholds are based on matching scores calculated at each letter level, allowing a certain dynamic and elasticity to the model. As we are interested in a complete postal address recognition system, we have also focused our attention on digit recognition, proposing different neural and stochastic solutions. To increase the accuracy and robustness of the classifiers a combination scheme is also proposed. The results obtained on different datasets written on Latin and Bengali scripts have shown the interest of the method and the recognition module developed will be integrated in a generic system for the Indian postal automation.

<p>The literature on J. K. Rowling’s Harry Potter is prolific. People have written on various topics dealing with issues such as translation, etymology and diverse areas concerning the language. In this essay, I examine whether linguistic features such as reporting verbs, adverbs of manner and adjectives contribute to the depiction of heroic and villainous characters. Before conducting this research, my assumptions were that there would be a great difference in the value of the words depending on the character they were associated with. I wanted to see if the heroic characters used verbs and adverbs with positive connotations, and the villainous characters verbs and adverbs with negative connotations. I also wanted to know if the adjectives describing the characters could, in themselves, clearly indicate whether a character was a hero or a villain.</p><p>The results of my research suggested that the choice of particular verbs and adverbs contributed only indirectly to the depiction of the characters. Without context, it was not possible to know if the character was a hero or a villain simply by identifying the verbs and adverbs used to describe their speech. By contrast, the choice of particular adjectives did appear to indicate more clearly whether a character was hero or villain. Finally, the results of my research indicated that context, rather than the use of particular linguistic features was often the most important factor in contributing to the portrayal of characters in the novel.</p>

近年來電腦計算能力的進步使得3D虛擬環境得到廣泛的應用。本研究希望能在虛擬環境中結合人體動畫和音樂的特色，以人體動畫來詮釋音樂。我們希望能設計一個智慧型的人體動作產生器，賦予虛擬人物表達音樂特徵的能力，讓動作會因為“聽到”不同的音樂而有所不同。基於人類聽覺的短暫性，系統會自動抓取音樂特徵後將音樂切割成多個片段、對每一片段獨立規劃動作並產生動畫。過去動畫與音樂相關的研究中，許多生成的動作都經由修改或重組運動資料庫中的動作。本研究分析音樂和動作之間的關係，使用程序式動畫產生法自動產生多變且適當的詮釋動作。實驗顯示本系統能通用於LOA1人體模型和MIDI音樂；此外，透過調整系統中的參數，我們能產生不同風格的動畫，以符合不同使用者偏好和不同音樂曲風的特色。 / In recent years, the improvement of computing ability has contributed to the　wide application of 3D virtual environment. In the thesis, we propose to combine character animation with music for music interpretation in 3D virtual environment. The system proposed in the thesis is an intelligent avatar motion generator, which generates expressive motions according to music features. The system can extract music features from input music data, segment a music into several music segments, and then plan avatar animation. In the literature, much music-related animation research uses reconstruction and modification of existing motion to compose new animations. In this work, we analyze the relationship between music and motions, and then use procedural animation to automatically generate applicable and variable motions to interpret music. Our experiments show that the system can accept LOA1 models and midi as inputs in general, and generate appropriate expressive motions by modifying parameters according to users’ preference or music style.

Darbo tikslas – išnagrinėti Stakliškių miestelio istorijos raidą XVII–XX a. pirmojoje pusėje. Iki šiol Stakliškių miestelio istorijos kompleksinio tyrimo nebuvo atlikta. Nors vieni ar kiti tyrinėtojai užfiksavo svarbesnius miestelio raidos įvykius, tačiau nuoseklaus vientiso tyrimo neatliko. Todėl ši priežastis paskatino autorę imtis tokio tyrimo. Autorės atrasti nauji, netyrinėti archyviniai šaltiniai svariai papildys turimą informaciją apie Stakliškes. Jie į mokslinę apyvartą įtraukiami pirmą kartą. Visuomenine prasme aktuali tema: auga visuomenės susidomėjimas Stakliškių miestelio istorija, jo paveldu. Ši priežastis paskatino parengti nuoseklią Stakliškių miestelio istorijos studiją. Subjektyvus-asmeninis noras detaliau pažinti gimtojo krašto istoriją, su ja supažindinti miestelio bendruomenę ir moksleivius. Šiuo metu naujoje švietimo koncepcijoje yra akcentuojama, kad mokyklose istorijos mokymą reikia pradėti nuo lokalinės istorijos (savo gatvės, kaimo/miesto, rajono) mokymo ir pereiti prie valstybės istorijos pažinimo. Tačiau dėl informacijos apie gimtąjį kraštą trūkumo, daugeliu atvejų tai neįmanoma padaryti. Todėl autorė siekė užpildyti Stakliškių miestelio istorijos tyrimų spragą. / The subject of this work for the Master of Science is the history of the Town of Stakliskes during the 17th Century through the first half of 20th Century. The work consists of introduction, 3 chapters with sections, conclusion, listings of abbreviations, sources and bibliography, as well as the enclosures. This kind of job structure was influenced by the chronological-problematic job research principal. The author discussing the historic development of the Town of Stakliskes, by distinguishing its most important stages, describing the stages of its religions heritage, and identifying its population’s demographic, social-economic, religious and cultural-public work during that historic period. Therefore the historic development of the events are outlined in the first chapter of this work, together with explanation of the most important factors (the origin of the estate and the church in Stakliskes). The second chapter talks about the history of the church in Stakliskes, its architectural style and the preservation of artistic and historic values. In the third chapter of this work the author analyzes the population situation and its social work during the 17th Century through the first half of 20th Century. This work is enriched with the enclosures, which include statistic tables with the population census in the 19th Century, created by the author. Also included are a variety of the church archival documents, which are exposed for the first time. Finally, there are... [to full text]

This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures. The first stage of our system allows detecting and tracking a bare hand in a cluttered background using face subtraction, skin detection and contour comparison. The second stage allows recognizing hand gestures using bag-of-features and multi-class Support Vector Machine (SVM) algorithms. Finally, a grammar has been developed to generate gesture commands for application control. Our hand gesture recognition system consists of two steps: offline training and online testing. In the training stage, after extracting the keypoints for every training image using the Scale Invariance Feature Transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multi-class SVM to build the classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using my algorithm. Then, the keypoints are extracted for every small image that contains the detected hand posture and fed into the cluster model to map them into a bag-of-words vector, which is fed into the multi-class SVM classifier to recognize the hand gesture. Another hand gesture recognition system was proposed using Principle Components Analysis (PCA). The most eigenvectors and weights of training images are determined. In the testing stage, the hand posture is detected for every frame using my algorithm. Then, the small image that contains the detected hand is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined among the test weights and the training weights of each training image to recognize the hand gesture. Two application of gesture-based interaction with a 3D gaming virtual environment were implemented. The exertion videogame makes use of a stationary bicycle as one of the main inputs for game playing. The user can control and direct left-right movement and shooting actions in the game by a set of hand gesture commands, while in the second game, the user can control and direct a helicopter over the city by a set of hand gesture commands.

Cette thèse porte sur les traits de personnalité associés aux comportements délinquants. De façon plus spécifique, elle s’intéresse à la contribution des traits de personnalité psychopathiques évalués à l’adolescence pour prédire les conduites délinquantes au début de l’âge adulte, lorsque sont également considérés des indices comportementaux. Elle s’inscrit dans le cadre d’une étude longitudinale plus large destinée à décrire les adolescents des Centres jeunesse du Québec. Aux fins de la thèse, un sous-groupe de jeunes, de sexe masculin, a été sélectionné : ces jeunes présentent un trouble des conduites ou ont manifesté des comportements délinquants au cours de l’adolescence. Cette sélection vise à cerner les adolescents les plus susceptibles de présenter des traits psychopathiques, eu égard à la faible prévalence du trouble dans la population générale. Quarante-huit adolescents ont accepté de participer à l'entrevue utilisant la PCL-SV (Psychopathy Checklist Screening Version). Un premier volet de la thèse valide, au Québec, une version française d’une mesure de la psychopathie adaptée à l'adolescence, la PCL-SV. Les indices de fidélité et de validité sont satisfaisants et comparables à ce qui est rapporté avec d’autres versions de la PCL auprès d’adolescents et d’adultes. Les résultats appuient la pertinence de son utilisation auprès des adolescents. Un second volet du projet porte sur la contribution d’une mesure des traits psychopathiques à l’adolescence à la prédiction des conduites délinquantes au début de l’âge adulte. Les traits psychopathiques, tels qu’évalués à l’aide de la PCL-SV, sont un apport significatif aux indices de comportements délinquants dans la prédiction des conduites délinquantes autorapportées deux ans plus tard. Finalement, un dernier volet explore une approche dimensionnelle dans la conceptualisation de la psychopathie, sous l’angle d’un modèle général de la personnalité : le Modèle à cinq facteurs (MCF). Ce volet porte sur la capacité de ce modèle, alternative au modèle catégoriel, à distinguer des jeunes au plan de la gravité de leur délinquance. Les jeunes présentant une délinquance distinctive ont une plus forte propension à rechercher les sensations fortes que ceux dont la délinquance est générale. Les résultats mettent en lumière l’importance d’une composante d’impulsivité comme élément caractéristique d’un sous-groupe de jeunes présentant une délinquance distinctive. L’étude appuie l’utilisation d’un modèle général de la personnalité pour cerner des traits associés à la psychopathie, permettant ainsi d’identifier un noyau dur de délinquants. L’ensemble du projet permet d’établir la valeur ajoutée d’une mesure des traits psychopathiques à l’adolescence pour la prédiction des conduites délinquantes. Il met en lumière l’importance d’une composante d’impulsivité chez les jeunes impliqués dans une délinquance distinctive. C’est l’une des rares études longitudinales s’intéressant à la délinquance autorapportée et à la psychopathie sous l’angle des facettes du MCF chez des adolescents. Il y a une telle hétérogénéité parmi les jeunes délinquants qu’une mesure valide de la psychopathie à l’adolescence permettra une identification plus fiable des jeunes susceptibles de poursuivre leur trajectoire criminelle à l’âge adulte. Les implications cliniques des résultats et les recommandations pour des recherches futures sont reprises dans la conclusion de l’ouvrage. / This thesis is interested in personality traits associated with delinquent behavior. More specifically, it seeks to clarify the contribution of psychopathic personality traits assessed in adolescence to predict antisocials behaviors in early adulthood, when are also considered behavioral indices. It is part of a broader longitudinal study aimed at describing adolescents in the care of Quebec Youth Centres. For research purposes, a subgroup of young males has been selected; those with a conduct disorder or who have exhibited delinquent behaviors during adolescence. The purpose of such a selection was to identify young people who are most likely to have psychopathic traits, given the low prevalence of the disorder in the general population. Forty-eight teenagers have agreed to participate in the interview using the PCL-SV (Psychopathy Checklist Screening Version). A first shutter of the thesis validates, in Quebec, a French version of a measurement of psychopathy adapted for a use with teenagers, the PCL-SV. Results show indices of fidelity and validity satisfactory and comparable with what is brought back with other versions of the PCL used with teenagers and adults. They support the relevance of its use with teenagers. A second part of the dissertation verifies the contribution of psychopathic traits in adolescence to predict antisocial conduct in early adulthood. Results show that psychopathic traits, as measured by the PCL-SV, make a significant contribution above and beyond indices of delinquent behavior to predict self-reported antisocial conduct two years later. Finally, a last chapter explores a dimensional approach in the conceptualization of psychopathy, in terms of a general model of personality: the Five Factor Model (FFM). It seeks to determine its ability to distinguish youths with conduct disorders in terms of the severity of their delinquency. Results show that youths with a serious delinquency have a higher propensity to seek sensations than those whose delinquency is weak. Results highlight the importance of impulsivity as a characteristic element of a subgroup of youths with serious delinquency. The study supports the use of a general model of personality to capture features associated with psychopathy and to identify a hard core of delinquents. The entire project establishes the added-value of a measure of psychopathic traits in adolescence in predicting antisocial behavior. It highlights the importance of a component of impulsivity among youth involved in serious delinquency. This is one of the few longitudinal studies concerned with self-reported delinquency and psychopathy in terms of the facets of the FFM in adolescents. There is such heterogeneity among young offenders; a valid measure of psychopathy in adolescence will allow more specific types and a more reliable identification of young people likely to continue their criminal career into adulthood. Clinical implications of the findings and recommendations for future research are included in the conclusion of the thesis.

Nous étudions dans cette thèse une représentation particulière de signaux fondée sur une méthode d’apprentissage statistique, qui consiste à modéliser des données comme combinaisons linéaires de quelques éléments d’un dictionnaire appris. Ceci peut être vu comme une extension du cadre classique des ondelettes, dont le but est de construire de tels dictionnaires (souvent des bases orthonormales) qui sont adaptés aux signaux naturels. Un succès important de cette approche a été sa capacité à modéliser des imagettes, et la performance des méthodes de débruitage d’images fondées sur elle. Nous traitons plusieurs questions ouvertes, qui sont reliées à ce cadre : Comment apprendre efficacement un dictionnaire ? Comment enrichir ce modèle en ajoutant une structure sous-jacente au dictionnaire ? Est-il possible d’améliorer les méthodes actuelles de traitement d’image fondées sur cette approche ? Comment doit-on apprendre le dictionnaire lorsque celui-ci est utilisé pour une tâche autre que la reconstruction de signaux ? Y a-t-il des applications intéressantes de cette méthode en vision par ordinateur ? Nous répondons à ces questions, avec un point de vue multidisciplinaire, en empruntant des outils d’apprentissage statistique, d’optimisation convexe et stochastique, de traitement des signaux et des images, de vison par ordinateur, mais aussi d'optimisation sur des graphes. / We study in this thesis a particular machine learning approach to represent signals that that consists of modelling data as linear combinations of a few elements from a learned dictionary. It can be viewed as an extension of the classical wavelet framework, whose goal is to design such dictionaries (often orthonormal basis) that are adapted to natural signals. An important success of dictionary learning methods has been their ability to model natural image patches and the performance of image denoising algorithms that it has yielded. We address several open questions related to this framework: How to efficiently optimize the dictionary? How can the model be enriched by adding a structure to the dictionary? Can current image processing tools based on this method be further improved? How should one learn the dictionary when it is used for a different task than signal reconstruction? How can it be used for solving computer vision problems? We answer these questions with a multidisciplinarity approach, using tools from statistical machine learning, convex and stochastic optimization, image and signal processing, computer vision, but also optimization on graphs.

Detection and positioning of anatomical landmarks, also called points of interest(POI), is often a concept of interest in medical image processing. Different measures or automatic image analyzes are often directly based upon positions of such points, e.g. in organ segmentation or tissue quantification. Manual positioning of these landmarks is a time consuming and resource demanding process. In this thesis, a general method for positioning of anatomical landmarks is outlined, implemented and evaluated. The evaluation of the method is limited to three different POI; left femur head, right femur head and vertebra T9. These POI are used to define the range of the abdomen in order to measure the amount of abdominal fat in 3D data acquired with quantitative magnetic resonance imaging (MRI). By getting more detailed information about the abdominal body fat composition, medical diagnoses can be issued with higher confidence. Examples of applications could be identifying patients with high risk of developing metabolic or catabolic disease and characterizing the effects of different interventions, i.e. training, bariatric surgery and medications. The proposed method is shown to be highly robust and accurate for positioning of left and right femur head. Due to insufficient performance regarding T9 detection, a modified method is proposed for T9 positioning. The modified method shows promises of accurate and repeatable results but has to be evaluated more extensively in order to draw further conclusions.

This thesis explores cultural differences on interactive design features used in websites of South Korea and the United Kingdom from the perspective of both: professional website designers and end-users. It also investigates how the use of interactive design features from different cultures change over time. Four interaction types on websites; User to Interface (U2I), User to Content (U2C), User to Provider (U2P), and User to User (U2U) interactivity, and three interaction types on blogs; Blogger to Interface (B2I), Blogger to Content (B2C) and Blogger to Blogger (B2B) interactivity have been identified. Four cultural dimensions were used for the theoretical base of this study based on which four hypotheses were proposed in relation to the interaction types identified above; (a) High versus Low Context cultures for U2I, (b) High versus Low Uncertainty Avoidance for U2C, (c) High versus Low Power Distance for U2P and (d) Individualism versus Collectivism for U2U interactivity, in order to discover the effects of national cultures on interactivity in websites. We derived our own interactivity dimensions and mapped them to the four interaction types for websites and three for blogs. Interactive design features were derived from interactivity dimensions and examined in our studies. The findings revealed that there have been some changes towards homogeneity in the use of interactive design features on charity websites between South Korea and United Kingdom although there is still evidence of some cultural differences. With regard to end-users’ perspective, the result show that the use of interactive design features of blogs may be influenced by culture but this is only within a certain context. The findings also provide a valuable indication that users interacting within the same blog service can be considered as being shared concerns rather than shared national location, thus create a particular type of community in which bloggers are affected by social influence so they adopt a shared set of value, preferences and style that would indicate almost a common social culture. As a result, the cultural differences derived from their country of origin do not have that much impact.