Clustering is the process in which data is differentiated, classified according to some criteria. As a result of partitioning process, data is grouped into clusters for specific purpose. In a social network, clustering of people is one of the most popular problems. Therefore, we mainly concentrated on finding an efficient algorithm for this problem. In our study, data is made up of two types of entities (e.g., people, groups vs. political issues, religious beliefs) and distinct from most previous works, signed weighted bipartite graphs are used to model relations among them. For the partitioning criterion, we use the strength of the opinions between the entities. Our main intention is to partition the data into k-clusters so that entities within clusters represent strong relationship. One such example from a political domain is the opinion of people on issues. Using the signed weights on the edges, these bipartite graphs can be partitioned into two or more clusters. In political domain, a cluster represents strong relationship among a group of people and a group of issues. After partitioning, each cluster in the result set contains like-minded people and advocated issues. Our work introduces a general mechanism for k-way partitioning of signed bipartite graphs. One of the great advantages of our thesis is that it does not require any preliminary information about the structure of the input dataset. The idea has been illustrated on real and randomly generated data and promising results have been shown.

The purpose of this study is to investigate whether the location of buying stocks in a Nordic cross-listed company matters in terms of 1) earning abnormal returns, or 2) gaining in optimizing the amount spent by buying the specific stock cheap. Nowadays, markets are becoming more integrated and if we believe in the efficient market hypothesis, prices of the same class of stocks paying the same dividend annually, of an MNC must be the same irrespective of the stock exchange it is listed upon. Though efficient market hypothesis exists in theory, market imperfection is a reality. All the Nordic (Swedish, Finnish, Norwegian, Danish and Icelandic) firms listed on foreign stock exchanges in addition to their home market have been included in the sample. In fact, this sample represents 100% of the population. The daily prices of cross-listed stocks have been analyzed and conclusions have been drawn based on the mean returns and mean prices along with Wilcoxon Signed-Rank test statistics. The data have been analyzed over the last ten years capturing the recent economic cycle. The whole period has also been divided into three sub-periods to establish comparisons with the whole period. This paper reports that even though returns on cross-listed stocks are statistically same over all periods, prices of the stocks vary according to the location of listing. That is, investors can buy from a stock exchange where the specific stock is underpriced thereby decreasing the amount invested in absolute term and optimizing the amount spent if not the return. The returns and prices have analyzed using the local currency of the MNC’s country of origin and Special Drawing Rights (SDRs). No considerable differences on the returns or pattern of price movements have been observed while using two currencies.

Dans cette thèse, nous considérons des questions relatives aux homomorphismes de quatre types distincts de graphes : les graphes orientés, les graphes orientables, les graphes 2-arête colorés et les graphes signés. Pour chacun des ces quatre types, nous cherchons à déterminer le nombre chromatique, le nombre de clique relatif et le nombre de clique absolu pour différentes familles de graphes planaires : les graphes planaires extérieurs, les graphes planaires extérieurs de maille fixée, les graphes planaires et les graphes planaires de maille fixée. Nous étudions également les étiquetages "2-dipath" et "L(p,q)" des graphes orientés et considérons les catégories des graphes orientables et des graphes signés. Nous étudions enfin les différentes relations pouvant exister entre ces quatre types d'homomorphismes de graphes.

Title: Binary Signed Digit Representations of Integers in Cryptanalysis of Hash Functions Author: Jiří Vábek Department: Department of Algebra Supervisor: doc. RNDr. Jiří Tůma, DrSc., Department of Algebra Abstract: The work summarizes two main papers, A New Type of 2-block Colli- sions in MD5 and On the Number of Binary Signed Digit Representations of a Given Weight, while containing also the wider introduction to the topic of crypt- analysis of MD5 and binary signed digit representations (BSDR's). In the first paper we have implemented and applied Stevens algorithm to the newly proposed initial message differences and constructed a new type of collisions in MD5. In the second paper we have introduced and proved a new improved bound for the number of optimal BSDR's and also a new recursive bound for the number of BSDR's of a given integer with a given overweight. In addition to the results in mentioned papers, the generalized result is stated with the new bound for the number of optimal D-representations of natural numbers with D = {0, 1, 3}. Keywords: hash function, MD5, binary signed digit representation (BSDR), non- adjacent form (NAF) 1

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação tem como objetivo aplicar um algoritmo genético (GA) ao projeto de filtros FIR com coeficientes quantizados representados em somas de potências de dois com sinal (SPT). Os filtros FIR apresentam configurações que permitem a obtenção de fase linear, atributo desejado em diversas aplicações que necessitam de atraso de grupo constante. A representação SPT, de fácil implementação em circuitos, foi discutida e uma comparação das representações SPT mínimas e canônicas foi feita, baseada no potencial de redução de operações e na variedade de valores representáveis. O GA é aplicado na otimização dos coeficientes SPTs do filtro, para que este cumpra as suas especificações de projeto. Foram feitas análises sobre o efeito que diversos parâmetros do GA como a intensidade de seleção, tamanho das populações, cruzamento, mutação, entre outros, têm no processo de otimização. Foi proposto um novo cruzamento que produz a recombinação dos coeficientes e que obteve bons resultados. Aplicou-se o algoritmo obtido na produção de filtros dos tipos passa-baixas, passa-altas, passa-faixas e rejeita-faixas.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação tem como objetivo aplicar um algoritmo genético (GA) ao projeto de filtros FIR com coeficientes quantizados representados em somas de potências de dois com sinal (SPT). Os filtros FIR apresentam configurações que permitem a obtenção de fase linear, atributo desejado em diversas aplicações que necessitam de atraso de grupo constante. A representação SPT, de fácil implementação em circuitos, foi discutida e uma comparação das representações SPT mínimas e canônicas foi feita, baseada no potencial de redução de operações e na variedade de valores representáveis. O GA é aplicado na otimização dos coeficientes SPTs do filtro, para que este cumpra as suas especificações de projeto. Foram feitas análises sobre o efeito que diversos parâmetros do GA como a intensidade de seleção, tamanho das populações, cruzamento, mutação, entre outros, têm no processo de otimização. Foi proposto um novo cruzamento que produz a recombinação dos coeficientes e que obteve bons resultados. Aplicou-se o algoritmo obtido na produção de filtros dos tipos passa-baixas, passa-altas, passa-faixas e rejeita-faixas.

The ability to automatically estimate the volume of timber is becoming increasingly important within the timber industry. The large number of timber trucks arriving each day at Swedish timber terminals fortifies the need for a volume estimation performed in real-time and on-the-go as the trucks arrive. This thesis investigates if a volumetric integration of disparity maps acquired from a Multi-View Stereo (MVS) system is a suitable approach for automatic volume estimation of timber loads. As real-time execution is preferred, efforts were made to provide a scalable method. The proposed method was quantitatively evaluated on datasets containing two geometric objects of known volume. A qualitative comparison to manual volume estimates of timber loads was also made on datasets recorded at a Swedish timber terminal. The proposed method is shown to be both accurate and precise under specific circumstances. However, robustness is poor to varying weather conditions, although a more thorough evaluation of this aspect needs to be performed. The method is also parallelizable, which means that future efforts can be made to significantly decrease execution time.

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Dans cette thèse, nous étudions la sémantique des relations entre les utilisateurs et des forces antagonistes que nous observons naturellement dans diverses relations sociales, comme hostilité ou méfiance. L'étude de ces relations soulève de nombreux problèmes à la fois techniques, puisque l'arsenal mathématique n'est souvent pas adapté aux liens négatifs, mais aussi pratiques à cause de la difficulté rencontrée pour collecter de telles données (expliciter une relation négative est perçu comme malvenu pour de nombreux utilisateurs). Nous nous intéressons alors aux solutions alternatives de collecte afin d'inférer ces relations négatives à partir d'autres contenus. En particulier, nous allons utiliser les jugements communs que les utilisateurs partagent à propos d'items (données des systèmes de recommandation). Nous apportons trois contributions. Dans la première, nous allons aborder le cas des accords sur les items qui peuvent ne pas avoir la même sémantique selon qu'ils concernent des items appréciés ou non par les utilisateurs. Nous verrons que le fait de ne pas aimer un même produit n'est pas synonyme de similarité. Ensuite, nous allons prendre en compte dans notre seconde contribution les distributions de notes des utilisateurs et des items afin de mesurer si les accords ou les désaccords arrivent par hasard ou non, afin notamment d'éviter les conséquences des différents biais utilisateurs et items présents dans ce type de données. Enfin, notre troisième contribution consistera à exploiter ces différents résultats afin de prédire le signe des liens entre utilisateurs à partir des seuls jugements communs à propos des items et sans aucune information sociale négative. / In this thesis, we study the semantic of relations between users and, in particular, the antagonistic forces we naturally observe in various social relationships, such as hostility or suspicion. The study of these relationships raises many problems both techniques - because the mathematical arsenal is not really adapted to the negative ties - and practical, due to the difficulty of collecting such data (explaining a negative relationship is perceived as intrusive and inappropriate for many users). That’s why we focus on the alternative solutions consisting in inferring these negative relationships from more widespread content. We use the common judgments about items the users share, which are the data used in recommender systems. We provide three contributions, described in three distinct chapters. In the first one, we discuss the case of agreements about items that may not have the same semantics if they involve appreciated items or not by two users. We will see that disliking the same product does not mean similarity. Afterward, we consider in our second contribution the distributions of user ratings and items ratings in order to measure whether the agreements or disagreements may happen by chance or not, in particular to avoid the user and item biases observed in this type of data. Our third contribution consists in using these results to predict the sign of the links between users from the only positive ties and the common judgments about items, and then without any negative social information.