Colombia’s biggest challenge is to resolve its half-century old armed conflict which began already to affect its neighbours. In this regard, Colombian foreign policy becomes crucial to respond with the internal and external challenges Colombia faces. Colombia has been historically aligned to the United States who has become one of the main destinations of Colombian exports as well as the leading sponsor in the fight against drugs and the guerrilla groups. However, the recent take over of President Juan Manuel Santos in August 2010 seems to have produced a shift in this regard. Santos has tried to increase Colombia’s interaction with other Latin American countries which has triggered several speculations about a move away from Washington, its main ally. Only some months have passed and it is already visible how the existent dynamics between Colombia and other international actors are taking a different shape. This work investigates the causes and possible impacts of this shift in Colombia’s foreign policy on the internal conflict. Supported by an analytical background on the significance of the external conditions surrounding a conflict, this research was conducted by favouring qualitative methods. Presidential interventions and newspaper articles were analysed by applying discourse analysis. The external perceptions were collected using structured interviews with professors, journalists, diplomats within the Andean region. The exploratory results suggest that a shift in the Colombian foreign policy indeed took place and was highly perceived by other international actors. It does not respond to a unique cause but to a set of different motives as for example the disappointment with US policies, economic pragmatism, the isolation of Colombia in South America, among others reasons. Furthermore, it is pointed out the way the shift could affect the conflict as well as feasible scenarios for the future. / Colombia ha sido históricamente uno de los aliados incondicionales de los Estados Unidos. Su políticaexterior se ha dirigido principalmente hacia este país, el cual con el tiempo se convirtió tanto en el mayorcomprador de las exportaciones colombianas, así como en el principal financiador en la lucha contra elnarcotráfico y las guerrillas. No obstante, la reciente toma de posesión del Presidente Juan Manuel Santosel pasado 7 de agosto de 2010, parece haber producido un cambio en este aspecto. El gobierno Santosha hecho un esfuerzo por incrementar las relaciones de Colombia con otros países latinoamericanos locual ha desatado diversas especulaciones sobre un eventual distanciamiento de Washington, su principalaliado. Este artículo investiga si efectivamente se ha dado un cambio en la política exterior colombiana,sus causas, y su eventual impacto en el conflicto armado. Los resultados exploratorios sugieren queefectivamente ha habido un giro en la política exterior colombiana y que tal cambio fue advertido por suspaíses vecinos y otros actores internacionales. Este giro no responde a un sólo motivo si no a múltiplescausas. Adicionalmente, este trabajo señala el impacto de tal cambio en el conflicto armado, así comoposibles escenarios para el futuro.

Field pea (Pisum sativum L.) is an important grain legume in western Canada. Growers can, however, be reluctant to include pulse crops such as field pea in their rotation because they are poor competitors with weeds. This thesis research was conducted to determine whether competitive differences exist among semi-leafless field pea cultivars and to determine the mechanism(s) driving competitive differences. Cultivars included in the studies were chosen on the basis of varying seed size and vine length, which are traits known to confer competitive ability. Differences in competitive ability were identified among cultivars as yield loss ranged from 9% to 31% and 14% to 31% for model weed seed return. However, cultivars were inconsistent in their competitive ranking as cultivars typically performed well for one metric, but not both. None of the traits measured in this study correlated with competitive ability. The greenhouse research was unable to identify the mechanism responsible for these competitive differences. Focal pea plants generally responded to the presence of below-ground neighbours by allocating more resources to shoot production. Therefore, semi-leafless field pea cultivars exhibit differences in below-ground responses to neighbours and it may be useful to include this as part of the selection criteria in breeding programs.

Tuberculosis (TB) is called a disease of poverty and is the main cause of death from infectious diseases among adults. In 1993 the World Health Organisation (WHO) declared TB to be a global emergency; however there were still approximately 1.4 million deaths due to TB in 2011. This thesis contains a detailed study of the existing literature regarding the global risk factors of TB. The risk factors identified from the literature review search which were also available from the NFHS-3 survey were then analysed to determine how well we could identify respondents who are at high risk of TB. We looked at the stigma and misconceptions people have regarding TB and include detailed reports from the existing literature of how a persons wealth, health, education, nutrition, and HIV status affect how likely the person is to have TB. The difference in the risk factor distribution for the TB and non-TB populations were examined and classification trees, nearest neighbours, and logistic regression models were trialled to determine if it was possible for respondents who were at high risk of TB to be identified. Finally gender-specific statistically likely directed acyclic graphs were created to visualise the most likely associations between the variables.

This thesis investigates new clustering paradigms and algorithms based on the principle of the shared nearest-neighbors (SNN. As most other graph-based clustering approaches, SNN methods are actually well suited to overcome data complexity, heterogeneity and high-dimensionality.The first contribution of the thesis is to revisit existing shared neighbors methods in two points. We first introduce a new SNN formalism based on the theory of a contrario decision. This allows us to derive more reliable connectivity scores of candidate clusters and a more intuitive interpretation of locally optimum neighborhoods. We also propose a new factorization algorithm for speeding-up the intensive computation of the required sharedneighbors matrices.The second contribution of the thesis is a generalization of the SNN clustering approach to the multi-source case. Whereas SNN methods appear to be ideally suited to sets of heterogeneous information sources, this multi-source problem was surprisingly not addressed in the literature beforehand. The main originality of our approach is that we introduce an information source selection step in the computation of candidate cluster scores. As shown in the experiments, this source selection step makes our approach widely robust to the presence of locally outlier sources. This new method is applied to a wide range of problems including multimodal structuring of image collections and subspace-based clustering based on random projections. The third contribution of the thesis is an attempt to extend SNN methods to the context of bipartite k-nn graphs. We introduce new SNN relevance measures revisited for this asymmetric context and show that they can be used to select locally optimal bi-partite clusters. Accordingly, we propose a new bipartite SNN clustering algorithm that is applied to visual object's discovery based on a randomly precomputed matching graph. Experiments show that this new method outperformed state-of-the-art object mining results on OxfordBuilding dataset. Based on the discovered objects, we also introduce a new visual search paradigm, i.e. object-based visual query suggestion.

Background: With the increase in automating the performance testing strategies, many efforts have been made to detect the Software Performance Antipatterns (SPAs). These performance antipatterns have become a major threat to software platforms at the enterprise level, and detecting these anomalies is essential in any company dealing with performance-sensitive software as these processes should be performed quite often. Due to the complexity of the process, the manual identification of performance issues has become challenging and time-consuming. Objectives: The thesis aims to address and solve the issues mentioned above by developing a tool that automatically Characterizes and Detects Software Performance Antipatterns. The goal is to automate the parameterization process of the existing approach that helps characterize SPAs and improve the interpretation of detection of SPAs. These two processes are integrated into the tool designed to be deployed in the CI/CD pipeline. The developed tool is named Chanterelle. Methods: A case study and a survey has been used in this research. A case study has been conducted at Ericsson. A similar process as in the existing approach has been automated using python. A literature review is conducted to identify an appropriate approach to improve the interpretation of the detection of SPAs. A static user validation has been conducted with the help of a survey consisting of Chanterelle feasibility and usability questions. The responses are provided by Ericsson staff (developers and tester in the field of Software performance) after the tool is presented. Results: The results indicate that the automated parameterization and detection process proposed in this thesis have a considerable execution time compared to the existing approaches and helps the developers interpret the detection results easily. Moreover, it does not include domain experts t run the tests. The results of the static user validation show that Chanterelle is feasible and usable as a tool to be used by the developers. Conclusions: The validation of the tool suggests that Chanterelle helps the developers to interpret the performance-related bugs easily. It performs the automated parameterization and detection process in a considerable time when compared with the existing approaches.

Förekomsten av friends-and-neighbours-effekten, det vill säga när röstningsmönster är påverkade av geografisk samhörighet mellan politiker och väljare, är ännu outforskad i en svensk kontext. Denna kandidatuppsats undersöker därav förekomsten av friends-and-neighbours-effekten utifrån partiledarens geografiska uppväxtkommun. De sex kommunerna Vingåker, Nacka, Sollefteå, Kristianstad, Täby och Eskilstuna, de tre valåren 2002, 2010 och 2018, samt de två partierna Socialdemokraterna och Moderaterna utgör uppsatsens utgångspunkt. Datamaterial från Svensk valundersökning (SNES) används i logistiska regressionsanalyser för att besvara frågeställningarna om huruvida friends-and-neighbours-effekten finns närvarande i svenska väljares röstningsmönster samt om effekten skiljer sig mellan höger- och vänsterväljare. Resultatet av analyserna redovisas i form av genomsnittliga marginaleffekter (Average Marginal Effects) och tyder framför allt på förekomsten av friends-and-neighbourseffekten i Sollefteå när Stefan Löfvén var partiledare under valåret 2018. I resterande kommuner är effekten inte möjlig att urskilja eller bekräfta. Friends-and-neighbours-effekten är således mer framträdande bland socialdemokratiska än moderata väljare utifrån operationaliseringen av de aktuella variablerna.

Cette thèse s'intéresse au rôle de la cohésion lexicale dans différentes approches de l'analyse du discours. Nous yexplorons deux hypothèses principales:- l'analyse distributionnelle, qui permet de rapprocher des unités lexicales sur la base des contextes syntaxiques qu'ellespartagent, met au jour des relations sémantiques variées pouvant être exploitées pour la détection de la cohésion lexicaledes textes;- les indices lexicaux constituent des éléments de signalisation de l'organisation du discours pouvant être exploités aussibien à un niveau local (identification de relations rhétoriques entre constituants élémentaires du discours) qu'à un niveauglobal (repérage ou caractérisation de segments de niveau supérieur dotés d'une fonction rhétorique et garantissant lacohérence et la lisibilité du texte, par exemple passages à unité thématique).Concernant le premier point, nous montrons la pertinence d'une ressource distributionnelle pour l'appréhension d'une largegamme de relations impliquées dans la cohésion lexicale des textes. Nous présentons les méthodes de projection et defiltrage que nous avons mises en œuvre pour la production de sorties exploitables.Concernant le second point, nous fournissons une série d'éclairages qui montrent l'apport d'une prise en compte réfléchiede la cohésion lexicale pour une grande variété de problématiques liées à l'étude et au repérage automatique del'organisation textuelle: segmentation thématique de textes, caractérisation des structures énumératives, étude de lacorrélation entre lexique et structure rhétorique du discours et enfin détection de réalisations d'une relation de discoursparticulière, la relation d'élaboration. / This thesis considers the role of lexical cohesion in various approaches of discourse analysis. Two main hypotheses arestudied:- distributional analysis, which allows to bring together lexical units based on the syntactic contexts they share, highlightsdiverse semantic relations which can be employed in the detection of lexical cohesion in texts;- lexical cues are involved in discourse signalization and can be used both at a local level (identification of rhetoricalrelations between elementary discourse units) and at a global level (detection or characterization of higher levelsegments).In reference to the first hypothesis, we show that a distributional resource is strongly relevant in the analysis of a widepanel of relations having lexical cohesion roles in texts. We introduce projection and filtering methods for thisdistributional resource.In reference to the second hypothesis, we provide a series of outlooks showing the improvement brought by carefulconsideration of lexical cohesion in a large panel of settings within the study of textual organisation and its automaticdetection: thematic segmentation of texts, enumerative structures characterization, study of the correlation betweenlexicon and the rhetorical structure of discourse, and finally detection of realisations of a specific discourse relation, theElaboration relation.

Cette thèse étudie les méthodes de regroupement basées sur le principe des plus proches voisins partagés (SNN). Comme la plupart des autres approches de clustering à base de graphe, les méthodes SNN sont effectivement bien adaptées à surmonter la complexité des données, l'hétérogénéité et la haute dimensionnalité. La première contribution de la thèse est de revisiter une méthode existante basée sur les voisins partagés en deux points. Nous présentons d'abord un formalisme basé sur la la théorie de décision à contrario. Cela nous permet de tirer des scores de connectivité plus fiable des groupes et une interprétation plus intuitive des voisinage selectionnés optimalement. Nous proposons également un nouveau algorithme de factorisation pour accélérer le calcul intensif nécessaire des matrices des voisins partagés. La deuxième contribution de cette thèse est une généralisation de la classification SNNau cas multi-source. La principale originalité de notre approche est que nous introduisons une étape de sélection des sources d'information optimales dans le calcul de scores de groupes candidats. Chaque groupe est alors associé à son propre sous-ensemble optimal des modalités. Comme le montre le expériences, cette étape de sélection de source rend notre approche largement robuste à la présence de sources locales aberrantes. Cette nouvelle méthode est appliquée à un large éventail de problèmes, y compris la structuration multimodale des collections d'images et dans le regroupement dans des sous-espaces basés sur les projections aléatoires.La troisième contribution de la thèse est une tentative pour étendre les méthodes SNNdans le contexte des graphes biparites. Nous introduisons de nouvelles mesures de pertinence SNNrevisitées pour ce contexte asymétrique et nous montrons qu'elles peuvent être utiliséespour sélectionner localement des voisinages optimales. En conséquence, nous proposons un nouveau algorithme de clustering bipartite SNN qui est appliqué à la découverte d'objets visuels.Les expériences montrent que cette nouvelle méthode est meilleure par rapport aux méthodes de l'état de l'art. Basé sur les objets découverts, nous introduisons également un paradigme de recherche visuelle, c.-à-d les objet basés sur la suggestion de requêtes visuel les. / This thesis investigates new clustering paradigms and algorithms based on the principle of the shared nearest-neighbors (SNN. As most other graph-based clustering approaches, SNN methods are actually well suited to overcome data complexity, heterogeneity and high-dimensionality.The first contribution of the thesis is to revisit existing shared neighbors methods in two points. We first introduce a new SNN formalism based on the theory of a contrario decision. This allows us to derive more reliable connectivity scores of candidate clusters and a more intuitive interpretation of locally optimum neighborhoods. We also propose a new factorization algorithm for speeding-up the intensive computation of the required sharedneighbors matrices.The second contribution of the thesis is a generalization of the SNN clustering approach to the multi-source case. Whereas SNN methods appear to be ideally suited to sets of heterogeneous information sources, this multi-source problem was surprisingly not addressed in the literature beforehand. The main originality of our approach is that we introduce an information source selection step in the computation of candidate cluster scores. As shown in the experiments, this source selection step makes our approach widely robust to the presence of locally outlier sources. This new method is applied to a wide range of problems including multimodal structuring of image collections and subspace-based clustering based on random projections. The third contribution of the thesis is an attempt to extend SNN methods to the context of bipartite k-nn graphs. We introduce new SNN relevance measures revisited for this asymmetric context and show that they can be used to select locally optimal bi-partite clusters. Accordingly, we propose a new bipartite SNN clustering algorithm that is applied to visual object’s discovery based on a randomly precomputed matching graph. Experiments show that this new method outperformed state-of-the-art object mining results on OxfordBuilding dataset. Based on the discovered objects, we also introduce a new visual search paradigm, i.e. object-based visual query suggestion.

Information on the location of mobile nodes in Mobile Ad-hoc Networks (MANETs) has the potential to significantly improve network performance. This thesis uses node location information to develop new techniques for route discovery in on-demand routing protocols such as the Ad-hoc On-Demand Distance Vector (AODV), thus making an important contribution to enhancing the experience of using mobile networks. A Candidate Neighbours to Rebroadcast the Route Request (CNRR) approach has been proposed to reduce the deleterious impact, known as the broadcast storm, of RREQ packets flooding in traditional on-demand routing protocols. The main concept behind CNRR is specifying a set of neighbours which will rebroadcast the received RREQ. This is a departure from the traditional approach of all receiving nodes rebroadcasting RREQs and has the effect of reducing the problem of redundancy from which mobile networks suffer. The proposed protocol has been developed in two phases: Closest-CNRR and Furthest-CNRR. The simulation results show that the proposed algorithms have a significant effect as they reduce the routing overhead of the AODV protocol by up to 28% compared to the C-CNRR, and by up to 17.5% compared to the F-CNRR. Notably, the proposed algorithms simultaneously achieve better throughput and less data dropping. The Link Stability and Energy Aware protocol (LSEA) has been developed to reduce the overhead while increasing network lifetimes. The LSEA helps to control the global dissemination of RREQs in the network by eliminating those nodes that have a residual energy level below a specific threshold value from participation in end-to-end routes. The proposed LSEA protocol significantly increases network lifetimes by up to 19% compared with other on-demand routing protocols while still managing to obtain the same packet delivery ratio and network throughput levels. Furthermore, merging the LSEA and CNRR concepts has the great advantage of reducing the dissemination of RREQs in the network without loss of reachability among the nodes. This increases network lifetimes, reduces the overhead and increases the amount of data sent and received. Accordingly, a Position-based Selective Neighbour (PSN) approach has been proposed which combines the advantages of zoning and link stability. The results show that the proposed technique has notable advantages over both the AODV and MAAODV as it improves delivery ratios by 24.6% and 18.8%, respectively.

David Frič FRIENDS AND NEIGHBOURS EFFECT ON VOTING IN THE KRÁLOVÉHRADECKÝ REGION Abstract This work deals with one of spatially contextual impacts on electoral behavior, namely the so- called friends and neighbours effect. It consists of influencing a voter's favor by the residence of a candidate around which the candidate usually gains more votes than an average for the whole constituency or more votes than would be expected by other criteria. The work verifies attendance and strength of this effect on the example of three kinds of elections in Královéhradecký Region. It analyzes friends and neighbours effect on voting in the elections to the Chamber of Deputies, the Regional Council and the Senate. The results of potency of the effect are examined separately in each of these elections and then compares results of the analyzes of these elections to each other, thereby provides a unique comparative perspective of this phenomenon in the Czech electoral systems. The significance of the friends and neighbours effect is also compared among selected political actors. The main part of the analysis focuses on their electoral results in individual municipalities as well as in the whole region, with regard to differences in results of candidates' hometowns. To illustrate the significance of the friends and...