This thesis addresses the problem of improving the delineation of skylines, also referred to as skyline detection, in occluded and challenging environments where existing skyline delineation methods may struggle or fail. Delineated skylines can be used in monocular camera localization methods by comparing delineated skylines to digital elevation model data to estimate a position based on known terrain. This is particularly useful in GPS-denied environments in which active sensing is either impractical or undesirable for various reasons, so that passive sensing using monocular cameras is necessary and/or strategically advantageous. This thesis presents a novel method of skyline delineation using deep learning-based semantic segmentation of monocular camera images to detect natural skylines of distant landscapes in the presence of occlusions. Skylines are extracted from semantic segmentation predictions as the boundary between pixel clusters labeled as terrain to those labeled as sky, with additional segmentation classes representing the known set of potential occlusions in a given environment. Additionally, each pixel in the detected skyline contours are assigned a confidence score based on local intensity gradients to reduce the potential impacts of erroneous skyline contours on position estimation. The utility of these delineated skylines is demonstrated by obtaining orientation and position estimates using existing methods of skyline-based localization. In these methods, the delineated natural skyline is compared to rendered skylines using digital elevation model data and the position estimate is obtained by finding the closest match. Results from the proposed skyline delineation method using semantic segmentation, with accompanying localization demonstration, is presented on two distinct data sets. The first is obtained from the Perseverance Rover operating in the Jezero Crater region of Mars, and the second is obtained from an uncrewed surface vessel operating in the Gulf of Koper, Slovenia. / Denna avhandling tar upp problemet med att förbättra avgränsningen av skylines, även kallad skylinedetektion, i tilltäppta och utmanande miljöer där befintliga skylineavgränsningsmetoder kan kämpa eller misslyckas. Avgränsade skylines kan användas i monokulära kameralokaliseringsmetoder genom att jämföra avgränsade skylines med digitala höjdmodelldata för att uppskatta en position baserat på känd terräng. Detta är särskilt användbart i GPS-nekas miljöer där aktiv avkänning är antingen opraktisk eller oönskad av olika skäl, så att passiv avkänning med användning av monokulära kameror är nödvändig och/eller strategiskt fördelaktig. Denna avhandling presenterar en ny metod för skylineavgränsning med användning av djupinlärningsbaserad semantisk segmentering av monokulära kamerabilder för att detektera naturliga skylines av avlägsna landskap i närvaro av ocklusioner. Horisonter extraheras från semantiska segmenteringsförutsägelser som gränsen mellan pixelkluster märkta som terräng till de märkta som himmel, med ytterligare segmenteringsklasser som representerar den kända uppsättningen potentiella ocklusioner i en given miljö. Dessutom tilldelas varje pixel i de detekterade skylinekonturerna ett konfidenspoäng baserat på lokala intensitetsgradienter för att minska den potentiella påverkan av felaktiga skylinekonturer på positionsuppskattning. Användbarheten av dessa avgränsade skylines demonstreras genom att erhålla orienterings- och positionsuppskattningar med hjälp av befintliga metoder för skylinebaserad lokalisering. I dessa metoder jämförs den avgränsade naturliga horisonten med renderade silhuetter med hjälp av digitala höjdmodelldata och positionsuppskattningen erhålls genom att hitta den närmaste matchningen. Resultat från den föreslagna metoden för skylineavgränsning med semantisk segmentering, med tillhörande lokaliseringsdemonstration, presenteras på två distinkta datamängder. Den första kommer från Perseverance Rover som verkar i Jezero Crater-regionen på Mars, och den andra erhålls från ett obemannat ytfartyg som verkar i Koperbukten, Slovenien.

Cable logging will become more important as harvesting shifts to greater annual proportions on steep terrain in New Zealand. The costs of cable logging are considerably higher than that of conventional ground-based methods. Improving cost-effectiveness has been identified as key to ensuring the forestry industry remains cost competitive in the international market. This thesis focuses on ways to better understand and improve cable logging methods by specifically focusing on rigging configurations. The investigation was conducted through a comprehensive literature review, an industry survey to establish current use and preferences, a Delphi survey with experts to establish actual advantages and disadvantages, scale model testing to establish some fundamental knowledge of tension to deflection relationship, and finally a series of targeted case studies to establish both productivity and skyline tension in actual operations. Each of these aspects of the research topic employed different methodology. The literature review highlighted the most relevant research relating to cable logging world-wide spanning nearly a century. Various research papers, manuals, books and computer software were summarized. While many aspects of cable yarding operations have been investigated, much of it focusing on various aspects of operational efficiency through case studies, there is very limited information with regard to rigging configurations. The survey of 50 cable logging practitioners determined what rigging configurations were commonly used in New Zealand. It includes their perceived advantages and disadvantages for varying levels of deflection, but also for specific scenarios such as pulling away from native forest boundaries and flying logs over a stream. Results showed that there were many conflicting perceptions about rigging configuration options. Using an expert panel, a Delphi process was used to derive consensus on what advantages were truly unique to each configuration. This allowed the longer lists of perceived advantages from the industry survey to be pared down to a concise list of ad/disadvantages that will be used in the updating of the Best Practice Guidelines for Cable Logging. To increase our fundamental understanding of tension / payload / deflection relationships, an experiment was conducted in a controlled environment. Using a model yarder in a lab and continuous tension and video recording devices, the dynamic skyline behavior of three similar configurations were tested: North Bend, South Bend and Block in the Bight. The tensions were compared by use of a two-way analysis of variance, which indicated configuration and choker length were significant variables in some but not all of the dynamic load tests. Results also showed that some configurations performed better than others in minimizing the shock loads due to dropping into full suspension, impact with ground objects, and breakout during bridling. Finally, a series of eight studies were conducted on targeted logging operations where relevant stand and terrain parameters were related to the continuous skyline tension monitoring, and recording of productivity through time study. The three targeted configurations included (1) North Bend, (2) Standing skyline using a motorized slack-pulling carriage and (3) a live skyline using a motorized grapple carriage. Results showed that peak and average tensions, as well as amplification factors and the payload to tension relationship, varied between configurations. The study also showed that tensions could be collected to compute measures of payload and tension efficiency, which provided insight into operational performance. The safe working load was exceeded in 53% of all cycles studied and across seven of eight study sites and 14 of 16 spans. Cycle times were significantly different between rigging configurations and that production information could be used to compute measures of labor and energy consumption as well as payload and tension efficiency; which also provide insight into operational performance. The industry should give serious consideration to the use of tension monitors. Tension monitors have many benefits and have the potential to improve cable logging operations in New Zealand. Monitoring tensions can help one learn new techniques or methods (i.e. rigging configurations), help improve payload analysis software for future planning and help evaluate new technology and machinery.

In the era of "big data revolution," marked by an exponential growth of information, extracting value from data enables analysts and businesses to address challenging problems such as drug discovery, fraud detection, and earthquake predictions. Multi-Criteria Decision Support (MCDS) queries are at the core of big-data analytics resulting in several classes of MCDS queries such as OLAP, Top-K, Pareto-optimal, and nearest neighbor queries. The intuitive nature of specifying multi-dimensional preferences has made Pareto-optimal queries, also known as skyline queries, popular. Existing skyline algorithms however do not address several crucial issues such as performing skyline evaluation over disparate sources, progressively generating skyline results, or robustly handling workload with multiple skyline over join queries. In this dissertation we thoroughly investigate topics in the area of skyline-aware query evaluation. In this dissertation, we first propose a novel execution framework called SKIN that treats skyline over joins as first class citizens during query processing. This is in contrast to existing techniques that treat skylines as an "add-on," loosely integrated with query processing by being placed on top of the query plan. SKIN is effective in exploiting the skyline characteristics of the tuples within individual data sources as well as across disparate sources. This enables SKIN to significantly reduce two primary costs, namely the cost of generating the join results and the cost of skyline comparisons to compute the final results. Second, we address the crucial business need to report results early; as soon as they are being generated so that users can formulate competitive decisions in near real-time. On top of SKIN, we built a progressive query evaluation framework ProgXe to transform the execution of queries involving skyline over joins to become non-blocking, i.e., to be progressively generating results early and often. By exploiting SKIN's principle of processing query at multiple levels of abstraction, ProgXe is able to: (1) extract the output dependencies in the output spaces by analyzing both the input and output space, and (2) exploit this knowledge of abstract-level relationships to guarantee correctness of early output. Third, real-world applications handle query workloads with diverse Quality of Service (QoS) requirements also referred to as contracts. Time sensitive queries, such as fraud detection, require results to progressively output with minimal delay, while ad-hoc and reporting queries can tolerate delay. In this dissertation, by building on the principles of ProgXe we propose the Contract-Aware Query Execution (CAQE) framework to support the open problem of contract driven multi-query processing. CAQE employs an adaptive execution strategy to continuously monitor the run-time satisfaction of queries and aggressively take corrective steps whenever the contracts are not being met. Lastly, to elucidate the portability of the core principle of this dissertation, the reasoning and query processing at different levels of data abstraction, we apply them to solve an orthogonal research question to auto-generate recommendation queries that facilitate users in exploring a complex database system. User queries are often too strict or too broad requiring a frustrating trial-and-error refinement process to meet the desired result cardinality while preserving original query semantics. Based on the principles of SKIN, we propose CAPRI to automatically generate refined queries that: (1) attain the desired cardinality and (2) minimize changes to the original query intentions. In our comprehensive experimental study of each part of this dissertation, we demonstrate the superiority of the proposed strategies over state-of-the-art techniques in both efficiency, as well as resource consumption.

This project describes a technique for segmenting regions of sky in an image from the remainder of the image. This segmentation technique is part of a method for predicting the solar exposure at a location of interest from a set of photographs. Given the latitude and longitude of the position and the direction and field of view of the camera it is possible to calculate the position of the sun in the image at a particular time on a particular day. If that position is in a sky region of the image then the location will be exposed to the sun at that time. Critical to the success of this method for determining solar exposure is the image processing used to separate the sky from the rest of the image. This work is concerned with finding a technique which can do this for images taken under different weather conditions. The general approach to separate the sky from the rest of the image is to use the Canny edge detector and the morphology closing algorithm to find the regions in the image. The brightness and area of each region are then used to determine which regions are sky. The FloodFill algorithm is applied to identify all pixels in each sky region. An extensive empirical study is used to find a set of threshold values for the Canny edge detector, applied to the blue colour channel, which allow successful identification of the sky regions in a wide range of images. Tests using different camera filters show that they do not usefully increase the contrast between the sky and the rest of the image, when a standard compact camera is used. The work reported in this thesis shows that this approach of finding edges to identify possible sky regions works successfully on a wide range of images although there will always be situations, such as when the image is taken directly into the sun, where manual adjustment to the identified regions may be required.

在資料庫的處理中，top-k查詢幫助使用者從龐大的資料中萃取出具有價值的物件，它將資料庫中的物件依照給分公式給分後，選擇出分數最高的前k個回傳給使用者。然而在多數的情況下，一個物件也許不只有一個分數，要如何在多個分數中仍然選擇出整體最高分的前k個物件，便成為一個新的問題。在本研究中，我們將這樣的物件用不確定資料來表示，而每個物件的不確定性則是其帶有機率的分數以表示此分數出現的可能性，並提出一個新的問題：Best-kGROUP查詢。在此我們將情況模擬為一個複合式競賽，其中有多個子項目，每個項目的參賽人數各異，且最多需要k個人參賽；我們希望能針對此複合式競賽挑選出最佳的k個球員組合。當我們定義一個較佳的組合為其在較多項目居首位的機率比另一組合高，而最佳的組合則是沒有比它更佳的組合。為了加快挑選的速度，我們利用動態規劃的方式與篩選的演算法，將不可能的組合先剔除；所剩的組合則是具有天際線特質的組合，在這些天際線組合中，我們可以輕易的找出最佳的組合。此外，在實驗中，對於在所有球員中挑選最佳的組合，Best-kGROUP查詢也有非常優異的表現。 / In a large database, top-k query is an important mechanism to retrieve the most valuable information for the users. It ranks data objects with a ranking function and reports the k objects with the highest scores. However, when an object has multiple scores, how to rank objects without information loss becomes challenging. In this paper, we model the object with multiple scores as an uncertain data object and the uncertainty of the object as a distribution of the scores, and consider a novel problem named Best-kGROUP query. Imagine the following scenario. Assume there is a composite competition consisting of several games each of which requires a distinct number of players. Suppose the largest number is k, and we want to select the best group of k players from all the players for the competition. A group x is considered better than another group y if x has higher aggregated probability to be the top ones in more games than y. In order to speed up the selection process, the groups worse than another group definitely should first be discarded. We identify these groups using a dynamic programming based approach and a filtering algorithm. The remaining groups with the property that none of them have higher aggregated probability to be the top ones for all games against the other groups are called skyline groups. From these skyline groups, we can easily compare them to select the best group for the composite competition. The experiments show that our approach outperforms the other approaches in selecting the best group to defeat the other groups in the composite competitions.

Made available in DSpace on 2016-06-02T19:52:14Z (GMT). No. of bitstreams: 1 DissVRCZ.pdf: 976414 bytes, checksum: eee2d15b158b26949f458c4e38bd444c (MD5) Previous issue date: 2005-12-15 / This work analyses the emergence of Competence concept and its implications for workers management on organizations, included considering the existent discussion about the necessity of substituting the Qualification concept for the Competence one, on attempt of making a better aprehension about the complexes aspects inherent to contemporary set. For that, were realized a bibliographyc research related to the theme and a field research. Through configuration of a more dynamic set around organizations, resulting mainly of the tecnology advance process, with effect in the society evolution, emerge adaptation needs that demand reestructuration actions of administrative and productive ambit, which one influence, over all, on humans resources management. From observation of high workers rotation number that ocurred in the Volkswagen motors plant on, located in São Carlos city, interwiews were realized with the target of identifying the criterions that govern the personnel management politics practiced on this organization, the factors that contribute to the construction of carreer expectancy and analysing the professional skyline evolution demanded as a response to observed workers rotation. Several aspects inherent to Competence logic were implicitament identified on studied organizational surrounding, which ones influence on the politcs of personnel management, on construction and frustration related to carreer expectance and on aspects that compose the professional skylines demanded. Besides, it is evident that the Competence approach is actually in vigour, and too that transition through enterprise pass since its implantation, culminating on bigger stabilization of its strucutre, represents a fundamental element on expectations and oportunities generated in such surrounding. / Este trabalho analisa a emergência do conceito de Competência e suas implicações para a gestão dos trabalhadores nas organizações, inclusive considerando a discussão existente em torno da necessidade de substituir o conceito de Qualificação pelo de Competência, na tentativa de melhor apreender os complexos aspectos inerentes ao contexto contemporâneo. Para tanto, foram realizadas uma pesquisa bibliográfica relacionada ao tema e uma pesquisa de campo. A partir da configuração de um cenário mais dinâmico em torno das organizações, resultante principalmente do processo de avanço tecnológico, com efeito na evolução da sociedade, emergem necessidades de adaptação que demandam ações de reestruturação de âmbito administrativo e produtivo, as quais influenciam, sobretudo, na gestão dos recursos humanos. Partindo-se da observação da alta rotatividade de funcionários ocorrida na fábrica de motores da Volkswagen localizada na cidade de São Carlos, entrevistas foram realizadas objetivando identificar os parâmetros que regem as políticas de gestão de pessoal praticadas nesta organização, os fatores que contribuem para a construção da expectativa de carreira, bem como analisar a evolução do perfil profissional demandado em resposta à rotatividade observada. Vários aspectos inerentes à lógica da Competência foram implicitamente identificados no ambiente organizacional estudado, os quais influenciam nas políticas de gestão de pessoal, na construção e frustração relativas a expectativa de carreira e nos aspectos que compõem os perfis profissionais demandados. Além disso, fica claro que a abordagem da Competência está vigente atualmente, e também que a transição por que passa a empresa desde sua implantação, culminando na maior estabilização de sua estrutura, representa um elemento fundamental nas expectativas e oportunidades geradas em tal ambiente.

The subject of this thesis entitled What does an invisible city look like is the perception of a city and the way it is represented. The work is based on urban semiotics that sees urban environment as a particular system of communication. The methods of sensory urbanism and rhythm analysis are employed as well. The author asks whether the cities could be represented by other than visual symbols as it is usually the case for the products of tourism industry (guidebooks, souvenirs, etc.). Usually, the symbol of a particular city is formed by the image of its skyline. In Prague, this is the skyline of the Prague Castle, in Paris, it is the Eiffel tower, in New York, it is the Statue of Liberty, etc. But every city has definitely many other qualities. What are they? To find the answer, the author asks for help the visually impaired people. These people can tell easily what are the non-visual qualities of the urban space as they experience them necessarily in their everyday life and use them for better orientation. The author interviewed the visually impaired people and she also observed the way they read the city in real. The practical part of the thesis focuses on the Prague city centre.

The building site is situated on the interesection of Třída Genrála Píky and Provazníkova streets in Brno. In the neighboring building there are commercial and administrative spaces. The main crossroad was redesigned to minimize the residual traffic areas. Based on urbanistic study we designed the corner high-rise dominant. We create a point of view at the skyline of Brno. By pushing back the volume we have a small square. Central comunication core allows transparent facade.

Cette thèse s'est déroulée dans le cadre du projet ANR FOSTER, "FOuille de données Spatio-Temporelles : application à la compréhension et à la surveillance de l'ERosion" (ANR-2010-COSI-012-02, 2011-2014). Dans ce contexte, nous nous sommes intéressés à la modélisation de données spatio-temporelles dans des graphes enrichis de sorte que des calculs de motifs sur de telles données permettent de formuler des hypothèses intéressantes sur les phénomènes à comprendre. Plus précisément, nous travaillons sur la fouille de motifs dans des graphes relationnels (chaque noeud est identifié de fa\c con unique), attribués (chaque noeud du graphe est décrit par des attributs qui sont ici numériques), et dynamiques (les valeurs des attributs et les relations entre les noeuds peuvent évoluer dans le temps). Nous proposons un nouveau domaine de motifs nommé motifs de co-évolution. Ce sont des triplets d'ensembles de noeuds, d'ensembles de pas de temps et d'ensembles d'attributs signés, c'est à dire des attributs associés à une tendance (croissance,décroissance). L'intérêt de ces motifs est de décrire un sous-ensemble des données qui possède un comportement spécifique et a priori intéressant pour conduire des analyses non triviales. Dans ce but, nous définissons deux types de contraintes, une contrainte sur la structure du graphe et une contrainte sur la co-évolution de la valeur des attributs portés par les noeuds. Pour confirmer la spécificité du motif par rapport au reste des données, nous définissons trois mesures de densité qui tendent à répondre à trois questions. À quel point le comportement des noeuds en dehors du motif est similaire à celui des noeuds du motif ? Quel est le comportement du motif dans le temps, est-ce qu'il apparaît soudainement ? Est-ce que les noeuds du motif ont un comportement similaire seulement sur les attributs du motif ou aussi en dehors ? Nous proposons l'utilisation d'une hiérarchie sur les attributs comme connaissance à priori de l'utilisateur afin d'obtenir des motifs plus généraux et adaptons l'ensemble des contraintes à l'utilisation de cette hiérarchie. Finalement, pour simplifier l'utilisation de l'algorithme par l'utilisateur en réduisant le nombre de seuils à fixer et pour extraire uniquement l'ensemble des motifs les plus intéressants, nous utilisons le concept de ``skyline'' réintroduit récemment dans le domaine de la fouille de données. Nous proposons ainsi trois algorithmes MINTAG, H-MINTAG et Sky-H-MINTAG qui sont complets pour extraire l'ensemble de tous les motifs qui respectent les différentes contraintes. L'étude des propriétés des contraintes (anti-monotonie, monotonie/anti-monotonie par parties) nous permet de les pousser efficacement dans les algorithmes proposés et d'obtenir ainsi des extractions sur des données réelles dans des temps raisonnables. / This thesis was conducted within the project ANR FOSTER, ``Spatio-Temporal Data Mining: application to the understanding and monitoring of erosion'' (ANR-2010-COSI-012-02, 2011-2014). In this context, we are interested in the modeling of spatio- temporal data in enriched graphs so that computation of patterns on such data can be used to formulate interesting hypotheses about phenomena to understand. Specifically, we are working on pattern mining in relational graphs (each vertex is uniquely identified), attributed (each vertex of the graph is described by numerical attributes) and dynamic (attribute values and relations between vertices may change over time). We propose a new pattern domain that has been called co-evolution patterns. These are trisets of vertices, times and signed attributes, i.e., attributes associated with a trend (increasing or decreasing). The interest of these patterns is to describe a subset of the data that has a specific behaviour and a priori interesting to conduct non-trivial analysis. For this purpose, we define two types of constraints, a constraint on the structure of the graph and a constraint on the co-evolution of the value worn by vertices attributes. To confirm the specificity of the pattern with regard to the rest of the data, we define three measures of density that tend to answer to three questions. How similar is the behaviour of the vertices outside the co-evolution pattern to the ones inside it? What is the behaviour of the pattern over time, does it appear suddenly? Does the vertices of the pattern behave similarly only on the attributes of the pattern or even outside? We propose the use of a hierarchy of attributes as an a priori knowledge of the user to obtain more general patterns and we adapt the set of constraints to the use of this hierarchy. Finally, to simplify the use of the algorithm by the user by reducing the number of thresholds to be set and to extract only all the most interesting patterns, we use the concept of ``skyline'' reintroduced recently in the domain of data mining. We propose three constraint-based algorithms, called MINTAG, H-MINTAG and Sky-H-MINTAG, that are complete to extract the set of all patterns that meet the different constraints. These algorithms are based on constraints, i.e., they use the anti-monotonicity and piecewise monotonicity/anti-monotonicity properties to prune the search space and make the computation feasible in practical contexts. To validate our method, we experiment on several sets of data (graphs) created from real-world data.

L'augmentation continue de la puissance des ordinateurs personnels (stations de travail ou PCs) et l'émergence de réseaux à haut débits fournissent de nouvelle opportunités de réalisation de machines parallèle à faible coût, en comparaison des machines parallèles traditionnelles. On peut aujourd 'hui construire de véritables machines parallèles en interconnectant des processeurs standards. Le fonctionnement de cet ensemble de processeurs en tant que machines parallèle est alors assuré par des logiciels tels que PVM et MPI. Quelle que soit la machine parallèle considérée, concevoir des applications parallèles impose, soit des outils de parallélisation automatique, soit un effort du programmeur suivant des méthodologies de programmation. Dans cette thèse, nous proposons une méthodologie de parallélisation des méthodes numériques. En général les méthodes numériques sont une chaîne d'algorithmes s'appelant les uns après les autres tout au long de leur exécution. A moins d'aborder leur parallélisation à partir du problème physique qu'elles traitent, par exemple par des techniques de décomposition de domaines, l'approche de parallélisation la plus réaliste est celle de type client/serveur.