Zugl.: Münster (Westfalen), Univ., Diss., 2005

University, Diss., 2005--Münster (Westfalen).

abstract: Continuous advancements in biomedical research have resulted in the production of vast amounts of scientific data and literature discussing them. The ultimate goal of computational biology is to translate these large amounts of data into actual knowledge of the complex biological processes and accurate life science models. The ability to rapidly and effectively survey the literature is necessary for the creation of large scale models of the relationships among biomedical entities as well as hypothesis generation to guide biomedical research. To reduce the effort and time spent in performing these activities, an intelligent search system is required. Even though many systems aid in navigating through this wide collection of documents, the vastness and depth of this information overload can be overwhelming. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also facilitate discovery of the unknown information implicitly conveyed in the texts. This thesis presents the different approaches used for large scale biomedical named entity recognition, and the challenges faced in each. It also proposes BioEve: an integrative framework to fuse a faceted search with information extraction to provide a search service that addresses the user's desire for "completeness" of the query results, not just the top-ranked ones. This information extraction system enables discovery of important semantic relationships between entities such as genes, diseases, drugs, and cell lines and events from biomedical text on MEDLINE, which is the largest publicly available database of the world's biomedical journal literature. It is an innovative search and discovery service that makes it easier to search/navigate and discover knowledge hidden in life sciences literature. To demonstrate the utility of this system, this thesis also details a prototype enterprise quality search and discovery service that helps researchers with a guided step-by-step query refinement, by suggesting concepts enriched in intermediate results, and thereby facilitating the "discover more as you search" paradigm. / Dissertation/Thesis / M.S. Computer Science 2010

La personne morale ne peut consentir que par l'intermédiaire de ses organes sociaux. Ceux-ci ont pour fonction d'exprimer la volonté sociale en exerçant les pouvoirs qui leur sont attribués par la loi ou les statuts. Ce dispositif particulier, inhérent à l'abstraction radicale qui caractérise la personnalité morale, conduit trop souvent à considérer que le consentement d'une personne morale se réduit à un acte de représentation et, en conséquence, à apprécier ce consentement en la personne des organes représentants. Nous avons d'abord analysé la spécificité du consentement du fait de la personnalité morale (Première partie) à partir de ses deux composantes essentielles : la prise décisionnelle d'une part, l'acte de représentation d'autre part. II s'avère que le consentement de la personne morale, loin d'être réductible à un seul acte de représentation, est un processus organique organisé dans lequel la phase décisionnelle tient une place essentielle. Nous avons ensuite examiné l'approche juridique du consentement adaptée à la personnalité morale (Seconde partie). Après avoir étudié les modalités d'application des qualités ordinaires - individualité et intégrité - que doit revêtir le consentement de la personne morale, nous avons relevé les fonctions originales que ce consentement est susceptible de remplir. Si le consentement de la personne morale est toujours l'expression de l'intérêt social, d'autres fonctions peuvent également lui être assignées. Ainsi se présente-t-il actuellement comme un vecteur des bonnes pratiques de gouvernance. / The legal entity can give its consent only through its management bodies. The latter's functions are to express the social wishes by exercising their powers that have be attributed to them by law or by statutes. This specific measure, which is inherent to the radical abstraction that characterizes the legal entity, too often leads to the idea that the consent of the legal entity is reduced to an act of representation and thus leads to assessing this consent in its representing bodies. We have, first of all, analysed the special feature of the consent in light of the legal entity (First Part) through Iwo essential componants: the decision making on the one hand, the act of representation on the other hand. The consent of the legal entity proves to be far more than one single act of representation and actually a structured organic process in which the decision making phase holds an essential spot. We have then, second of ail, analysed the legal aspect of the consent suited to the legal entity (Second Part). After studying the implementing provisions of the usual features - individuality and integrity - that the consent of a legal entity needs to take on, we have raised the original functions that this consent is susceptible to fulfill. I the consent of the legal entity is always the expression of the social interest, other functions can also be assigned to it. Thus it can actually be a vector of good corporate governance practices.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-09-11T19:44:07Z No. of bitstreams: 1 DEMETRIO GOMES MESTRE – TESE (PPGCC) 2018.pdf: 15362740 bytes, checksum: eb531a72836b3c7f2f4e0171c7f563dc (MD5) / Made available in DSpace on 2018-09-11T19:44:07Z (GMT). No. of bitstreams: 1 DEMETRIO GOMES MESTRE – TESE (PPGCC) 2018.pdf: 15362740 bytes, checksum: eb531a72836b3c7f2f4e0171c7f563dc (MD5) Previous issue date: 2018-03-27 / Entity Matching (EM), ou seja, a tarefa de identificar entidades que se referem a um mesmo objeto do mundo real, é uma tarefa importante e difícil para a integração e limpeza de fontes de dados. Uma das maiores dificuldades para a realização desta tarefa, na era de Big Data, é o tempo de execução elevado gerado pela natureza quadrática da execução da tarefa. Para minimizar a carga de trabalho preservando a qualidade na detecção de entidades similares, tanto para uma ou mais fontes de dados, foram propostos os chamados métodos de indexação ou blocagem. Estes métodos particionam o conjunto de dados em subconjuntos (blocos) de entidades potencialmente similares, rotulando-as com chaves de bloco, e restringem a execução da tarefa de EM entre entidades pertencentes ao mesmo bloco. Apesar de promover uma diminuição considerável no número de comparações realizadas, os métodos de indexação ainda podem gerar grandes quantidades de comparações, dependendo do tamanho dos conjuntos de dados envolvidos e/ou do número de entidades por índice (ou bloco). Assim, para reduzir ainda mais o tempo de execução, a tarefa de EM pode ser realizada em paralelo com o uso de modelos de programação tais como MapReduce e Spark. Contudo, a eficácia e a escalabilidade de abordagens baseadas nestes modelos depende fortemente da designação de dados feita da fase de map para a fase de reduce, para o caso de MapReduce, e da designação de dados entre as operações de transformação, para o caso de Spark. A robustez da estratégia de designação de dados é crucial para se alcançar alta eficiência, ou seja, otimização na manipulação de dados enviesados (conjuntos de dados grandes que podem causar gargalos de memória) e no balanceamento da distribuição da carga de trabalho entre os nós da infraestrutura distribuída. Assim, considerando que a investigação de abordagens que promovam a execução eficiente, em modo batch ou tempo real, de métodos de indexação adaptativa de EM no contexto da computação distribuída ainda não foi contemplada na literatura, este trabalho consiste em propor um conjunto de abordagens capaz de executar a indexação adaptativas de EM de forma eficiente, em modo batch ou tempo real, utilizando os modelos programáticos MapReduce e Spark. O desempenho das abordagens propostas é analisado em relação ao estado da arte utilizando infraestruturas de cluster e fontes de dados reais. Os resultados mostram que as abordagens propostas neste trabalho apresentam padrões que evidenciam o aumento significativo de desempenho da tarefa de EM distribuída promovendo, assim, uma redução no tempo de execução total e a preservação da qualidade da detecção de pares de entidades similares. / Entity Matching (EM), i.e., the task of identifying all entities referring to the same realworld object, is an important and difficult task for data sources integration and cleansing. A major difficulty for this task performance, in the Big Data era, is the quadratic nature of the task execution. To minimize the workload and still maintain high levels of matching quality, for both single or multiple data sources, the indexing (blocking) methods were proposed. Such methods work by partitioning the input data into blocks of similar entities, according to an entity attribute, or a combination of them, commonly called “blocking key”, and restricting the EM process to entities that share the same blocking key (i.e., belong to the same block). In spite to promote a considerable decrease in the number of comparisons executed, indexing methods can still generate large amounts of comparisons, depending on the size of the data sources involved and/or the number of entities per index (or block). Thus, to further minimize the execution time, the EM task can be performed in parallel using programming models such as MapReduce and Spark. However, the effectiveness and scalability of MapReduce and Spark-based implementations for data-intensive tasks depend on the data assignment made from map to reduce tasks, in the case of MapReduce, and the data assignment between the transformation operations, in the case of Spark. The robustness of this assignment strategy is crucial to achieve skewed data handling (large sets of data can cause memory bottlenecks) and balanced workload distribution among all nodes of the distributed infrastructure. Thus, considering that studies about approaches that perform the efficient execution of adaptive indexing EM methods, in batch or real-time modes, in the context of parallel computing are an open gap according to the literature, this work proposes a set of parallel approaches capable of performing efficient adaptive indexing EM approaches using MapReduce and Spark in batch or real-time modes. The proposed approaches are compared to state-of-the-art ones in terms of performance using real cluster infrastructures and data sources. The results carried so far show evidences that the performance of the proposed approaches is significantly increased, enabling a decrease in the overall runtime while preserving the quality of similar entities detection.

This diploma thesis is focused on determination of a subjective value of the CEZ GROUP holding at December 31th 2012. The holding is well known especially be-cause of generating, distribution and selling electric energy in the six European states. This thesis includes a strategic analysis, a financial analysis, an analysis of value drivers, a design of a financial plan and an application of all three pricing approaches -- the asset approach, the market approach and the income approach. Specifically there were used methods as the book value method, the comparable company analysis and the DCF entity method. All results were compared both together and with the real value which had been accepted by markets on the spe-cific date.

The main aim of the diploma thesis is to identify the risks and barriers of the internationalization process of Czech micro-enterprises in agrarian industry. The theoretical part deals with internationalization and globalization, small, medium and micro businesses, motivators, risks and barriers related to foreign market. The second part is devoted to analysis of the current situation of small, medium and micro-entities in the Czech Republic. The factors of motivation, barriers and risks of internationalization of chosen enterprises are described based on results of in-depth interview by author. The data is compared with results from different sectors and surveys. Furthermore, there are proposals which lead to elimination of problematic factors

With the growing demand for information in various domains, sharing of information from heterogeneous data sources is now a necessity. Data integration approaches promise to combine data from these different sources and present to the user a single, unified view of these data. However, although these approaches offer high quality services for the managing and integrating of data, they come with a high cost. This is because a great amount of manual effort to form relationships across data sources is needed to set up the data integration system. A newer variant of data integration, known as dataspaces, aims to spread the large manual effort spent at the start of the data integration system to the rest of the system's phases. This is achieved by soliciting from the user their feedback on a chosen artefact of a dataspace, either by explicit ways or implicitly. This practice is known as pay-as-you-go, where a user continuously pays to the data integration system, by providing feedback, to gain improvements in the quality of data integration. This PhD addresses two challenges in data integration by using pay-as-you-go approaches. The first is to identify instances relevant to a user's information need, calling for semantic mappings to be closely considered. Our contribution is a technique that ranks mappings with the help of implicit user feedback (i.e., terms found in query logs). Our evaluation shows that to produce stable rankings, our technique does not require large-sized query logs, and that our generated ranking is able to respond satisfactorily to the amount of terms inclined towards a particular data source, where we describe it as skew. The second challenge that we address is the identification of duplicate instances from disparate data sources. We contribute a strategy that uses explicitly-obtained user feedback to drive an evolutionary search algorithm to find suitable parameters for an underlying clustering algorithm. Our experiments show that optimising the algorithm's parameters and introducing attribute weights produces fitter clusters than clustering alone. However, our strategy to improve on integration quality can be quite expensive. Therefore, we propose a pruning technique to select from a dataset any records that are informative. Our experiment shows that on most of the datasets, our pruner produce comparably fit clusters with more feedback received.

Detta projekt har, för företaget Gisys räkning, gått ut på att från grunden skapa en applikation som förenklar processen när en nyanställning sker i företaget. Med detta menas ett gränssnitt där man kan lägga upp nya personer, utskick av formulär där den kommande medarbetaren får fylla i uppgifter och önskemål, utskick av övriga mail och checklistor där ansvarig på Gisys kan bocka av vad som är gjort och inte. Resultatet av denna applikation ses nu som en start på något större, efter många avstämningsmöten har kallar vi nu detta ett mindre intranät där nyanställningsprocessen snarare är en modul utav den större applikationen. Efter ett lyckat arbete och god respons från Gisys så finns planer alltså på att vidareutveckla applikationen med fler moduler.

O trabalho se divide em duas partes, sendo a primeira delas, de caráter introdutório, com a pretensão de percorrer, sucintamente, os principais aspectos doutrinários consagrados ao longo do tempo pela ciência jurídica a respeito das pessoas jurídicas. Nesse primeiro impulso, são analisados os diferentes enfoques de conceituação da pessoa jurídica, bem como são delineadas suas remotas origens no Direito Romano. São apontados e discutidos seus requisitos e o momento de seu nascimento, sendo o aspecto fundamental o estudo da capacidade e personalidade da pessoa jurídica, ou seja, sua aptidão para ser sujeito de direitos e obrigações e de exercê-los na ordem civil. Finalmente, aborda-se a transformação, desconsideração e a morte da pessoa jurídica, completando desse modo o seu ciclo vital. A segunda parte se propõe a analisar a (re)presentação da pessoa jurídica, seja por meio de seus órgãos, verificando-se, nesta hipótese, a representação, seja por meio de procuradores, sendo necessário, sob esse aspecto, o estudo do negócio jurídico, do contrato de mandato e da representação, em sua acepção técnica de negócio jurídico autônomo. Assim, é então possível enfrentar o fenômeno da Aparência de Direito ou Teoria da Aparência, sendo desenvolvida sua conceituação, bem como descritos seus requisitos essenciais e os efeitos de sua aplicação. Ao cabo, empreende-se a análise dos principais feitos judiciais levados a julgamento no âmbito do Supremo Tribunal Federal e do Superior Tribunal de Justiça, com a oportunidade de compreender como as Cortes Superiores brasileiras aplicam no caso concreto os institutos e fenômenos teorizados, especialmente a Teoria da Aparência.