The literature is clear that intentional or unintentional clustering of data elements typically results in the inflation of the estimated standard error of fixed parameter estimates. This study is unique in that it examines the impact of multilevel data structures on subject ability which are random effect predictions known as empirical Bayes estimates in the one-parameter IRT / Rasch model. The literature on the impact of complex survey design on latent trait models is mixed and there is no "best practice" established regarding how to handle this situation. A simulation study was conducted to address two questions related to ability estimation. First, what impacts does design based clustering have with respect to desirable statistical properties when estimating subject ability with the one-parameter IRT / Rasch model? Second, since empirical Bayes estimators have shrinkage properties, what impacts does clustering of first-stage sampling units have on measurement validity-does the first-stage sampling unit impact the ability estimate, and if so, is this desirable and equitable? Two models were fit to a factorial experimental design where the data were simulated over various conditions. The first model Rasch model formulated as a HGLM ignores the sample design (incorrect model) while the second incorporates a first-stage sampling unit (correct model). Study findings generally showed that the two models were comparable with respect to desirable statistical properties under a majority of the replicated conditions-more measurement error in ability estimation is found when the intra-class correlation is high and the item pool is small. In practice this is the exception rather than the norm. However, it was found that the empirical Bayes estimates were dependent upon the first-stage sampling unit raising the issue of equity and fairness in educational decision making. A real-world complex survey design with binary outcome data was also fit with both models. Analysis of the data supported the simulation design results which lead to the conclusion that modeling binary Rasch data may resort to a policy tradeoff between desirable statistical properties and measurement validity. / Ph. D.

Loading of data from slow persistent memory (disk storage) to main memory represents a bottleneck for current interactive visual data exploration applications, especially when applied to huge volumnes of data. Semantic caching of queries at the client-side is a recently emerging technology that can significantly improve the performance of such systems, though it may not in all cases fully achieve the near real-time responsiveness required by such interactive applications. We hence propose to augment the semantic caching techniques by applying prefetching. That is, the system predicts the user's next requested data and loads the data into the cache as a background process before the next user request is made. Our experimental studies confirm that prefetching indeed achieves performance improvements for interactive visual data exploration. However, a given prefetching technique is not always able to correctly predict changes in a user's navigation pattern. Especially, as different users may have different navigation patterns, implying that the same strategy might fail for a new user. In this research, we tackle this shortcoming by utilizing the adaptation concept of strategy selection to allow the choice of prefetching strategy to change over time both across as well as within one user session. While other adaptive prefetching research has focused on refining a single strategy, we instead have developed a framework that facilitates strategy selection. For this, we explored various metrics to measure performance of prefetching strategies in action and thus guide the adaptive selection process. This work is the first to study caching and prefetching in the context of visual data exploration. In particular, we have implemented and evaluated our proposed approach within XmdvTool, a free-ware visualization system for visually exploring hierarchical multivariate data. We have tested our technique on real user traces gathered by the logging tool of our system as well as on synthetic user traces. Our results confirm that our adaptive approach improves system performance by selecting a good combination of prefetching strategies that adapts to the user's changing navigation patterns.

The relational database model was defined in the 1970‟s and is the dominating database type today.  The main difference between data from a relational database and a hierarchical data structure is that the relational database stores records in tables. The records have no particular order, but can include links in terms of relationships with other records. A hierarchical structure organizes data in the form of a tree structure  and  can for an example be found in organizational structures in which different levels involves different responsibilities.  If the data stored in a relational database is to be presented in a hierarchically, a conversion of the data structure is required. The intention of this paper is to describe how such a conversion can be performed.   To investigate the conversion methods, case studies has been conducted on the basis of a specific organization‟s hierarchical structure. Web based prototypes were developed in Silverlight to evaluate the conversion of a hierarchical structure, based on the organization that was represented in a relational database. Existing tools were used in order to extract data from a database and transfer data in a client-server architecture.  The result is a framework for the conversion of relational data into hierarchical structure and describes the process step by step. A conversion process includes the design of the database source, extraction and transfer of data to a web client and the algorithm for performing the conversion into a tree structure. / Relationsdatabaser definierades på 1970-talet och är den dominerande databastypen idag. Skillnaden mellan data i en relationsdatabas och en hierarkisk datastruktur är att relationsdatabasen sparar poster i tabeller. Poster i tabellerna behöver ingen inbördes ordning, men kan omfatta  kopplingar i form av relationer till andra poster. En hierarkisk struktur organiserar data i form av trädstruktur och återfinns till exempel i organisationsstrukturer där olika nivåer innefattar olika ansvarsområden.  Om data som sparats i en relationsdatabas skall visas upp hierarkiskt krävs en omvandling av datastrukturen. Syftet med uppsatsen är att redogöra för hur en sådan omvandling kan utföras.  För att utreda omvandlingsmetoder har fallstudier bedrivits utifrån en specifik organisations hierarkiska struktur. Webbaserade prototyper utvecklades i Silverlight för att utvärdera omvandling till hierarkisk struktur utifrån organisationen som fanns representerad i en relationsdatabas.  Till hjälp existerar verktyg för att extrahera data ur databas samt överföra data i klient-server arkitektur.  Resultatet är ett ramverk för omvandling av relationsdata till hierarkisk struktur  och beskriver processen steg för steg. En omvandlingsprocess omfattar utformning av databas för källa, extrahering och överföring av data till en webbklient samt  algoritm  för utförande av omvandling till trädstruktur.

This dissertation proposes two novel manifold graph-based ranking systems for Content-Based Image Retrieval (CBIR). The two proposed systems exploit the synergism between relevance feedback-based transductive short-term learning and semantic feature-based long-term learning to improve retrieval performance. Proposed systems first apply the active learning mechanism to construct users' relevance feedback log and extract high-level semantic features for each image. These systems then create manifold graphs by incorporating both the low-level visual similarity and the high-level semantic similarity to achieve more meaningful structures for the image space. Finally, asymmetric relevance vectors are created to propagate relevance scores of labeled images to unlabeled images via manifold graphs. The extensive experimental results demonstrate two proposed systems outperform the other state-of-the-art CBIR systems in the context of both correct and erroneous users' feedback.

No description available.

Ray tracing is used in computer graphics to generate images. The process of rendering images using ray tracing includes testing large counts of rays for intersection against geometry. Testing for ray-geometry intersection is more formally known as the Ray Shooting Problem (RSP) and has broad applications across multiple communities. Hierarchical acceleration structures are frequently employed to index geometry and increase processing speed. Such hierarchical structures make it almost impossible for central processing units to predict memory access and branching patterns. This project focuses on the Bounding Volume Hierarchy (BVH) structure and improving its performance when querying large batches of first hit ray-geometry intersections. The core contribution is an Interleaved Prefetching Ray Traversal (IPRT) algorithm that addresses memory and branching issues. Five standardized test scenarios with varying geometric complexity provide evaluation data. The experimental evaluation suggests that for incoherent rays, IPRT achieves 6:1 - 41:8% faster performance compared to Stackless Traversal. However, for fully coherent rays, performance is 68:8 - 149:1% slower. These results suggest that for select ray tracing workloads that elicit low coherence, the IPRT algorithm is likely to outperform Stackless Traversal. A microarchitectural analysis affirms previous research; memory accesses and branching behavior are critical for performance. Surprisingly, addressing each component in isolation yields no significant performance improvement. It is paramount to address the two simultaneously, as the IPRT algorithm does successfully. / Ray tracing används inom datorgrafik för att generera bilder. Att rendera bilder med ray tracing kräver att datorer simulerar stora mängder ljusstrålar i en virtuell miljö. Problemet att beräkna om en stråle träffar geometri är mer formellt känt som Ray Shooting Problem (RSP) och har breda applikationer inom flera områden. Hierarkiska accelerationsstrukturer används ofta för att indexera geometri och öka beräkningshastighet. Sådana hierarkiska strukturer gör det nästan omöjligt för centrala processorenheter att förutsäga minnesåtkomst och förgreningsmönster. Detta projekt fokuserar på Bounding Volume Hierarchy (BVH) strukturen och dess prestanda. En ny algoritm tas fram för att behandla dessa identifierade problem: Interleaved Prefetching Ray Traversal (IPRT). Fem standardiserade testscener med varierande geometrisk komplexitet används för experimentell utvärdering. Den experimentella utvärderingen antyder i jämförelse med Stackless Traversal så uppnår IPRT-algoritmen 6:1 - 41:8% bättre prestanda för osammanhängande strålar. När det gäller helt sammanhängande strålar är prestandan dock 68:8 - 149:1% långsammare. En mikroarkitektisk analys bekräftar tidigare forskning; minnesåtkomst och förgreningsbeteende är mycket viktigt för prestanda. Isolerad optimering av faktorerna ger dessvärre ingen signifikant prestandaförbättring. Det är därför ytterst viktigt att optimera båda komponenter samtidigt, vilket IPRT-algoritmen lyckas med.

Um dos estudos observacionais mais difundidos e usados em epidemiologia veterinária é o estudo do tipo transversal. Sua popularidade ocorre por fatores como baixo custo e rapidez comparados com outros tipos de estudos, além de ajudar a estimar a prevalência de uma doença (desfecho) e postular fatores associados com o desfecho, que poderão ser confirmados como fatores causais em outros tipos de estudos epidemiológicos. Porém, este tipo de estudo apresenta dois importantes desafios: a dependência dos dados, muito frequente dada a típica estrutura populacional de animais dentro do mesmo rebanho ou fazenda e a escolha da medida de associação para desfechos binários, tão frequentes neste modelo de estudo. Com o objetivo de contribuir com a compreensão global da epidemiologia do aborto bovino associado à Neospora caninum tendo em conta a estrutura populacional, construiu-se um modelo misto com os dados de um estudo transversal realizado em duas regiões do Rio Grande do Sul. Usaram-se dados de 60 propriedades amostradas em duas regiões (noroeste e sudeste) e 1256 bovinos. A percentagem de aborto dentro de cada rebanho variou entre 1% e 30%. Vacas soropositivas tiveram 6,63 vezes mais chances de ter histórico de aborto (IC 95%: 4,41-13,20). As chances de uma vaca ter histórico de aborto foram 5,18 vezes maiores na região noroeste em relação à região sudeste (IC 95%: 1,83-20,80). Um coeficiente de correlação intraclasse de 16% foi estimado, indicando que 16% da variação da ocorrência de abortamentos não explicados pelos efeitos fixos foram devido as fazendas. Já na segunda parte deste trabalho, uma revisão sistemática foi realizada considerando um conjunto diverso de revistas e jornais com o objetivo de verificar os métodos estatísticos usados e a adequação das interpretações das medidas de associação estimadas em estudos transversais na área de medicina veterinária. Um total de 62 artigos foi avaliado. A revisão mostrou que, independentemente do nível de prevalência relatado no artigo, 96% deles empregou regressão logística e, portanto, estimaram razão de chances (RC). Nos artigos com prevalência superior a 10%, 23 deles fizeram uma interpretação adequada da RC como uma “razão de chances” ou simplesmente não fizeram uma interpretação direta da RC, enquanto 23 artigos interpretaram de forma inadequada a RC, considerando-a como risco ou probabilidade. Entre os artigos com prevalência inferior a 10%, apenas três interpretaram a RC como uma “razão de chances”, cinco interpretaram como risco ou probabilidade e em um, apesar de ter estimado a razão de prevalências (RP), foi interpretado de forma inadequada. Paralelamente, com o objetivo de exemplificar o uso de métodos estatísticos que estimam diretamente a razão de prevalências (RP), medida mais adequada para os estudos transversais, um conjunto de dados obtidos a partir de um estudo transversal sobre a ocorrência de anticorpos (AC) contra o vírus da diarreia viral bovina (BVDV) foi usado. Os AC foram medidos em amostras de tanque de leite de rebanhos leiteiros localizados no estado do Rio Grande do Sul, em que os possíveis fatores associados puderam ser avaliados. Entre os métodos utilizados, as maiores discrepâncias nas medidas de associação estimadas foram observadas com a regressão logística tomando-se como referência a regressão log-binomial. Finalmente, é importante que este tipo de desafio seja atendido pelos pesquisadores que realizam estudos transversais, ou seja, considerar a estrutura das populações nas análises, cuidado ao escolher o tipo de modelo estatístico empregado para desfecho binário e interpretação dos estimadores. / The commonest study design used in veterinary epidemiology is the cross-sectional study. Its popularity lies on the fact of the short time needed and low costs compared with other types of studies; moreover, this type of study estimates prevalence and associated factors, which may be elucidated as causal in another type of epidemiological studies. However, this type of study presents two major challenges: a very common dependence between data given the typical structure of the animal population, i.e., animals within herds or farms and the choice of measure of association for binary outcomes, frequently used in this type of study. In order to contribute to the understanding of the epidemiology of bovine abortion associated with Neospora caninum, a mixed model accounting for the hierarchical structure of cattle population using data from a cross-sectional study conducted in two regions (northwest and southeast) of Rio Grande do Sul was made. Data from 60 dairy herds and 1256 sampled cattle were used. The percentage of abortions in each herd ranged between 1% and 30%. Seropositive cows were 6.63 times more likely to have a history of abortion (95% CI: 4.41 to 13.20). The chances of a cow have a history of abortion were 5.18 times higher in the northwest comparing with the southeast region (95% CI: 1.83 to 20.80). An intraclass correlation coefficient (ICC) of 16% was estimated which means that 16% of the variation in abortion occurrence not explained by the fixed effects is due to farms. In the second part of this work, a systematic review was conducted considering a range of journals and newspapers in order to verify the statistical methods used and the adequacy of the interpretations of the measures of association estimated in cross-sectional studies from the veterinary medicine field. A total of 62 articles were revised. The review showed that, regardless of the reported prevalence, 96% of them employed logistic regression, therefore estimating odds ratio (OR). From the articles that reported prevalence rates above 10%, 23 of them did a proper interpretation of OR as an odds ratio, or simply did not make a direct interpretation of the OR, while 23 articles interpreted improperly the OR as a risk or probability. Among the articles that reported prevalence rates lower than 10%, only three interpreted the OR as an odds ratio, five interpreted as a risk or probability and only one, despite the estimated prevalence ratio (PR), it was improperly interpreted. Meanwhile, in order to exemplify the use of statistical methods to estimate directly the PR, the more appropriate measure of association in cross-sectional studies, a data set obtained from a cross-sectional study to estimate the occurrence of antibodies (AB) against bovine viral diarrhea virus (BVDV) in milk was used; AB were measured in bulk tank samples from dairy herds located in the state of Rio Grande do Sul, Brazil, and also possible associated factors were estimated. Among the methods used, major discrepancies in the measures of association estimated were observed with the logistic regression, comparing with the log-binomial regression. Finally, it is important that such challenges are met by the researchers that undertake cross-sectional studies.

Invasive species represent a major concern; they can result in serious ecological and economic losses and are recognised as one of the most serious threats to global species diversity. Plant invasions are of particular concern in New Zealand, which has high proportions of both naturalised and endemic plant species. In this thesis I focussed on the invasive plant Hieracium lepidulum, an exotic weed introduced from Europe to New Zealand prior to 1941. It is invasive in a variety of habitats in the South Island, where it has steadily increased in distribution and abundance over the last 50 years, and is thought to have detrimental impacts on native plant communities. I investigated factors influencing its invasion success and tested for impacts on native plant communities, making extensive use of existing plots into which H. lepidulum was experimentally introduced in 2003. I examined how community richness, turnover, resource availability and propagule pressure of the invader interacted to determine the invasion success of H. lepidulum. Results differed markedly above and below treeline. Above treeline, plots with higher richness and turnover were more invaded; below treeline, plots with higher available light were more invaded. In both habitats, these findings were modified by the influence of propagule pressure; at low propagule pressure, site characteristics were non-significant in explaining invasion success, while at higher propagule pressure these effects became significant. To test for impacts resulting in altered community composition and structure, I looked for changes in community richness, diversity and evenness subsequent to H. lepidulum introduction. As impacts may be more apparent at fine spatial scales, I made measurements at a 5 x 5 cm cell scale in addition to the established 30 x 30 cm plot scale. Plot species richness increased from 2003 to 2009 and a component of this increase was associated with H. lepidulum density. Other relationships between the plant community and H. lepidulum were generally non-significant. Results showed that H. lepidulum has had no negative effects on community richness, evenness or diversity. Despite being able to opportunistically colonise grassland sites with high turnover, and forest sites subject to canopy disturbance, dependant on propagule pressure, it appears H. lepidulum has not impacted community composition or structure.

<p>For researches in the field of the data mining and machine learning the necessary condition is an availability of various input data set. Now researchers create the databases of such sets. Examples of the following systems are: The UCI Machine Learning Repository, Data Envelopment Analysis Dataset Repository, XMLData Repository, Frequent Itemset Mining Dataset Repository. Along with above specified statistical repositories, the whole pleiad from simple filestores to specialized repositories can be used by researchers during solution of applied tasks, researches of own algorithms and scientific problems. It would seem, a single complexity for the user will be search and direct understanding of structure of so separated storages of the information. However detailed research of such repositories leads us to comprehension of deeper problems existing in usage of data. In particular a complete mismatch and rigidity of data files structure with SDMX - Statistical Data and Metadata Exchange - standard and structure used by many European organizations, impossibility of preliminary data origination to the concrete applied task, lack of data usage history for those or other scientific and applied tasks.</p><p>Now there are lots of methods of data miming, as well as quantities of data stored in various repositories. In repositories there are no methods of DM (data miming) and moreover, methods are not linked to application areas. An essential problem is subject domain link (problem domain), methods of DM and datasets for an appropriate method. Therefore in this work we consider the building problem of ontological models of DM methods, interaction description of methods of data corresponding to them from repositories and intelligent agents allowing the statistical repository user to choose the appropriate method and data corresponding to the solved task. In this work the system structure is offered, the intelligent search agent on ontological model of DM methods considering the personal inquiries of the user is realized.</p><p>For implementation of an intelligent data and metadata exchange repository the agent oriented approach has been selected. The model uses the service oriented architecture. Here is used the cross platform programming language Java, multi-agent platform Jadex, database server Oracle Spatial 10g, and also the development environment for ontological models - Protégé Version 3.4.</p>

Um dos estudos observacionais mais difundidos e usados em epidemiologia veterinária é o estudo do tipo transversal. Sua popularidade ocorre por fatores como baixo custo e rapidez comparados com outros tipos de estudos, além de ajudar a estimar a prevalência de uma doença (desfecho) e postular fatores associados com o desfecho, que poderão ser confirmados como fatores causais em outros tipos de estudos epidemiológicos. Porém, este tipo de estudo apresenta dois importantes desafios: a dependência dos dados, muito frequente dada a típica estrutura populacional de animais dentro do mesmo rebanho ou fazenda e a escolha da medida de associação para desfechos binários, tão frequentes neste modelo de estudo. Com o objetivo de contribuir com a compreensão global da epidemiologia do aborto bovino associado à Neospora caninum tendo em conta a estrutura populacional, construiu-se um modelo misto com os dados de um estudo transversal realizado em duas regiões do Rio Grande do Sul. Usaram-se dados de 60 propriedades amostradas em duas regiões (noroeste e sudeste) e 1256 bovinos. A percentagem de aborto dentro de cada rebanho variou entre 1% e 30%. Vacas soropositivas tiveram 6,63 vezes mais chances de ter histórico de aborto (IC 95%: 4,41-13,20). As chances de uma vaca ter histórico de aborto foram 5,18 vezes maiores na região noroeste em relação à região sudeste (IC 95%: 1,83-20,80). Um coeficiente de correlação intraclasse de 16% foi estimado, indicando que 16% da variação da ocorrência de abortamentos não explicados pelos efeitos fixos foram devido as fazendas. Já na segunda parte deste trabalho, uma revisão sistemática foi realizada considerando um conjunto diverso de revistas e jornais com o objetivo de verificar os métodos estatísticos usados e a adequação das interpretações das medidas de associação estimadas em estudos transversais na área de medicina veterinária. Um total de 62 artigos foi avaliado. A revisão mostrou que, independentemente do nível de prevalência relatado no artigo, 96% deles empregou regressão logística e, portanto, estimaram razão de chances (RC). Nos artigos com prevalência superior a 10%, 23 deles fizeram uma interpretação adequada da RC como uma “razão de chances” ou simplesmente não fizeram uma interpretação direta da RC, enquanto 23 artigos interpretaram de forma inadequada a RC, considerando-a como risco ou probabilidade. Entre os artigos com prevalência inferior a 10%, apenas três interpretaram a RC como uma “razão de chances”, cinco interpretaram como risco ou probabilidade e em um, apesar de ter estimado a razão de prevalências (RP), foi interpretado de forma inadequada. Paralelamente, com o objetivo de exemplificar o uso de métodos estatísticos que estimam diretamente a razão de prevalências (RP), medida mais adequada para os estudos transversais, um conjunto de dados obtidos a partir de um estudo transversal sobre a ocorrência de anticorpos (AC) contra o vírus da diarreia viral bovina (BVDV) foi usado. Os AC foram medidos em amostras de tanque de leite de rebanhos leiteiros localizados no estado do Rio Grande do Sul, em que os possíveis fatores associados puderam ser avaliados. Entre os métodos utilizados, as maiores discrepâncias nas medidas de associação estimadas foram observadas com a regressão logística tomando-se como referência a regressão log-binomial. Finalmente, é importante que este tipo de desafio seja atendido pelos pesquisadores que realizam estudos transversais, ou seja, considerar a estrutura das populações nas análises, cuidado ao escolher o tipo de modelo estatístico empregado para desfecho binário e interpretação dos estimadores. / The commonest study design used in veterinary epidemiology is the cross-sectional study. Its popularity lies on the fact of the short time needed and low costs compared with other types of studies; moreover, this type of study estimates prevalence and associated factors, which may be elucidated as causal in another type of epidemiological studies. However, this type of study presents two major challenges: a very common dependence between data given the typical structure of the animal population, i.e., animals within herds or farms and the choice of measure of association for binary outcomes, frequently used in this type of study. In order to contribute to the understanding of the epidemiology of bovine abortion associated with Neospora caninum, a mixed model accounting for the hierarchical structure of cattle population using data from a cross-sectional study conducted in two regions (northwest and southeast) of Rio Grande do Sul was made. Data from 60 dairy herds and 1256 sampled cattle were used. The percentage of abortions in each herd ranged between 1% and 30%. Seropositive cows were 6.63 times more likely to have a history of abortion (95% CI: 4.41 to 13.20). The chances of a cow have a history of abortion were 5.18 times higher in the northwest comparing with the southeast region (95% CI: 1.83 to 20.80). An intraclass correlation coefficient (ICC) of 16% was estimated which means that 16% of the variation in abortion occurrence not explained by the fixed effects is due to farms. In the second part of this work, a systematic review was conducted considering a range of journals and newspapers in order to verify the statistical methods used and the adequacy of the interpretations of the measures of association estimated in cross-sectional studies from the veterinary medicine field. A total of 62 articles were revised. The review showed that, regardless of the reported prevalence, 96% of them employed logistic regression, therefore estimating odds ratio (OR). From the articles that reported prevalence rates above 10%, 23 of them did a proper interpretation of OR as an odds ratio, or simply did not make a direct interpretation of the OR, while 23 articles interpreted improperly the OR as a risk or probability. Among the articles that reported prevalence rates lower than 10%, only three interpreted the OR as an odds ratio, five interpreted as a risk or probability and only one, despite the estimated prevalence ratio (PR), it was improperly interpreted. Meanwhile, in order to exemplify the use of statistical methods to estimate directly the PR, the more appropriate measure of association in cross-sectional studies, a data set obtained from a cross-sectional study to estimate the occurrence of antibodies (AB) against bovine viral diarrhea virus (BVDV) in milk was used; AB were measured in bulk tank samples from dairy herds located in the state of Rio Grande do Sul, Brazil, and also possible associated factors were estimated. Among the methods used, major discrepancies in the measures of association estimated were observed with the logistic regression, comparing with the log-binomial regression. Finally, it is important that such challenges are met by the researchers that undertake cross-sectional studies.