Realizar o agrupamento de fluxos de dados contínuos e multidimensionais (multidimensional data streams) é uma tarefa dispendiosa, visto que esses tipos de dados podem possuir características peculiares e que precisam ser consideradas, dentre as quais destacam-se: podem ser infinitos, tornando inviável, em muitas aplicações realizar mais de uma leitura dos dados; ponto de dados podem possuir diversas dimensões e a correlação entre as dimensões pode impactar no resultado final da análise e; são capazes de evoluir com o passar do tempo. Portanto, faz-se necessário o desenvolvimento de métodos computacionais adequados a essas características, principalmente nas aplicações em que realizar manualmente tal tarefa seja algo impraticável em razão do volume de dados, por exemplo, na análise e predição do comportamento climático. Nesse contexto, o objetivo desse trabalho de pesquisa foi propor técnicas computacionais, eficientes e eficazes, que contribuíssem para a extração de conhecimento de fluxos de dados com foco na tarefa de agrupamento de fluxos de dados similares. Assim, no escopo deste trabalho, foram desenvolvidos dois métodos para agrupamento de fluxos de dados evolutivos, multidimensionais e potencialmente infinitos, ambos baseados no conceito de dimensão fractal, até então não utilizada nesse contexto na literatura: o eFCDS, acrônimo para evolving Fractal Clustering of Data Streams, e o eFCC, acrônimo para evolving Fractal Clusters Construction. O eFCDS utiliza a dimensão fractal para mensurar a correlação, linear ou não, existente entre as dimensões dos dados de um fluxo de dados multidimensional num período de tempo. Esta medida, calculada para cada fluxo de dados, é utilizada como critério de agrupamento de fluxos de dados com comportamentos similares ao longo do tempo. O eFCC, por outro lado, realiza o agrupamento de fluxos de dados multidimensionais de acordo com dois critérios principais: comportamento ao longo do tempo, considerando a medida de correlação entre as dimensões dos dados de cada fluxo de dados, e a distribuição de dados em cada grupo criado, analisada por meio da dimensão fractal do mesmo. Ambos os métodos possibilitam ainda a identificação de outliers e constroem incrementalmente os grupos ao longo do tempo. Além disso, as soluções propostas para tratamento de correlações em fluxos de dados multidimensionais diferem dos métodos apresentados na literatura da área, que em geral utilizam técnicas de sumarização e identificação de correlações lineares aplicadas apenas à fluxos de dados unidimensionais. O eFCDS e o eFCC foram testados e confrontados com métodos da literatura que também se propõem a agrupar fluxos de dados. Nos experimentos realizados com dados sintéticos e reais, tanto o eFCDS quanto o eFCC obtiveram maior eficiência na construção dos agrupamentos, identificando os fluxos de dados com comportamento semelhante e cujas dimensões se correlacionam de maneira similar. Além disso, o eFCC conseguiu agrupar os fluxos de dados que mantiveram distribuição dos dados semelhante em um período de tempo. Os métodos possuem como uma das aplicações imediatas a extração de padrões de interesse de fluxos de dados proveniente de sensores climáticos, com o objetivo de apoiar pesquisas em Agrometeorologia. / To cluster multidimensional data streams is an expensive task since this kind of data could have some peculiarities characteristics that must be considered, among which: they are potencially infinite, making many reads impossible to perform; data can have many dimensions and the correlation among them could have an affect on the analysis; as the time pass through they are capable of evolving. Therefore, it is necessary the development of appropriate computational methods to these characteristics, especially in the areas where performing such task manually is impractical due to the volume of data, for example, in the analysis and prediction of climate behavior. In that context, the research goal was to propose efficient and effective techniques that clusters multidimensional evolving data streams. Among the applications that handles with that task, we highlight the evolving Fractal Clustering of Data Streams, and the eFCC acronym for evolving Fractal Clusters Construction. The eFCDS calculates the data streams fractal dimension to correlate the dimensions in a non-linear way and to cluster those with the biggest similarity over a period of time, evolving the clusters as new data is read. Through calculating the fractal dimension and then cluster the data streams the eFCDS applies an innovative strategy, distinguishing itself from the state-of-art methods that perform clustering using summaries techniques and linear correlation to build their clusters over unidimensional data streams. The eFCDS also identifies those data streams who showed anomalous behavior in the analyzed time period treating them as outliers. The other method devoleped is called eFCC. It also builds data streams clusters, however, they are built on a two premises basis: the data distribution should be likely the same and second the behavior should be similar in the same time period. To perform that kind of clustering the eFCC calculates the clusters fractal dimension itself and the data streams fractal dimension, following the evolution in the data, relocating the data streams from one group to another when necessary and identifying those that become outlier. Both eFCDS and eFCC were evaluated and confronted with their competitor, that also propose to cluster data streams and not only data points. Through a detailed experimental evaluation using synthetic and real data, both methods have achieved better efficiency on building the groups, better identifying data streams with similar behavior during a period of time and whose dimensions correlated in a similar way, as can be observed in the result chapter 6. Besides that, the eFCC also cluster the data streams which maintained similar data distribution over a period of time. As immediate application the methods developed in this thesis can be used to extract patterns of interest from climate sensors aiming to support researches in agrometeorology.

To protect and restore the biological integrity of streams, we need to be able to both detect biological degradation and infer likely causes of impairment. Managers often use biological indices to measure biological condition and detect degradation. However, the ability to detect degradation can be limited by the performance of the indices we develop. Index performance varies widely, but the sources of this variation are often unclear. In addition, although bioassessments are useful tools for detecting biological degradation, they do not identify stressors associated with impairment. My thesis research had two general goals: 1) develop statistically and ecologically robust indices to measure biological condition in Nevada streams and 2) quantify relationships between land uses, stressors, and biological condition to infer likely causes of degradation. I developed two biological indices for Nevada streams, a multimetric index (MMI) and observed to expected (O/E) taxa ratios, and determined if index performance was related to site isolation and sample evenness. The Nevada O/E indices were relatively imprecise compared with those from other regions, which likely results from low assemblage predictability associated with spatial isolation of aquatic habitats in arid regions. In contrast, the Nevada MMI was more precise than most previously developed MMIs, likely the result of using models to reduce natural variation in index scores. Sample evenness was positively associated with both O/E and MMI scores. Adjustments of index scores for sample evenness increased index precision, but also altered relative differences in index values and therefore inferences of biological impairment at specific sites. I also quantified relationships between biological condition, instream stressors, and land uses and used a weight of evidence approach to infer likely causes of degradation. Land uses such as agriculture, urbanization, and mining were associated with the spatial distributions of instream stressors, and these stressors were associated with variation in biological condition. Total dissolved solids and metal contamination were the stressors most strongly associated with biological condition. By detecting biological degradation and identifying important stressors and their potential sources, the tools I developed should help managers target conservation and restoration efforts and improve their ability to protect freshwater resources.

Maintaining optimum levels of dissolved oxygen (DO) in natural water systems has become crucial for scientists and decision makers. In general, DO concentrations less than 5 mg/L stress many types of aquatic organisms including fishes. Uncontrolled growth of aquatic autotrophs (i.e., algae and macrophytes) may alter DO concentration if the growth exceeded the capacity of the aquatic food web structure. Primary production and respiration, the two main metabolic processes associated with aquatic autotrophs, were estimated, compared, and critiqued for three streams in Northern Utah, USA. These streams have been under consideration for many years due to their impaired water quality, as they supply water to Cutler Reservoir, the sink of all the transported sediment and nutrients. This study includes estimation of the metabolic rates, examination of the driving/limiting factors, examination of the consequences of the relevant rates on water quality, and a comparison of two methods of estimation of the metabolic rates. The outcome of this research will help scientists and decision makers build knowledgeable strategies to manage DO in the streams based on the given critiques on the cause and effect of the respective metabolic rates. It will also help reduce the cost and time associated with the frequent need to use physical field measurements to estimate metabolic rates in rivers and streams.

Headwater streams are extremely vulnerable to the consequences of land-use change as they are tightly coupled with the surrounding landscape. Understanding the natural processes that influence the structure and function of these ecosystems will improve our understanding of how land-use change affects them. Benthic substratum habitat was investigated in a sub-tropical headwater stream by quantifying temporal change to sediment texture of surface sediments (less than 10cm), over four years. Hydrological characteristics were also surveyed in detail, as hydrological regime is a primary determinant of sediment transportation. Additionally, measures of hydro-geological features - hydraulic conductivity and groundwater depth were made in order to explore features of sediment habitat that extend beyond the sediment-water interface. Whilst the typical discharge pattern was one of intermittent base flows and infrequent, yet extreme flood events associated with monsoonal rain patterns, the study period also encompassed a drought and a one in hundred year flood. Rainfall and discharge did not necessarily reflect the actual conditions in the stream. Surface waters were persistent long after discharge ceased. On several occasions the stream bed was completely dry. Shallow groundwater was present at variable depths throughout the study period, being absent only at the height of the drought. The sediments were mainly gravels, sand and clay. Changes in sediment composition were observed for fine particulates (size categories less than 2mm). The grain size change in the finer sediment fractions was marked over time, although bedload movement was limited to a single high discharge event. In response to a low discharge regimen (drought), sediments characteristically showed non-normal distributions and were dominated by finer materials. High-energy discharge regimes (flood) were characterised by coarsening of sands and a diminished clay fraction. Particulate organic matter from sediments showed trends of build-up and decline with the high and low discharge regimes, respectively. Benthic habitats were described according to prevailing hydro-geological parameters. Faunas from sediment substratum samples were associated with identified habitat categories. The fauna reflected the habitat variability in terms of hydrological disturbance of the substratum structure and intermittency of discharge. An applied multivariate procedure was used to correlate temporally changing environmental parameters and faunal abundance data. Faunas were correlated with a group of variables dominated by either discharge variables or sediment textural parameters. Sediment characteristics that affect substratum quality and substratum preference at the micro-scale were investigated via hypotheses testing. A model of carbon loss was used to determine how long particulate organic matter could potentially sustain microbial activity under experimental conditions. An estimate of up to 200 days was determined from this laboratory experiment. Secondly, enriched carbon isotopes were used in a field-based experiment to establish a link between sediments and macrofauna. Enrichment via organic sediments was found for various detritivorous and carnivorous taxa. In the 'third' experiment, artificial treatments were applied to elucidate substratum preference. Fauna was offered the choice of variable quantities of clay and/or quality of organic matter. There were no significant preferences found for the different substratum treatments, although further investigation is needed and a different outcome from this method may be achieved under more benign field conditions than those encountered during this experiment. Finally, the study was set within a context of the primary features of scale. Climate and hydrological features, including linkages with the alluvial aquifer and terrestrial ecosystem, and their potential to change within 'ecological time' are perceived as critical to understanding the role of benthic sediment substratum.

Intermittent headwater streams serve important functions in semi-arid rangelands, both for humans and wildlife. However, few studies have assessed species-environment relationships for fish and benthic macroinvertebrate assemblages in these systems. Additionally, no published studies could be found that addressed the influence of juniper coverage in watersheds on assemblage structure of these taxa. Increased juniper coverage in recent decades is believed to be associated with decreased water yields in central Texas streams. During summer 2003 and spring 2004, I examined potential effects of juniper cover on aquatic ecology. Fishes, benthic macroinvertebrates, and the physicochemical habitat were investigated in spring-fed headwater tributaries of the Pedernales River. My objectives were to: 1) describe the typical fish and benthic macroinvertebrate assemblages in headwater creeks of the Pedernales River basin; 2) compare seasonal variability of fish and benthic macroinvertebrate assemblages; 3) identify species-environment relationships in this river basin; and 4) evaluate the influence of juniper coverage in the watershed, relative tolocal and landscape-level environmental factors, on the structure of fish and benthic macroinvertebrate assemblages. A total of 4,181 individual fish were collected in summer 2003 samples, 551 fish were collected in spring 2004, 59,555 macroinvertebrates were captured in summer 2003 samples, and 51,500 macroinvertebrates were collected in spring 2004. Assemblages were typical for the area and habitat conditions. Faunal richness was lower in spring than in summer, possibly due to a combination of sampling after a relatively dry period in the spring, and lack of winter refugia in the form of deep pools. Fish assemblages may structure based principally on abiotic factors in spring, the harsher season (less available water), whereas predation pressure may influence structure in summer. Another important environmental gradient for both fish and invertebrate assemblages contrasts pool and run mesohabitats. In general, juniper cover was weakly associated with fish and invertebrate assemblages, although it tended to be associated with relatively high quality habitat for sensitive taxa (flowing runs with coarse substrate; deep, connected pools). In these intermittent streams, local-scale environmental factors probably are the dominant influences on fish and benthic macroinvertebrate assemblages. Implications for future studies are discussed.

Forestry affects most of the forest-covered land in Sweden. In the landscape, the most common stream type is headwaters, which are important sites for many processes and organisms in both the terrestrial and the aquatic ecosystems. The aim of this study was to investigate how the abundance of benthic invertebrate functional feeding groups in headwater streams develops after clear-cutting and if it also is possible to detect a change in the composition of feeding groups. The study also attempts to determine what factors have an effect on temporal changes in abundance of these groups. For the study, 11 sites in northern Sweden were sampled for benthic invertebrates using a Surber-sampler, and for each site canopy-cover and pH was obtained. Further, the age of the surrounding forest at each was visually assessed and created a 100-year gradient along which temporal changes in abundance of the functional feeding groups were investigated. The results revealed that the total abundance of organisms was the highest short after clear-cutting and afterward decreased to the lowest level in streams with the highest age of surrounding forest. Significant results for the functional feeding groups were found for predators, shredders and scrapers, which also had the highest levels of abundance early after clear-cutting and thereafter decreased. The result shows that clear-cutting, not only changes the fundamental terrestrial conditions, but also has an impact on the abundance of different benthic functional feeding group.

This study extends the methodology for the delineation of capture zones to base flow contribution areas for stream reaches under the assumption of constant average annual base flow in the stream. The methodology is applied to the Alder Creek watershed in southwestern Ontario, using three different numerical models. The three numerical models chosen for this research were Visual Modflow, Watflow and HydroGeoSphere. Capture zones were delineated for three different stream segments with reverse particle tracking and reverse transport. The modelling results showed that capture zones delineated for streams are sensitive to the discretization scheme and the different processes considered (i.e. unsaturated zone, surface flow). It is impossible to predict the size, shape and direction of the capture zones delineated based on the model selected. Also, capture zones for different stream segments will reach steady-state at different times. In addition, capture zones are highly sensitive to differences in hydraulic conductivity due to calibration. It was found that finite element based integrated groundwater - surface water models such as HydroGeoSphere are advantageous for the delineation of capture zones for streams. Capture zones created for streams are subject to greater uncertainty than capture zones created for extraction wells. This is because the hydraulic gradients for natural features are very small compared to those for wells. Therefore, numerical and calibration errors can be the same order of magnitude as the gradients that are being modelled. Because of this greater uncertainty, it is recommended that particle tracking and reverse transport always be used together when delineating capture zones for stream reaches. It is uncertain which probability contour to choose when the capture zone is delineated by reverse transport alone. The reverse particle tracks help choose the appropriate probability contour to represent the stream capture zone.

Das Internet ist ein riesiger Experimentierkasten für neue Anwendungssysteme. Potenziell enthält insbesondere das sogenannte Web 2.0 Ideen und Mechanismen, die auch im Organisationsumfeld die Zusammenarbeit zwischen Mitarbeitern unterstützen können. Ein jüngstes Beispiel hierfür sind die von Facebook bekannten Activity Streams. Fraglich ist nun, wie eine Adaption dieses Web 2.0-Vorbilds in Organisationen auszugestalten ist. Hierfür ist zu klären, welcher Anwendungsfall von Activity Streams abgedeckt werden kann, welche Anforderungen hieraus sowie aus dem allgemeinen organisationalen Kontext entstehen und wie schließlich ein entsprechendes Anwendungssystem zu konzipieren ist. Die Arbeit zielt auf die Beantwortung dieser Fragestellungen in Form eines Fachkonzepts, welches anschließend durch eine prototypische Implementierung sowie die Durchführung von Fallstudien in realen Einsatzszenarien Anwendung findet.

Intermittent headwater streams serve important functions in semi-arid rangelands, both for humans and wildlife. However, few studies have assessed species-environment relationships for fish and benthic macroinvertebrate assemblages in these systems. Additionally, no published studies could be found that addressed the influence of juniper coverage in watersheds on assemblage structure of these taxa. Increased juniper coverage in recent decades is believed to be associated with decreased water yields in central Texas streams. During summer 2003 and spring 2004, I examined potential effects of juniper cover on aquatic ecology. Fishes, benthic macroinvertebrates, and the physicochemical habitat were investigated in spring-fed headwater tributaries of the Pedernales River. My objectives were to: 1) describe the typical fish and benthic macroinvertebrate assemblages in headwater creeks of the Pedernales River basin; 2) compare seasonal variability of fish and benthic macroinvertebrate assemblages; 3) identify species-environment relationships in this river basin; and 4) evaluate the influence of juniper coverage in the watershed, relative tolocal and landscape-level environmental factors, on the structure of fish and benthic macroinvertebrate assemblages. A total of 4,181 individual fish were collected in summer 2003 samples, 551 fish were collected in spring 2004, 59,555 macroinvertebrates were captured in summer 2003 samples, and 51,500 macroinvertebrates were collected in spring 2004. Assemblages were typical for the area and habitat conditions. Faunal richness was lower in spring than in summer, possibly due to a combination of sampling after a relatively dry period in the spring, and lack of winter refugia in the form of deep pools. Fish assemblages may structure based principally on abiotic factors in spring, the harsher season (less available water), whereas predation pressure may influence structure in summer. Another important environmental gradient for both fish and invertebrate assemblages contrasts pool and run mesohabitats. In general, juniper cover was weakly associated with fish and invertebrate assemblages, although it tended to be associated with relatively high quality habitat for sensitive taxa (flowing runs with coarse substrate; deep, connected pools). In these intermittent streams, local-scale environmental factors probably are the dominant influences on fish and benthic macroinvertebrate assemblages. Implications for future studies are discussed.

Online mining association rules over data streams is an important issue in the area of data mining, where an association rule means that the presence of some items in a transaction will imply the presence of other items in the same transaction. There are many applications of using association rules in data streams, such as market analysis, network security, sensor networks and web tracking. Mining closed frequent itemsets is a further work of mining association rules, which aims to find the subsets of frequent itemsets that could extract all frequent itemsets. Formally, a closed frequent itemset is an frequent itemset which has no superset with the same support as it. Since data streams are continuous, high-speed, and unbounded, archiving everything from data streams is impossible. That is, we can only scan once for the data streams and it is a main-memory database. Therefore, previous algorithms to mine closed frequent itemsets in the traditional database are not suitable for data streams. On the other hand, many applications are interested in the most recent data, and there is a model to deal with the most recent data in data streams, called emph{Sliding Window Model}, which acquires the recent data with a window size meets this characteristic. One of well-known algorithms for mining closed frequent itemsets which based on the sliding window model is the NewMoment algorithm. However, the NewMoment algorithm could not efficiently mine closed frequent itemsets in data streams, since they will generate closed frequent itemsets and many unclosed frequent itemsets. Moreover, when data in the sliding window is incrementally updated, the NewMoment algorithm needs to reconstruct the whole tree structure. Therefore, in this thesis, we propose a sliding window approach, the Subset-Lattice algorithm, which embeds the subset property into the lattice structure to efficiently mine closed frequent itemsets. Basically, Our proposed algorithm considers five kinds of set concepts : (1) equivalent, (2) superset, (3) subset, (4) intersection, (5) empty relation, when data items are inserted. We judge closed frequent itemsets without generating unclosed frequent itemsets by these five kinds of set concepts. Moreover, when data in the sliding window is incrementally updated, our Subset-Lattice algorithm will not reconstruct the whole lattice structure. Therefore, our Subset-Lattice algorithm is more efficient than the Moment algorithm. Furthermore, we use the bit-pattern to represent the itemsets, and use bit-operations to speed up the set-checking. From our simulation results, we show that our Subset-Lattice algorithm needs less memory and less processing time than the NewMoment algorithm. When window slides, the execution time could be saved up to 50\%.