Riparian corridors in California are known to be an important but reduced and degraded resource for landbirds. In spite of previous research, the habitat characteristics that correlate with high landbird abundance remain poorly understood. In particular, the scale at which predictive models are useful (fine scale, watershed, sub-region or region) is ill defined. Herein, point count-based abundance indices for 8 riparian associated/obligate species with uniform and high detection probabilities are correlated with biotic and abiotic habitat variables: a sums of squares procedure is used to select the top 5 predictive variables for each species, best fit linear models are selected in an information theoretic framework, and the relative importance of individual variables assessed. These analyses identified site and vegetation characteristics that could serve as targets for restoration and conservation efforts within this coastal central California region. The specific characteristics vary somewhat across the 8 species I surveyed. In addition, the characteristics that I have found important as predictors are distinct from analyses that others have conducted. Therefore, just as we should probably accept regional variation in the composition of riparian avifaunas, we should also probably expect regional variation in the relationship between habitat variables and avian abundance. It appears that important habitat characteristics vary at the fine, watershed, sub-region and regional scales thus reducing the generality of all of the currently available models.

Orientador: Prof. Dr. David Correa Martins Júnior / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Ciência da Computação, 2014.

Un pointé précis des temps de premières arrivées sismiques joue un rôle important dans de nombreuses études d’imagerie sismique. Un nouvel algorithme adaptif est développé combinant trois approches associant l’utilisation de fenêtres multiples imbriquées, l’estimation des propriétés statistiques d’ordre supérieur et le critère d’information d’Akaike. L’algorithme a l’avantage d’intégrer plusieurs propriétés (l’énergie, la gaussianité, et la stationnarité) dévoilant la présence des premières arrivées. Tandis que les incertitudes de pointés ont, dans certains cas, d’importance équivalente aux pointés eux-mêmes, l’algorithme fournit aussi automatiquement une estimation sur leur incertitudes. La précision et la fiabilité de cet algorithme sont évaluées en comparant les résultats issus de ce dernier avec ceux provenant d’un pointé manuel, ainsi que d’autres pointeurs automatiques. Cet algorithme est simple à mettre en œuvre et ne nécessite pas de grandes performances informatiques. Cependant, la présence de bruit dans les données peut en dégrader la performance. Une double sommation dans le domaine temporel est alors proposée afin d’améliorer la détectabilité des premières arrivées. Ce processus est fondé sur un principe clé : la ressemblance locale entre les traces stackées. Les résultats montrent l’intérêt qu’il y a à appliquer cette sommation avant de réaliser le pointé automatique. / Accurate picking of first arrival times plays an important role in many seismic studies, particularly in seismic tomography and reservoirs or aquifers monitoring. A new adaptive algorithm has been developed based on combining three picking methods (Multi-Nested Windows, Higher Order Statistics and Akaike Information Criterion). It exploits the benefits of integrating three properties (energy, gaussianity, and stationarity), which reveal the presence of first arrivals. Since time uncertainties estimating is of crucial importance for seismic tomography, the developed algorithm provides automatically the associated errors of picked arrival times. The comparison of resulting arrival times with those picked manually, and with other algorithms of automatic picking, demonstrates the reliable performance of this algorithm. It is nearly a parameter-free algorithm, which is straightforward to implement and demands low computational resources. However, high noise level in the seismic records declines the efficiency of the developed algorithm. To improve the signal-to-noise ratio of first arrivals, and thereby to increase their detectability, double stacking in the time domain has been proposed. This approach is based on the key principle of the local similarity of stacked traces. The results demonstrate the feasibility of applying the double stacking before the automatic picking.

Orientador: Simone Aparecida Vieira / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-27T10:19:45Z (GMT). No. of bitstreams: 1 Bakker_YvonneVanessa_M.pdf: 1853475 bytes, checksum: 2ff87ee7761a486f4b4ef47d5be567c8 (MD5) Previous issue date: 2015 / Resumo: A Mata Atlântica é um dos principais biomas do mundo sendo considerada um dos 25 hotspots de biodiversidade. Dentre os ecossistemas associados à Mata Atlântica, a Floresta de Restinga foi quase totalmente dizimada, restando apenas 0,5% de sua área original. A Restinga se caracteriza por ocorrer nos cordões arenosos ao longo da costa onde o solo é distrófico e sujeito a inundações sazonais. Entre as comunidades que ocorrem nas florestas de restinga, destacam-se as epífitas vasculares que, por não terem contato com o solo, possuem adaptações ecológicas que garantem a aquisição de nutrientes via deposição seca e úmida. Para avaliar o papel das epífitas vasculares no funcionamento das Florestas de Restinga realizou-se o levantamento quantitativo da biomassa das epífitas vasculares em uma área de um hectare de Floresta de Restinga, no Núcleo Picinguaba do Parque Estadual da Serra do Mar (PESM), no litoral norte paulista, município de Ubatuba. Para tanto, foi coletado todo o material epifítico presente em 23 forófitos com DAP entre 4,9 e 41,7 cm, previamente selecionados. Cada forófito foi dividido por zonas ecológicas (copa, galhos e tronco), buscando amostrar os indivíduos arbóreos com diferentes (a) arquitetura de copa (A, para palmeiras; B para copa pequena e C, para copa grande) e (b) índice de cobertura por epífitas (ICE) que classifica os indivíduos arbóreos de acordo com o porte e a biomassa das epífitas. Esse material foi então separado e determinado o peso seco por grupos de epífitas: Arácea (Araceae, Gesneriaceae e Piperaceae), Bromeliacea, Orchidaceae e Miscelânia (Cactaceae, Pteridófitas, raízes, e solo aéreo). A zona ecológica que apresentou maior biomassa epifítica foi o tronco, com 54% do total, seguida pelos galhos com 45% do total. A biomassa epifítica variou de 0,01 kg a 28,9 kg por forófito. A biomassa epifítica total de um hectare de floresta, foi estimada em 2,32 Mg ha-1 representando apenas 1,34% de toda biomassa viva acima do solo, no entanto sua contribuição é de 18% da biomassa fotossintetizante da floresta e de mais de 10 Mg ha-1 de biomassa fresca evidenciando a importante contribuição do componente para o funcionamento do ecossistema. A estimativa de biomassa através do modelo alométrico desenvolvido neste estudo, utilizando-se como variáveis preditoras o índice de cobertura por epífitas e o DAP do forófito, representa um importante avanço nos estudos que envolvem a quantificação da biomassa de epífitas vasculares, sendo de fácil utilização e passível de aplicação em diferentes fitofisionomias, permitindo a comparação entre estudos distintos / Abstract: The Atlantic Forest is one of the most important biomes of the world and is considered one of the 25 hotspots of biodiversity. Among the ecosystems associated with the Atlantic Forest, one of the more endangered is the Restinga Forest with only 0,5% of its original area preserved. Restinga is the seasonally flooded coastal forest that occurs in sandy ridges along the coast where the soil is extremely poor in nutrients, very acid and subject to seasonal flooding. Among the communities that occur in Restinga forest, we highlight the vascular epiphytes that by not depending on soil nutrients, may play an important role in nutrient dynamics in these systems. To evaluate the role of vascular epiphytes in Restinga Forests, this study proceeded a quantitative survey of the biomass of vascular epiphytes in an area of one hectare of Restinga forest, in Picinguaba at the Serra do Mar State Park (PESM), Ubatuba, north coast of São Paulo State. On 23 phorophytes with diameter at breast height (DBH) ? 4.8 cm, previously selected, was all the epiphytic material collected, divided by ecological zones (canopy, branches and trunk). The trees were sample trees with different (a) canopy architecture (A, to palm trees; B, to small crown; and C, for large crown) and (b) coverage ratio by epiphytes (ICE), which classifies individual trees according to the size and biomass of epiphytes. This material was separate and determined the dry weight per epiphytes groups: Arácea (Araceae, Gesneriaceae and Piperaceae), Bromeliacea, Orchidaceae and Miscellany (Cactaceae, Pteridophytes, roots, organic matter). The ecological zone with the highest biomass epiphytic was the trunk, with 54% of the total, followed by branches with 45%. An allometric model for the estimation of epiphytes biomass as a function of the host tree DBH, ICE and dry weight of epiphytes was develop based in the information collected. From this model, biomass of vascular epiphytes was estimate in 2,32 Mg ha-1 for 1ha of Restinga forest. The epiphytic biomass per host tree varied from 0.01 kg to 28.9 kg. The total epiphytic biomass represent only 1.34% of all living biomass above ground (AGB), but its contribution is 18% of the photosynthetic biomass of the forest and more than 10 Mg ha-1 of wet biomass, showing the importance of this component to the functioning of the ecosystem. The estimate of biomass through allometric model developed in this study, using as predictors the epiphyte coverage index and the DAP of the host tree, represents an important advance in studies involving the quantification of biomass of vascular epiphytes, being easy to use and applicable in different vegetation types, allowing comparison between different studies / Mestrado / Ecologia / Mestra em Ecologia

Denna studie fokuserar på att klassificera hat-meddelanden riktade mot mobiloperatörerna Verizon,  AT&amp;T and Sprint. Huvudsyftet är att med hjälp av maskininlärningsalgoritmen Support Vector Machines (SVM) klassificera meddelanden i fyra kategorier - Hat, Orsak, Explicit och Övrigt - för att kunna identifiera ett hat-meddelande och dess orsak. Studien resulterade i två metoder: en "naiv" metod (the Naive Method, NM) och en mer "avancerad" metod (the Partial Timeline Method, PTM). NM är en binär metod i den bemärkelsen att den ställer frågan: "Tillhör denna tweet klassen Hat?". PTM ställer samma fråga men till en begränsad mängd av tweets, dvs bara de som ligger inom ± 30 min från publiceringen av hat-tweeten. Sammanfattningsvis indikerade studiens resultat att PTM är noggrannare än NM. Dock tar den inte hänsyn till samtliga tweets på användarens tidslinje. Därför medför valet av metod en avvägning: PTM erbjuder en noggrannare klassificering och NM erbjuder en mer utförlig klassificering. / This study focused on finding the hate tweets posted by the customers of three mobileoperators Verizon, AT&amp;T and Sprint and identifying the reasons for their dissatisfaction. The timelines with a hate tweet were collected and studied for the presence of an explanation. A machine learning approach was employed using four categories: Hate, Reason, Explanatory and Other. The classication was conducted with one-versus-all approach using Support Vector Machines algorithm implemented in a LIBSVM tool. The study resulted in two methodologies: the Naive method (NM) and the Partial Time-line Method (PTM). The Naive Method relied only on the feature space consisting of the most representative words chosen with Akaike Information Criterion. PTM utilized the fact that the majority of the explanations were posted within a one-hour time window of the posting of a hate tweet. We found that the accuracy of PTM is higher than for NM. In addition, PTM saves time and memory by analysing fewer tweets. At the same time this implies a trade-off between relevance and completeness. / <p>Opponent: Kristina Wettainen</p>

本研究乃透過國際間各國之比較，以了解匯率變動對貿易收支與國內產生之效果。共 分成兩大部分，第一部分探討匯率變動對貿易收支的影響。根據傳統的國際收支理論 ，認為在某些情況下，一國匯率的貶值可以改善貿易收支。Miles （１９７９）首先 針對匯率與貿易收支的關係進行實證研究。然而，由於生產與消費有時間落後的現象 ，匯率變動對貿易的效果往往無法立即反映，甚至呈現先惡化再逐步改善的情況，一 般稱為Ｊ曲線效果。針對開發中國家是否存在Ｊ曲線效果，Bahmani-Oskooee （１９ ８５）利用Almon 三階多項分配加以驗證。本文係根據他的模型加以延伸，文中運用 Almon 多項分配方法探討１９７３至１９８７年十個工業國家與十個開發中國家，匯 率變動對貿易收支的影響。為了估計落後期數與多項分配階數，使用兩階段的程序， 首先以Akaike提出的final prediction errer為標準，選擇最適落後期數，然後再檢 定多項分配的階數。第二部分探討匯率變動對產出的影響，依照傳統的理論，匯率貶 值會引起出口增加、進口減少，使國內產出擴充。然而Cooper（１９７１）觀察落後 國家資料，卻發現貶值對國內產出有緊縮效果。Edwards （１９８６）首先使用變異 成分分析開發中國家之匯率變動效果，本文對Edwards 的模型加以延伸，利用Almon 多項分配方法估計，檢視匯率變動是否有Cooper效果，同時比較國際間各國之差異。

This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.

Pharmacometrics is widely used in drug development. Models are developed to describe pharmacological measurements with data gathered from a clinical trial. The information can then be applied to, for instance, safely establish dose-response relationships of a substance. Glycated hemoglobin (HbA1c) is a common biomarker used by models within antihyperglycemic drug development, as it reflects the average plasma glucose level over the previous 8-12 weeks. There are five different nonlinear mixed-effects models that describes HbA1c-formation. They use different biomarkers such as mean plasma glucose (MPG), fasting plasma glucose (FPG), fasting plasma insulin (FPI) or a combination of those. The aim of this study was to compare their performances on a population and an individual level using model averaging (MA) and to explore if reduced trial durations and different treatment could affect the outcome. Multiple weighting methods were applied to the MA workflow, such as the Akaike information criterion (AIC), cross-validation (CV) and a bootstrap model averaging method. Results show that in general, models that use MPG to describe HbA1c-formation on a population level could potentially outperform models using other biomarkers, however, models have shown similar performance on individual level. Further studies on the relationship between biomarkers and model performances must be conducted, since it could potentially lay the ground for better individual HbA1c-predictions. It can then be applied in antihyperglycemic drug development and to possibly reduce sample sizes in a clinical trial. With this project, we have illustrated how to perform MA on the aforementioned models, using different biomarkers as well as the difference between model weights on a population and individual level.

In this reviewwe discuss methodology to ascertain the amount of information in given data sets with respect to determination of model parameters with desired levels of uncertainty.We do this in the context of least squares (ordinary,weighted, iterative reweightedweighted or "generalized", etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in the biological and environmental sciences.

No description available.