Otimização do controle do diagrama de radiação de radares de varredura para rastreio de foguetes usando o método GAMMC para o Caso Planar (GAMMC-P)

Launching centers are designed for scientific and commercial activities with aerospace vehicles. Rockets Tracking Systems (RTS) are part of the infrastructure of these centers and they are responsible for collecting and processing the data trajectory of vehicles. Generally, Parabolic Reflector Radars (PRRs) are used in RTS. However, it is possible to use radars with antenna arrays, or Phased Arrays (PAs), so called Phased Arrays Radars (PARs). Thus, the excitation signal of each radiating element of the array can be adjusted to perform electronic control of the radiation pattern in order to improve functionality and maintenance of the system. Therefore, in the implementation and reuse projects of PARs, modeling is subject to various combinations of excitation signals, producing a complex optimization problem due to the large number of available solutions. In this case, it is possible to use offline optimization methods, such as Genetic Algorithms (GAs), to calculate the problem solutions, which are stored for online applications. Hence, the Genetic Algorithm with Maximum-Minimum Crossover (GAMMC) optimization method was used to develop the GAMMC-P algorithm that optimizes the modeling step of radiation pattern control from planar PAs. Compared with a conventional crossover GA, the GAMMC has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, the GAMMC prevents premature convergence, increases population fitness and reduces the processing time. Therefore, the GAMMC-P uses a reconfigurable algorithm with multiple objectives, different coding and genetic operator MMC. The test results show that GAMMC-P reached the proposed requirements for different operating conditions of a planar RAV.

Anomaly detection from time-changing environmental sensor data streams

This thesis stems from the project with real-time environmental monitoring company EMSAT Corporation. They were looking for methods to automatically ag spikes and other anomalies in their environmental sensor data streams. The problem presents several challenges: near real-time anomaly detection, absence of labeled data and time-changing data streams. Here, we address this problem using both a statistical parametric approach as well as a non-parametric approach like Kernel Density Estimation (KDE). The main contribution of this thesis is extending the KDE to work more effectively for evolving data streams, particularly in presence of concept drift. To address that, we have developed a framework for integrating Adaptive Windowing (ADWIN) change detection algorithm with KDE. We have tested this approach on several real world data sets and received positive feedback from our industry collaborator. Some results appearing in this thesis have been presented at ECML PKDD 2015 Doctoral Consortium.

Mapped cetacean habitat suitability and richness in the Azores, links to ArcGIS files

Marine spatial planning and ecological research call for high-resolution species distribution data. However, those data are still not available for most marine large vertebrates. The dynamic nature of oceanographic processes and the wide-ranging behavior of many marine vertebrates create further difficulties, as distribution data must incorporate both the spatial and temporal dimensions. Cetaceans play an essential role in structuring and maintaining marine ecosystems and face increasing threats from human activities. The Azores holds a high diversity of cetaceans but the information about spatial and temporal patterns of distribution for this marine megafauna group in the region is still very limited. To tackle this issue, we created monthly predictive cetacean distribution maps for spring and summer months, using data collected by the Azores Fisheries Observer Programme between 2004 and 2009. We then combined the individual predictive maps to obtain species richness maps for the same period. Our results reflect a great heterogeneity in distribution among species and within species among different months. This heterogeneity reflects a contrasting influence of oceanographic processes on the distribution of cetacean species. However, some persistent areas of increased species richness could also be identified from our results. We argue that policies aimed at effectively protecting cetaceans and their habitats must include the principle of dynamic ocean management coupled with other area-based management such as marine spatial planning.

Beam Angle Optimization for Automated Coplanar IMRT Lung Plans

Purpose: To investigate the effect of incorporating a beam spreading parameter in a beam angle optimization algorithm and to evaluate its efficacy for creating coplanar IMRT lung plans in conjunction with machine learning generated dose objectives.

Methods: Fifteen anonymized patient cases were each re-planned with ten values over the range of the beam spreading parameter, k, and analyzed with a Wilcoxon signed-rank test to determine whether any particular value resulted in significant improvement over the initially treated plan created by a trained dosimetrist. Dose constraints were generated by a machine learning algorithm and kept constant for each case across all k values. Parameters investigated for potential improvement included mean lung dose, V20 lung, V40 heart, 80% conformity index, and 90% conformity index.

Results: With a confidence level of 5%, treatment plans created with this method resulted in significantly better conformity indices. Dose coverage to the PTV was improved by an average of 12% over the initial plans. At the same time, these treatment plans showed no significant difference in mean lung dose, V20 lung, or V40 heart when compared to the initial plans; however, it should be noted that these results could be influenced by the small sample size of patient cases.

Conclusions: The beam angle optimization algorithm, with the inclusion of the beam spreading parameter k, increases the dose conformity of the automatically generated treatment plans over that of the initial plans without adversely affecting the dose to organs at risk. This parameter can be varied according to physician preference in order to control the tradeoff between dose conformity and OAR sparing without compromising the integrity of the plan.

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Impact of protected forests on rural household fuel tree planting and deforestation: Chiro District, Ethiopia

This study aims at exploring the potential impact of forest protection intervention on rural households’ private fuel tree planting in Chiro district of eastern Ethiopia. The study results revealed a robust and significant positive impact of the intervention on farmers’ decisions to produce private household energy by growing fuel trees on their farm. As participation in private fuel tree planting is not random, the study confronts a methodological issue in investigating the causal effect of forest protection intervention on rural farm households’ private fuel tree planting through non-parametric propensity score matching (PSM) method. The protection intervention on average has increased fuel tree planting by 503 (580.6%) compared to open access areas and indirectly contributed to slowing down the loss of biodiversity in the area. Land cover/use is a dynamic phenomenon that changes with time and space due to anthropogenic pressure and development. Forest cover and land use changes in Chiro District, Ethiopia over a period of 40 years was studied using remotely sensed data. Multi temporal satellite data of Landsat was used to map and monitor forest cover and land use changes occurred during three point of time of 1972,1986 and 2012. A pixel base supervised image classification was used to map land use land cover classes for maps of both time set. The result of change detection analysis revealed that the area has shown a remarkable land cover/land use changes in general and forest cover change in particular. Specifically, the dense forest cover land declined from 235 ha in 1972 to 51 ha in 1986. However, government interventions in forest protection in 1989 have slowed down the drastic change of dense forest cover loss around the protected area through reclaiming 1,300 hectares of deforested land through reforestation program up to 2012.

Algorithme de branch-and-price-and-cut pour le problème de conception de réseaux avec coûts fixes, capacités et un seul produit

De nombreux problèmes liés aux domaines du transport, des télécommunications et de la logistique peuvent être modélisés comme des problèmes de conception de réseaux. Le problème classique consiste à transporter un flot (données, personnes, produits, etc.) sur un réseau sous un certain nombre de contraintes dans le but de satisfaire la demande, tout en minimisant les coûts. Dans ce mémoire, on se propose d'étudier le problème de conception de réseaux avec coûts fixes, capacités et un seul produit, qu'on transforme en un problème équivalent à plusieurs produits de façon à améliorer la valeur de la borne inférieure provenant de la relaxation continue du modèle. La méthode que nous présentons pour la résolution de ce problème est une méthode exacte de branch-and-price-and-cut avec une condition d'arrêt, dans laquelle nous exploitons à la fois la méthode de génération de colonnes, la méthode de génération de coupes et l'algorithme de branch-and-bound. Ces méthodes figurent parmi les techniques les plus utilisées en programmation linéaire en nombres entiers. Nous testons notre méthode sur deux groupes d'instances de tailles différentes (gran-des et très grandes), et nous la comparons avec les résultats donnés par CPLEX, un des meilleurs logiciels permettant de résoudre des problèmes d'optimisation mathématique, ainsi qu’avec une méthode de branch-and-cut. Il s'est avéré que notre méthode est prometteuse et peut donner de bons résultats, en particulier pour les instances de très grandes tailles.

Three Essays on Taxation, Growth and Consumption

The purpose of this dissertation is to examine three distributional issues in macroeconomics. First I explore the effects fiscal federalism on economic growth across regions in China. Using the comprehensive official data set of China for 31 regions from 1952 until 1999, I investigate a number of indicators used by the literature to measure federalism and find robust support for only one such measure: the ratio of local total revenue to local tax revenue. Using a difference-in-difference approach and exploiting the two-year gap in the implementation of a tax reform across different regions of China, I also identify a positive relationship between fiscal federalism and regional economic growth. The second paper hypothesizes that an inequitable distribution of income negatively affects the rule of law in resource-rich economies and provides robust evidence in support of this hypothesis. By investigating a data set that contains 193 countries and using econometric methodologies such as the fixed effects estimator and the generalized method of moments estimator, I find that resource-abundance improves the quality of institutions, as long as income and wealth disparity remains below a certain threshold. When inequality moves beyond this threshold, the positive effects of the resource-abundance level on institutions diminish quickly and turn negative eventually. This paper, thus, provides robust evidence about the endogeneity of institutions and the role income and wealth inequality plays in the determination of long-run growth rates. The third paper sets up a dynamic general equilibrium model with heterogeneous agents to investigate the causal channels which run from a concern for international status to long-run economic growth. The simulation results show that the initial distribution of income and wealth play an important role in whether agents gain or lose from globalization.

Total sediment thickness grid of the Southern Pacific Ocean off West Antarctica, links to NetCDF files

Paleotopographic models of the West Antarctic margin, which are essential for robust simulations of paleoclimate scenarios, lack information on sediment thickness and geodynamic conditions, resulting in large uncertainties. A new total sediment thickness grid spanning the Ross Sea-Amundsen Sea-Bellingshausen Sea basins is presented and is based on all the available seismic reflection, borehole, and gravity modeling data offshore West Antarctica. This grid was combined with NGDC's global 5 arc minute grid of ocean sediment thickness (Whittaker et al., 2013, doi:10.1002/ggge.20181) and extends the NGDC grid further to the south. Sediment thickness along the West Antarctic margin tends to be 3-4 km larger than previously assumed. The sediment volume in the Bellingshausen, Amundsen, and Ross Sea basins amounts to 3.61, 3.58, and 2.78 million km³, respectively. The residual basement topography of the South Pacific has been revised and the new data show an asymmetric trend over the Pacific-Antarctic Ridge. Values are anomalously high south of the spreading ridge and in the Ross Sea area, where the topography seems to be affected by persistent mantle processes. In contrast, the basement topography offshore Marie Byrd Land cannot be attributed to dynamic topography, but rather to crustal thickening due to intraplate volcanism. Present-day dynamic topography models disagree with the presented revised basement topography of the South Pacific, rendering paleotopographic reconstructions with such a limited dataset still fairly uncertain.

El multilateralismo como intervencionismo. Estados Unidos y la Sociedad de Naciones en América Latina (1930-1946)

Este artículo analiza una dinámica de intervenciones de Estados Unidos en América Latina que no ha atraído suficientemente la atención de los historiadores. En los años treinta y cuarenta, cuando Europa se hundía en una nueva confrontación bélica, ciertos sectores del gobierno y del mundo empresarial norteamericano intentaron articular una nueva relación con los países del continente basada en una propuesta de multilateralismo que se había configurado dentro de la Sociedad de Naciones (SN). Estos estadounidenses intentaron establecer una dinámica de relaciones triangulares con los gobiernos latinoamericanos y los organismos técnicos de la SN. Gracias a ello, como se mostrará en este artículo para el caso del funcionamiento del Comité Fiscal de la Sociedad de Naciones, los latinoamericanos fueron capaces de influir en el tipo de políticas que debían emanar de esta relación triangular. La importancia de esta historia no es menor. La relación triangular entre Estados Unidos, América Latina y la SN sirvió de base para la reconstrucción de la gobernanza global liderada por los Estados Unidos tras la guerra.

Combining Taxonomies using Word2vec

Taxonomies have gained a broad usage in a variety of fields due to their extensibility, as well as their use for classification and knowledge organization. Of particular interest is the digital document management domain in which their hierarchical structure can be effectively employed in order to organize documents into content-specific categories. Common or standard taxonomies (e.g., the ACM Computing Classification System) contain concepts that are too general for conceptualizing specific knowledge domains. In this paper we introduce a novel automated approach that combines sub-trees from general taxonomies with specialized seed taxonomies by using specific Natural Language Processing techniques. We provide an extensible and generalizable model for combining taxonomies in the practical context of two very large European research projects. Because the manual combination of taxonomies by domain experts is a highly time consuming task, our model measures the semantic relatedness between concept labels in CBOW or skip-gram Word2vec vector spaces. A preliminary quantitative evaluation of the resulting taxonomies is performed after applying a greedy algorithm with incremental thresholds used for matching and combining topic labels.

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

Prognostic role of the LCS6 KRAS variant in locally advanced rectal cancer: results of the EXPERT-C trial.

Background: Lethal-7 (let-7) is a tumour suppressor miRNA which acts by down-regulating several oncogenes including KRAS. A single-nucleotide polymorphism (rs61764370, T > G base substitution) in the let-7 complementary site 6 (LCS-6) of KRAS mRNA has been shown to predict prognosis in early-stage colorectal cancer (CRC) and benefit from anti-epidermal growth factor receptor monoclonal antibodies in metastatic CRC. Patients and methods: We analysed rs61764370 in EXPERT-C, a randomised phase II trial of neoadjuvant CAPOX followed by chemoradiotherapy, surgery and adjuvant CAPOX plus or minus cetuximab in locally advanced rectal cancer. DNA was isolated from formalin-fixed paraffin-embedded tumour tissue and genotyped using a PCR-based commercially available assay. Kaplan–Meier method and Cox regression analysis were used to calculate survival estimates and compare treatment arms. Results: A total of 155/164 (94.5%) patients were successfully analysed, of whom 123 (79.4%) and 32 (20.6%) had the LCS-6 TT and LCS-6 TG genotype, respectively. Carriers of the G allele were found to have a statistically significantly higher rate of complete response (CR) after neoadjuvant therapy (28.1% versus 10.6%; P = 0.020) and a trend for better 5-year progression-free survival (PFS) [77.4% versus 64.5%: hazard ratio (HR) 0.56; P = 0.152] and overall survival (OS) rates (80.3% versus 71.9%: HR 0.59; P = 0.234). Both CR and survival outcomes were independent of the use of cetuximab. The negative prognostic effect associated with KRAS mutation appeared to be stronger in patients with the LCS-6 TT genotype (HR PFS 1.70, P = 0.078; HR OS 1.79, P = 0.082) compared with those with the LCS-6 TG genotype (HR PFS 1.33, P = 0.713; HR OS 1.01, P = 0.995). Conclusion: This analysis suggests that rs61764370 may be a biomarker of response to neoadjuvant treatment and an indicator of favourable outcome in locally advanced rectal cancer possibly by mitigating the poor prognosis of KRAS mutation. In this setting, however, this polymorphism does not appear to predict cetuximab benefit.

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Proposition de nouvelles fonctionnalités WikiSIG pour supporter le travail collaboratif en Geodesign

L’émergence du Web 2.0 se matérialise par de nouvelles technologies (API, Ajax…), de nouvelles pratiques (mashup, geotagging…) et de nouveaux outils (wiki, blog…). Il repose principalement sur le principe de participation et de collaboration. Dans cette dynamique, le Web à caractère spatial et cartographique c’est-à-dire, le Web géospatial (ou GéoWeb) connait lui aussi de fortes transformations technologiques et sociales. Le GéoWeb 2.0 participatif se matérialise en particulier par des mashups entre wikis et géobrowsers (ArgooMap, Geowiki, WikiMapia, etc.). Les nouvelles applications nées de ces mashups évoluent vers des formes plus interactives d’intelligence collective. Mais ces applications ne prennent pas en compte les spécificités du travail collaboratif, en particulier la gestion de traçabilité ou l’accès dynamique à l’historique des contributions. Le Geodesign est un nouveau domaine fruit de l’association des SIG et du design, permettant à une équipe multidisciplinaire de travailler ensemble. Compte tenu de son caractère émergent, le Geodesign n’est pas assez défini et il requiert une base théorique innovante, de nouveaux outils, supports, technologies et pratiques afin de s’adapter à ses exigences complexes. Nous proposons dans cette thèse de nouvelles fonctionnalités de type WikiSIG, bâties sur les principes et technologies du GéoWeb 2.0 et visant en particulier à supporter la dimension collaborative du processus de Geodesign. Le WikiSIG est doté de fonctionnalités wiki dédiées à la donnée géospatiale (y compris dans sa composante géométrique : forme et localisation) permettant d’assurer, de manière dynamique, la gestion documentée des versions des objets et l’accès à ces versions (et de leurs métadonnées), facilitant ainsi le travail collaboratif en Geodesign. Nous proposons également la deltification qui consiste en la capacité de comparer et d’afficher les différences entre deux versions de projets. Finalement la pertinence de quelques outils du géotraitement et « sketching » est évoquée. Les principales contributions de cette thèse sont d’une part d’identifier les besoins, les exigences et les contraintes du processus de Geodesign collaboratif, et d’autre part de proposer des nouvelles fonctionnalités WikiSIG répondant au mieux à la dimension collaborative du processus. Pour ce faire, un cadre théorique est dressé où nous avons identifié les exigences du travail collaboratif de Geodesign et proposé certaines fonctionnalités WikiSIG innovantes qui sont par la suite formalisés en diagrammes UML. Une maquette informatique est aussi développée de façon à mettre en oeuvre ces fonctionnalités, lesquelles sont illustrées à partir d’un cas d’étude simulé, traité comme preuve du concept. La pertinence de ces fonctionnalités développées proposées est finalement validée par des experts à travers un questionnaire et des entrevues. En résumé, nous montrons dans cette thèse l’importance de la gestion de la traçabilité et comment accéder dynamiquement à l’historique dans un processus de Geodesign. Nous proposons aussi d’autres fonctionnalités comme la deltification, le volet multimédia supportant l’argumentation, les paramètres qualifiant les données produites, et la prise de décision collective par consensus, etc.