Benchmarking sobre técnicas de otimização para modelos de apoio à decisão na medicina intensiva

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Retroanálise de parâmetros geomecânicos baseada em algoritmos de otimização

Dissertação de mestrado integrado em Engenharia Civil

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Does bounded rationality lead to individual heterogeneity? The impact of the experimentation process and of memory constraints

In this paper we explore the effect of bounded rationality on the convergence of individual behavior toward equilibrium. In the context of a Cournot game with a unique and symmetric Nash equilibrium, firms are modeled as adaptive economic agents through a genetic algorithm. Computational experiments show that (1) there is remarkable heterogeneity across identical but boundedly rational agents; (2) such individual heterogeneity is not simply a consequence of the random elements contained in the genetic algorithm; (3) the more rational agents are in terms of memory abilities and pre-play evaluation of strategies, the less heterogeneous they are in their actions. At the limit case of full rationality, the outcome converges to the standard result of uniform individual behavior.

MR MAQ: algorisme de Read Mapping utilitzant la plataforma Hadoop

L’èxit del Projecte Genoma Humà (PGH) l’any 2000 va fer de la “medicina personalitzada” una realitat més propera. Els descobriments del PGH han simplificat les tècniques de seqüenciació de tal manera que actualment qualsevol persona pot aconseguir la seva seqüència d’ADN complerta. La tecnologia de Read Mapping destaca en aquest tipus de tècniques i es caracteritza per manegar una gran quantitat de dades. Hadoop, el framework d’Apache per aplicacions intensives de dades sota el paradigma Map Reduce, resulta un aliat perfecte per aquest tipus de tecnologia i ha sigut l’opció escollida per a realitzar aquest projecte. Durant tot el treball es realitza l’estudi, l’anàlisi i les experimentacions necessàries per aconseguir un Algorisme Genètic innovador que utilitzi tot el potencial de Hadoop.

Chagas disease in Mexico: an analysis of geographical distribution during the past 76 years - A review

Literature from 1928 through 2004 was compiled from different document sources published in Mexico or elsewhere. From these 907 publications, we found 19 different topics of Chagas disease study in Mexico. The publications were arranged by decade and also by state. This information was used to construct maps describing the distribution of Chagas disease according to different criteria: the disease, vectors, reservoirs, and strains. One of the major problems confronting study of this zoonotic disease is the great biodiversity of the vector species; there are 30 different species, with at least 10 playing a major role in human infection. The high variability of climates and biogeographic regions further complicate study and understanding of the dynamics of this disease in each region of the country. We used a desktop Genetic Algorithm for Rule-Set Prediction procedure to provide ecological models of organism niches, offering improved flexibility for choosing predictive environmental and ecological data. This approach may help to identify regions at risk of disease, plan vector-control programs, and explore parasitic reservoir association. With this collected information, we have constructed a data base: CHAGMEX, available online in html format.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Evolution of C(4) phosphoenolpyruvate carboxykinase in grasses, from genotype to phenotype.

C(4) photosynthesis is an adaptation over the classical C(3) pathway that has evolved multiple times independently. These convergences are accompanied by strong variations among the independent C(4) lineages. The decarboxylating enzyme used to release CO(2) around Rubisco particularly differs between C(4) species, a criterion used to distinguish three distinct biochemical C(4) subtypes. The phosphoenolpyruvate carboxykinase (PCK) serves as a primary decarboxylase in a minority of C(4) species. This enzyme is also present in C(3) plants, where it is responsible for nonphotosynthetic functions. The genetic changes responsible for the evolution of C(4)-specific PCK are still unidentified. Using phylogenetic analyses on PCK sequences isolated from C(3) and C(4) grasses, this study aimed at resolving the evolutionary history of C(4)-specific PCK enzymes. Four independent evolutions of C(4)-PCK were shown to be driven by positive selection, and nine C(4)-adaptive sites underwent parallel genetic changes in different C(4) lineages. C(4)-adaptive residues were also observed in C(4) species from the nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME) subtype and particularly in all taxa where a PCK shuttle was previously suggested to complement the NADP-ME pathway. Acquisitions of C(4)-specific PCKs were mapped on a species tree, which revealed that the PCK subtype probably appeared at the base of the Chloridoideae subfamily and was then recurrently lost and secondarily reacquired at least three times. Linking the genotype to subtype phenotype shed new lights on the evolutionary transitions between the different C(4) subtypes.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

Molecular genetics of charcot-marie-tooth disease: from genes to genomes.

Charcot-Marie-Tooth disease (CMT) is a heterogeneous group of disorders of the peripheral nervous system, mainly characterized by distal muscle weakness and atrophy leading to motor handicap. With an estimated prevalence of 1 in 2,500, this condition is one of the most commonly inherited neurological disorders. Mutations in more than 30 genes affecting glial and/or neuronal functions have been associated with different forms of CMT leading to a substantial improvement in diagnostics of the disease and in the understanding of implicated pathophysiological mechanisms. However, recent data from systematic genetic screening performed in large cohorts of CMT patients indicated that molecular diagnosis could be established only in ∼50-70% of them, suggesting that additional genes are involved in this disease. In addition to providing an overview of genetic and functional data concerning various CMT forms, this review focuses on recent data generated through the use of highly parallel genetic technologies (SNP chips, sequence capture and next-generation DNA sequencing) in CMT families, and the current and future impact of these technologies on gene discovery and diagnostics of CMTs.

Spacial debris collector robot : An AI-based and autonomous debris collector satellite simulation

In this paper the core functions of an artificial intelligence (AI) for controlling a debris collector robot are designed and implemented. Using the robot operating system (ROS) as the base of this work a multi-agent system is built with abilities for task planning.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Phylogenetic analyses of C4 photosynthesis evolution in grasses: genetics of convergence and convergence of genes

Summary : During the evolutionary diversification of organisms, similar ecological constraints led to the recurrent appearances of the same traits (phenotypes) in distant lineages, a phenomenon called convergence. In most cases, the genetic origins of the convergent traits remain unknown, but recent studies traced the convergent phenotypes to recurrent alterations of the same gene or, in a few cases, to identical genetic changes. However, these cases remain anecdotal and there is a need for a study system that evolved several times independently and whose genetic determinism is well resolved and straightforward, such as C4 photosynthesis. This adaptation to warm environments, possibly driven by past atmospheric CO2 decreases, consists in a CO2-concentrating pump, created by numerous morphological and biochemical novelties. All genes encoding C4 enzymes already existed in C3 ancestors, and are supposed to have been recruited through gene duplication followed by neo-functionalization, to acquire the cell specific expression pattern and altered kinetic properties that characterize Ca-specific enzymes. These predictions have so far been tested only in species-poor and ecologically marginal C4 dicots. The monocots, and especially the grass family (Poaceae), the most important C4 family in terms of species number, ecological dominance and economical importance, have been largely under-considered as suitable study systems. This thesis aimed at understanding the evolution of the C4 trait in grasses at a molecular level and to use the genetics of C4 photosynthesis to infer the evolutionary history of the C4 phenotype and its driving selective pressures. A molecular phylogeny of grasses and affiliated monocots identified 17 to 18 independent acquisitions of the C4 pathway in the grass family. A relaxed molecular clock was used to date these events and the first C4 evolution was estimated in the Chloridoideae subfamily, between 32-25 million years ago, at a period when atmospheric CO2 abruptly declined. Likelihood models showed that after the COZ decline the probability of evolving the C4 pathway strongly increased, confirming low CO2 as a likely driver of C4 photosynthesis evolution. In order to depict the genetic changes linked to the numerous C4 origins, genes encoding phopshoenolpyruvate carboxylase (PEPC), the key-enzyme responsible for the initial fixation of atmospheric CO2 in the C4 pathway, were isolated from a large sample of C3 and C4 grasses. Phylogenetic analyses were used to reconstruct the evolutionary history of the PEPC multigene family and showed that the evolution of C4-specific PEPC had been driven by positive selection on 21 codons simultaneously in up to eight C4 lineages. These selective pressures led to numerous convergent genetic changes in many different C4 clades, highlighting the repeatability of some evolutionary processes, even at the molecular level. PEPC C4-adaptive changes were traced and used to show multiple appearances of the C, pathway in clades where species tree inferences were unable to differentiate multiple C4 appearances and a single appearance followed by C4 to C3 reversion. Further investigations of genes involved in some of the C4 subtypes only (genes encoding decarboxylating enzymes NADP-malic enzyme and phosphoenolpyruvate carboxykinase) showed that these C4-enzymes also evolved through strong positive selection and underwent parallel genetic changes during the different Ca origins. The adaptive changes on these subtype-specific C4 genes were used to retrace the history of the C4-subtypes phenotypes, which revealed that the evolution of C4-PEPC and C4-decarboxylating enzymes was in several cases disconnected, emphasizing the multiplicity of the C4 trait and the gradual acquisition of the features that create the CO2-pump. Finally, phylogenetic analyses of a gene encoding the Rubisco (the enzyme responsible for the fixation of CO2 into organic compounds in all photosynthetic organisms) showed that C4 evolution switched the selective pressures on this gene. Five codons were recurrently mutated to adapt the enzyme kinetics to the high CO2 concentrations of C4 photosynthetic cells. This knowledge could be used to introgress C4-like Rubisco in C3 crops, which could lead to an increased yield under predicted future high CO2 atmosphere. Globally, the phylogenetic framework adopted during this thesis demonstrated the widespread occurrence of genetic convergence on C4-related enzymes. The genetic traces of C4 photosynthesis evolution allowed reconstructing events that happened during the last 30 million years and proved the usefulness of studying genes directly responsible for phenotype variations when inferring evolutionary history of a given trait. Résumé Durant la diversification évolutive des organismes, des pressions écologiques similaires ont amené à l'apparition récurrente de certains traits (phénotypes) dans des lignées distantes, un phénomène appelé évolution convergente. Dans la plupart des cas, l'origine génétique des traits convergents reste inconnue mais des études récentes ont montré qu'ils étaient dus dans certains cas à des changements répétés du même gène ou, dans de rares cas, à des changements génétiques identiques. Malgré tout, ces cas restent anecdotiques et il y a un réel besoin d'un système d'étude qui ait évolué indépendamment de nombreuses fois et dont le déterminisme génétique soit clairement identifié. La photosynthèse dite en Ça répond à ces critères. Cette adaptation aux environnements chauds, dont l'évolution a pu être encouragé par des baisses passées de la concentration atmosphérique en CO2, est constituée de nombreuses nouveautés morphologiques et biochimiques qui créent une pompe à CO2. La totalité des gènes codant les enzymes Ç4 étaient déjà présents dans les ancêtres C3. Leur recrutement pour la photosynthèse Ç4 est supposé s'être fait par le biais de duplications géniques suivies par une néo-fonctionnalisation pour leur conférer l'expression cellule-spécifique et les propriétés cinétiques qui caractérisent les enzymes C4. Ces prédictions n'ont jusqu'à présent été testées que dans des familles C4 contenant peu d'espèces et ayant un rôle écologique marginal. Les graminées (Poaceae), qui sont la famille C4 la plus importante, tant en termes de nombre d'espèces que de dominance écologique et d'importance économique, ont toujours été considérés comme un système d'étude peu adapté et ont fait le sujet de peu d'investigations évolutives. Le but de cette thèse était de comprendre l'évolution de la photosynthèse en C4 chez les graminées au niveau génétique et d'utiliser les gènes pour inférer l'évolution du phénotype C4 ainsi que les pressions de sélection responsables de son évolution. Une phylogénie moléculaire de la famille des graminées et des monocotylédones apparentés a identifié 17 à 18 acquisitions indépendantes de la photosynthèse chez les graminées. Grâce à une méthode d'horloge moléculaire relâchée, ces évènements ont été datés et la première apparition C4 a été estimée dans la sous-famille des Chloridoideae, il y a 32 à 25 millions d'années, à une période où les concentrations atmosphériques de CO2 ont décliné abruptement. Des modèles de maximum de vraisemblance ont montré qu'à la suite du déclin de CO2, la probabilité d'évoluer la photosynthèse C4 a fortement augmenté, confirmant ainsi qu'une faible concentration de CO2 est une cause potentielle de l'évolution de la photosynthèse C4. Afin d'identifier les mécanismes génétiques responsables des évolutions répétées de la photosynthèse C4, un segment des gènes codant pour la phosphoénolpyruvate carboxylase (PEPC), l'enzyme responsable de la fixation initiale du CO2 atmosphérique chez les plantes C4, ont été séquencés dans une centaine de graminées C3 et C4. Des analyses phylogénétiques ont permis de reconstituer l'histoire évolutive de la famille multigénique des PEPC et ont montré que l'évolution de PEPC spécifiques à la photosynthèse Ça a été causée par de la sélection positive agissant sur 21 codons, et ce simultanément dans huit lignées C4 différentes. Cette sélection positive a conduit à un grand nombre de changements génétiques convergents dans de nombreux clades différents, ce qui illustre la répétabilité de certains phénomènes évolutifs, et ce même au niveau génétique. Les changements sur la PEPC liés au C4 ont été utilisés pour confirmer des évolutions indépendantes du phénotype C4 dans des clades où l'arbre des espèces était incapable de différencier des apparitions indépendantes d'une seule apparition suivie par une réversion de C4 en C3. En considérant des gènes codant des protéines impliquées uniquement dans certains sous-types C4 (deux décarboxylases, l'enzyme malique à NADP et la phosphoénolpyruvate carboxykinase), des études ultérieures ont montré que ces enzymes C4 avaient elles-aussi évolué sous forte sélection positive et subi des changements génétiques parallèles lors des différentes origines de la photosynthèse C4. Les changements adaptatifs sur ces gènes liés seulement à certains sous-types C4 ont été utilisés pour retracer l'histoire des phénotypes de sous-types C4, ce qui a révélé que les caractères formant le trait C4 ont, dans certains cas, évolué de manière déconnectée. Ceci souligne la multiplicité du trait C4 et l'acquisition graduelle de composants participant à la pompe à CO2 qu'est la photosynthèse C4. Finalement, des analyses phylogénétiques des gènes codant pour la Rubisco (l'enzyme responsable de la fixation du CO2 en carbones organiques dans tous les organismes photosynthétiques) ont montré que l'évolution de la photosynthèse Ça a changé les pressions de sélection sur ce gène. Cinq codons ont été mutés de façon répétée afin d'adapter les propriétés cinétiques de la Rubisco aux fortes concentrations de CO2 présentes dans les cellules photosynthétiques des plantes C4. Globalement, l'approche phylogénétique adoptée durant cette thèse de doctorat a permis de démontré des phénomène fréquents de convergence génétique sur les enzymes liées à la photosynthèse C4. Les traces génétiques de l'évolution de la photosynthèse C4 ont permis de reconstituer des évènements qui se sont produits durant les derniers 30 millions d'années et ont prouvé l'utilité d'étudier des gènes directement responsables des variations phénotypiques pour inférer l'histoire évolutive d'un trait donné.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

Prediction in transformed images

The study is related to lossless compression of greyscale images. The goal of the study was to combine two techniques of lossless image compression, i.e. Integer Wavelet Transform and Differential Pulse Code Modulation to attain better compression ratio. This is an experimental study, where we implemented Integer Wavelet Transform, Differential Pulse Code Modulation and an optimized predictor model using Genetic Algorithm. This study gives encouraging results for greyscale images. We achieved a better compression ration in term of entropy for experiments involving quadrant of transformed image and using optimized predictor coefficients from Genetic Algorithm. In an other set of experiments involving whole image, results are encouraging and opens up many areas for further research work like implementing Integer Wavelet Transform on multiple levels and finding optimized predictor at local levels.