Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agents Location Using Hidden Markov Models

We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent's position using the forward algorithm. Second, it uses the Baum-Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method

Cartographie génétique fine par le graphe de recombinaison ancestral

Thèse diffusée initialement dans le cadre d'un projet pilote des Presses de l'Université de Montréal/Centre d'édition numérique UdeM (1997-2008) avec l'autorisation de l'auteur

A preliminary study of mercury exposure and blood pressure in the Brazilian Amazon

BACKGROUND: Fish is considered protective for coronary heart disease (CHD), but mercury (Hg) intake from fish may counterbalance beneficial effects. Although neurotoxic effects of methylmercury (MeHg) are well established, cardiovascular effects are still debated. The objective of the present study was to evaluate blood pressure in relation to Hg exposure and fish consumption among a non-indigenous fish-eating population in the Brazilian Amazon. METHODS: The study was conducted among 251 persons from six communities along the Tapajós River, a major tributary of the Amazon. Data was obtained for socio-demographic information, fish consumption, height and weight to determine body mass index (BMI), systolic and diastolic blood pressure, and Hg concentration in hair samples. RESULTS: Results showed that overall, systolic and diastolic blood pressure, were relatively low (mean: 113.9 mmHg ± 14.6 and 73.7 mmHg ± 11.0). Blood pressure was significantly associated with hair total Hg (H-Hg), age, BMI and gender. No association was observed between fish consumption and blood pressure, although there were significant inter-community differences. Logistic regression analyses showed that the Odds Ratio (OR) for elevated systolic blood pressure (≥ 130 mmHg) with H-Hg ≥ 10 μg/g was 2.91 [1.26–7.28], taking into account age, BMI, smoking, gender and community. CONCLUSION: The findings of this preliminary study add further support for Hg cardiovascular toxicity

Mapping Rare Variants by the Coalescent

Non UBCUnreviewedAuthor affiliation: UQAMFacult

Composite likelihood methods in statistical genetics

Due to the dimension and the dependency structure of genetic data, composite likelihood methods have found their natural place in the statistical methodo-logy involving such data. After a brief description of the type of data one encounters in population genetic studies, we introduce the questions of interest concerning the main genetic parameters in population genetics, and present an up-to-date review on how composite likelihoods have been used to estimate these parameters

A Composite-Conditional-Likelihood Approach for Gene Mapping Based on Linkage Disequilibrium in Windows of Marker Loci

A composite-conditional-likelihood (CCL) approach is proposed to map the position of a trait-influencing mutation (TIM) using the ancestral recombination graph (ARG) and importance sampling to reconstruct the genealogy of DNA sequences with respect to windows of marker loci and predict the linkage disequilibrium pattern observed in a sample of cases and controls. The method is designed to fine-map the location of a disease mutation, not as an association study. The CCL function proposed for the position of the TIM is a weighted product of conditional likelihood functions for windows of a given number of marker loci that encompass the TIM locus, given the sample configuration at the marker loci in those windows. A rare recessive allele is assumed for the TIM and single nucleotide polymorphisms (SNPs) are considered as markers. The method is applied to a range of simulated data sets. Not only do the CCL profiles converge more rapidly with smaller window sizes as the number of simulated histories of the sampled sequences increases, but the maximum-likelihood estimates for the position of the TIM remain as satisfactory, while requiring significantly less computing time. The simulations also suggest that non-random samples, more precisely, a non-proportional number of controls versus the number of cases, has little effect on the estimation procedure as well as sample size and marker density beyond some threshold values. Moreover, when compared with some other recent methods under the same assumptions, the CCL approach proves to be competitive.gene mapping, linkage disequilibrium, composite likelihood, conditional likelihood, ancestral recombination graph, importance sampling,

A Composite-Conditional-Likelihood Approach for Gene Mapping Based on Linkage Disequilibrium in Windows of Marker Loci

A composite-conditional-likelihood (CCL) approach is proposed to map the position of a trait-influencing mutation (TIM) using the ancestral recombination graph (ARG) and importance sampling to reconstruct the genealogy of DNA sequences with respect to windows of marker loci and predict the linkage disequilibrium pattern observed in a sample of cases and controls. The method is designed to fine-map the location of a disease mutation, not as an association study. The CCL function proposed for the position of the TIM is a weighted product of conditional likelihood functions for windows of a given number of marker loci that encompass the TIM locus, given the sample configuration at the marker loci in those windows. A rare recessive allele is assumed for the TIM and single nucleotide polymorphisms (SNPs) are considered as markers. The method is applied to a range of simulated data sets. Not only do the CCL profiles converge more rapidly with smaller window sizes as the number of simulated histories of the sampled sequences increases, but the maximum-likelihood estimates for the position of the TIM remain as satisfactory, while requiring significantly less computing time. The simulations also suggest that non-random samples, more precisely, a non-proportional number of controls versus the number of cases, has little effect on the estimation procedure as well as sample size and marker density beyond some threshold values. Moreover, when compared with some other recent methods under the same assumptions, the CCL approach proves to be competitive.

Constraints over Intervals for Specification Based Automatic Software Test Generation

International audienceDeveloping critical software and ensuring its compliance with lawful requirements are difficult, expensive and resource-intensive activities. In the aeronautical industry, it is required to provide some quality guarantees in terms of robustness and functional safety. Documented guidance [1] to produce certifiable software describes the software life cycle processes and verification and validation activities. Among those guidelines, we would like to draw the attention on the need for a description of the functional behavior of the software. A test set for the validation and verification of the software is designed from this functional specification. To develop a test campaign, the test designer must ask him-or herself two questions: • Where to test? That is, which point in the software will be more likely to be badly implemented, i.e., which test case can allow us to detect an incorrect behavior. • How to reach that test case? That is, which configuration of the system under test will allow us to perform the verification of this test case. In order to implement specification based automatic test generation, we first formalize the functional behavior of the software by means of constraints programming [2] over interval variables. Then, with the help of interval constraint solving techniques [3], we describe a method to automatically achieve the two steps of specification based test design. First, we use a mutation testing approach [4] over interval constraints to evaluate the quality of the test set and generate new test cases

Annexe 8 : exposition au mercure et pression sanguine

Published in the Environmental health : a global access science source, 2006, 5:29In ARCHIV 126838Background: Fish is considered protective for coronary heart disease (CHD), but mercury (Hg) intake from fish may counterbalance beneficial effects. Although neurotoxic effects of methylmercury (MeHg) are well established, cardiovascular effects are still debated. The objective of the present study was to evaluate blood pressure in relation to Hg exposure and fish consumption among a non-indigenous fish-eating population in the Brazilian Amazon. Methods: The study was conducted among 251 persons from six communities along the Tapajós River, a major tributary of the Amazon. Data was obtained for socio-demographic information, fish consumption, height and weight to determine body mass index (BMI), systolic and diastolic blood pressure, and Hg concentration in hair samples. Results: Results showed that overall, systolic and diastolic blood pressure, were relatively low (mean: 113.9 mmHg ± 14.6 and 73.7 mmHg ± 11.0). Blood pressure was significantly associated with hair total Hg (H-Hg), age, BMI and gender. No association was observed between fish consumption and blood pressure, although there were significant inter-community differences. Logistic regression analyses showed that the Odds Ratio (OR) for elevated systolic blood pressure (≥ 130 mmHg) with H-Hg ≥ 10 μg/g was 2.91 [1.26–7.28], taking into account age, BMI, smoking, gender and community. Conclusion: The findings of this preliminary study add further support for Hg cardiovascular toxicity