MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

An Efficient Nominal Unification Algorithm

Nominal Unification is an extension of first-order unification where terms can contain binders and unification is performed modulo α equivalence. Here we prove that the existence of nominal unifiers can be decided in quadratic time. First, we linearly-reduce nominal unification problems to a sequence of freshness and equalities between atoms, modulo a permutation, using ideas as Paterson and Wegman for first-order unification. Second, we prove that solvability of these reduced problems may be checked in quadràtic time. Finally, we point out how using ideas of Brown and Tarjan for unbalanced merging, we could solve these reduced problems more efficiently

Time constant of the cerebral arterial bed in normal subjects.

The time constant of cerebral arterial bed (in brief time constant) is a product of brain arterial compliance (C(a)) and resistance (CVR). We tested the hypothesis that in normal subjects, changes in end-tidal CO(2) (EtCO(2)) affect the value of the time constant. C(a) and CVR were estimated using mathematical transformations of arterial pressure (ABP) and transcranial Doppler (TCD) cerebral blood flow velocity waveforms. Responses of the time constant to controlled changes in EtCO(2) were compared in 34 young volunteers. Hypercapnia shortened the time constant (0.22 s [0.17, 0.26] vs. 0.16 s [0.13, 0.20]; p = 0.000001), while hypocapnia lengthened the time constant (0.22 s [0.17, 0.26] vs. 0.23 s [0.19, 0.32]; p < 0.0032). The time constant was negatively correlated with changes in EtCO(2) (R(partial) = -0.68, p < 0.000001). This was associated with a decrease in CVR when EtCO(2) increased (R(partial) = -0.80, p < 0.000001) and C(a) remained independent of changes in EtCO(2). C(a) was negatively correlated with mean ABP (R(partial) = -0.68, p < 0.000001). In summary, the time constant shortens with increasing EtCO(2). Its potential role in cerebrovascular investigations needs further studies.

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images

The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

Parole, personnage et sujet dans les récits littéraires de Benjamin Constant

Même si Alison Fairlie, Tzvetan Todorov, Han Verhoeff et Simone Balayé ont reconnu l'importance de la parole dans les récits littéraires de Benjamin Constant (Amélie et Germaine, Cécile, Ma vie et Adolphe), dans leurs commentaires ces critiques ont surtout mis en évidence les échecs et les malentendus inhérents à toute communication verbale. Au-delà de ces constatations, il restait à montrer que les récits constantiens donnent à voir et à comprendre l'intérêt que cet écrivain nourrissait pour la parole, tout particulièrement pour la parole privée -celle qu'il a choisi de mettre en scène dans ces quatre oeuvres, qui acquièrent, grâce à cette spécificité, une manière d'unité. Cette parole intime, aux antipodes de la parole publique, s'offre comme un champ d'investigation illimité tant le locuteur est alors impliqué dans sa pratique verbale. Les introspections des narrateurs-personnages constantiens font naître la peinture d'un sujet moderne, fragilisé dans sa vie personnelle et peu engagé dans la vie sociale, mais elles offrent surtout un vaste panorama des situations d'interlocution et présentent en creux les nombreuses ressources de la parole. Ces récits, qui accordent une attention tout à fait signifiante à l'écriture de la parole, mais échappent parfois à toute classification générique, parviennent à mimer les incertitudes de leur narrateur-personnage tout en révélant que c'est par la parole, originale et singulière, que le sujet s'individualise expérience rendue souvent difficile à cause de la langue conventionnelle dont usent ceux que l'on rencontre dans les lieux de sociabilité, en ce XIXe siècle naissant.

Time of ruin in a risk model with generalized Erlang (n) interclaim times and a constant dividend barrier

In this paper we analyze the time of ruin in a risk process with the interclaim times being Erlang(n) distributed and a constant dividend barrier. We obtain an integro-differential equation for the Laplace Transform of the time of ruin. Explicit solutions for the moments of the time of ruin are presented when the individual claim amounts have a distribution with rational Laplace transform. Finally, some numerical results and a compare son with the classical risk model, with interclaim times following an exponential distribution, are given.

Non-constant discounting in finite horizon: The free terminal time case

This paper derives the HJB (Hamilton-Jacobi-Bellman) equation for sophisticated agents in a finite horizon dynamic optimization problem with non-constant discounting in a continuous setting, by using a dynamic programming approach. A simple example is used in order to illustrate the applicability of this HJB equation, by suggesting a method for constructing the subgame perfect equilibrium solution to the problem.Conditions for the observational equivalence with an associated problem with constantdiscounting are analyzed. Special attention is paid to the case of free terminal time. Strotz¿s model (an eating cake problem of a nonrenewable resource with non-constant discounting) is revisited.