Validation of a system of classifying female substance abusers on the basis of personality and motivational risk factors for substance abuse.

This study explored the validity of classifying a community-recruited sample of substance-abusing women (N?=?293) according to 4 personality risk factors for substance abuse (anxiety sensitivity, introversion-hopelessness, sensation seeking, and impulsivity). Cluster analyses reliably identified 5 subtypes of women who demonstrated differential lifetime risk for various addictive and nonaddictive disorders. An anxiety-sensitive subtype demonstrated greater lifetime risk for anxiolytic dependence, somatization disorder, and simple phobia, whereas an introverted-hopeless subtype evidenced a greater lifetime risk for opioid dependence, social phobia, and panic and depressive disorders. Sensation seeking was associated with exclusive alcohol dependence, and impulsivity was associated with higher rates of antisocial personality disorder and cocaine and alcohol dependence. Finally, a low personality risk subtype demonstrated lower lifetime rates of substance dependence and psychopathology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

CEVCLUS: evidential clustering with instance-level constraints for relational data

Recent advances in clustering consider incorporating background knowledge in the partitioning algorithm, using, e.g., pairwise constraints between objects. As a matter of fact, prior information, when available, often makes it possible to better retrieve meaningful clusters in data. Here, this approach is investigated in the framework of belief functions, which allows us to handle the imprecision and the uncertainty of the clustering process. In this context, the EVCLUS algorithm was proposed for partitioning objects described by a dissimilarity matrix. It is extended here so as to take pairwise constraints into account, by adding a term to its objective function. This term corresponds to a penalty term that expresses pairwise constraints in the belief function framework. Various synthetic and real datasets are considered to demonstrate the interest of the proposed method, called CEVCLUS, and two applications are presented. The performances of CEVCLUS are also compared to those of other constrained clustering algorithms.     

An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.     

Threshold protocols in survivor set systems

Many replication protocols employ a threshold model when expressing failures they are able to tolerate. In this model, one assumes that no more than t out of n components can fail, which is a good representation when failures are independent and identically distributed (IID). In many real systems, however, failures are not IID, and a straightforward application of threshold protocols yields suboptimal results. Here, we examine the problem of transforming threshold protocols into survivor-set protocols tolerating dependent failures. Our main goal is to show the equivalence between the threshold model and the core/survivor set model. Toward this goal, we develop techniques to transform threshold protocols into survivor set ones. Our techniques do not require authentication, self-verification or encryption. Our results show in one case that we can transform a threshold protocol to a subset by spreading a number of processes across processors. This technique treats a given threshold algorithm as a black box, and consequently can transform any threshold algorithm. However, it has the disadvantage that the transformation is not possible for all sets of survivor sets. The second technique instead focuses on transforming voters: functions that evaluate to a value out of a set of tallied values in a replication protocol. Voters are an essential part of many fault-tolerant protocols, and we show a universal way of transforming them. With such a transformation we expect that a large number of protocols in the literature can be directly transformed with our technique. It is still an open problem, however, if the two models are equivalent, and our results constitute an important first step in this direction.     

Polyominoes simulating arbitrary-neighborhood zippers and tilings

This paper provides a bridge between the classical tiling theory and the complex-neighborhood self-assembling situations that exist in practice.The neighborhood of a position in the plane is the set of coordinates which are considered adjacent to it. This includes classical neighborhoods of size four, as well as arbitrarily complex neighborhoods. A generalized tile system consists of a set of tiles, a neighborhood, and a relation which dictates which are the “admissible” neighboring tiles of a given tile. Thus, in correctly formed assemblies, tiles are assigned positions of the plane in accordance with this relation.We prove that any validly tiled path defined in a given but arbitrary neighborhood (a zipper) can be simulated by a simple “ribbon” of microtiles. A ribbon is a special kind of polyomino, consisting of a non-self-crossing sequence of tiles on the plane, in which successive tiles stick along their adjacent edge.Finally, we extend this construction to the case of traditional tilings, proving that we can simulate arbitrary-neighborhood tilings by simple-neighborhood tilings, while preserving some of their essential properties.     

Statistical tolerance analysis of a hyperstatic mechanism,using system reliability methods

The quality level of a mechanism can be evaluated a posteriori after several months by following the number of warranty returns. However, it is more interesting to evaluate a predicted quality level in the design stage: this is one of the aims of statistical tolerance analysis. A possible method consists of computing the defect probability (P_D) expressed in ppm. It represents the probability that a functional requirement will not be satisfied in mass production. For assembly reasons, many hyperstatic mechanisms require gaps, which their functional requirements depend on. The defect probability assessment of such mechanisms is not straightforward, and requires advanced numerical methods. This problem particularly interests the VALEO W.S. company, which experiences problems with an assembly containing gaps. This paper proposes an innovative methodology to formulate and compute the defect probability of hyperstatic mechanisms with gaps in two steps. First, a complex feasibility problem is converted into a simpler problem. Then the defect probability is efficiently computed thanks to system reliability methods and the m-dimensional multivariate normal distribution Φ_m. Finally, a sensitivity analysis is provided to improve the original design. The whole approach is illustrated with an industrial case study, but can be adapted to other similar problems.     

Computational methods for database repair by signed formulae*

We introduce a simple and practical method for repairing inconsistent databases. Given a possibly inconsistent database, the idea is to properly represent the underlying problem, i.e., to describe the possible ways of restoring its consistency. We do so by what we call signed formulae, and show how the ‘signed theory’ that is obtained can be used by a variety of off-the-shelf computational models in order to compute the corresponding solutions, i.e., consistent repairs of the database. *This paper is a revised and extended version of [9].     

3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface

Three-dimensional surface defect inspection remains a challenging task. This paper describes a novel automatic vision-based inspection system that is capable of detecting and characterizing defects on an airplane exterior surface. By analyzing 3D data collected with a 3D scanner, our method aims to identify and extract the information about the undesired defects such as dents, protrusions or scratches based on local surface properties. Surface dents and protrusions are identified as the deviations from an ideal, smooth surface. Given an unorganized point cloud, we first smooth noisy data by using Moving Least Squares algorithm. The curvature and normal information are then estimated at every point in the input data. As a next step, Region Growing segmentation algorithm divides the point cloud into defective and non-defective regions using the local normal and curvature information. Further, the convex hull around each defective region is calculated in order to englobe the suspicious irregularity. Finally, we use our new technique to measure the dimension, depth, and orientation of the defects. We tested and validated our novel approach on real aircraft data obtained from an Airbus A320, for different types of defect. The accuracy of the system is evaluated by comparing the measurements of our approach with ground truth measurements obtained by a high-accuracy measuring device. The result shows that our work is robust, effective and promising for industrial applications.     

Estimation of polyvinyl alcohol cryogel mechanical properties with four ultrasound elastography methods and comparison with gold standard testings

Tissue-mimicking phantoms are very useful in the field of tissue characterization and essential in elastography for the purpose of validating motion estimators. This study is dedicated to the characterization of polyvinyl alcohol cryogel (PVA-C) for these types of applications. A strict fabrication procedure was defined to optimize the reproducibility of phantoms having a similar elasticity. Following mechanical stretching tests, the phantoms were used to compare the accuracy of four different elastography methods. The four methods were based on a one-dimensional (1-D) scaling factor estimation, on two different implementations of a 2-D Lagrangian speckle model estimator (quasistatic elastography methods), and on a 1-D shear wave transient elastography technique (dynamic method). Young's modulus was investigated as a function of the number of freeze-thaw cycles of PVA-C, and of the concentration of acoustic scatterers. Other mechanical and acoustic parameters-such as the speed of sound, shear wave velocity, mass density, and Poisson's ratio-also were assessed. The Poisson's ratio was estimated with good precision at 0.499 for all samples, and the Young's moduli varied in a range of 20 kPa for one freeze-thaw cycle to 600 kPa for 10 cycles. Nevertheless, above six freeze-thaw cycles, the results were less reliable because of sample geometry artifacts. However, for the samples that underwent less than seven freeze-thaw cycles, the Young's moduli estimated with the four elastography methods showed good matching with the mechanical tensile tests with a regression coefficient varying from 0.97 to 1.07, and correlations R2 varying from 0.93 to 0.99, depending on the method.