Dynamic task allocation for a man-machine symbiotic system

This report presents a methodological approach to the dynamic allocation of tasks in a man-machine symbiotic system in the context of dexterous manipulation and teleoperation. This report addresses a symbiotic system containing two symbiotic partners which work toward controlling a single manipulator arm for the execution of a series of sequential manipulation tasks. It is proposed that an automated task allocator use knowledge about the constraints/criteria of the problem, the available resources, the tasks to be performed, and the environment to dynamically allocate task recommendations for the man and the machine. The presentation of the methodology includes discussions concerning the interaction of the knowledge areas, the flow of control, the necessary communication links, and the replanning of the task allocation. Examples of task allocation are presented to illustrate the results of this methodolgy

Paying Positive to Go Negative: Advertisers' Competition and Media Reports

This paper analyzes a two-sided market for news where advertisers may pay a media outlet to conceal negative information about the quality of their own product (paying positive to avoid negative) and/or to disclose negative information about the quality of their competitors' products (paying positive to go negative). We show that whether advertisers have negative consequences on the accuracy of news reports or not ultimately depends on the extent of correlation among advertisers' products. Specifically, the lower the correlation among the qualities of the advertisers' products, the (weakly) higher the accuracy of the media outlet' reports. Moreover, when advertisers' products are correlated, a higher degree of competition in the market of the advertisers' products may decrease the accuracy of the media outlet's reports.

The 3-D world modeling with updating capability based on combinatorial geometry

A 3-D world modeling technique using range data is discribed. Range data quantify the distances from the sensor focal plane to the object surface, i.e., the 3-D coordinates of discrete points on the object surface are known. The approach proposed herein for 3-D world modeling is based on the Combinatorial Geometry (CG) method which is widely used in Monte Carlo particle transport calculations. First, each measured point on the object surface is surrounded by a small sphere with a radius determined by the range to that point. Then, the 3-D shapes of the visible surfaces are obtained by taking the (Boolean) union of all the spheres. The result is an unambiguous representation of the object's boundary surfaces. The pre-learned partial knowledge of the environment can be also represented using the CG Method with a relatively small amount of data. Using the CG type of representation, distances in desired directions to boundary surfaces of various objects are efficiently calculated. This feature is particularly useful for continuously verifying the world model against the data provided by a range finder, and for integrating range data from successive locations of the robot during motion. The efficiency of the proposed approach is illustrated by simulations of a spherical robot in a 3-D room in the presence of moving obstacles and inadequate prelearned partial knowledge of the environment

Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems

The present work proposes a fast-convergent fault detection and isolation (FDI) scheme for linear systems affected by model uncertainties, such as unknown inputs or unbounded nonlinearities. The finite-time convergence is attained by transforming the I/O signals through Volterra operators with suitably designed kernel functions. A novel feature of the proposed approach is the exploitation of a system decomposition that allows removing the effect of intractable uncertainties while recasting the system dynamics in a form applicable for Volterra operators to achieve non-asymptotic estimation. Remarkably, the proposed approach can reconstruct the state variables of the system in an arbitrarily short time and the fault can be diagnosed efficiently by imposing detection and isolation thresholds on transformed signals. The detectability and isolability of the fault are also characterized. The proposed FDI scheme is applied in simulation to a web process system to diagnose the presence of actuator faults. Simulation results confirm the effectiveness of the proposed scheme in two scenarios with nonlinear uncertainties. Furthermore, comparisons are made between the proposed method and a Sliding Mode Control (SMC) method in terms of estimation performance and computational complexity

Eflornithine is Safer Than Melarsoprol for the Treatment of Second-Stage Trypanosoma Brucei Gambiense Human African Trypanosomiasis.

Patients with second-stage human African trypanosomiasis treated with eflornithine (n = 251) in 2003 in Kiri, southern Sudan, had an adjusted relative risk of death of 0.2 and experienced significantly fewer cutaneous and neurological adverse effects than did patients who were treated with melarsoprol in 2001 and 2002 (n = 708)

Premier bilan du projet de renforcement du dispositif addictologique de l’Ouest vaudois : évaluation de la période 2015-2016

Objectifs et méthode : A la demande du Service de la santé publique (SSP), un premier état des lieux du projet a été mené en juin 2016, soit dix-huit mois après son démarrage, afin d’explorer les activités mises en oeuvre, les difficultés rencontrées et les lacunes constatées lors la mise en place de la collaboration et afin de proposer quelques pistes d’ajustement du dispositif. Une étude de cas descriptive a été réalisée au moyen d’entretiens semi-dirigés avec le responsable du Pôle addictologique et le directeur d’EdS et d’une analyse de documents relatifs au projet. L’analyse des données a porté d’une part sur l’implantation du projet en termes d’adhésion au protocole initial, d’exposition et de qualité et d’autre part sur les dimensions normative (vision globale du projet), fonctionnelle (outils et procédures régissant les rôles et les responsabilités) et clinique (outils et procédures définissant la prise en charge et l’accompagnement des patients) de la collaboration entre EdS et le Pôle addictologique

Fast-convergent Fault Detection and Isolation in an Uncertain Scenario

Abstract\u2014In this paper, a fast-convergent fault detection and isolation architecture is proposed for linear MIMO continuoustime systems. By exploiting a system decomposition technique and making use of kernel-based deadbeat estimators, the state variables can be estimated in a non-asymptotic way. Estimation residuals are then defined to detect the occurrence of a fault and identify the occurring fault function after fault detection. In the noisy scenario, thresholds are defined for the residual to distinguish the effect of the noise from that of the fault. Numerical examples are included to characterize the effectiveness of the proposed FDI architectur

Distributed fault detection and isolation for interconnected systems: a non-asymptotic kernel-based approach

In this paper, a novel framework is proposed for deadbeat distributed Fault Detection and Isolation (FDI) of large-scale continuous-time LTI dynamic systems. The monitored system is composed of several subsystems which are linearly interconnected with unknown parameterization. Each subsystem is monitored by a local diagnoser based on the measured local output, local inputs and the interconnection variables from the neighboring subsystems. The local FDI decision is based on two non-asymptotic state-parameter estimators using Volterra integral operators which eliminate the effect of the unknown initial conditions so that the estimates converge to the true value in a deadbeat manner and therefore the fault diagnosis can be achieved in finite time. Moreover, the unknown interconnection parameters and the unknown fault parameters are simultaneously estimated. Numerical examples are included to show the effectiveness of the proposed FDI architecture