Cognitive conflict in human-automation interactions: a psychophysiological study

The review of literature in sociology and distributed artificial intelligence reveals that the occurrence of conflict is a remarkable precursor to the disruption of multi-agent systems. The study of this concept could be applied to human factors concerns, as man-system conflict appears to provoke perseveration behavior and to degrade attentional abilities with a trend to excessive focus. Once entangled in such conflicts, the human operator will do anything to succeed in his current goal even if it jeopardizes the mission. In order to confirm these findings, an experimental setup, composed of a real unmanned ground vehicle, a ground station is developed. A scenario involving an authority conflict between the participants and the robot is proposed. Analysis of the effects of the conflict on the participants' cognition and arousal is assessed through heart-rate measurement (reflecting stress level) and eye-tracking techniques (index of attentional focus). Our results clearly show that the occurrence of the conflict leads to perseveration behavior and can induce higher heart rate as well as excessive attentional focus. These results are discussed in terms of task commitment issues and increased arousal. Moreover, our results suggest that individual differences may predict susceptibility to perseveration behavior.     

Effective discrepancy and numerical experiments

Many problems require the computation of a high dimensional integral, typically with a few tens of input factors, with a low number of integrand evaluations. To avoid the curse of dimensionality, we reduce the dimension before applying the Quasi-Monte Carlo method. We will show how to reduce the dimension by computing approximate Sobol indices of the variables with a two-levels fractional factorial design. Then, we will use the Sobol indices to define the effective discrepancy, which turns out to be correlated with the QMC error and thus enables one to choose a good sequence for the integral estimation.     

Estimation in X-bar control charts: effects and corrections

This paper presents an approach for improving the control limits of $ \overline{X} $ control charts when the parameters of the process are estimated and the control chart is in operation. In these conditions, the observed average run length (ARL) may be very different from the planned ARL since the parameter estimates may have a larger error. To minimize this problem, the data collected in effective control (phase 2) will be used to re-estimate the parameters with a precision greater than that obtained in phase 1. Thus, we defined a minimum sample size of observations of phase 2, which is constituted of a mixture of two normal distributions that should be used to re-estimate the process parameters. The proposal is illustrated with numerical example.     

容错的网络声明式程序

介绍了基于递归规则的网络声明式语言Netlog的语法和分布式不动点语义,定义了强良好的程序,并证明了强良好的程序的计算结果对有限的消息丢失不敏感.     

Methodological design and comparative evaluation of a MAS providing AmI

Researches on Ambient Intelligent and Ubiquitous Computing using wireless technologies have increased in the last years. In this work, we review several scenarios to define a multi-agent architecture that support the information needs of these new technologies, for heterogeneous domain. Our contribution consists of designing in a methodological way a Context Aware System (involving location services) using agents that can be used in very different domains. We describe all the steps followed in the design of the agent system. We apply a hybridizing methodology between GAIA and AUML. Additionally we propose a way to compare different agent architectures for Context Aware System using agent interactions. So, in this paper, we describe the assignment of weight values to agents interaction in two different MAS architectures for Context Aware problems solving different scenarios inspired in FIPA standard negotiation protocols.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

An agent-based genetic algorithm for hybrid flowshops with sequence dependent setup times to minimise makespan

This paper deals with a variant of flowshop scheduling, namely, the hybrid or flexible flowshop with sequence dependent setup times. This type of flowshop is frequently used in the batch production industry and helps reduce the gap between research and operational use. This scheduling problem is NP-hard and solutions for large problems are based on non-exact methods. An improved genetic algorithm (GA) based on software agent design to minimise the makespan is presented. The paper proposes using an inherent characteristic of software agents to create a new perspective in GA design. To verify the developed metaheuristic, computational experiments are conducted on a well-known benchmark problem dataset. The experimental results show that the proposed metaheuristic outperforms some of the well-known methods and the state-of-art algorithms on the same benchmark problem dataset.     

Use of discrete gradient operators for the automatic determination of vanishing points: Comparative analysis

Thales’ second theorem can be used for the automatic detection of the vanishing points of an image. This paper explores its reliability and accuracy according to the type of operator used for the detection of edges. An algorithm has been used which processes a photographic image according to the operator selected. The result is a point cloud which is then used to find the desired solution. The comparison between the four discrete gradient operators (Frei-Chen, Prewitt, Roberts and Sobel) has been made taking into account the resolution of the image and the number of vanishing points. The results obtained show that Frei-Chen’s operator shows good performance in determining vanishing points with respect to the spatial X axis, Sobel’s operator is the best for determining the vanishing point with respect to the spatial Y axis, Roberts’ operator gives good results for calculating vanishing points in both spatial axes, and Prewitt’s operator is not appropriate for processing this type of image.     

Two-level classifier ensembles for credit risk assessment

Many techniques have been proposed for credit risk assessment, from statistical models to artificial intelligence methods. During the last few years, different approaches to classifier ensembles have successfully been applied to credit scoring problems, demonstrating to be generally more accurate than single prediction models. The present paper goes one step beyond by introducing composite ensembles that jointly use different strategies for diversity induction. Accordingly, the combination of data resampling algorithms (bagging and AdaBoost) and attribute subset selection methods (random subspace and rotation forest) for the construction of composite ensembles is explored with the aim of improving the prediction performance. The experimental results and statistical tests show that this new two-level classifier ensemble constitutes an appropriate solution for credit scoring problems, performing better than the traditional single ensembles and very significantly better than individual classifiers.     

Overall performance measurement in a supply chain: towards a supplier-prime manufacturer based model

This study deals with the supply chain (SC) overall performance expression. The developed idea concerns more particularly the performance of the manufactured products. Indeed, two companies or more contribute to the manufacturing of products that are generally assembled by the prime manufacturer company. Moreover, in the industrial practice, performance scorecards are defined with regard to each process; and the overall performance is neither expressed for each company, nor for the whole SC. We propose here to identify the SC overall performance to the combination of the performances of the different involved companies in the SC. Thus, in order to obtain a definition of such performance, we choose to focus first on the performance of the prime manufacturer. In this sense, the approach is based on the SCOR model for the handling of the main processes around the considered product manufacturing. The prime manufacturer performance is then defined as the aggregation of its involved processes?? performances. While the prime manufacturer performance is strongly dependent on the suppliers?? performance, we suggest the integration of the impacting supplier performance into the prime manufacturer scorecards. From an operational point of view, the MACBETH methodology is used to coherently express both processes and overall performances. More precisely, the Choquet aggregation integral operator is applied in order to model mutual interactions between processes. Finally, the expression of a bearing??s manufacturer performance illustrates the proposition.