Integration framework for intelligent manufacturing processes

In this article, we describe a new approach to applying distributed artificial intelligence techniques to manufacturing processes. The construction of intelligent systems is one of the most important techniques among artificial intelligence research. Our goal is to develop an integrated intelligent system for real time manufacturing processes. An integrated intelligent system is a large knowledge integration environment that consists of several symbolic reasoning systems (expert systems) and numerical computation packages. These software programs are controlled by a meta-system which manages the selection, operation and communication of these programs. A meta-system can be implemented in different language environments and applied to many disciplines. This new architecture can serve as a universal configuration to develop high performance intelligent systems for many complicated industrial applications in real world domains.To whom all correspondence should be addressed.     

Clinical psychologists reflect on the usefulness of various components of graduate training.

Graduates of clinical training programs were surveyed to determine the degree to which they have found various graduate school experiences useful in their professional work. Samples of academic clinical psychologists and practicing clinical psychologists reported time allocation and preference for various professional activities, perceived usefulness of various theoretical orientations, and the influence on their current professional work of 19 different graduate training topics. Results suggest that where differences exist, academic clinical psychologists are generally more satisfied with Boulder-model-inspired scientific training than are clinical practitioners. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Further results on local stability of REM algorithm with time-varying delays

This letter presents some further results on the local stability in equilibrium for Internet congestion control algorithm proposed by Low et al., (IEEE/ACM Transactions on Networking, 1999). The propagation delay d(t) is assumed to be time-varying and have maximum and minimum delay bounds (i.e., d/sub m//spl les/d(t)/spl les/d/sub M/), which is more general than the assumption (0相似文献   

The social consequences of expressive suppression.

At times, people keep their emotions from showing during social interactions. The authors' analysis suggests that such expressive suppression should disrupt communication and increase stress levels. To test this hypothesis, the authors conducted 2 studies in which unacquainted pairs of women discussed an upsetting topic. In Study 1, one member of each pair was randomly assigned to (a) suppress her emotional behavior, (b) respond naturally, or (c) cognitively reappraise in a way that reduced emotional responding. Suppression alone disrupted communication and magnified blood pressure responses in the suppressors' partners. In Study 2, suppression had a negative impact on the regulators' emotional experience and increased blood pressure in both regulators and their partners. Suppression also reduced rapport and inhibited relationship formation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The relationship between bioelectrical impedance phase angle and subjective global assessment in advanced colorectal cancer

Background  

Bioelectrical Impedance (BIA) derived phase angle is increasingly being used as an objective indicator of nutritional status in advanced cancer. Subjective Global Assessment (SGA) is a subjective method of nutritional status. The objective of this study was to investigate the association between BIA derived phase angle and SGA in advanced colorectal cancer.     

Effect of sampling density on the measurement of stream condition indicators in two lowland Australian streams

There is widespread application of indicators to the assessment of environmental condition of streams. These indicators are intended for use by managers in making various comparative and absolute assessments and often have a role in resource allocation and performance assessment. Therefore, the problem of formally defining confidence in the results is important but difficult because the sampling strategies used are commonly based on a compromise between the requirements of statistical rigour and the pragmatic issues of access and resources. It is rare to see this compromise explicitly considered and consequently there is seldom quantification of the uncertainty that could affect the confidence a manager has in an indicator. In this paper, we present a method for quantitatively assessing the tradeoffs between sampling density and uncertainty in meeting various monitoring objectives. Assessments using judgement‐based representative reaches are shown to be unreliable; instead a sampling approach is recommended based on the random selection of measuring sites. A detailed dataset was collected along two streams in Victoria, Australia, and the effect of sampling density was assessed by subsampling from this dataset with precision related to the number of sites assessed per reach length and the intensity of the sampling at each site. The sampling scheme to achieve a given precision is shown to depend on the monitoring objective. In particular, three objectives were considered: (1) making a baseline assessment of current condition; (2) change detection; and (3) detection of a critical threshold in condition. Change detection is shown to be more demanding than assessing baseline condition with additional sampling effort required to achieve the same precision. Sampling to detect a critical threshold depends on nominating acceptable values of Type I and II error and the size of the effect to be detected. Copyright © 2006 John Wiley & Sons, Ltd.