减少手术创伤始终是妇科肿瘤手术快速康复的决定性因素

减少手术创伤始终是快速康复的决定性因素,这一点在目前的加速康复外科研究尤其是复杂手术,如妇科肿瘤手术中尚未得到充分重视。尊重学习曲线、全面规划手术方案、总结失利经验、开展前瞻性研究是解决此问题的主要方案。本文着重讨论妇科肿瘤手术创伤对术后加速康复的影响及可能的改进措施。     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

Performance prediction of a hybrid‐excitation synchronous machine with axially arranged excitation poles and permanent‐magnet poles

This paper presents a method of predicting the steady‐state performance of a new hybrid‐excitation synchronous machine (HESM) theoretically. The field pole of this HESM is axially divided into two parts; one is an excitation part and the other a permanent‐magnet (PM) part. A nonlinear equivalent circuit, which can include the saliency of the rotor and the magnetic saturation due to the iron core, is derived. Based on this equivalent circuit, the steady‐state performance of the HESM is calculated, and the results are confirmed through experiments. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(2): 43–49, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20033     

Self-learning inductive inference machines

Self-knowledge is a concept that is present in several philosophies. In this article, we consider the issue of whether or not a learning algorithm can in some sense possess self-knowledge. The question is answered affirmatively. Self-learning inductive inference algorithms are taken to be those that learn programs for their own algorithms, in addition to other functions.
La connaissance de soi est un concept qui se retrouve dans plusieurs philosophies. Dans cet article, les auteurs s'interrogent à savoir si un algorithme d' apprentissage peut dans une certaine mesure posséder la connaissance de soi. lis apportent une reponse positive a cette question. Les algorithmes d'inference inductive autodidactes sont ceux qui font l'apprentissage de programmes pour leurs propres algorithmes, en plus d' autres fonctions.     

Evaluating the design of flexible manufacturing systems

Evaluating the design of flexible manufacturing systems is complex. Developing a measure of performance useful for evaluating alternate designs continues to be interesting. Here, total productivity of the system is proposed as an appropriate measure. Specification of parameters based upon strategic considerations for this measure are discussed. Finally, the usefulness of the measure is demonstrated through an example.     

Hierarchical intelligent control with flexible AC transmission systems application

A novel hierarchical intelligent controller configuration is proposed using an artificial neural network as a control-mode classifier in the supervisory level and a set of pre-designed controllers in the lower level. Controller outputs are modified nonlinearly by the classifying signals in a structure resembling one artificial neuron with adaptively changed weights. The lower-level local controllers are implemented using neural networks. An illustrative example of this approach is based on the transient stabilization of a single-machine infinite-bus system studied in Flexible AC Transmission Systems (FACTS) research.     

Machine translation of non-literary texts: Some Canadian experiences

A survey was carried out of past and current Canadian experiences with machine-aided translation (MAT) systems of non-literary texts in one government institution and three industrial settings. Each organization requires a great deal of translation and had conducted several experiments in the use of MAT. The survey supports positive conclusions about the prospects for expanded use of computers in translation.The authors express their thanks to all those who helped in the preparation of this paper. We are particularly grateful to the staff of the translation departments of the organizations mentioned in the paper for their kind cooperation and their willingness to answer our questions: Chantal Delorme ofIBM Canada, Lorraine Desmarais and Mr. Plamondon of Bell Canada, Pierre Tellier of the Department of the Secretary of State, Maria Russo and Raymond Lapointe of the Xerox Corporation. Furthermore we thank Prof. Graeme Hirst for helpful discussion.     

Improved Estimates for the Accuracy of Small Disjuncts

Learning systems often describe a target class as a disjunction of conjunctions of conditions. Recent work has noted that small disjuncts, i.e., those supported by few training examples, typically have poor predictive accuracy. One model of this accuracy is provided by the Bayes-Laplace formula based on the number of training examples covered by the disjunct and the number of them belonging to the target class. However, experiments show that small disjuncts associated with target classes of different relative frequencies tend to have different error rates. This note defines the context of a disjunct as the set of training examples that fail to satisfy at most one of its conditions. An empirical adaptation of the Bayes-Laplace formula is presented that also makes use of the relative frequency of the target class in this context. Trials are reported comparing the performance of the original formula and the adaptation in six learning tasks.     

Peer-assisted learning interventions with elementary school students: A meta-analytic review.

A meta-analytic review of group comparison design studies evaluating peer-assisted learning (PAL) interventions with elementary school students produced positive effect sizes (ESs) indicating increases in achievement (unweighted mean ES = 0.59, SD = 0.90; weighted ES, d = 0.33, p