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.     

心电地图仪中工频干扰的一种滤除方法

在心电地图仪中记录到的体表心电信号往往由于电磁的影响而引进工频干扰．基于体表心电信号中工频干扰的特点，作者提出了一种滤除工频干扰的方法，即就单独—胸导联信号通过提高频谱的分辨率来估计工频干扰的频率；基于最小均方误差准则来估计各导联信号中工频干扰的幅度和相位。文中还给出了该算法的流程图和滤波性能分析。模拟结果表明了该算法的有效性。应用该算法对心电地图仪中的工频干扰进行对消，取得了满意的结果。     

测定钠中杂质的手动阻塞计的研究

文章介绍了测定钠中杂质浓度的手动阻塞计的原理、装置和实验结果。为了减少测量误差,我们研究了影响准确测定阻塞温度的因素,并且找到了减少测量误差的办法。在同样的杂质饱和温度下,该阻塞计测得的高、低阻塞温度所对应的杂质浓度差是很接近的。对氧其差值为1.03ppm;对氢为0.0763ppm。     

CNC中插补和轴伺服的微机仿真

本文级出了在ＰＣ机上对一个自己开发ＣＮＣ系统插祉和轴伺服控制进行仿真的结果。它包含按插补原理对直线、圆和渐开线的插补以及对轴伺服控制中的位置环和前馈控制的仿真。轴伺服马达通过一个二阶连续系统模型来仿真，最后得出对伺服进行前馈控制补偿可显著改善系统的输出。     

静态电子轨道衡组成部分解析及其合理选择

阐述静态电子轨道衡诸多优点;工作原理、允许误差及误差分配;轨道衡的结构组成部分、解析各部分的工作特性及技术指标要求;合理选配及推荐实例.     

Foveation-Based Error Resilience and Unequal Error Protection over Mobile Networks

By exploiting new human-machine interface techniques, such as visual eyetrackers, it should be possible to develop more efficient visual multimedia services associated with low bandwidth, dynamic channel adaptation and robust visual data transmission. In this paper, we introduce foveation-based error resilience and unequal error protection techniques over highly error-prone mobile networks. Each frame is spatially divided into foveated and background layers according to perceptual importance. Perceptual importance is determined either through an eye tracker or by manually selecting a region of interest. We attempt to improve reconstructed visual quality by maintaining the high visual source throughput of the foveated layer using foveation-based error resilience and error correction using a combination of turbo codes and ARQ (automatic reQuest). In order to alleviate the degradation of visual quality, a foveation based bitstream partitioning is developed. In an effort to increase the source throughput of the foveated layer, we develop unequal delay-constrained ARQ (automatic reQuest) and rate compatible punctured turbo codes where the punctual pattern of RCPC (rate compatible punctured convolutional) codes in H.223 Annex C is used. In the simulation, the visual quality is significantly increased in the area of interest using foveation-based error resilience and unequal error protection; (as much as 3 dB FPSNR (foveal peak signal to noise ratio) improvement) at 40% packet error rate. Over real-fading statistics measured in the downtown area of Austin, Texas, the visual quality is increased up to 1.5 dB in PSNR and 1.8 dB in FPSNR at a channel SNR of 5 dB.     

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.     

A new minimum zone method for evaluating flatness errors

A new minimum zone method for flatnes error analyis is proposed in this article. Based on the criteria for the minimum zone solution and strict rules for data exchange, a simple and rapid algorithm, called the control plane rotation scheme, is developed for the flatness analysis of a flat surface. Experimental work was performed, and some examples are given in terms of the minimum zone and least-squares solutions.     

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.