超薄带精密轧机辊形调节计算机控制

介绍一种超薄带精密轧机的计算机控制系统改造。超薄带精密轧机用于轧制０．０１ｍｍ～０．５ｍｍ的超薄带材，其辊形调节系统是影响带材板形的关键部分。原系统响应慢，可靠性差，难以满足精轧要求。现对该轧机进行改造，采用计算机，将ＰＣＭ（ＰｕｌｓｅｃｏｄｅＭｏｄｕｌａｔｉｏｎ－脉冲码调制）控制与二次型性能指标最优化控制相结合的控制方法用于轧机的的全面管理与控制，不仅大大提高系统精度与运行可靠性，而且实现调整与控制自动化。目前已投入正常运行。     

On-Line Shape recognition with incremental training using binary synaptic weights algorithm

Recognition of hand drawn shapes is beneficial in drawing packages and automated sketch entry in handheld computers. In this paper, we propose a new approach to on-line geometric shape recognition with incremental training function, which utilizes a heuristic function to reduce noise and a neural network for classification and on-line training. Instead of recognizing segments of a drawing and then performing syntactical analysis to match with a predefined shape, which is weak in terms of generalization and dealing with noise, we examine the shape as a whole. The main concept of the recognition method is derived from the fact that internal angles are very important in the perceived shape of outlines. Our application's aim is to recognize elliptic, rectangular, and triangular shapes in a way similar to human cognition of these shapes. Human beings recognize such basic shapes regardless of the variations in size, noise on the shape border, rotation and in the case of triangles, regardless of the type of the triangle. The key concept is that the neural network learns the relationships between the internal angles of a shape and its classification, therefore only a few training samples which represent the class of the shape are sufficient. Fast meremental training, which is performed on-line, is accomplished by the use of the Binary Synaptic Weights algorithm, a one pass, feedforward neural network training algorithm. Incremental training offers the advantage of adjusting the recognition capability of the system to the user's drawings. the results are very successful, such that the neural network correctly classified shapes that did not have any resemblance to the shapes in the initial training set.     

莱钢冷轧轧机弯辊控制系统分析

对莱钢冷轧六辊单机架的弯辊系统进行研究与分析,介绍板形控制系统的原理和使用效果。     

基于启发式规则优化的网页元素提取方法

网页信息提取方法中的启发式规则,是识别网页标签信息、利用网页节点分析结果、针对网页不同内容、完成信息提取的重要手段。本研究在对现有启发式规则进行研究分析的基础上,提出了几种优化的启发式规则,实现对网页标题、发布时间、来源以及正文内容等元素信息的精准提取。本研究进一步提出了运用编辑距离算法实现正文内容提取准确率的判定,并提出阙值优化方法,克服了正文提取中噪声节点多、内容识别不完全的缺陷,大大提高了提取的准确度。     

Perspective:Societally connected multimedia across cultures

The advance of the Internet in the past decade has radically changed the way people communicate and col- laborate with each other. Physical distance is no more a barrier in online social networks, but cultural differences (at the individual, community, as well as societal levels) still govern human-human interactions and must be con- sidered and leveraged in the online world. The rapid de-ployment of high-speed Internet allows humans to interact using a rich set of multimedia data such as texts, pictures, and videos. This position paper proposes to define a new research area called ’connected multimedia’, which is the study of a collection of research issues of the super-area social media that receive little attention in the literature. By connected multimedia, we mean the study of the social and technical interactions among users, multimedia data, and devices across cultures and explicitly exploiting the cultural differences. We justify why it is necessary to bring attention to this new research area and what benefits of this new research area may bring to the broader scientific research community and the humanity.     

基于Adams的摆杆输送机动力学仿真分析

采用Adams脚本语言建模,自动完成摆杆输送机整体系统的轨道、链条、摆杆和工件之间的装配约束和载荷边界条件的设定等.对某卡车白车身涂装过程进行动力学仿真分析,求得系统整体运行时所需的驱动力大小、链节间的相互作用力和进行静力学分析所需的载荷条件等,分析结果可指导摆杆输送机的整体设计.     

Searching minimax game trees under memory space constraint

Games such as CHESS, GO and OTHELLO can be represented by minimax game trees. Among various search procedures to solve such game trees,- and SSS^* are perhaps most well known. Although it is proved that SSS^* explores only a subset of the nodes explored by-, - is commonly believed to be faster in real applications, since it requires very little memory space and hence its storage management cost is low. Contrary to this folklore, however, this paper reports, using the OTHELLO game as an example, that SSS^* is much faster than-. It is also demonstrated that SSS^* can be modified to make the required memory space controllable to some extent, while retaining the high efficiency of the original SSS^*.This research was partially supported by the Ministry of Education, Science and Culture of Japan, under a Scientific Grant-in-Aid.     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.