构建基于XML的在线备忘录

XML能够使用得Internet上的数据交换变得更方便,XML与数据库一样,都能够作为信息存储的途径。当数据量不大的时候,比如完成一个在线备忘录,XML作为数据存储具有关系数据库所无法比拟的优势。在asp.net中能够利用.net类库提供的类及方法轻松地构建一个基于XML的在线备忘录。     

Expansion of a matrix in terms of external products of configuration vectors

The paper proposes a neural-net iterative algorithm that allows us to represent any random symmetrical N×N matrix as a weighted Hebbian series of configuration vectors with a given accuracy. The iterative algorithm is shown to demonstrate the fastest convergence when the vectors of expansion are stable nods of the N-dimensional space corresponding to the extremums of the neural-net energy functional. It so proves that all conclusions about neural networks and optimization algorithms that are based on Hebbian matrices are true for any other type of matrix. The text was submitted by the author in English.     

A multi-agent intelligent system for efficient ERP maintenance

The Enterprise Resource Planning (ERP) system is an enterprise-wide integrated software package designed to uphold the highest quality standards of business process. However, for the time being, when the business condition has been changed, the system may not guarantee that the process embedded in ERP is still best. Moreover, since the ERP system is very complex, maintaining the system by trial and error is very costly. Hence, this paper aims to construct a support system that adjusts ERP system to environmental changes. To do so, we adopt multi-agent intelligent technology that enables autonomous cooperation with one another to monitor ERP databases and to find any exceptional changes and then analyze how the changes will affect ERP performance. Moreover, Petri net is applied to manage the complexity and dynamics of agents’ behavior. To show the feasibility of the idea, a prototype agent system, ERP/PN, is proposed and an experiment is conducted.     

Performance of N-body codes on hybrid machines

N-body codes are routinely used for simulation studies of physical systems, e.g. in the fields of computational astrophysics and molecular dynamics. Typically, they require only a moderate amount of run-time memory, but are very demanding in computational power. A detailed analysis of an N-body code performance, in terms of the relative weight of each task of the code, and how this weight is influenced by software or hardware optimisations, is essential in improving such codes. The approach of developing a dedicated device, GRAPE [J. Makino, M. Taiji, Scientific Simulations with Special Purpose Computers, Wiley, New York, 1998], able to provide a very high performance for the most expensive computational task of this code, has resulted in a dramatic performance leap. We explore on the performance of different versions of parallel N-body codes, where both software and hardware improvements are introduced. The use of GRAPE as a ‘force computation accelerator’ in a parallel computer architecture, can be seen as an example of a hybrid architecture, where special purpose device boards help a general purpose (multi)computer to reach a very high performance.     

Probabilistic characterisation of model error using Gaussian mixture model—With application to Charpy impact energy prediction for alloy steel

A novel approach to characterise the model prediction errors using a Gaussian mixture model is proposed. The motivation for this work lies behind many data models that are developed through prediction error minimisation with the assumption of a normal noise distribution. When the noise is non-normal, which may often be the case in complicated data modelling scenarios, the model prediction errors may contain rich information, which can be further exploited for model refinement and improvement. The key contents presented in this paper include: choosing the relevant variables to form the error data, optimising the number of Gaussian components required for the error data modelling, and fitting the Gaussian mixture parameters using an expectation-maximisation algorithm. Application of the proposed method for further model improvement, within the framework of hybrid deterministic/stochastic modelling, is also discussed. Preliminary results on the real industrial Charpy impact energy data for heat-treated steels show its effectiveness for model error characterisation, and the potential for model performance improvement in terms of prediction accuracy as well as providing accurate prediction confidence intervals.     

室内移动机器人超声传感器导航网络分布研究

对于室内广域移动机器人,超声波传感器网络是能够保证给定导航准确度的一种有效方法。合理的超声波传感器网络分布是实现超声波网络导航的重要条件。论述了超声波网络合理分布的原则,据此提出并分析了获得合理超声波传感器网络分布的四个步骤,仿真试验结果验证了它的有效性。     

运用现代技术,实施教育创新

随着校园网与多媒体网络技术的普及，现代技术在教育创新中的位置越来越重要，尤其是虚拟教室的出现，把教育创新提到了一个高度。从校园网、多媒体网络技术、仿真技术与虚拟教室几个方面来具体说明怎么运用现代技术实施教育创新。     

Combined Petri net modelling and AI-based heuristic hybrid search for flexible manufacturing systems—part II. Heuristic hybrid search

This two-part paper presents modelling and scheduling approaches of flexible manufacturing systems using Petri nets (PNs) and artificial intelligence (AI)-based heuristic search methods. In Part I, PN-based modelling approaches and basic AI-based heuristic search algorithms were presented. In Part II, a new heuristic function that exploits PN information is proposed. Heuristic information obtained from the PN model is used to dramatically reduce the search space. This heuristic is derived from a new concept, the resource cost reachability matrix, which builds on the properties of B-nets proposed in Part I. Two hybrid search algorithms, (1) an approach to model dispatching rules using analysis information provided by the PN simulation and (2) an approach of the modified stage-search algorithm, are proposed to reduce the complexity of large systems. A random problem generator is developed to test the proposed methods. The experimental results show promising results.     

有限资金约束下独立方案的比选

通过对独立方案在有限资金的约束下,进行方案组合比选的两种方法进行讨论,使两种方法结合在一起形成一种新的比选方法.