Knowledge discovery in corporate events by neural network rule extraction

Over the last two decades, artificial neural networks (ANN) have been applied to solve a variety of problems such as pattern classification and function approximation. In many applications, it is desirable to extract knowledge from trained neural networks for the users to gain a better understanding of the network’s solution. In this paper, we use a neural network rule extraction method to extract knowledge from 2222 dividend initiation and resumption events. We find that the positive relation between the short-term price reaction and the ratio of annualized dividend amount to stock price is primarily limited to 96 small firms with high dividend ratios. The results suggest that the degree of short-term stock price underreaction to dividend events may not be as dramatic as previously believed. The results also show that the relations between the stock price response and firm size is different across different types of firms. Thus, drawing the conclusions from the whole dividend event data may leave some important information unexamined. This study shows that neural network rule extraction method can reveal more knowledge from the data.     

一种带有链约束的连续型批处理机调度问题

针对链式约束下工件释放时间和工期同序的情况,证明了即使所有工件都是单位加工时间时,极小化最大拖期问题也是强NP-难的.对于工件的零时刻都到达且同一链中工件工期相同的特殊情况,给出了多项式时间的最优算法.     

两台流水机器协调分解调度问题

研究钢管加工流程中一类新型两台机器流水车间调度问题,工件在第一台机器上加工后被分解成多个子工件.对于最小化最大完成时间的情况,给出一个多项式时间的最优算法;对于最小化最大完成时间与惩罚费用之和的情况,给出一个拟多项式时间的动态规划算法;对于考虑生产前运输的最小化最大完成时间的情况,分析了问题的复杂性.证明了第一种情况的最优算法可作为后两种情况的2-近似算法.数值实验表明了算法的有效性.     

Computational simulation of Belousov–Zhabotinskii oscillating chemical reaction

The suitability of computational simulation of the Belousov–Zhabotinskii oscillating chemical reaction by differential kinetic methodology for resolving nonlinear multi-component system is demonstrated in this work. According to the Field–KÖrÖs–Noyes mechanism and the Oregonator model, the change of the concentrations of HBrO₂, bromide ion and cerium ion are simulated. The results of computational simulation are consistent with experimental results very well. At the same time, the effect of variables and parameters, especially the rate constant on the oscillation curve, are investigated deeply. A simple method of estimating rate constants is obtained through simulation the concentrations of key components of the system, and then comparison the simulation results with the experimental ones. The reasonable rate constant is also proposed.     

高阶旋转体时域有限差分法

旋转体时域有限差分法(BOR FDTD)是模拟电磁波与旋转对称目标体相互作用的一种高效算法,但目前的BOR FDTD对时间和空间的差分精度均只有二阶.通过把电磁场各分量作泰勒展开,并结合麦克斯韦方程,提出了BOR FDTD的三种高阶算法.相对于目前的BOR FDTD,三种高阶算法均不增加存储量.通过模拟简谐波与介质球的相互作用并和理论值作比较,证实了高阶算法在提高计算精度方面的有效性.此外还分析了三种高阶算法的优、缺点,给出了关于高阶算法应用的建议.     

An algorithm for recognizing palm polygons

A polygonP is said to be apalm polygon if there exists a pointxP such that the Euclidean shortest path fromx to any pointyP makes only left turns or only right turns. The set of all such pointsx is called thepalm kernel. In this paper we propose an O(E) time algorithm for recognizing a palm polygonP, whereE is the size of the visibility graph ofP. The algorithm recognizes the given polygonP as a palm polygon by computing the palm kernel ofP. If the palm kernel is not empty,P is a palm polygon.The extended abstract of this paper was reported at the Second Canadian Conference in Computational Geometry, pp. 246–251, 1990     

Exploring the Determinants of Artificial Intelligence (AI) Literacy: Digital Divide,Computational Thinking,Cognitive Absorption

To effectively utilize artificial intelligence (AI)-based technologies such as ChatGPT and realize their novel ethical issues, individuals must have a variety of knowledge and skills about AI. Such knowledge and skills have led to the emergence of AI literacy. Despite the importance of AI literacy in everyday life, little is known about its determinants. To better understand the determinants of AI literacy, we attempted to build a research model relying on previous research and different theoretical frameworks. The model incorporated digital divide, cognitive absorption, and computational thinking. As a major finding from the current study, computational thinking was found to be a significant determinant of AI literacy, which facilitate using, recognizing, and evaluating AI-based technologies. Moreover, we found out that individuals with physical access to information and communication technologies (ICTs) are more expected to use and recognize AI. Also, motivation and skills in using ICTs enable individuals to better evaluate the outcomes of AI-based technologies. The findings also showed that convenient access to ICTs contributes to a deep involvement with AI-based technologies in the use. Further, individuals with higher motivation and skills to use AI technologies are likely to have a pleasant experience after using these technologies.     

Effects of bottom profile on the circulation and classification of particles in cylindrical hydrocyclones

The cylindrical hydrocyclone has been increasingly used in coarse classification due to its reduced fine particle entrainment, but the loss of coarse particles to overflow remains an intractable problem. Based on the notion that the strong circulation flow caused by the flat bottom structure bears primary responsibility for the problem, this study designs eight unique bottom profiles to regulate the particle circulating flow and attempts to correlate particle circulation flow with classification performance. The effects of the bottom profile on flow field characteristics, particle spatial distribution, circulation flow rates, and grade efficiency are explored in detail using validated models in a Φ200 mm cylindrical hydrocyclone. The findings suggest that bottom profiles have the greatest effect on the axial velocity near the bottom and the grade efficiency of intermediate and coarse particles, while all unique designs have the potential to lower turbulence intensity. An ascending segment near the wall or a descending segment near the axis can help to mitigate the misplacement of coarse particles by reducing particle circulation flow without affecting the entrainment of fines appreciably. Additionally, two circles are found on each side of the cut plane, which is conducive to releasing coarse particles from the circulation flow. Regulation of particle circulation flow by adjusting bottom profile parameters can improve separation performance.     

On the linguistic nature of cyberspace and virtual communities

This paper argues for a linguistic explanation of the nature of Virtual Communities. Virtual Communities develop and grow in electronic space. or cyberspace. Authors such as Benedikt Meyrowitz and Mitchell have theorised about the nature of electronic space whilst Lefebvre. Popper, Hakim Bey (aka Lamborn Wilson) and Kuhn have theorised more generally about the nature of space. Extending this tradition and the works of these authors, this paper presents a language based perspective on the nature of electronic spaces. Behaviour in cyberspace is based on and regulated by hardware, software tools and interfaces. A definition of electronic space cannot be given beyond its linguistic characteristics, which underlie and sustain it. The author believes that the more users and developers understand the relationship between language and cyberspace, the more they will be able to use specific metaphors for dwelling and inhabiting it. In particular, MUDs/MOOs and the Web are interesting places for testing and observing social behaviours and dynamics.     

量子计算智能导论教学探索

随着智能信息处理技术的飞速发展,越来越多的学生对量子计算智能导论这门课产生了浓厚的兴趣。我们结合教学实践,将该门课程的教学内容划分为理论型和实践型,注重理论与实际应用相结合,以具体实例引导教学,从而加深学生对理论的理解,进而培养学生的实践能力和科研兴趣。本文介绍了这种教学方法。