光学薄膜元器件外观特性机器视觉检测系统

本系统利用工业级摄像头及开发包的机器视觉功能与计算软件编程控制技术相结合,通过与输入控制系统中的标准膜片模板外观品质进行对比,实现高速高效、准确识别检测光学薄膜器件中滤光片的外观缺陷。可在生产线上根据外观品质标准模板中设定的类别进行自动分类装盒。     

Supervised classification of share price trends

Share price trends can be recognized by using data clustering methods. However, the accuracy of these methods may be rather low. This paper presents a novel supervised classification scheme for the recognition and prediction of share price trends. We first produce a smooth time series using zero-phase filtering and singular spectrum analysis from the original share price data. We train pattern classifiers using the classification results of both original and filtered time series and then use these classifiers to predict the future share price trends. Experiment results obtained from both synthetic data and real share prices show that the proposed method is effective and outperforms the well-known K-means clustering algorithm.     

A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability

In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.     

An ant direction hybrid differential evolution heuristic for the large-scale passive harmonic filters planning problem

This article presents a heuristic which combines the orthogonal array experiment technique and an ant direction hybrid differential evolution algorithm (ADHDEOA) for planning of a large-scale passive harmonic filters problem. The addressed problem has a multi-bus and under abundant harmonic current sources in the system. In this study, an orthogonal array is first conducted to obtain the initial solution. Next, an ant direction hybrid differential evolution (ADHDE) is applied to search for a near optimum solution. The objective is to minimize the cost of the filter, the total demand distortion of harmonic currents and the total harmonic distortion of voltages at each bus simultaneously. In order to determine a set of weights of each term in the objective function, the simplest and most efficient form of triangular membership functions has been considered. The designed heuristic ADHDEOA is applied to a practical harmonic problem in a steel plant, and three design schemes are compared to demonstrate the performance of the ADHDEOA.     

基于LM3S316的微控制器仿真USB设备

提出了基于LM3S316实现与PC机通讯的方法.给出了硬件实现及软件设计思想.该方法使用微控制器仿真USB设备,降低了功耗、成本.     

A novel fault-tolerant execution model by using of mobile agents

The exponential expansion of the Internet and the widespread popularity of the World Wide Web give a challenge to experts on reliable and secure system design, e.g., e-economy applications. New paradigms are on demand and mobile agent technology is one of the features. In this paper, we propose a fault-tolerance execution model by using of mobile agents, for the purpose of consistent and correct performance with a required function under stated conditions for a specified period of time. Failures are classified into two classes based on their intrinsic different effects on mobile agents. For each kind of failure, a specified handling method is adopted. The introduction of exceptional handling method allows performance improvements during mobile agents’ execution. The behaviors of mobile agents are statistically analyzed through several key parameters, including the migration time from node to node, the life expectancy of mobile agents, and the population distribution of mobile agents, to evaluate the performance of our model. The analytical results give new theoretical insights to the fault-tolerant execution of mobile agents and show that our model outperforms the existing fault-tolerant models. Our model provides an effective way to improve the reliability of computer systems.     

The development of a sub-population genetic algorithm II (SPGA II) for multi-objective combinatorial problems

Previous research has shown that sub-population genetic algorithm is effective in solving the multi-objective combinatorial problems. Based on these pioneering efforts, this paper extends the SPGA algorithm with a global Pareto archive technique and a two-stage approach to solve the multi-objective problems. In the first stage, the areas next to the two single objectives are searched and solutions explored around these two extreme areas are reserved in the global archive for later evolutions. Then, in the second stage, larger searching areas except the middle area are further extended to explore the solution space in finding the near-optimal frontiers. Through extensive experimental results, SPGA II does outperform SPGA, NSGA II, and SPEA 2 in the parallel scheduling problems and knapsack problems; it shows that the approach improves the sub-population genetic algorithm significantly. It may be of interests for researchers in solving multi-objective combinatorial problems.     

Ubiquitous Personal Study: a framework for supporting information access and sharing

The information resources on the Web are diversified, the amount of which is increasing rapidly. Demands for selecting useful information from the Internet, managing personal contents, and sharing contents under control have risen. In this study, we propose the Ubiquitous Personal Study, a framework of personalized virtual study to support accessing, managing, organizing, sharing and recommending information. In this paper, we focus on discussing the framework, and design and implementation issues on how to implement it with Web 2.0 mash-up technology and Open Source Software.