Determination of model order for NARX models directly from input-output data

Nonlinear auto-regressive models with exogenous inputs (NARX models) have proved to be versatile and useful empirical models for industrial processes. There are a wide variety of identification methods and model structures from which to choose; in all methods, however, key parameters are the model orders, which are the number of past outputs and inputs used in the model. In this paper the methods of Lipschitz numbers and false nearest neighbors are evaluated as a means of estimating the model orders of dynamic, discrete-time NARX models. No specific model structure is assumed and the model orders are estimated directly from input-output data using only geometric concerns and the continuity property. The two methods are applied to several dynamic systems, including realistic process simulations and experimental data from the UCSB pH neutralization process, and the consistency and accuracy of these methods are examined. The usefulness of these methods of model order determination for radial basis function network (RBFN) identification is examined.     

基于椭圆曲线和三叉树的群组密钥协商方案

将椭圆曲线密码体制和三叉树引入到群组密钥协商中,提出了一种基于椭圆曲线和三叉树的群组密钥协商协议,由于无需向群组所有其它成员广播消息,其计算开销和通信开销均只有O（nlog3 n）。采用了用初始协商的密钥值加密随机数并产生杂凑值的方法使三叉树内部结点间也能进行安全的协商;当有群组成员变动时,通过发起者更新其随机数来提供协议的前向保密性和后向保密性,因此该方案适合于较大规模的动态群组。     

The Migration of Multi-tier E-commerce Applications to an Enterprise Java Environment

As technology evolves, many organizations face the problem of migrating legacy applications from one technology base to another. We report on a case study involving the migration of legacy code into the IBM® WebSphere® Commerce Suite product. Specifically, we focus on the problem of migrating applications that use traditional database access techniques to applications using the Enterprise JavaBean (EJB) programming model. Our results include a practical methodology that facilitates such migration, as well as a tool that supports this methodology. The tool has been released on IBM's alphaWorks site.     

Ontologies for Knowledge Management: An Information Systems Perspective

Knowledge management research focuses on concepts, methods, and tools supporting the management of human knowledge. The main objective of this paper is to survey basic concepts that have been used in computer science for the representation of knowledge and summarize some of their advantages and drawbacks. A secondary objective is to relate these techniques to information science theory and practice.The survey classifies the concepts used for knowledge representation into four broad ontological categories. Static ontologies describe static aspects of the world, i.e., what things exist, their attributes and relationships. A dynamic ontology, on the other hand, describes the changing aspects of the world in terms of states, state transitions and processes. Intentional ontologies encompass the world of things agents believe in, want, prove or disprove, and argue about. Finally, social ontologies cover social settings – agents, positions, roles, authority, permanent organizational structures or shifting networks of alliances and interdependencies.     

CrackTree: Automatic crack detection from pavement images

Pavement cracks are important information for evaluating the road condition and conducting the necessary road maintenance. In this paper, we develop CrackTree, a fully-automatic method to detect cracks from pavement images. In practice, crack detection is a very challenging problem because of (1) low contrast between cracks and the surrounding pavement, (2) intensity inhomogeneity along the cracks, and (3) possible shadows with similar intensity to the cracks. To address these problems, the proposed method consists of three steps. First, we develop a geodesic shadow-removal algorithm to remove the pavement shadows while preserving the cracks. Second, we build a crack probability map using tensor voting, which enhances the connection of the crack fragments with good proximity and curve continuity. Finally, we sample a set of crack seeds from the crack probability map, represent these seeds by a graph model, derive minimum spanning trees from this graph, and conduct recursive tree-edge pruning to identify desirable cracks. We evaluate the proposed method on a collection of 206 real pavement images and the experimental results show that the proposed method achieves a better performance than several existing methods.     

基于FPGA的PXI数据采集系统设计

从自主研发的角度,介绍了一种以PXI总线为接口,采用现场可编程门阵列（FPGA）为逻辑控制单元的数据采集系统;在介绍系统总体设计方案的基础上,详细讨论了采集部分的功能实现、FPGA的控制逻辑以及PXI接口电路的设计．晟后分析了仪器的驱动程序;根据本方案研制的数据采集系统已经成功地应用于实际测试系统中,其性能良好,工作稳定,达到了预期的设计目标。     

多边形叠置分析算法研究

在二维GIS系统中经常需要对图层中的多边形进行叠置分析,为了有效地分析不同系统提供的多边形图层数据,论文研究了地理信息系统中表示多边形图层的两种数据结构——简单数据结构和拓扑数据结构,以及分别适用于这两种情况的多边形叠置算法。拓扑数据结构下的算法现在已经很成熟,论文重点介绍简单数据结构情况下的算法。     

The development of human factors design guidelines

There is a growing information gap between the development of advanced human-machine systems, and the availability of human factors design criteria that can be applied during their design process. Despite increased interest in the development of human factors design guidelines, there also remains considerable uncertainty and concern regarding the actual utility of such information. Indeed, many existing human factors reference materials have been criticized by designers for being ‘too wordy’, ‘too general’, and ‘too hard to understand’. The development of clear, relevant, and useful human factors guidelines requires a judicious mix of science and art to overcome such criticisms. Specifically, while a number of empirical and systematic methods can be productively applied to their development, the final design guidelines will always represent a subjective integration of user requirements, design constraints, available information, and expert judgement. This paper summarizes procedures and heuristics associated with both the science and the art components of human factors design guideline development.     

Application of remote sensing to parks and protected area monitoring: Introduction to the special issue

This special issue is the result of sustained and highly collaborative efforts to improve the use of remotely sensed data to inform management of protected areas. The 15 papers in the issue address a diverse range of topics. These papers provide a conceptual basis and a framework for establishing monitoring programs, techniques and methods to make operational the use of remotely sensed data, case studies, and synthesis papers liking remotely sensed data to models used to inform ecological assessments. Studies in this issue necessarily confront the universal challenges of scale, both spatial and temporal, and the sometimes tenuous link between observed patterns and significant ecological process. A clear message is that the information needs of resource managers require information across scales, and these information demands will continue to motivate advances in the collection and analysis of remotely sensed data. This compilation of papers is unusual in (1) articulating a basic, if somewhat technical, foundation of remote sensing that is required for resource managers to effectively collaborate with remote sensing specialists, and (2) providing a framework for addressing monitoring resource issues that is likely to be of interest to many remote sensing specialists. We hope these papers inspire broader use of remotely sensed data to manage the increasingly rare and valuable resources in protected areas around the world.