非流形几何建模拓扑数据结构的研究

当前ＣＡＤ技术的发展趋势是特征造型，行为建模、信息集成。几何建模作为ＣＡＤ系统的核心，是影响ＣＡＤ系统功能的重要因素。非流形几何建模可以用统一的数据结构来表示线框、曲面、实体模型，从而为在底层实现特征造型。变量化设计、行为建模提供了可能。本文概括了非流形几何建模的基础理论知识，提出了一种基于非流形几何建模的新型拓扑数据结构，应用ＯＯＰ及开放式软件开发思想探讨了开发具有自主知识产权的三维实体ＣＡＤ平台拓扑数据结构的实现。

基于一种大数据应用架构的消费者行为分析

研究了一种大数据的应用程序框架,通过使用拓扑数据结构、共生技术分析和马尔科夫链理论来分析消费者的购买行为。首先将与消费者相关的数据转换成一种拓扑数据结构;然后使用拓扑关系、一种共生矩阵对消费者行为进行分析,推断出马尔柯夫链模型。仿真结果证实了该理论框架的有效性。

PDS管道模型三维拓扑关系解析方法的研究与实现

PDS软件被广泛应用于能源化工行业的三维工厂设计工作中,用于三维建模、工程图纸生成以及材料清单抽取等工作中。PDS模型数据包含三维拓扑关系数据和属性数据,由于三维拓扑关系数据存储在图形文件中,缺少有效的获取途径,造成部分设计需求无法实现。笔者通过研究发明了一种三维拓扑关系的解析方法,并且对其进行了程序实现,成功获取了PDS管道模型的三维拓扑关系数据,为开展各类需求开发奠定了基础,进一步拓宽了三维模型的应用范围。

GIS输入的摄影测量方法

为了拓宽ＧＩＳ的输入范围。文章研究了ＧＩＳ输入的摄影测量方法。该方法应用摄影测量理论的空间解析模型，选取已知地图坐标的控制纠正点．求解模型参数、经过坐标变换．以象片区划线的弧为基本单位进行数字化处理，得到地图坐标数据．由此坐标数据提取出弧和结点数据、最后生成与ＡＲＣ／ＮＦＯ系统相兼容的拓扑数据结构。经检验用该方法完全满足成图要求。

加密不规则三角网模型的关键算法研究

提出存储TIN模型数据的拓扑数据结构,自动搜索插值原始数据的"膨胀算法"以及用于插值的曲面样条函数的数学模型。利用具有优良数学特征的曲面样条函数,可以完成对TIN的加密处理。

Topology-Based Data Dissemination Approaches for Large Scale Data Centric Networking Architecture

Massive information flows are gen- erated from interactive processing and visua- lizations. To efficiently support information transmission over the Interact, information cen- tric architecture has been recently proposed. In this paper, we consider an information centric architecture, called the data centric networking architecture to provide communication servi- ces to big data, where a service identifier is used to name the data objects. We propose dif- ferent approaches for the dissemination of data objects in a large-scale data centric network. In particular, we propose various approaches to link the data dissemination approach with the topology of the Internet. Further, we eva- luate the proposed approaches with respect to data delivery efficiency, round-trip time imp- rovement, and deployment cost. Based on the results obtained from this study, it can be sh- own that by disseminating data objects to small ISPs, the data delivery efficiency can be significantly improved within an acceptable deployment cost.

A new representation of orientable 2-manifold polygonal surfaces for geometric modelling

Many graphics and computer-aided design applications require that the polygonal meshes used in geometric computing have the properties of not only 2-manifold but also are orientable. In this paper, by collecting previous work scattered in the topology and geometry literature, we rigorously present a theoretical basis for orientable polygonal surface representation from a modem point of view. Based on the presented basis, we propose a new combinatorial data structure that can guarantee the property of orientable 2-manifolds and is primal/dual efficient. Comparisons with other widely used data structures are also presented in terms of time and space efficiency.

Application of Management Information System Planning in Concurrent Engineering for Wooden Furniture Industry

This research is a development in management information system （MIS） planning based on operation analysis and development according to concurrent engineering approach and reestablishment of database management. According to our case study industry, such industry currently used traditional network systems such as LAN, and ＂Bus Network＂ Network Topology. Client/Server distributed computing has a problem with database management in data redundancy, data inconsistency, and data independency. For Network Topology, Bus Network has problem with multitasking since the network are able to handle only a set of data at a time so the traffic problem will occur when multiple users request for the service. Thus, such condition is inconsistent with concurrent engineering which must be able to access the data simultaneously. As a consequence, this study develops a network system, network system of working system, using LAN and ＂Star Network＂ network topology. The file server processing distributed is an application while database is stored in host computer or file server but the data will be processed in users＇ computer. When the user needs to access the data, file server will send it to the user and the user can further analysis or manage such data in the user computer, so called ＂Hierarchical Database Model＂. Hierarchical database structure is easily developed like general organization command structure with different level of responsibility. In details, the data level in the database is divided into three levels including DBI, DB2, and DB3, so development of simultaneously systemic flow and access of various critical data is performed in parallel. Furthermore, this is consistent with access of all three data levels including： Level 1 is overall dataflow of both inside and outside the organization; Level 2 is dataflow of each division in the organization; and Level 3 is dataflow of subunit in each division in the organization. After systemize flow and access of data with concurrent engineering as mentioned, it provided optimal efficiency in the whole production system management reducing loss in the whole system of the organization

Image feature optimization based on nonlinear dimensionality reduction

Image feature optimization is an important means to deal with high-dimensional image data in image semantic understanding and its applications. We formulate image feature optimization as the establishment of a mapping between highand low-dimensional space via a five-tuple model. Nonlinear dimensionality reduction based on manifold learning provides a feasible way for solving such a problem. We propose a novel globular neighborhood based locally linear embedding (GNLLE) algorithm using neighborhood update and an incremental neighbor search scheme, which not only can handle sparse datasets but also has strong anti-noise capability and good topological stability. Given that the distance measure adopted in nonlinear dimensionality reduction is usually based on pairwise similarity calculation, we also present a globular neighborhood and path clustering based locally linear embedding (GNPCLLE) algorithm based on path-based clustering. Due to its full consideration of correlations between image data, GNPCLLE can eliminate the distortion of the overall topological structure within the dataset on the manifold. Experimental results on two image sets show the effectiveness and efficiency of the proposed algorithms.