Management of multidimensional discrete data

Spatial database management involves two main categories of data: vector and raster data. The former has received a lot of in-depth investigation; the latter still lacks a sound framework. Current DBMSs either regard raster data as pure byte sequences where the DBMS has no knowledge about the underlying semantics, or they do not complement array structures with storage mechanisms suitable for huge arrays, or they are designed as specialized systems with sophisticated imaging functionality, but no general database capabilities (e.g., a query language). Many types of array data will require database support in the future, notably 2-D images, audio data and general signal-time series (1-D), animations (3-D), static or time-variant voxel fields (3-D and 4-D), and the ISO/IEC PIKS (Programmer's Imaging Kernel System) BasicImage type (5-D). In this article, we propose a comprehensive support ofmultidimensional discrete data (MDD) in databases, including operations on arrays of arbitrary size over arbitrary data types. A set of requirements is developed, a small set of language constructs is proposed (based on a formal algebraic semantics), and a novel MDD architecture is outlined to provide the basis for efficient MDD query evaluation.     

A semantic modeling approach for image retrieval by content

We introduce a semantic data model to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases. This model mimics the user's conceptual view of the image content, providing the framework and guidelines for preprocessing to extract image features. Based on the model constructs, a spatial evolutionary query language (SEQL), which provides direct image object manipulation capabilities, is presented. With semantic information captured in the model, spatial evolutionary queries are answered efficiently. Using an object-oriented platform, a prototype medical-image management system was implemented at UCLA to demonstrate the feasibility of the proposed approach.     

绝缘涂敷制件的加工工艺研究与应用

主要论述了电工绝缘粉末的性能及其在高压电器设备应用中的有关试验项目。     

晋城市煤炭加工利用现状、存在问题及发展建议

阐述了晋城市煤加工利用的现状 ,分析了煤炭加工利用存在的问题 ,提出了今后的发展建议     

基于图像的计算机辅助数控编程软件研究

研究了基于图像的数控自动编程方法，包括影响自动编程、图像骨架自动编程和轮廓自动编程方法，并实现了使用该方法的计算机辅助数控编程软件。     

C/O能谱测井数据预处理的两点改进意见

简单介绍了碳氧比测井的原理及通常的数据处理方法。分析了由常规数据处理所得曲线仍然存在的问题及可能的成因 ,并给出了可行的修正办法。讨论了另一种可行的曲线异常数据的检测、剔除方法。实践表明 :文章讨论的两点建议都是可行的 ,并且在提高测量曲线质量的同时也提高了地层含油饱和度的解释精度。     

现场总线技术在城市污水处理与气象中的应用

文章主要讨论了LonWorks现场总线技术在城市污水处理厂和气象指数预报中的应用。采用IPC和PLC控制结构对现场的各种设备实现控制和数据的采集，通过现场总线网络传输数据到中心控制室或远程终端，实现污水处理的自动控制和气象信息的实时采集和处理。     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

城市形象的建筑环境美学设计问题

城市形象是创造富于个性化城市的关键,而建筑环境美学设计水准则是体现城市形象的要素之一。据此,作者从分析中国城市形象的美学误区出发,研究了不同城市建筑品位的形成特点,进而提出塑造好宜人城市美学空间的科学思考。