如何做好电子阅览室的安全管理

防治病毒、防混乱和防泄密是图书馆电子阅览室安全管理中三个最主要的环节，本文针对这三个主要环节，提出了一些比较实用的具体方法及措施。     

论网络升级方式与光纤选择的关系

在重点说明影响传输光纤设计的主要问题的同时，简要介绍了各种升级方式所面临的主要技术挑战，并详细说明这些挑战对传输光纤提出的技术要求。     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.     

GENERALIZED INVERSE GROUP OF SIGNAL AND ITS IMPLEMENTATION WITH NEURAL NETWORKS

A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational simulation have shown that (1) there is a group of finite length of generalized inverse signals for any given finite signal, which forms the GIG; (2) each inverse group has different leaking coefficients, thus different abnormal states; (3) each GIG can be implemented by a grouped and improved single-layer perceptron which appears with fast convergence. When used in deconvolution, the proposed GIG can form a new parallel finite length of filtering deconvolution method. On off-line processing, the computational time is reduced to O(N) from O(N2). And the less the leaking coefficient is, the more reliable the deconvolution will be.     

NEURAL NETS SPEED FLOW CALCULATION

Neural Nets Successfully Solve Complex Fluid Flow Problem. Much research is being done in the area of neural networks, and industry is actively seeking successful application to real world problems. We describe here a successful application. We have used neural networks to model complex coolant flow patterns, such as those encountered in design of hypersonic aircraft. Previous calculation methods, while reasonably accurate, are iterative and extremely time consuming. Our new approach uses a hierarchical neural network architecture to model coolant flow distribution in multiple heat exchanger panels. This method is direct, fast, and accurate.     

Network model approach for calculating oscillating frequency of thermoacoustic prime mover

The network model is given and used to calculate the oscillating frequency of thermoacoustic prime mover. Theoretically calculated frequency by the model is plural, whose real part denotes actual frequency of the system, and imaginary part means attenuation coefficient of acoustic pressure. Numerical calculation is made under different conditions including different acoustic cavities, spacing between each parallel plate, gas pressures and system lengths. Theoretically calculated frequency and experimentally measured frequency are in quite good agreement.     

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor

Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed.     

图像压缩编码方法分析

介绍图像压缩编码技术发展过程,对图像压缩编码,特别是自适应预测编码、模型法编码、分形编码、小波变换压缩编码、神经网络压缩编码原理和特点进行分析,并阐述图像压缩编码的作用.     

智能同步光网络与多业务传送平台的应用

智能同步光网络(ASON)与多业务传送平台(MSTP)固其先进的智能性、可靠性、灵活性而得以发展和运用。本文根据智能光网络与多业务传送平台枝术的发展情况，结合北京通信传送网络的实际情况，探讨北京通信传送网的建设思路．     

人类HLA-DRB1基因型与民族和人群的神经网络无监督模式分类

HLA-DRB1等位基因主要参与人类的抗原免疫功能,对其进行比较研究,有助于追溯人类的进化迁移史,开发类群特异性药物.本研究以Matlab为平台,用自组织竞争网络(Self-Organizing Competitive Neural Network),对世界54个民族和人群、14个HLA-DRB1等位基因,进行了无监督模式分类.结果表明,各民族之间存在差异性,同民族的各人群之间有相似性.西伯利亚各人群,澳洲各土著人群,黑人各人群,南美印第安各人群,犹太族各人群,日本各人群,及欧美白人各人群有相对独立性:南美印第安人与西伯利亚人有高度相似性;中国民族在南方人群和北方人群间存在较大差异;中国汉族中,广东汉族地位特殊,与少数民族如拉祜族、瑶族关系密切.