基于扩展分形和CFAR特征融合的SAR图像目标识别

研究了多信息融合技术在SAR图像目标识别中的应用。将扩展分形特征(Extended Fractal)与双参数恒虚警特征(Double Parameter CFAR)形成的多信息进行融合处理。运用Dempster-Shafer证据理论，在决策层对SAR图像中的像素进行识别分类。实验结果表明通过融合对像素分类的准确性明显好于单特征的检测结果，减少了虚警概率，提高了系统的识别能力。     

Segmented polymer networks containing amino‐dendrimers

Polymer networks in which poly(propylene imine) dendrimers (Astramol?) are connected to each other by linear polytetrahydrofuran (polyTHF) segments, were prepared by two methods. The first method was a one‐step procedure in which bifunctionally living polyTHF, obtained by initiation of the THF polymerization with trifluoromethane sulfonic anhydride (triflic anhydride), was reacted with an amino‐dendrimer. This reaction was very fast but did not allow formation of the end products. The second method was a two‐step procedure. In a first step, living polyTHF, prepared with acryloyloxybutyl triflate as initiator, was grafted on an amino‐dendrimer, to form a star‐like, acrylate‐terminated polyTHF multi‐macromonomer with the dendrimer as core. In a second step, networks were obtained by Michael addition between the acrylate end‐groups and unreacted amino‐groups of the dendrimer. This cross‐linking reaction occurred spontaneously upon heating of the solution of the multi‐macromonomer with gelation times varying from a few minutes to a few hours, depending on the temperature and the composition of the prepolymers. With this method it was possible to prepare networks in the form of coatings or films. © 2003 Society of Chemical Industry     

An EM‐based adaptive multiple target tracking filter

Tracking targets of interest is one of the major research areas in radar surveillance systems. We formulate the problem as incomplete data estimation and apply EM to the MAP estimate. The resulting filter has a recursive structure analogous to the Kalman filter. The advantage is that the measurement‐update deals with multiple measurements in parallel and the parameter‐update estimates the system parameters on the fly. Experiments tracking separate targets in parallel show that tracking maintenance ratio of the proposed system is better than that of NNF and RMS position error is smaller than that of PDAF. Also, the system parameters are correctly obtained even from incorrect initial values. Copyright © 2001 John Wiley & Sons, Ltd.     

适用于快速平台测井的多通道核能谱测井仪设计

介绍一种基于快速平台测井要求的多通道核能谱测井仪设计方案。复杂可编程逻辑器件的应用使仪器功能增强，规模减小。该系统可对岩性密度长短源距脉冲信号、自然γ能谱脉冲信号进行多道脉冲幅度分析，并对补偿中子测井信号及井下多路常规模拟信号、脉冲信号进行数字化采集。数据传输采用曼彻斯特编码，传输方式可选择20kB／s半双工(兼容Atlas 3508)或下行20kB／s、上行41．66或93．75kB／s全双工方式(兼容Atlas WTS)，适应挂接到不同测井系统的需要。     

Object-oriented DBMS requirements

The requirements on an object-oriented DBMS for management of information in a large, complex enterprise are presented. These requirements aid in the achievement of an environment characterized by data sharing, open architectures, application and data portability, and assurance of data integrity. They were defined from the point of view of a user of the DBMS; therefore they describe the expected functionality of the DBMS and do not specify the method of implementation to achieve this functionality. They encompass requirements on the data model, query and data manipulation languages, the system architecure, interfaces to the system, change management, and transaction management.     

用于实时数据传输的滑动帧方法及其实现

根据某雷达系统对测量信号的快速传输要求,提出采用滑动帧的处理方法并在FPGA中实现,克服了传统帧处理难以满足快速传输要求的不足。阐述了滑动帧结构的构造思想,详述了滑动帧结构的特点及具体功能模块的实现。根据实际应用需求构造了滑动帧结构处理器,试验和应用结果表明设计可行有效,能充分满足实时数据传输的要求。     

The influence of raw material characteristics on the industrial pelletizing process and pellet quality

Industrial pelletizing of sawdust was carried out as a designed experiment in the factors: sawdust moisture content, fractions of fresh pine, stored pine and spruce. The process parameters and response variables were energy consumption, pellet flow rate, pellet bulk density, durability and moisture content. The final data consisted of twelve industrial scale runs. Because of the many response variables, data evaluation was by principal component analysis of a 12 × 9 data matrix. The two principal component model showed a clustering of samples, with a good reproducibility of the center points. It also showed a positive correlation of energy consumption, bulk density and durability all negatively correlated to flow rate and moisture content. The stored pine was more related to high durability and bulk density. The role of the spruce fraction was unclear. The design matrix, augmented with the process parameters was a 12 × 6 matrix. Partial least squares regression showed excellent results for pellet moisture content and bulk density. The model for durability was promising. A 12 × 21 data matrix of fatty- and resin acid concentrations measured by GC–MS showed the differences between fresh and stored pine very clearly. The influence of the spruce fraction was less clear. However, the influence of the fatty- and resin acids on the pelletizing process could not be confirmed, indicating that other differences between fresh and stored pine sawdust have to be investigated. This work shows that it is possible to design the pelletizing process for moderate energy consumption and high pellet quality.     

Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

Object data MODEL = object-oriented + semantic models

The term ‘object-oriented database’ has been used to refer to different characteristics and mechanisms supported by semantic databases and (behaviorally) object-oriented ones. While this indicates the current confusion due to the lack of a common model, it also suggests the potential desirability of combining these two kinds of modeling facilities into the same nutshell. This paper summarizes from these two paradigms the features common to both, the features influenced/adopted by each other, and the features which are presented in one paradigm but missing from the other. After a brief analysis and discussion of these features, we conclude this paper by proposing our major theme: a complete object data model should take the union of the facilities offered by these two kinds of models.