Fuzzy inferring mathematical morphology and optical implementation

Fuzzification is introduced into gray-scale mathematical morphology by using two-input one-output fuzzy rule-based inference systems. The fuzzy inferring dilation or erosion is defined from the approximate reasoning of the two consequences of a dilation or an erosion and an extended rank-order operation. The fuzzy inference systems with numbers of rules and fuzzy membership functions are further reduced to a simple fuzzy system formulated by only an exponential two-input one-output function. Such a one-function fuzzy inference system is able to approach complex fuzzy inference systems by using two specified parameters within it-a proportion to characterize the fuzzy degree and an exponent to depict the nonlinearity in the inferring. The proposed fuzzy inferring morphological operators tend to keep the object details comparable to the structuring element and to smooth the conventional morphological operations. Based on digital area coding of a gray-scale image, incoherently optical correlation for neighboring connection, and optical thresholding for rank-order operations, a fuzzy inference system can be realized optically in parallel. (C) 1996 Society of Photo-Optical Instrumentation Engineers.

gcs-ma: a group communication system for mobile agents

Reliable messaging is a key component necessary for mobile agent systems. Current researches focus on reliable one-to-one message delivery to mobile agents. But how to implement a group communication system for mobile agents remains an open issue, which is a powerful block that facilitates the development of fault-tolerant mobile agent systems. In this paper, we propose a group communication system for mobile agents (GCS-MA), which includes totally ordered multicast and membership management functions. We divide a group of mobile agents into several agent clusters,and each agent cluster consists of all mobile agents residing in the same sub-network and is managed by a special module, named coordinator. Then, all coordinators form a ring-based overlay for interchanging messages between clusters. We present a token-based algorithm, an intra-cluster messaging algorithm and an inter-cluster migration algorithm to achieve atomicity and total ordering properties of multicast messages, by building a membership protocol on top of the clustering and failure detection mechanisms. Performance issues of the proposed system have been analysed through simulations. We also describe the application of the proposed system in the context of the service cooperation middleware (SCM) project.

三维环境中基于ESMF的多机器人协作观测方法

提出了一种基于扩展集员估计（ESMF）的多机器人协作观测方法，该方法将多机器人之间的观测数据融合过程嵌入到估计过程当中，从而减少了数据处理的过程，增强了算法的快速性。同时，这种方法在实现协作观测时只需要协作机器人传送观测信息而不是整个的估计信息，因此可以减轻多机器人系统的通信负担。除此之外，该方法在融合多机器人的观测数据过程中避免了多余的近似过程，增加了观测的准确性。最后，给出了三维环境下的仿真结果，验证了方法的可行性。

基于模型差分析的旋翼飞行机器人航向与垂向预测控制方法

本文针对旋翼飞行机器人全包线机动飞行中的驱动器滞后以及动力学模型时变的问题,提出了应对不确定性动力学模型的基于模型差分析的增量平稳预测控制方法。该方法首先通过建立增量平稳预测过程模型来应对驱动器输出滞后与稳态模型以及系统工作点的不确定性,并提升控制系统鲁棒性。然后通过自适应集员滤波器在线估计系统瞬态动力学与名义模型的偏差来补偿全包线飞行中时变模型对于名义控制器跟踪性能的影响。最后,通过实际的飞行试验验证了此方法能够有效的解决全包线飞行中航向与垂向的驱动器滞后与动力学时变问题,并且可以实用于旋翼机器人航向与垂向的全包线自主飞行控制。

基于UD分解的自适应扩展集员估计方法

用于非线性椭球估计的扩展集员算法在实际应用中存存着数值稳定性差、计算复杂度高以及滤波器参数难以选择等问题.本文提出了一种基于UD分解的自适应扩展集员估计算法,用于解决非线性系统时变状态和参数的联合估计和定界问题.新算法将UD分解与序列更新和选择更新策略结合起米,改进了传统扩展集员算法的数值稳定性和实时性能;同时,对滤波器参数进行自适应选择以进一步降低计算复杂度并达到次优估计结果.仿真实验表明了该算法的有效性和鲁棒性.

基于最小二乘拟合的模糊隶属函数构建方法

针对当前模糊隶属函数构造方法中存在的问题,提出一种构造模糊隶属函数方法.采用最小二乘法拟合离散数据来获得隶属函数.为减小拟合误差,采用了3项措施以达到预期目标.所构建的隶属函数,对任意输入物理量可直接得到其对应模糊语言变量的隶属度,从而有效避免专家指定隶属度的主观臆断性及不一致性.该方法简单、求解精度高,具有广泛适用性和较强的应用价值.仿真结果证实了该方法的有效性.

反假频重建理论及其在储层预测中的应用

To extend the cross-hole seismic 2D data to outside 3D seismic data, reconstructing the low frequency data to high frequency data is necessary. Blind deconvolution method is a key technology. In this paper, an implementation of Blind deconvolution is introduced. And optimized precondition conjugate gradient method is used to improve the stability of the algorithm and reduce the computation. Then high-frequency retrieved Seismic data and the cross-hole seismic data is combined for constraint inversion. Real data processing proved the method is effective. To solve the problem that the seismic data resolution can’t meet the request of reservoir prediction in the river face thin-layers in Chinese eastern oil fields, a high frequency data reconstruction method is proposed. The extrema of the seismic data are used to get the modulation function which operated with the original seismic data to get the high frequency part of the reconstruction data to rebuild the wide band data. This method greatly saves the computation, and easy to adjust the parameters. In the output profile, the original features of the seismic events are kept, the common feint that breaking the events and adding new zeros to produce alias is avoided. And the interbeded details are enhanced compared to the original profiles. The effective band of seismic data is expended and the method is approved by the processing of the field data. Aim to the problem in the exploration and development of Chinese eastern oil field that the high frequency log data and the relative low frequency seismic data can’t be merged, a workflow of log data extrapolation constrained by time-phase model based on local wave decomposition is raised. The seismic instantaneous phase is resolved by local wave decomposition to build time-phase model, the layers beside the well is matched to build the relation of log and seismic data, multiple log info is extrapolated constrained by seismic equiphase map, high precision attributes inverse sections are produced. In the course of resolve the instantaneous phase, a new method of local wave decomposition --Hilbert transform mean mode decomposition(HMMD) is raised to improve the computation speed and noise immunity. The method is applied in the high resolution reservoir prediction in Mao2 survey of Daqing oil field, Multiple attributes profiles of wave impedance, gamma-ray, electrical resistivity, sand membership degree are produced, of which the resolution is high and the horizontal continuous is good. It’s proved to be a effective method for reservoir prediction and estimation.

三峡库区堆积层斜坡稳定性分级与应用研究

Considering the lacking of standard for the classification of Accumulative slopes so far, research working was conducted based on the results of geological investigation, data analysis and experiment carried out in Wanzhou. By mean of statistical method and grey system, the author studied in detail inflationary factors to Accumulative slopes. In order to study the mechanism of Rock-Soil Aggregate (RSA), numerical testing method was used. Coordinates in the two and three dimensional space and its corresponding rock fragments in the sample were generated randomly by VB and Particle flow code. After being built the models of RSA with different rock content, uniaxial and triaxial numerical simulation tests were carried out respectively. In order to study the effect of rainfall in Accumulative slopes, in situ infiltration testing had been conducted on site in Wanzhou, Three Gorges Area. Relationship between the infiltration rate and amount of precipitation has been obtained. Eleven factors are considered in the classification of Accumulative slopes in this paper.(1)On the basis of four basic factors and four inducing factors, sum-and-difference method for the classification system has been built. (2)After weight of factors being determined by analytic hierarchy process and membership function of Accumulative slopes stability being built in virtue of fuzzy mathematics, AHP-FM model of Accumulative slopes stability has been completed. In the end of this paper, having been applied on stability of Accumulative slopes in Three Gorge area and compared with result by limit equilibrium, classification system has good effect.

职业倦怠与自我和谐、人际信任的关系研究：中学校长与一般教师的对比

Job Burnout has been a focus of the Occupational Stress Research. As a typical,helping occupation, teacher has attracted widely attention and researches in the areas of pedagogy and psychology. The special subgroup of teacher, headmasters who are the elites of the Basic Education, is ignored. The research about principals’ Job Burnout is nearly blank after analyzing related documents and information. With the development of the society, people pay more and more attention to the education and put more demands on the headmasters, especially middle-school principals. They are required not only to be good educators, who are equipped with all the inner qualities as a teacher, but also good managers. So the main purpose of this research was to compare the principal group with ordinary teacher group, and reveal underling factors, such as background variables and psychological protection variables. A representative sample of Wenzhou middle school principals sized 192 and a sample of middle school teacher sized 302 were sampled from various schools. The educational version of burnout inventory, self consistency scale, and interpersonal trust scale were administrated to the two samples, together with some demographic variables of interest. The applicability and equivalence of the three instruments used in this study were checked. Based on well-established reliability and cross-sample congruence of measures, the difference between principals and teachers was test. Then the contributing factors were analysis gradually. The five background variables were examined one by one in the two samples separately. A multiple covariance analysis was conducted to test whether there remained any difference between these two samples on the variables of interest. Regression analysis was used to further control the effect of self harmony and interpersonal trust to test the difference between two samples. Mediating analysis was conducted to build the relationship among the three constructs. The main results of the research were stated as following: 1. The internal consistency coefficients of all the scales were good, and no difference exited between the two groups. The measurement equivalence of three instruments was established well. The measures could be applied to and comparing the two samples. 2. The self-harmony, and interpersonal trust of principals were better than the ordinary middle-school teachers. Job Burnout of principals was significant lower than teachers. 3. Demographic variables like the gender, age groups, income levels, disricts, and the type of school, were important influencing factors. The difference patterns of the variables on these five variables in two samples had similarity and distinction. 4. After controlling the background variables, there remained significant difference between principals and teachers on the variables of interest. 5. Job Burnout negatively correlated with self-harmony and interpersonal trust. That is to say，the lower the degree of self-harmony and interpersonal are, the serious of the Job Burnout is, The correlation between the self-harmony and the interpersonal trust was positive. 6. After statistically controlling the background variables and psychological variables, there still exited significant difference between two groups of this study. Also, self harmony and interpersonal trust were significant protection predictors to different aspect of job burnout. 7. Mediating analysis was conducted to the residual score of the three constructs after controlling the five variables and group membership. Self harmony partially mediated the relationship between interpersonal trust and job burnout. That is, interpersonal trust had indirect effect to burnout mediated by self harmony, also had direct effect to burnout.

认知电位时空模式研究

This report mainly focused on methodology of spatiotemporal patterns (STP) of cognitive potentials or event-related potentials (ERP). The representation of STP of brain wave is an important issue in the research of neural assemblies. This paper described methods of parametric 3D head or brain modeling and its corresponding interpolation for functional imaging based on brain waves. The 3D interpolation method is an extension of cortical imaging technique. It can be used with transformed domain features of brain wave on realistic head or brain models. The simulating results suggests that it is a better method in comparison with the global nearest neighbor technique. A stable and definite STP of brainwave referred as microstate may become basic element for comprehending sophisticated cognitive processes. Fuzzy c-mean algorithm was applied to segmentation STPs of ERP into microstates and corresponding membership functions. The optimal microstate number was estimated with both the trends of objective function against increasing clustering number and the decorrelation technique base don microstate shape similarity. Comparable spatial patterns may occur at different moments in time with fuzzy indices and thus the serial processing limit generated from behavioral methods has been break through. High-resolution frequency domain analysis was carried out with multivariate autoregressive model. Bases on a 3D interpolation mentioned above, visualization of dynamical coordination of cerebral network was realized with magnitude-squared partial coherence. Those technique illustrated with multichannel ERP of 9 subjects when they undertook Strop task. Stroop effects involves several regions during post-perception stage with technique of statistical parameter mapping based F-test [SPM(F)]. As SPM(F) suggested task effects occurred within 100 ms after stimuli presentation involved several sensory regions, it may reflect the top-down processing effect.