模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

Unified equation of state based on the lattice fluid theory for phase equilibria of complex mixtures part I. Molecular thermodynamic framework

Consistent calculation of fugacities of fluid mixtures remains as one of the most important subjects in contemporary molecular thermodynamics. In practice, equations of state (EOSs) and g^E-models have been used. However, most EOSs are erroneous for condensed phases at high densities and g^E-models are inapplicable for pressuresensitive systems. Recently to remedy the shortcomings in both approaches, there has been a surge of new g^E-EOS mixing rules. By equating any set of EOS and g^E-models, the limitations in both approaches could be resolved significantly. However, the self-consistency in the underlying concept of those mixing rules remains controversial. During the last several years, the present authors proposed a new lattice-fluid EOS and its simplification relevant to phase equilibrium calculations. Without employing any g^E-EOS mixing rule and with only two parameters for a pure component and one adjustable interaction energy parameter for a binary mixture, results obtained to date demonstrated that the EOSs are quantitatively applicable to a great variety of phase equilibrium properties of mixtures, especially, for complex and/or macromolecular systems. In the present article we summarize the EOSs and extended the applications to liquid-liquid Equilibria. In part I, we discussed briefly the molecular thermodynamic aspects of general derivation of the EOS and a brief discussion of applying the EOSs to pure fluids while the illustrative application to various real mixture systems is discussed in part II.     

相似理论在真空灭弧室研究和设计中的应用

本文应用相似理论得出,真空灭弧室中电弧运动速度与电流强度成线性关系的相似准则,和极限开断电流与触头直径、开距间的经验公式。认为用小电流模型来研究大电流真空灭弧室是可行的。     

Public grid computing participation: An exploratory study of determinants

Using the Internet, “public” computing grids can be assembled using “volunteered” PCs. To achieve this, volunteers download and install a software application capable of sensing periods of low local processor activity. During such times, this program on the local PC downloads and processes a subset of the project's data. At the completion of processing, the results are uploaded to the project and the cycle repeats.     

Evaluation of a proper controller performance for maximum-power point tracking of a stand-alone PV system

In this paper the implementation of a suggested stand-alone PV system, for maximum-power point tracking (MPPT), is carried out. Also, this paper presents a comparative study, through experimental work, between the conventional PI controller and the fuzzy logic controller (FLC) under different atmospheric conditions. The implemented system with both the PI controller and the FLC gives a good maximum-power operation of the PV array, but the tracking capability for different optimum operating points is better and faster for the case of using the FLC compared to the case of using the PI controller.     

A novel fuzzy clustering algorithm for the analysis of axillary lymph node tissue sections

Recently Fourier Transform Infrared (FTIR) spectroscopic imaging has been used as a tool to detect the changes in cellular composition that may reflect the onset of a disease. This approach has been investigated as a mean of monitoring the change of the biochemical composition of cells and providing a diagnostic tool for various human cancers and other diseases. The discrimination between different types of tissue based upon spectroscopic data is often achieved using various multivariate clustering techniques. However, the number of clusters is a common unknown feature for the clustering methods, such as hierarchical cluster analysis, k-means and fuzzy c-means. In this study, we apply a FCM based clustering algorithm to obtain the best number of clusters as given by the minimum validity index value. This often results in an excessive number of clusters being created due to the complexity of this biochemical system. A novel method to automatically merge clusters was developed to try to address this problem. Three lymph node tissue sections were examined to evaluate our new method. These results showed that this approach can merge the clusters which have similar biochemistry. Consequently, the overall algorithm automatically identifies clusters that accurately match the main tissue types that are independently determined by the clinician.     

Cryptography and cryptographic protocols

We survey the paradigms, approaches and techniques used to conceptualize, define and provide solutions to natural cryptographic problems. We start by presenting some of the central tools (e.g., computational difficulty, pseudorandomness, and zero-knowledge proofs), and next turn to the treatment of encryption and signature schemes. We conclude with an extensive treatment of secure cryptographic protocols both when executed in a stand-alone manner and when many sessions of various protocols are concurrently executed and controlled by an adversary. The survey is intended for researchers in distributed computing, and assumes no prior familiarity with cryptography.Received: June 2001, Accepted: July 2002,     

Hybrid Approach for Addressing Uncertainty in Risk Assessments

Parameter uncertainty is a major aspect of the model-based estimation of the risk of human exposure to pollutants. The Monte Carlo method, which applies probability theory to address model parameter uncertainty, relies on a statistical representation of available information. In recent years, other uncertainty theories have been proposed as alternative approaches to address model parameter uncertainty in situations where available information is insufficient to identify statistically representative probability distributions, due in particular to data scarcity. The simplest such theory is possibility theory, which uses so-called fuzzy numbers to represent model parameter uncertainty. In practice, it may occur that certain model parameters can be reasonably represented by probability distributions, because there are sufficient data available to substantiate such distributions by statistical analysis, while others are better represented by fuzzy numbers (due to data scarcity). The question then arises as to how these two modes of representation of model parameter uncertainty can be combined for the purpose of estimating the risk of exposure. This paper proposes an approach (termed a hybrid approach) which combines Monte Carlo random sampling of probability distribution functions with fuzzy calculus. The approach is applied to a real case of estimation of human exposure, via vegetable consumption, to cadmium present in the surficial soils of an industrial site located in the north of France. The application illustrates the potential of the proposed approach, which allows the uncertainty affecting model parameters to be represented in a way that is consistent with the information at hand. Also, because the hybrid approach takes advantage of the “rich” information provided by probability distributions, while retaining the conservative character of fuzzy calculus, it is believed to hold value in terms of a “reasonable” application of the precautionary principle.     

SECANT-FUZZY LINEAR REGRESSION METHOD FOR HARMONIC COMPONENTS ESTIMATION IN A POWER SYSTEM

In order to avoid unnecessary damage of electrical equipments and installations,high quality power should be delivered to the end user and strict control on frequency should be made, Therefore, it is important to estimate the power system's harmonic components with higher accuracy. This paper presents a new approach for estimating harmonic component in a power system using secant - fuzzy linear regression method. In this approach the non - sinusoidal voltage or current waveform is written as I linear function. The coefficient of this function is assumed to be fuzzy number with a membership function that has center and spread value. The time dependent quantity is written as Taylor series with two different time dependent quantities. The objective is to use the sample obtained from the transmission line to find the power system harmonic components and frequencies. We used an experimental voltage signal from a sub power station as a numerical test.     

Syntactic mismatches in machine translation

This paper addresses one of the central problems arising at the transfer stage in machine translation: syntactic mismatches, that is, mismatches between a source-language sentence structure and its equivalent target-language sentence structure. The level at which we assume the transfer to be carried out is the Deep-Syntactic Structure (DSyntS) as proposed in the Meaning-Text Theory (MTT). DSyntS is abstract enough to avoid all types of divergences that result either from restricted lexical co-occurrence or from surface-syntactic discrepancies between languages. As for the remaining types of syntactic divergences, all of them occur not only interlinguistically, but also intralinguistically; this means that establishing correspondences between semantically equivalent expressions of the source and target languages that diverge with respect to their syntactic structure is nothing else than paraphrasing. This allows us to adapt the powerful intralinguistic paraphrasing mechanism developed in MTT for purposes of interlinguistic transfer.