Zhang Yong-chuan

A Digital Image Scrambling Method Based on AES and Error-Correcting Code

A new scrambling method of true color images based on AES algorithm is proposed. It takes the structure of true color images into full consideration, and decreases the complexity. The analytical method of cryptography is first used in this paper to analyze the security of disordered images; at the same time, an error-correcting code is designed to prevent passive attacks based on bit modification. Experimental results show that the method is safe, efficient and has great ability of error correcting.

A novel automated separator based on dual energy gamma-rays transmission

The paper describes a novel automated separator, of which the key point is the determination of ash in coal by a technique based on the attenuation of dual energy γ-rays transmission. The technique is often used to determine the concentration of a higher atomic number (Z) component in a lower Z matrix. We designed a novel apparatus to realize the on-line non-contact measurement of ash in the virgin lump coal during the process of conveying. As a result, the gangues in the virgin lump coal are recognized by using a threshold ash method and removed by the pneumatic actuator. In this paper the principle of this measurement and the arrangement for separation are presented. Both the main factors affecting the dynamic determination and methods for reducing errors in analysis are also proposed. Furthermore, the experimental verification of the analysis has been conducted. The results are in good agreement with the theoretical analysis.

Early-age electrical resitivity and reactive capacity of mineral admixtures in mortars

A non-contacting electrical resistivity measurement device used to investigate the effect of different types and contents of mineral admixtures on the hydration performance of mortanrs during early age. The experimental results show that the changes of measured resistivity with time of hydration can be used to describe the hydration characteristics of cement-based materials, as well as the physical and chemical behavior of fly ash; blast furnance slag and silica fume at the very early ages. With an increasing replacement ratio of mineral admixtures, for the specimens blended with fly ash or slag, the resistivity increases firstly, then the following flatting period extends and after setting the resistivity increasing becomes slow and consequently a lower resistivity value at 24 hours occurs. This is due to the dilution effect and lower pozzolanic/hydraulic activity of fly ash and slag. However, for the samples incorporated with silica fume, the resistivity value through 24 hours is lower with shorter flatting period and larger slope in the resistivity curves, which is because of its particle size effect and higher pozzolanic activity of silica fume. Moreover, non-contacting resistivity measurement might provide a helpful information to predict the long term performance including the durability of cement-based materials at early ages.

Fault Diagnosis of Hydroturbine Generating Units Based on Least Squares Support Vector Machines

The algorithm of support vector machines (SVM), a novel machine learning method based on statistical learning theory, has been successfully used in pattern recognition and function estimation. The theory of least squares support vector machines (LS-SVM) is a least squares version of standard SVM, which involves equality instead of inequality constraints and works with a least squares object function. A systematic approach based on LS-SVM and wavelet decomposition for fault diagnosis of hydroturbine generating units (HGU) is proposed in this paper. The vibration signals under abnormal conditions are collected and preprocessed with the wavelet decomposition and feature information of signals is extracted as the feature vectors for training and testing the LS-SVM. To classify multiple fault modes of HGU, a multiclass classifier based on LS-SVM with minimum output codes (MOC) is constructed and used in the fault diagnosis for HGU. Its showed in the simulation result that the fault types can be identified and diagnosed by the above method. Compared with the result of a RBF neural network, more excellent identification accuracy indicates the feasibility and effectiveness of LS-SVM in the fault diagnosis of HGU.

Modeling and Analysis of a Fuzzy Control Real-Time Event Channel

This paper presents the modeling and analysis of a fuzzy control algorithm related with Real-time Event Channel. One problem with Real-time Event Channel is that it is sensitive to overload. By modeling and analyzing the performance of Real-time Event Channe.. Thus a fuzzy control mechanism of Real-time Event Channel performance is presented, to control and adjust maximum customers number of Notification Service system. Finally, we fulfilled simulation experiment on mechanism, the outcome shows that fuzzy control can be accommodated to the change of Real-time Event Channel system load and system model more easily, and can control the load at random more efficiently than usual controller do.

Fuzzy Control Improves Real-Time Event Channel Performance

Real-time Event Channel is increasingly being used in a wide variety of Distributed real-time and embedded (DRE) computing systems. One problem with Real-time Event Channel is that it is sensitive to overload. By analyzing and simulating the performance of Real-time Event Channel..this paper revealed the relationship between maximum customers number permitted by Real-time Event Channel and utilization of the system. Thus a fuzzy control mechanism of Real-time Event Channel performance is presented, to control and adjust maximum customers number of Notification Service system. Finally, we fulfilled simulation experiment on mechanism, the outcome shows that fuzzy control can be accommodated to the change of Real-time Event Channel system load and system model more easily, and can control the load at random more efficiently than usual controller do.