硅灰混凝土的研究及其在公路道面的应用

 了提高道路路面混凝土的抗磨能力，采用硅灰代替部分水泥的方法，对硅灰混凝土的性能进行了较系统的试验研究。成果表明其抗压强度、抗弯强度、抗磨强度等指标都得到明显提高，全面达到和超过了规范要求。并已在丹江口水利枢纽上坝公路中得到应用，实践证明硅灰混凝土技术可靠、经济合理、易于施工。特别是抗磨度的提高，对延长公路路面的使用寿命具有重要意义。     

Thermal analysis of a ceramic coating diesel engine piston using 3-D finite element method

In this study, firstly, thermal analyses are investigated on a conventional (uncoated) diesel piston, made of aluminum silicon alloy and steel. Secondly, thermal analyses are performed on pistons, coated with MgO-ZrO₂ material by means of using a commercial code, namely ANSYS. Finally, the results of four different pistons are compared with each other. The effects of coatings on the thermal behaviors of the pistons are investigated. It has been shown that the maximum surface temperature of the coated piston with material which has low thermal conductivity is improved approximately 48% for the AlSi alloy and 35% for the steel.     

Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

Security flaws in a recent RFID delegation protocol

Radio frequency identification (RFID) tag delegation enables a centralized back-end server to delegate the right to identify and authenticate a tag to specified readers. This should be used to mitigate the computational load on the server side and also to solve the issues in terms of latency and dependency on network connectivity. In this study, we describe a basic RFID delegation architecture and then under this model, we investigate the security of an RFID delegation protocol: Song Mitchell delegation (SMD), which is recently proposed by Song and Mitchell. We point out security flaws that have gone unnoticed in the design and present two attacks namely, a tag impersonation attack and a desynchronization attack against it. We also discover a subtle flaw by which a delegated entity can still keep its delegation rights after the expire of them—this infringes security policy of the scheme. More precisely, we show that the protocol will be still vulnerable to previously mentioned attacks, even if the back-end server ends the delegation right of a delegated reader and update the secrets of the delegated tags. To counteract such flaws, we improve the SMD protocol with a stateful variant so that it provides the claimed security properties.     

Extraction of voltage harmonics using multi-layer perceptron neural network

This paper presents a harmonic extraction algorithm using artificial neural networks for Dynamic Voltage Restorers (DVRs). The suggested algorithm employs a feed forward Multi Layer Perceptron (MLP) Neural Network with error back propagation learning to effectively track and extract the 3rd and 5th voltage harmonics. For this purpose, two different MLP neural network structures are constructed and their performances compared. The effects of hidden layer, supervisors and learning rate are also presented. The proposed MLP Neural Network algorithm is trained and tested in MATLAB program environment. The results show that MLP neural network enable to extract each harmonic effectively.