Applied Mechanics and Materials Vols. 48-49

Abstract: The existence of trusted subjects is a major complication in implementing multilevel secure (MLS) systems. In MLS, trusted subjects are granted with privileges to perform operations possibly violating mandatory access control policies. It is difficult to prevent them from data leakage with out too strict confinement. This paper reconsiders the privilege from the view of sensitive data and presents a dynamic trusted domain (DTD) mechanism for trusted subjects. In DTD, a domain is associated with a special label structure (LabelVector) distinguishing security policies and builds an isolated environment based on virtualization for a certain trusted subject. The channel for the trusted subject to communicate with outsider is controlled by a trusted request decision maker (TRDM). Only the request satisfies the rules on domain label and security levels can be passed through.

Abstract: By using space-harmonic analysis method, the characteristics of vibrational power flow and sound radiation of an infinite submerged cylindrical shell with internal rings and bulkheads are studied analytically. The harmonic motion of the shell and the pressure field in the fluid are described by Flügge shell equations and Helmholtz equation, respectively. The coupling condition on the outer surface of the shell wall is introduced to obtain the vibrational equation of this coupled system. Both four kinds of forces (moments) between rings and shell and between bulkheads and shell are considered. The solution is obtained in series form by expanding the system responses in terms of the space harmonics of the spacings of both ring stiffeners and bulkheads. The vibrational power flow and radiated sound power are obtained and the influences of various complicating effects such as the ring, bulkhead and fluid loading on the results are analyzed. The analytic model is close to engineering practice, which will give some guidelines for noise reduction of this kind structure.

Abstract: This paper introduces the principle in the application of eddy current technology to detect defects on the surface of aluminum profile and several factors of detecting the depth and precision. On this basis it designs a set of closed-loop system which can be used for the detection and repair of defects in the production line, and outlooks its academic significance and application prospect.

Abstract: 40Cr steel is categorized as quenched-tempered steels and is widely used in gears, bolts, couplings, spindles, etc. To study the plastic deformation behaviour of the steel after quenching and tempering, compression and double-pass compression tests have been carried out. The quenched samples are tempered at the temperature of 540oC, 580oC, 600oC and 630oC, and the microstructures, compression load, hardness after compression and load of double-pass compression are investigated. The compression peak load is higher when the tempering temperature is lower. The hardness average and its increase amplitude decrease with the tempering temperature. An interesting phenomenon of the double-pass compression load can be well explained by the microstructures.

Abstract: The purpose of this paper is to introduce a general scenario for Enterprise SNS knowledge community of E-Learning to promote knowledge innovation, including four sub processes and two knowledge techniques. First, four sub processes are researched respectively, including: motivation to acquire new knowledge, knowledge searching and collection, knowledge decision-making and knowledge innovation. Second, knowledge base and recommendation are two knowledge techniques. The paper underscores the significance of E-Learning to improve knowledge innovation in enterprise and a case study is given. Keywords: E-Learning; SNS; knowledge community; knowledge innovation;

Abstract: EAF steelmaking is a complex physical and chemical reactions，has Highly nonlinearity, time variability and strong coupling. As the electrode's contact with the charging circuit, charging the collapse of the gasification furnace components and liquid metal boiling and other factors, often result in dramatic fluctuations in arc current. At this point we need to quickly adjust the location of electrodes, so that arc current stable base on this within a certain range. This article in the fuzzy control and neural network’s foundation,will study a kind based on three-phase consciousness electric arc furnace predictive control new method, Using the fuzzy neural network control adjusting electrode, further enhancing the effectiveness of electric arc furnace’synthesis movement.

Abstract: Television data collection and return technologies are one of key technologies in television secure broadcasting system, TV video content surveillance, TV program copyright protection, and client advertisement broadcasting. In china, the dominating methods of TV video content surveillance are manual tape recording and whole TV program Automatic Return. Manual method costs too much, whole TV program return method needs lots of net bandwidth and storage space. This paper proposes a new method of television data collection and return technology, video field is extracted from continuous video and coded at frequency of about one field per second, in other words, one field is extracted from continuous fifty fields of original video for PAL TV system, extracted frame can be coded by all means, for example JPEG2000, or intra mode code of H.264 or MPEG2. TV programs whose content and topic change most frequently are news and advertisement program, which may change topic in five to ten seconds, so extracted sequences hold the same topic and content and enough information with original video for TV program content surveillance application. The data quantity of extracted sequence is about 3 percent of the original video program, which will save large quantity of network bandwidth and storage space. One hardware implementation method of this technology based on embedded system is proposed, the TV Field Extractor, which circularly extracts images from target TV program, uses high-performance compression algorithm for image compression and stores the final output sequences of stationary images on the hard disk, or transmits these sequences to the monitoring center via network. This method evidently reduces device cost, network bandwidth and storage space, which can be widely adopted in TV program content surveillance and TV secure broadcasting system.

Abstract: The aim of this paper is to introduce a class of stochastic competitive system with age-structure. By using klmogorou's inequality, Bark holder -Davis -Gundy's lemma, Ito’s formula, some special inequalities and some criteria are obtained for the exponential stability of stochastic competitive system.

Abstract: This paper presents methods based on chemometrics analysis to select the optimal model for variety discrimination of ginkgo (Ginkgo biloba L.) tablets by using a visible/short-wave near-infrared spectroscopy (Vis/NIRS) system. The tablet varieties used in the research include Da na kang, Xin bang, Tian bao ning, Yi kang, Hua na xing, Dou le, Lv yuan, Hai wang, and Ji yao. All samples (n=270) were scanned in the Vis/NIR region between 325-1075nm using a spectrograph. Principal component artificial neural network (PC-ANN) was used to identify the tablet varieties. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN. Independent component analysis (ICA) was executed to select several optimal wavelengths based on loading weights. The absorbance values log (1/R), corresponding to the wavelengths of 481nm, 1000nm, 460nm, 572nm, 658nm, 401nm, 998nm, 996nm, 468nm and 661nm were then chosen as the input data of artificial neural network (IC-ANN), and the discrimination rate was reached at 95.6%, which was better than PC-ANN. The results indicated that ginkgo tablets discrimination was good based on the both methods.

Abstract: In order to improve reliability of excavator’s hydraulic system, a fault detection approach based upon dynamic general regression neural network (GRNN) approach was proposed. Dynamic GRNN is an extension of GRNN, which could effectively caputure the dynamic behavior of the nonlinear process. With this approach, normal samples were used as training data to develop a dynamic GRNN model in the first step. Secondly, this dynamic GRNN model performed as a fault determinant of the test fault. Experimental faults were used to validate the approach. Experimental results show that the proposed fault detection approach could effectively applied to the excavator’s hydraulic system.