Cit-CSP及其应用

介绍了Cit-CSP--Cit/E-commerce信息安全保障平台子系统，并阐述了它所提供的消息摘要、块加密、加密(公钥)、签名和MAC等功能和服务。     

An Approximate Model of Multistage Automatic Transfer Lines with Possible Scrapping Of Workpieces

We consider multistage automatic transfer lines with unreliable stages, finite interstage buffer storages, and possible scrapping of workpieces. It is assumed that the first stage never idles and the last stage never becomes blocked. Assuming that uptimes and downtimes of a stage are geometrically distributed, an approximate model is developed to compute different performance measures of the transfer line. The results obtained through the approximate model are compared to the exact results for three-stage transfer lines and to simulation results for longer transfer lines. It is observed that the approximate results are good in almost all cases considered.     

Signature analysis and defect detection in layered manufacturing of ceramic sensors and actuators

This paper presents the concept of a process signature for the use of online signature analysis and defect detection in the layered manufacturing (LM) of ceramic sensors and actuators. To achieve the high quality of parts built by the fused deposition of ceramics (FDC), an online process-monitoring system is implemented to detect the processing defects. Using a process signature extracted from the image of a layer captured by the monitoring system, an ideal image is created that is then compared to the original image to detect and identify the defects. Some results of signature analysis and defect detection for single-material and multi-material parts are also presented.Received: 22 July 1999, Accepted: 21 October 2001, Published online: 29 October 2003 Correspondence to: Mohsen A. JafariThis work was supported by the Office of Naval Research under grant # N-0014-96-1-1175. Ref. US Patent # S-5738817, April 14, 1998.     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

     

Ultra-low power MEMS micro-heater device

Microsystem Technologies - In this paper, we propose a simple design for the heating device with ultra-low power consumption. The device is composed of a micro heater made of Nichrome (20/80)...     

Thermal modeling in cylindrical coordinates using effective conductivity

Predictive thermometry, utilizing minimally invasive sampling techniques, is an essential ingredient in the development of hyperthermia treatment planning capabilities. The authors demonstrate a powerful, but simple approach toward predicting temperature distributions in tissues, based on analytic solution, using in cylindrical symmetry, of the heat diffusion equation. Conduction and localized perfusion effects are combined as an effective conductivity term, readily measurable, and parametrized in a general exponential form. The proposed approach allows a first-order approximation to modeling three typical situations: hypoxic or necrotic tumor core with homogeneously perfused periphery; highly perfused periphery (in rapidly growing tumors); or perfused central cover with a less well-supplied periphery (such as for some invasive tumors). The utility and strength of this approach is that it provides a rapid, accurate model of directly observing the technical quality to be expected for different heating methods, making it possible to optimally configure source distributions in a treatment planning setting.     

Robust and stable flow shop scheduling with unexpected arrivals of new jobs and uncertain processing times

In real scheduling problems, some disruptions and unexpected events may occur. These disruptions cause the initial schedule to quickly become infeasible and non-optimal. In this situation, an appropriate rescheduling method should be used. In this paper, a new approach has been proposed to achieve stable and robust schedule despite uncertain processing times and unexpected arrivals of new jobs. This approach is a proactive–reactive method which uses a two-step procedure. In the first step an initial robust solution is produced proactively against uncertain processing times using robust optimization approach. This initial robust solution is more insensitive against the fluctuations of processing times in future. In the next step, when an unexpected disruption occurs, an appropriate reactive method is adopted to deal with this unexpected event. In fact, in the second step, the reactive approach determines the best modified sequence after any unexpected disruption based on the classical objective and performance measures. The robustness measure is implemented in the reactive approach to increase the performance of the real schedule after disruption. Computational results indicate that this method produces better solutions in comparison with four classical heuristic approaches according to effectiveness and performance of solutions.     

Investigation into the effect of carboxylic acid monomer on particle nucleation and growth in emulsifier-free emulsion copolymerization of styrene-butadiene-acrylic acid

Latexes of carboxylated styrene-butadiene rubber were prepared via batch emulsion copolymerization with different amounts of acrylic acid in the absence of emulsifier. The effect of acid monomer was investigated in the particle formation and growth. It was observed that the amount of acrylic acid strongly affected the particle formation. The number of particles and thus polymerization rate increased with increasing of the acid content. There was no significant difference in the polymerization rate per particle in all experiments. The results show that in this case particle growth process is less dependent on the acrylic acid amount in comparison with its influence on nucleation stage and then particle number. Several parameters such as polymerization rate and number of latex particle per unit volume of the aqueous phase were calculated. Attempt was made to evaluate the average number of growing chain per particle. Also average particle diameter of the above carboxylated SBR latexes was obtained through some calculations from the direct measurement of average particle diameter in the swollen state by light scattering technique for the first time.