ANISOTROPIC EFFECTS OF QUASI-ISOTROPIC COMPOSITES(I)──MODELLING

Experimental obseryations show that quasi-isotropic materials, such as N-axial fibre-reinforced composites and woven materials . exhibit various degrees of anisotrpy in elasticity and strength, and the anisotropy in strengty is normally stronger than that in elasticity.In view of some available experimental data and based on the general formulation of the constitutive equations and .failure criteria of quasi-isotropic materials established by using the theory of repesentations for tensor functions, we postulate several applicable models of the constitutive equations and strength for 3and 4-axial quasi-isotropic materials to reveal the anisotropic effects In a continued work (Part II) the anisotropic effect in strength of an infintely large plate with a single elliptical hole or crack is studied. and the proposed stiffness and strength modelsare verified in terms of micro-mechanical analyses.

Differently implicational α-universal triple I restriction method of (1, 2, 2) type

From the viewpoints of both fuzzy system and fuzzy reasoning, a new fuzzy reasoning method which contains the α- triple I restriction method as its particular case is proposed. The previous α-triple I restriction principles are improved, and then the optimal restriction solutions of this new method are achieved, especially for seven familiar implications. As its special case, the corresponding results of α-triple I restriction method are obtained and improved. Lastly, it is found by examples that this new method is more reasonable than the α-triple I restriction method.

Soil Parameter Identification for Wheel-terrain Interaction Dynamics and Traversability Prediction

This paper presents a novel technique for identifying soil parameters for a wheeled vehicle traversing unknown terrain. The identified soil parameters are required for predicting vehicle drawbar pull and wheel drive torque, which in turn can be used for traversability prediction, traction control, and performance optimization of a wheeled vehicle on unknown terrain. The proposed technique is based on the Newton Raphson method. An approximated form of a wheel-soil interaction model based on Composite Simpson＇s Rule is employed for this purpose. The key soil parameters to be identified are internal friction angle, shear deformation modulus, and lumped pressure-sinkage coefficient. The fourth parameter, cohesion, is not too relevant to vehicle drawbar pull, and is assigned an average value during the identification process. Identified parameters are compared with known values, and shown to be in agreement. The identification method is relatively fast and robust. The identified soil parameters can effectively be used to predict drawbar pull and wheel drive torque with good accuracy. The use of identified soil parameters to design a traversability criterion for wheeled vehicles traversing unknown terrain is presented.

Mathematical Foundation of Basic Algorithms of Fuzzy Reasoning

Algorithm of fuzzy reasoning has been successful applied in fuzzy control,but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper,structure of basic algorithms of fuzzy reasoning was studied, its rationality was discussed from the viewpoint of logic and mathematics, and three theorems were proved. These theorems shows that there always exists a mathe-~matical relation (that is, a bounded real function) between the premises and the conclusion for fuzzy reasoning, and in fact various algorithms of fuzzy reasoning are specific forms of this function. Thus these results show that algorithms of fuzzy reasoning are theoretically reliable.

The Rectangle Rule for Computing Cauchy Principal Value Integral on Circle

The classical composite rectangle (constant) rule for the computation of Cauchy principle value integral with the singular kernel is discussed. We show that the superconvergence rate of the composite midpoint rule occurs at certain local coodinate of each subinterval and obtain the corresponding superconvergence error estimate. Then collation methods are presented to solve certain kind of Hilbert singular integral equation. At last, some numerical examples are provided to validate the theoretical analysis.

Web Service Composition Based on QoS Rules

For workflow-based service composition approach,the relations between the Web service QoS and environments are usually not considered,so that the information about QoS for composite service selection is inaccurate.It makes the selected composite service inefficient,or even unexecutable.To address this problem,a novel service composition approach based on production QoS rules is proposed in this paper.Generally,it is very difficult to directly analyze how different kinds of environment factors influence the Web service QoS.We adopt ＂black-box＂ analysis method of optimizing composite services,discovering the knowledge such as ＂the QoS of one Web service will be higher in specific environments＂.In our approach,the execution information of the composite service is recorded into a log first,which will be taken as the basis of the subsequent statistical analysis and data mining.Then,the timely QoS values of the Web services are estimated and the production QoS rules being used to qualitatively express the different performances of the Web service QoS in different environments are mined.At last,we employ the mined QoS knowledge of the Web services to optimize the composite service selection.Extensive experimental results show that our approach can improve the performance of selected composite services on the premise of assuring the selecting computation cost.

Support optimal scheduling with weighted random forest for operation resources

Operation-related resources are lots of manpower and material with the characteristics of high cost and high income in hospitals,and scheduling optimization is a very important research issue in medical service.In this paper,to cope with the actualities of operation resources scheduling,such as poor planning,lack of standardized scheduling rules,chaotic use of the operating rooms,and many human interference factors,we propose a systematic approach to optimize scheduling problems based on multiple characteristics of operating resources.We frst design a framework that includes the composite dispatching rules(CDR),optimization ideology,and feedback mechanism,in which the CDR integrates fexible operating time,hold-up time of medical facilities,available time of medical staf,and multiple constraints.The optimization ideology is carried out through a learning model based on the weighted random forest(WRF)algorithm.The feedback mechanism enables the approach to realize closed-loop optimizations adaptively.Finally,the superiority of the systematic scheduling approach(SSA)is analyzed through numerical experiments on a simulation platform.Results of the simulation experiments show that the proposed scheduling method can improve performances signifcantly,especially in the waiting time of patients.