Relative importance,specific investment and ownership in interorganizational systems

Implementation and maintenance of interorganizational systems (IOS) require investments by all the participating firms. Compared with intraorganizational systems, however, there are additional uncertainties and risks. This is because the benefits of IOS investment depend not only on a firm’s own decisions, but also on those of its business partners. Without appropriate levels of investment by all the firms participating in an IOS, they cannot reap the full benefits. Drawing upon the literature in institutional economics, we examine IOS ownership as a means to induce value-maximizing noncontractible investments. We model the impact of two factors derived from the theory of incomplete contracts and transaction cost economics: relative importance of investments and specificity of investments. We apply the model to a vendor-managed inventory system (VMI) in a supply chain setting. We show that when the specificity of investments is high, this is a more critical determinant of optimal ownership structure than the relative importance of investments. As technologies used in IOS become increasingly redeployable and reusable, and less specific, the relative importance of investments becomes a dominant factor. We also show that the bargaining mechanism—or the agreed upon approach to splitting the incremental payoffs—that is used affects the relationship between these factors in determining the optimal ownership structure of an IOS.

Effect of Relative Reduction on Property of Steel-Mushy Cu-Graphite Composite

The rolling treatment of steel-mushy QTi3.5-3.5 graphite composite was conducted under different relative reduction at room temperature. The effect of room-temperature rolling on interfacial mechanical property of steel-mushy QTi3.5-3.5 graphite composite was studied and the relationship between interfacial shear strength and relative reduction was established. The results show that, for steel-mushy QTi3.5-3.5 graphite composite, which consists of 1.2 mm-thick 08AI steel plate and 2.8 mm-thick QTi3.5-3.5 graphite layer, there is a nonlinear relationship between interfacial shear strength and relative reduction in graphite layer. When relative reduction is smaller than 1.1%, interfacial shear strength increases with increasing the relative reduction. When relative reduction is larger than 1.1%, interfacial shear strength decreases with increasing the relative reduction. When relative reduction is 1.1%, the largest interfacial shear strength of 145.2 MPa can be obtained.     

进口空气相对湿度对直接蒸发冷却式空调机性能的影响

本文就进口空气的相对湿度对直接蒸发冷却式空调机性能的影响进行了分析,得出了在保证一定冷却效果的条件下冷却效率、填料厚度和出口空气相对湿度与进口空气相对湿度的关系曲线.     

移动环境下实时事务处理

1 引言实时数据库就是其中的事务和数据都可能有时间限制的数据库。近些年来,越来越多的研究人员对于移动实时数据库系统(Mobile Real-Time Database System:MRTDBS)中高效的事务处理方法进行了研究,一般认为移动实时数据库就是移动环境(如GSM网络和无线局域网)所支持的实时数据库系统。对于实时事务来说,其完成时间一般有相应的时间约束,满足事务截止时间约束往往比事务逻辑完全正确更重要,例如对于股票查询的延迟响应会导致失去很好的交易机会。为了满足事务的截止时间约束,人们提出了不同的事务调度技术和并发控制协议。     

赣州市五大产业生产方程与组合预测

依据数学和经济学的理论方法，利用赣州市的历史统计数据，对赣州市的农业、工业、建筑业、运输业、商业分别建立生产方程，进而开展组合预测。     

The Complete Solution of the Competitive Rank Selection Problem

Two decision-makers A and B observe sequentially a given permutation of n uniquely rankable options. A and B have one choice each (without recall) and both must make a choice. At each step only the relative ranks are known, and A has the priority of choice. At the end the (absolute) ranks are compared and the winner is the one who has chosen the better rank. Extending results by Enns and Ferenstein [6] and Berry et al. [1] this article gives, for both A and B , the optimal strategy and the corresponding winning probabilities. We show in particular that the limiting winning probabilities for A and B do exist, which closes a most important gap in the work of previous authors. This also provides an algorithm for numerically computing the limiting value of these probabilities. Although our proof is analytic in a strong sense, it is interesting to see that it would have been very hard to assemble it without the help of computer algebra. The reason is that the functions we have to investigate display subranges of indices which contrast considerably with respect to error terms when certain terms are replaced by approximations, and that computations were very helpful to locate those ranges where a particularly fine tuning of error estimates turned out to be indispensable. Received October 1997; revised March 15, 1998.     

Normal vector compression of 3D mesh model based on clustering and relative indexing

As the transmission of 3D shape models through Internet becomes more important, the compression issue of shape models gets more critical. While the compressions of topology and geometry have been explored significantly, the same issue for normal vectors has not yet been studied as much as it deserves.

Presented in this paper is an approach to compress the normal vectors of a 3D mesh model using the concept of clustering and relative indexing. The model is assumed to be manifold triangular mesh model with normal vectors associated with vertices. The proposed scheme clusters the normal vectors of given model and the representative normal vector of each cluster is referred to via a mixed use of relative as well as absolute indexing concepts. It turns out that the proposed approach achieves a significant compression ratio (less than 10% of the original VRML model files) without a serious sacrifice of the visual quality.     

相对增益矩阵方法在柔性交流输电系统多变量控制器交互影响分析中的应用

提出了一种分析FACTS多个控制回路之间交互影响的新方法：改进相对增益矩阵(Relative gain array，RGA)方法，使其可对合成控制系统不同控制过程之间的交互影响进行分析，以利于设计人员通过考察各输入对输出变量的影响程度，选取控制变量与被控量之间的最佳搭配。为了验证所提出方法的有效性，将其用于指导FACTS阻尼控制器的设计。数字仿真结果表明，利用该方法进行UPFC阻尼控制器附加回路的选取，能取得较满意的效果。     

Local collision avoidance of multiple robots using avoidability measure and relative distance

This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the velocity of the robots. To implement the concept to avoid collision among multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. These repulsive force and attractive force are added to form the driving force for robot motion. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, since the usual potential field method initiates avoidance motion later than the proposed method, it sometimes fails preventing collision or causes hasty motion to avoid other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.     

Iterative learning of model reference adaptive controller for uncertain nonlinear systems with only output measurement

In this paper, a model reference adaptive control strategy is used to design an iterative learning controller for a class of repeatable nonlinear systems with uncertain parameters, high relative degree, initial output resetting error, input disturbance and output noise. The class of nonlinear systems should satisfy some differential geometric conditions such that the plant can be transformed via a state transformation into an output feedback canonical form. A suitable error model is derived based on signals filtered from plant input and output. The learning controller compensates for the unknown parameters, uncertainties and nonlinearity via projection type adaptation laws which update control parameters along the iteration domain. It is shown that the internal signals remain bounded for all iterations. The output tracking error will converge to a profile which can be tuned by design parameters and the learning speed is improved if the learning gain is large.