加速器机头散射对三维水箱数据采集的影响

将三维水箱中央控制单元在数据采集时分别放置于离加速器小机头1 m、4 m处,在保证其余条件和采集流程不变的情况下先后采集两套数据,比较两套数据的差异。使用Oncentr。计划系统分别基于以上两套数据进行建模,比较开野和临床病例剂量计算结果的差异。实验结果表明:百分深度剂量和射野离轴比野外剂量偏高,小野输出因子偏大,大野输出因子偏小。用受加速器机头散射影响较大的数据建模后,方野和病人剂量计算结果均较正常数据明显偏高。

Modeling the Appraisal of Cloud Systems＇ Implementation

Intensity of competition, especially global competition, has driven many organizations to search for innovative ways to improve productivity and performance. This trend has led many firms to adopt approaches to implement cloud systems. Cloud systems have distinct characteristics that differentiate it from traditional internet services, due to a number of significant innovation factors. For example, firms need improved access to high-speed intemet as well as access to customer relationship management （CRM） and enterprise resource planning （ERP） capacities. This means that the interest of many firms in the implementation of cloud systems has increased. Although cloud systems are designed to facilitate knowledge transfer, currently, there is no method to ensure that knowledge transfer is useful or relevant to a firm. This in turn means that finns need to ensure that the cloud system has the capabilities to screen knowledge for compliance against some known knowledge characteristics. The use of cloud systems could result in an efficient delivery of innovation knowledge in an effective way. This paper presents an approach for assessment of the successful implementation of cloud systems. This paper also discusses the various success factors of cloud systems for global innovation.

Model Reference Adaptive Control for Networked Distributed Systems with Strong Interconnections and Communication Delays

In recent years, networked distributed control systems（NDCS） have received research attention. Two of the main challenges that such systems face are possible delays in the communication network and the effect of strong interconnections between agents. This paper considers an NDCS that has delays in the communication network, as well as strong interconnections between its agents. The control objective is to make each agent track efficiently a reference model by attenuating the effect of strong interconnections via feedback based on the delayed information. First, the authors assume that each agent knows its own dynamics, as well as the interconnection parameters, but receives information about the states of its neighbors with some communication delay. The authors propose a distributed control scheme and prove that if the interconnections can be weakened and if the communication delays are small enough, then the proposed scheme guarantees that the tracking error of each agent is bounded with a bound that depends on the size of the weakened interconnections and delays, and reduces to zero as these uncertainties reduce to zero. The authors then consider a more realistic situation where the interconnections between agents are unknown despite the cooperation and sharing of state information. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense with respect to the size of the weakened interconnections and delays, provided the weakened interconnections and time delays are small enough. The authors then consider the case that each agent knows neither its dynamics nor the interconnection matrices. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense provided the weakened interconnections and time delays are small enough. Finally, the authors present an illustrative example to present the applicability and effectiveness of the proposed schemes.