平板收缩流的对数构象模拟

本文采用对数构象方法,结合同位网格有限体积离散,对由Oldroyd-B本构模型描述的粘弹性流体流动的高We数问题(High Weissenberg Number Problem,HWNP)进行了研究,对等温不可压条件下的平面Poiseuille流和4:1平板收缩流进行了数值模拟.平面Poiseuille流在不同We数时的数值结果验证了对数构象方法在简单流动中的有效性.在4:1粘弹性收缩流的数值模拟中,对数构象方法和传统方法在低We数时流场中的流线、应力等的对比结果验证了对数构象方法在复杂流动中的有效性.高We数时的数值结果表明:对于Oldroyd-B模型,对数构象方法可提高求解时的稳定性,并可将临界We数由传统方法的2.5提高到5.0.

Topology-Based Data Dissemination Approaches for Large Scale Data Centric Networking Architecture

Massive information flows are gen- erated from interactive processing and visua- lizations. To efficiently support information transmission over the Interact, information cen- tric architecture has been recently proposed. In this paper, we consider an information centric architecture, called the data centric networking architecture to provide communication servi- ces to big data, where a service identifier is used to name the data objects. We propose dif- ferent approaches for the dissemination of data objects in a large-scale data centric network. In particular, we propose various approaches to link the data dissemination approach with the topology of the Internet. Further, we eva- luate the proposed approaches with respect to data delivery efficiency, round-trip time imp- rovement, and deployment cost. Based on the results obtained from this study, it can be sh- own that by disseminating data objects to small ISPs, the data delivery efficiency can be significantly improved within an acceptable deployment cost.

DATABASE STRUCTURE FOR THE INTEGRATION OF RS WITH GIS BASED ON SEMANTIC NETWORK

The integration of remote sensing (RS) with geographical information system (GIS) is a hotspot in geographical information science.A good database structure is important to the integration of RS with GIS,which should be beneficial to the complete integration of RS with GIS,able to deal with the disagreement between the resolution of remote sensing images and the precision of GIS data,and also helpful to the knowledge discovery and exploitation.In this paper,the database structure storing the spatial data based on semantic network is presented.This database structure has several advantages.Firstly,the spatial data is stored as raster data with space index,so the image processing can be done directly on the GIS data that is stored hierarchically according to the distinguishing precision.Secondly,the simple objects are aggregated into complex ones.Thirdly,because we use the indexing tree to depict the relationship of aggregation and the indexing pictures expressed by 2_D strings to describe the topology structure of the objects,the concepts of surrounding and region are expressed clearly and the semantic content of the landscape can be illustrated well.All the factors that affect the recognition of the objects are depicted in the factor space,which provides a uniform mathematical frame for the fusion of the semantic and non_semantic information.Lastly,the object node,knowledge node and the indexing node are integrated into one node.This feature enhances the ability of system in knowledge expressing,intelligent inference and association.The application shows that this database structure can benefit the interpretation of remote sensing image with the information of GIS.

An oversampling approach for mining program specifications

Automatic protocol mining is a promising approach for inferring accurate and complete API protocols. However, just as with any data-mining technique, this approach requires sufficient training data（object usage scenarios）. Existing approaches resolve the problem by analyzing more programs, which may cause significant runtime overhead. In this paper, we propose an inheritance-based oversampling approach for object usage scenarios（OUSs）. Our technique is based on the inheritance relationship in object-oriented programs. Given an object-oriented program p, generally, the OUSs that can be collected from a run of p are not more than the objects used during the run. With our technique, a maximum of n times more OUSs can be achieved, where n is the average number of super-classes of all general OUSs. To investigate the effect of our technique, we implement it in our previous prototype tool, ISpec Miner, and use the tool to mine protocols from several real-world programs. Experimental results show that our technique can collect 1.95 times more OUSs than general approaches. Additionally, accurate and complete API protocols are more likely to be achieved. Furthermore, our technique can mine API protocols for classes never even used in programs, which are valuable for validating software architectures, program documentation, and understanding. Although our technique will introduce some runtime overhead, it is trivial and acceptable.