Zhu Huaji

Research on the Ontology-Based Complex Event Processing Engine of RFID Technology for Agricultural Products

In order to improve the discriminating capacity of the RFID tags for agricultural products traceability data, a new handling engine ORFID-CEP for complex events of agricultural products RFID Tag based on ontology, is proposed by introducing the event ontology model into the field of the agricultural products quality safety administration. In the new engine, the ontology model of RFID event, semantic space and the rules of the event ontology are defined. In the RFID practical application instances, the number of the fringe real-time events is so large that those methods used in current systems can not handle them in time. Thus, many significant events are lost. Aiming to overcome the problem, the transform system of work flow for the complex event ontology and the optimized strategies for event exploration, event operation and restrictive conditions of event appearance are established. Experimental results show that the new engine can mine more complex events with semantic information than the conventional Esper-CEP engine. Additionally, the new engine is steadier than the Esper-CEP engine. With increasing number of the events, the growth rate of the new engine for mining complex events raises more quickly than Esper-CEP, which indicates that the engine has the good ability of information process.

Modeling Incremental Information of Topographic Database Based on OEM

The distribution of the update information of topographic database is still one of the main open challenges for many data producers. The incremental method is transfer of a data set that is restricted to objects which have been changed since the last transfer. This paper focuses on the modeling and description of incremental information, which is the precondition of distribution. In order to accomplish this task, firstly we analyze the characteristics of incremental information of topographic database. By analysis, we find out that the incremental information is semi-structured by nature. In this respect, this paper investigates the use of SSD (semi-structured data) models--an innovative approach recently developed in Information Technology--for modeling incremental information. A framework for the representation of geographic entities in OEM (Object Exchange Model), a popular model for semi-structured data, is introduced. Additionally, it is shown how to map the OEM representation of incremental information to XML (eXtensible Markup Language) description. Using XML to describe incremental information can help users understand this kind of information and update their databases. A simplified case study in the application domain of the distribution of topographical data is examined closely.

Classification model of increment changes of geographical object based on multifold state difference

The analysis of geographical changes has been one of the important directions of the GIS research agenda over the past ten years. But an explicit representation of increment change which clearly describes the semantics of change and supports the database tracking of geographical changes are not completely considered within current researches. In order to clearly distinguish the increment change, we propose a new hiberarchy model which includes four arithmetic formulas. The arithmetic formulas are computed based on several states of the geographical objects, including the whole state of the geographical object in the real world, the whole state of the geographical object in the database, the spatial state of the geographical object, i.e. dimension, shape, position and size. By the values of the four arithmetic parameters in the model, all kinds of atomic increment changes affecting the single object and multi-object can be affirmed. Based on the atomic increment changes, the complex increment changes can be compounded which provides precondition for increment transfer of spatial data.