2010, Vol.15, No.5

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

pISSN : 1598-849X / eISSN : 2383-9945
https://journal.kci.go.kr/jksci

The success of semantic web depends largely on the semantic annotation which systematizes knowledge for the construction and production of ontology. Therefore, the efficiency of semantic annotation is very important in order to change many knowledge expressions and generate into ontology instances. In this paper, we presents a generation system of rule-based ontology instances which are produced accurately and efficiently via semantic annotation in conventional web sites. In conventional studies, the manual process is necessary for finding relevant information, comparing it with ontology, and entering information. We propose a new method that manages keyword data regarding extracted information and rule information separately. Thus, it is quite practical to extract information efficiently from various web documents by adding a small number of keywords and rules. The proposed method shows the possibility of ontology instance generation which reuses the rules and keywords from the various websites.

The Optimal results of Kalman Filtering on the Inverted Pendulum System requires an effective factor such as the noise covariance matrix Q, the measurement noise covariance matrix R and the initial error covariance matrix . We present a special case where the optimality of the filter is not destroyed and not sensitive to scaling of these covariance matrix because these factors are unknown or are known only approximately in the practical situation. Moreover, the error covariance matrices issued by this method predict errors in the state estimate consistent with the scaled covariance matrices and not the issued state estimates. Various results using the scalar gain are derived to described the relations among the three covariance matrices, Kalman Gain and the error covariance matrices. This paper is described as follows: Section III a brief overview of the Inverted Pendulum system. Section IV deals with the mathematical dynamic model of the system used for the computer simulation. Section V presents a various simulation results using the scalar gain.

With the advances in the information technology and mobile communications, we now face increasing demands for various services based on both of position tracking of moving objects and their efficient index scheme. Accordingly, the TPR*-tree, which were proposed for efficiently tracking moving objects and predicting their positions in the future time, has drawn much intention. As the TRP*-tree came from the R-tree that is suitable for indexing static objects, it does not support cheap update costs. Therefore, it seems to be very costly to index moving objects if there are frequent occurrences of node updates caused by continuously changing velocities and positions. If some moving objects with high velocities have node updates, in particular, then the TPR*-tree may suffer from many unnecessary updates in the wide range of tree regions. To avoid such a problem, we propose a method that can keep fast-moving objects in the child nodes of the root node, thereby saving node update costs in the TPR*-tree. To show our performance advantages and retaining TPR*-tree features, we performed some performance experiments using a simulation technique.