• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.699-708
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• 2002

Since various terminals and different networks get involved in playing of a multimedia presentation, the case that the presentation QoS at a destination should be different from the QoS of multimedia data at a source occurs frequently. For playing the multimedia presentation, the multimedia data at a source should be transcoded into the multimedia data satisfying the QoS required at the terminal. The problem of generating the transcoding path is that, for a given multimedia presentation, different transcoding paths depending the terminal and networks should be generated. That is, a fixed transcoding path cannot be applied to a multimedia presentation. Instead, whenever the terminal and network to play the presentation get determined, a proper transcoding path should be regenerated automatically. In this paper, the algorithm for generating the transcoding path and the method for checking the playability of the generated path are proposed. The generating algorithm adopted the technique of Context Free Grammar in describing the set of transcoding resources and a user's transcoding rules in order to utilize the well-known compiler techniques. For the playability check, a method of computing the transcoding time and the delay time between data units are proposed. Finally all the proposed methods were implemented in the stream engine, called Transcore and the presentation-authoring tool, called VIP, we had developed. And the test results with a sample scenario were presented at the last.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.985-996
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• 2006

As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.