• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.31 no.5
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• pp.1-11
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• 1999

Wood components, cellulose and lignin, are degraded simultaneously and the general outline for the complementary character of carbohydrates and lignin decomposition as well as the existence of enzymatic systems combining these processes is still valid. The degradatiion of free cellulose or hemicellulose into monosaccharides has long been known to be relatively simple, but the mechanism of lignin degradatiion wasn ot solved very clearly yet. Anyway the biodegradation of woold constituents is understood at present as an enzymatic process. Kigninolytic activity has been correlated with lignin and manganese peroxidases. At present the attention is paid to laccase. Laccase oxidizes lignin molecule to phenoxy radicals and quinones . This oxidation can lead to the cleavageo f C-C or C-O bonds in the lignin phenyl-propane subunits, resulting either in degradation of both side chains and aromatic rings, or in demethylation processes. The role of laccase lies in the "activation" of some low molecular weight mediators and radicals produced by fungal cultures. Such activated factors produced also in cooperation with other enzymes are probably exported to the wood environment where they work in degradation processes as the ' enzyme messengers." It is worth mentioning that only fungi possessing laccase show demethylating activity. Thus demethylation, the process important for ligninolysis, is probably caused exclusively by laccase. Under natural conditions laccase seems to work with other fungal enzymes , mediators and mediating radicals. It has shown the possibility of direct Bjrkman lignin depolymerization by cooperative activity of laccase and glucose oxidase.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.476-485
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• 2006

The Resource Description Framework(RDF), which emerged with the semantic web, is settling down as a standard for representing information about the resources in the World Wide Web Hence, a lot of research on storing and query processing RDF documents has been done and several RDF storage systems, such as Sesame and Jena, have been developed. But the research on updating RDF documents is still insufficient. When a RDF document is changed, data in the RDF triple store also needs to be updated. However, current RDF triple stores don't support incremental update. So updating can be peformed only by deleting the old version and then storing the new document. This updating method is very inefficient because RDF documents are steadily updated. Furthermore, it makes worse when several RDF documents are stored in the same database. In this paper, we propose an incremental update algorithm on RDF, documents in triple stores. We use a text matching technique for two versions of a RDF document and compensate for the text matching result to find the right target triples to be updated. We show that our approach efficiently update RDF documents through experiments with real-life RDF datasets.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.41-52
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• 2012

According to 2005 Korea National Health and Nutrition Survey, it has been reported that 32.9% men and 31.8% women have Metabolic syndrome among the population of age 30 and over. The importance of prevention and management is being emphasized in Metabolic syndrome which is a complex disease related to various generic and environmental factors like other chronical disease. In this study we suggest an service based on the data using the system architecture, ontology and Jena2.0 inference engine and organizing the disease-related guideline. The study also arrives at the result through proper interpretation and reasoning process using health management service model based on ontology. The accuracy according to the situation was tested and 930 data samples were selected and experimented. We drew a conclusion that the much personalized data is available, the more personalized services are possible. Since the risk factors of Metabolic syndrome are various, it would be effective to suggest customized services based on various personalized data.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.77-88
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• 2008

Having observed the restriction of the current Web technology, the semantic Web has been developed, and it now has grown up with the core help of the W3C to a level where it recommends the OWL Web ontology language. Besides, in order to deduce the information out of OWL data, several inference systems have been developed such as Jena, Jess, and JTP. Unfortunately, however, quite few systems can effectively handle recently developed OWL data, and further, due to the limitation of file-based operation, the current inference systems cannot meet the requirements for handing huge OWL data. An efficient method for storing and searching ontology data is essential for ensuring stable information inference processes. In this study, firstly, we proposed a model based on the database management system to transform and store OWL data and to enable deduction process from the database. Secondly, we designed and implemented an effective OWL storing system based on our model. Finally, we compare our system with the previous inference systems through experimental performance analysis.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.75-80
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• 2018

In this paper, we propose heterogeneous lifelog mining model in health big-data platform. It is an ontology-based mining model for collecting user's lifelog in real-time and providing healthcare services. The proposed method distributes heterogeneous lifelog data and processes it in real time in a cloud computing environment. The knowledge base is reconstructed by an upper ontology method suitable for the environment constructed based on the heterogeneous ontology. The restructured knowledge base generates inference rules using Jena 4.0 inference engines, and provides real-time healthcare services by rule-based inference methods. Lifelog mining constructs an analysis of hidden relationships and a predictive model for time-series bio-signal. This enables real-time healthcare services that realize preventive health services to detect changes in the users' bio-signal by exploring negative or positive correlations that are not included in the relationships or inference rules. The performance evaluation shows that the proposed heterogeneous lifelog mining model method is superior to other models with an accuracy of 0.734, a precision of 0.752.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.11-20
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• 2015

In this paper, we propose a context awareness system to transfer accurate information of the app store based on collective intelligence. By using collective intelligence the system minimizes the errors that could occur when an individual process the problems, recommends APIs for developers and builds the app store for not only customers but also developers. In addition, this system applies the ontology technique to aware the context of consumers, recommends the app suitable for the consumer and provides the information for app developers. By utilizing the deduction technique of the Jena, the context awareness system infers the context of a consumer and constructs the app store system which improves the existing app stores. In the point of service transfer and accuracy, the proposed app store system module show better performance than the existing app store.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

• Proceedings of the Membrane Society of Korea Conference
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• 2001.10a
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• pp.39-50
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• 2001

The performance of membranes is governed their pore struture. Pore structures of porous materials can be determined by a number of techniques. However, The novel technique, capillary folw porometry has a number of advantages. In this technique, the sample is brought in contact with a liquid that fills the pores in the membrane spontaneously. Gas under pressure is used to force the liquid from the pores and increase gas flow. Gas flow rate measured as a function of gas pressure in wet and dry samples yield data on the largest pore size, the mean flow pore size, flow distribution and permeability. Pore characteristics of a number of membranes were measured using this technique. This technique did not require the use of any toxic material and the pressure employed was low. Capillary flow porometry is a suitable technique for measurement of the pore structure of many membranes.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.559-561
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• 2004

최근 비즈니스 프로세스 통합에 관련된 다양한 연구를 통해, 수많은 비즈니스 프로세스 언어 및 표기법들이 개발되고 있다. 표준화되지 않은 다양한 비즈니스 프로세스 언어들은 비즈니스 프로세스를 자동화하려는 기업들뿐만 아니라, 비즈니스에 참여하는 일반 사용자에게도 혼동을 가져온다. 본 논문은 다양하고 표준화되지 않은 비즈니스 프로세스 언어들을 모두 디자인할 수 있기 위한 적응적인 모델을 제안한다. Jena와 JGraph와 같은 기존 모델의 장점들을 조합하고 단점을 보완하여 개발되었다. 본 논문에서 제안한 모델은 파이프-필터 아키텍쳐를 이용해 비즈니스 프로세스의 데이터를 단계적으로 추출한다. 그리고 추출된 데이터는 다양한 환경에 적응하기 위해, 해쉬 또는 링크드 리스트의 자료 구조에 저장되어 관리된다. 마지막으로, 저장된 데이터들은 사용자의 요구에 따라 실행언어로 변환되거나 다시 GUI에 보여 진다.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1197-1200
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• 2005

시맨틱 웹에서 지능형 검색은 잘 구축된 온톨로지의 추론에 의해 가능하다. 온톨로지는 간단히 표현하면 단어와 관계들로 구성된 사전으로서 어느 특정 도메인에 관련된 단어들을 계층적 구조로 표현한다. 이런 구조는 다양한 방법으로 표현이 가능하며 추론에 적합한 구조인 N-TRIPLE로의 변환을 위해 JENA API를 사용한다.