• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.619-624
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• 2004

The quantity of business information like to be shared enterprise information and business catalog quickly increased because of activating e-commerce. Necessary of metadata management which is using RDF was required. RDF metadata management does not have to be restricted by RDF/RDFS knowledges, has to describe web resources and has to support metadata validation. But research which supports this is not enough. In this paper we enable to create and manage RDF/RDFS document using various interfaces, change from metadata to N-Triple and verify metadata validation.

• Journal of Environmental Science International
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• v.24 no.2
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• pp.237-244
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• 2015

This objectives of research are to figure out combustion characteristics with increasing temperature with petrochemical sludge by adding wasted organic matters which are waste electric wire, anthracite coal and sawdust, and to exam heating value and ignition temperature for using refused derived fuels(RDFs). After analyzing TGA/DTG, petrochemical sludge shows a rapid weight reduction by vaporing of inner moisture after $170^{\circ}C$. Gross weight reduction rate, ignition temperature and combustion rates represent 68.6%, $221.9^{\circ}C$ and 54.1%, respectively. In order to assess the validity of the RDFs, the petrochemical sludge by adding wasted organic matters which are waste electric wire, anthracite coal and waste sawdust. The materials are mixed with 7:3(petrochemical sludge : organic matters)(wt%), and it analyzes after below 10% of moisture content. The ignition temperatures and combustion rates of the waste electric wire, anthracite coal and waste sawdust are $410.6^{\circ}C$, $596.1^{\circ}C$ and $284.1^{\circ}C$, and 85.6%, 30.7% and 88.8% respectively. In heating values, petrochemical sludge is 3,600 kcal/kg. And the heating values of mixed sludge (adding 30% of the waste electric wire, anthracite coal and waste sawdust) each increase up to 4,600 kcal/kg, 4,100 kcal/kg and 4,300 kcal/kg. It improves the ignition temperatures and combustion rates by mixing petrochemical sludge and organic matters. It is considered that the production of RDFs is sufficiently possible by using of petrochemical sludge by mixing wasted organic matters.

• Journal of KIISE
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• v.43 no.9
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• pp.963-973
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• 2016

Providing a semantic knowledge system using media ontologies requires not only conventional axiom reasoning but also knowledge extension based on various types of reasoning. In particular, spatio-temporal information can be used in a variety of artificial intelligence applications and the importance of spatio-temporal reasoning and expression is continuously increasing. In this paper, we append the LOD data related to the public address system to large-scale media ontologies in order to utilize spatial inference in reasoning. We propose an RDFS/Spatial inference system by utilizing distributed memory-based framework for reasoning about large-scale ontologies annotated with spatial information. In addition, we describe a distributed spatio-temporal SPARQL parallel query processing method designed for large scale ontology data annotated with spatio-temporal information. In order to evaluate the performance of our system, we conducted experiments using LUBM and BSBM data sets for ontology reasoning and query processing benchmark.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.383-389
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• 2005

The purpose of this paper is to develop the metadata on the information of research result in Science and technology and to design the domain knowledge structure using semantic web technology for further implementation. In this paper, we first analyze the existing theories and techniques related to the metadata in such fields as R&D research result, international standard, and semantic web. Then, we extract and group the relevant factors from Dublin Core, CERIF, and the research results for building the integrated metadata framework. Based on our proposed metadata, we design a domain knowledge structure which employs RDF/RDFS as knowledge representation tool. Therefore, we can implement the ontology which produce the 'intelligent' information service and improve the interoperability between the research institutions. Also, the metadata can be used as the basis for developing National R&D Performance Information, and in terms of research institutions, can be used as tools for managing the their own research results information systematically and consistently.

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1865-1868
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• 2016

Background: The number of patients with oral cancer in India is increasing gradually (especially in younger people). Although the diagnostic modalities and therapeutic management of oral cancer are improving, the treatment outcome and prognosis of oral cancer remain poor. The absence of definite early warning symptoms for most head and neck cancers suggests that sensitive and specific biomarkers are likely to be important in screening for high-risk patients. Aims: To analyze serum adenosine deaminase (ADA) levels in oral squamous cell carcinoma (OSCC) cases who reported to our institute. Materials and Methods: A prospective study was performed on 100 histopathologically proven cases of OSCC (study group) and 100 normal healthy individuals (control group). Independent sample and one sample t-tests and one way ANOVA followed by Tuckey's POST HOC test were conducted for analysis. Results: Statistically significant increase in serum ADA levels was observed in OSCC cases compared to the control group. Also serum ADA level increased significantly with the histopathological grade. Conclusions: Serum ADA levels in OSCC may be a useful diagnostic and prognostic biomarkers in clinical practice and our findings suggest that a large-scale study is warranted to confirm clinical utility as a prognostic and diagnostic biomarker.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.226-241
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• 2014

LOD(Linked Open Data) is composed of RDF triples which are based on ontologies. They are identified, linked, and accessed under the principles of linked data. Publications of LOD data sets lead to the extension of LOD cloud and ultimately progress to the web of data. However, if ontologically the same things in different LOD data sets are identified by different URIs, it is difficult to figure out their sameness and to provide trustworthy links among them. To solve this problem, we suggest a Trustworthiness Improving Link Evaluation, TILE for short, technique. TILE evaluates links in 4 steps. Step 1 is to consider the inference property of syntactic elements in LOD data set and then generate RDF triples which have existed implicitly. In Step 2, TILE appoints predicates, compares their objects in triples, and then evaluates links between the subjects in the triples. In Step 3, TILE evaluates the predicates' syntactic property at the standpoints of subject description and vocabulary definition and compensates the evaluation results of Step 2. The syntactic elements considered by TILE contain RDFS, OWL, OWL2 which are recommended by W3C. Finally, TILE makes the publisher of LOD data set review the evaluation results and then decide whether to re-evaluate or finalize the links. This leads the publishers' responsibility to be reflected in the trustworthiness of links among the data published.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.3
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• pp.165-186
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• 2020

Although BIBFRAME is recognized as a new bibliographic standard that can replace the existing MARC structure, the vastness of the descriptive items shows many limitations to be applied in library communities. Thus this study proposed separating the descriptive levels of BIBFRAME as a way to enhance the applicability of BIBFRAME. The descriptive level of BIBFRAME was divided into three stages: core, standard, and detailed levels based on the bibliographic area of ISBD 2011. This separation was semantically implemented using RDF/RDFS syntax. The levels of description in BIBFRAME was defined as Class Granularity and Class Element, and the Property Relation was defined for the linkage between the Classes defined and the BIBFRAME. By applying this syntactic structure, the relationships between the BIBFRAME descriptive items separated by each descriptive level could be linked with each other. This approach is expected to ensure applicability in the creation and sharing of bibliographic data using BIBFRAME.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.1
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• pp.27-38
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• 2009

To investigate the feasibility of refuse derived fuels (RDFs) combined of sewage sludge and combustible wastes such as substitutive fuels instead of a stone coal, several different RDFs made with different mixtures of sewage sludge and combustible wastes were analyzed by various experiments. The combustion characteristics for the RDFs were investigated by analyzing fuel gases, and heating values were also measured by a bomb calorimeter. The fundamental properties such as moisture contents, ratios of combustible materials, amounts of ashes, heavy metals, ratios of each chemical elements and heating values were analyzed in accordance with mixing ratios of wt(%) for researching the characteristics of the RDFs. $RDF_{k-1}$ was made of mixing materials which were dried sewage sludge, food wastes and combustible wastes. $RDF_{k-2}$ was made of mixing materials which were peat-moss, tar and sewage sludge. Combustion experiments were carried out at the optimal conditions which were m=2 under air-fuel condition and $850^{\circ}C$. The retention times in the combustor were set at 5, 10 and 15minutes. 50 g of RDFs was put in the combustor for each experiments. The ranges for heating values of $RDF_{k-1}$ with different mixing ratios were from 6,900 kcal/kg to 8120 kcal/kg. The ranges for heating values of $RDF_{k-2}$ with different mixing ratios were from 4,014 kcal/kg to 8,050 kcal/kg. As a result of this study, the heating values, moisture contents, components of chemical elements and mixing ratios of the materials in RDFs had big effects on the efficiency of the combustion. In $RDF_{k-1}$, the higher amounts of combustible wastes in the mixtures, the higher heating values, concentrations of $C_xH_y$ and amounts of ashes were produced. In $RDF_{k-2}$, the higher tar amounts in the mixtures caused the higher heating values, amounts of ashes, concentrations of CO gas and CxHy.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.19-30
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• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.