• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.689-698
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• 2011

In South Korea, Total Maximum Daily Load (TMDL) has been enforced since 2004 to restore and manage water quality in the watersheds. However, the appraisal of TMDL in South Korea has lots of weaknesses to establish the plan for recovery of water quality because it just evaluates the target water quality during the particular flow duration interval. In the United States, Load Duration Curve (LDC) method bas been widely used in the TMDL to evaluate the water quality and pollutant loads considering variation of stream flow. In a recent study, web-based Load Duration Curve system was developed to create the LDC automatically and provide the convenience of use. In this study, web-based Load Duration Curve system was applied in the Gapyeongcheon watershed using the daily flow and 8-day interval water quality data, and Q-L Rating Curve was used to evaluate the water quality and pollutant load in the watershed, also. As a result of study, water quality and pollutant load in Gapyeongcheon watershed were met with water quality standard and allocated load in the all flow durations. Web-based Load Duration Curve system could be applied to the appraisal of South Korean TMDL because it can be used to judge the impaired flow duration and build up the plan of load reduction, and it could enhance the publicity. But, web-based Load Duration Curve system should be enhanced through addition of load assessment tools such as Q-L rating curve to evaluate water quality and pollutant load objectively.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• 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.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.117-135
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• 2003

This study is to propose a procedure solving scale problem of traditional collaborative filtering (CF) approach. The CF approach generally uses some similarity measures like correlation coefficient. So, as the user of the Website increases, the complexity of computation increases exponentially. To solve the scale problem, this study suggests a clustering model-based approach using Self-Organizing Map (SOM) and RFM (Recency, Frequency, Momentary) method. SOM clusters users into some user groups. The preference score of each item in a group is computed using RFM method. The items are sorted and stored in their preference score order. If an active user logins in the system, SOM determines a user group according to the user's characteristics. And the system recommends items to the user using the stored information for the group. If the user evaluates the recommended items, the system determines whether it will be updated or not. Experimental results applied to MovieLens dataset show that the proposed method outperforms than the traditional CF method comparatively in the recommendation performance and the computation complexity.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.27-30
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• 2006

GIS 분야에서 데이터 교환의 표준으로 OGC(Open Geospatial Consortium)에서 GML(Geography Markup Language)이 제안되어 웹 어플리케이션이나 공간 데이터 교환에서 사용이 일반화 되어가고 있다. 또한, 공간 데이터를 효과적으로 수집하여 의사결정을 지원하기 위한 시스템인 공간 데이터 웨어하우스에서도 GML 데이터를 추출하여 소스 데이터로 활용하는 것이 요구되고 있다. 하지만 GML 은 반구조형식(semi-structured)의 데이터 형식을 가진다. 따라서 기존 구조적인 데이터와는 추출하는 방식이 다르므로 GML 의 특징에 맞는 공간 데이터 추출이 수행되어야 한다. 본 논문에서는 공간 데이터 웨어하우스에서 GML 기반의 공간 데이터 소스를 추출할 때, 중복되는 공간 객체를 하나의 표현으로 통합하여 효율적으로 적재하는 기법을 제안한다. 이는 GQuery를 이용하여 GML 데이터를 추출한 후, GML 스키마를 메타데이터에서 관리하는 스키마 정보와 비교하여 공간 데이터 웨어하우스에 통합된 공간 데이터를 제공하는 기법이다. 성능평가에서는 기존의 GML 데이터를 추출하는 기법과 제안기법과의 비교를 통하여 제안 기법의 기존 기법에 비해 평균적으로 약 9.95%의 성능향상을 보였다.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.231-236
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• 2013

Recently, to improve the user response times of Android applications, several studies have been proposed to combine the idea of Ahead-of-Time compilation into Dalvik virtual machine, which uses Just-in-Time compilation. The studies, however, require modifications of the Dalvik executables of target applications, thus are difficult to be adopted for legacy applications already deployed. This paper proposes a JITwP(JIT with Precompile) technique that precompiles hot traces at application launch time with no modification of the Dalvik executable. It improves the user response times of target applications by providing precompile hints prepared offline. Our experimental results demonstrate a 4% improvement in terms of execution time for the Web browser application.

• Journal of Biosystems Engineering
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• v.29 no.2
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• pp.159-166
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• 2004

In this study, we have developed a web-based management system for greenhouse teleoperation. The remote control system consisted of a database, a web-server, a controller in greenhouse, and clients. The database in the server stored user's information and greenhouse conditions was used to manage user's login and conditioning data. The management system developed by using Java applet, which was a client program for effective and easy management of greenhouse, monitored the greenhouse in real time. Master and driver boards were installed in the greenhouse control unit. Database on flowering to collect and analyze data exchanged data with the server. The master board could be managed effectively by timer routine, repeat control within setting time, and algorithm of setting points. Also, the greenhouse conditions could be controlled by manual or remote controller(PC) through a web browser in internet. Furthermore, all of the control devices of the greenhouse were managed by remote control of using PC and checked via camera installed in greenhouse. Finally, we showed the experimental results of the system which was installed in Pusan Horticultural Experiment Station.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.59-73
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• 2005

Caching query results and reusing them in processing of subsequent queries is an important query optimization technique. Materialized view and view indexing are the representative examples of such a technique. The two schemes had received much attention for relational databases, and have been investigated for XML data since XML emerged as the standard for data exchange on the Web. In XML view indexing, XML view xv which is the result of an XML query is represented as an XML view index(XVI), a structure containing the identifiers of xv's underlying XML elements as well as the information on xv. Since XVI for xv stores just the identifiers of the XML elements not the elements themselves, when xv is requested, its XVI should be materialized against xv's underlying XML documents. In this paper, we address the problem of integrating an XML view index management system with an RDBMS based XML storage system. The proposed system was implemented in Java on Windows 2000 Server with each of two different commercial RDBMSs, and used in evaluating performance improvement through XML view indexing as well as its overheads. The experimental results revealed that XML view indexing was very effective with an RDBMS based XML storage system while its overhead was negligible.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.600-608
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• 2017

Recently data growth rates are growing exponentially according to the rapid expansion of internet. Since users need some of all the information, they carry a heavy workload for examination and discovery of the necessary contents. Therefore information retrieval must provide hierarchical class information and the priority of examination through the evaluation of similarity on query and documents. In this paper we propose an Multi-class support vector machines model based clustering for hierarchical document categorization that make semantic search possible considering the word co-occurrence measures. A combination of hierarchical document categorization and SVM classifier gives high performance for analytical classification of web documents that increase exponentially according to extension of document hierarchy. More information retrieval systems are expected to use our proposed model in their developments and can perform a accurate and rapid information retrieval service.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.1-11
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• 2022

With the development of deep learning technology, various research and development are underway to estimate preference rankings through learning, and it is used in various fields such as web search, gene classification, recommendation system, and image search. Approximation algorithms are used to estimate deep learning-based preference ranking, which builds more than k comparison sets on all comparison targets to ensure proper accuracy, and how to build comparison sets affects learning. In this paper, we propose a k-disjoint comparison set generation algorithm and a k-chain comparison set generation algorithm, a novel algorithm for generating paired comparison sets for crowd-sourcing-based deep learning affinity measurements. In particular, the experiment confirmed that the k-chaining algorithm, like the conventional circular generation algorithm, also has a random nature that can support stable preference evaluation while ensuring connectivity between data.