• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.85-102
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• 2003

Nowadays an information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to make the conversion rule which changes the hierarchical architecture to 2-dimensional information. Accordingly the modeling methodology for storing each structured information in relational database is needed. In this paper, we introduce a XML modeling methodology to design W3C XML schema using UML and we propose a unified design methodology for relational database schema to store XML data efficiently in relational databases. In the second place, in order to verify objectivity of a unified design methodology. By the way of Ronald Bourret, First we introduce the method of the transformation from XML schema to object model and second we translate object model into relational database schema. Therefore we show the mutual consistency between those consequence, and so can verify a unified design methodology.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1098_1099
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• 2009

In this paper, we present the estimation of wind turbine power generation using Cascade Architectures of Fuzzy Neural Networks(CAFNN). The proposed model uses the wind speed average, the standard deviation and the past output power as input data. The CAFNN identification process uses a 10-min average wind speed with its standard deviation. The method for rule-based fuzzy modeling uses Gaussian membership function. It has three fuzzy variables with three modifiable parameters. The CAFNN's configuration has three Logic Processors(LP) that are constructed cascade architecture and an effective optimization method uses two-level genetic algorithm. First, The CAFNN is trained with one-day average input variables. Once the CAFNN has been trained, test data are used without any update. The main advantage of using CAFNN is having simple structure of system with many input variables. Therefore, The proposed CAFNN technique is useful to predict the wind turbine(WT) power effectively and hence that information will be helpful to decide the control strategy for the WT system operation and application.

• Architectural research
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• v.20 no.2
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• pp.53-64
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• 2018

A nonlinear analytical model has been proposed for two-span two-story reinforced concrete frames with relaxed section details. The analytical model is composed of beam, column, and beam-column joint elements. The goal of this study is to develop a simple and light nonlinear model for two-dimensional reinforced concrete frames since research in earthquake engineering is usually involved in a large number of nonlinear dynamic analyses. Therefore, all the nonlinear behaviors are modeled to be concentrated on flexural plastic hinges at the end of beams and columns, and the center of beam-column joints. The envelope curve and hysteretic rule of the nonlinear model for each element are determined based on experimental results, not theoretical approach. The simple and light proposed model can simulate the experimental results well enough for nonlinear analyses in earthquake engineering. Consequently, the proposed model will make it easy to developing a nonlinear model of the entire frame and help to save time to operate nonlinear analyses.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.508-519
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• 2018

In order to design the hull form of an underwater vehicle in the conceptual design phase, the dynamic characteristics depending on the hull form parameters should be identified. Course-keeping stability, turning ability, yaw-checking ability, and mission competence are set to be the indices of the dynamic characteristics, and the geometric parameters for the bare hull and rudder are set to be the hull form design parameters. The total sensitivity of the dynamic characteristics with respect to the hull form parameters is calculated by the chain rule of the partial sensitivity of the dynamic characteristics with respect to the hydrodynamic coefficients, and the partial sensitivity of the hydrodynamic coefficients with respect to the hull form parameters. Based on the sensitivity analysis, important hull form parameters are selected, and those optimal values to satisfy the required intercept time of mission competence of a specific underwater vehicle and turning rate are estimated.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.1
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• pp.95-104
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• 2011

As sea state harsher in the ocean space, more large motion and wave loads occurs on ships hull by non-linear phenomena. To consider nonlinear effect on ships hull in the structural design verification, the direct calculation method with numerical approach is used rather than rule values for the reliable accuracy. In this paper, the non-linear wave loads analysis in time domain is performed by using a Rankine Panel Method together with numerical schemes. Linear calculations have been carried out based on DNV CSA-2 notation to generate the motion responses and wave loads of large ships. By short and long term analysis, the design wave amplitudes are selected for the nonlinear analysis. The maximum wave induced bending moment in hogging and sagging conditions are calculated in the nonlinear analysis. Also, the green water effect on the wave induced vertical bending moment was investigated. The results show the vertical bending moments are more influenced by green water in sagging condition than in hogging condition due to green water loading.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.25-29
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• 2002

There is an increasing interest in high-speed signal processing in modern telecommunication and SC circuit, HDTV, ISDN. There are many methods of high-speed signal processing. This paper describes a design approach for the realization of high-frequency Op-amp in CMOS technology. A limiting factor in Op-amp based analog integrated circuits is the limited useful frequency range. this thesis will develop a CMOS op-amp architecture with improved gainband width product with this technique an op-amp will achieve up to 170MHz (CL=2pF) unity-gain frequency with a 1.2-micron design rule. This CMOS op-amp is particularly suitable for achieving wide and stable closed-loop band widths, such as required in high-frequency SC filters, high-speed analog circuits.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.9
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• pp.904-917
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• 2010

Much research on ontology has been done during the last decade in order to represent knowledge and connect data semantically in AI and Semantic Web areas. However, ontologies might be represented and defined in different ways depending on knowledge and intention of users. It causes heterogeneity problem that the same concept can be differently expressed. This paper introduces a XOB (XMDR-based Ontology Builder) system based on XMDR to resolve the problem. XOB creates ontologies by reusing classes and relations defined in XMDR. XOB therefore is able to either solve or minimize the heterogeneity problem among ontologies. This paper introduces the conceptual model and overall architecture of the proposed system XOB. This paper defines the process, algorithm, ontology generation rule that is required to create ontologies by using concepts registered in XMDR. Our proposal supports higher standardization than the previous approaches, and it provides many advantages such as consistent concept usage, easy semantic exchange, and so on. Therefore, XOB enables high-quality ontology creation and reduces cost for ontology integration and system development.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.147-156
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• 2010

There are some of the studies on sensor middleware. However the standard middleware has not yet been defined. Especially, this paper focuses on the processing an intelligent service of the main functions of middleware. Several applications in the sensor network environment support not only monitoring services, but also sensor-based context-awareness and intelligent services based on sensors. However, the previous studies about USN middleware only mentioned the need for intelligent service and did not discuss the architecture and method for supporting the intelligent service in detail. Therefore this paper designs a USN middleware for providing intelligent services and proposes the method for processing the services. For this purpose, this paper proposes the Sensor-Service ontology to define the concept of services and sensors for USN applications and the relationship between them. The Sensor-Service ontology is used to infer high-level information from low-level information. To apply a variety of environmental context to intelligent services, the paper uses the rule-based reasoning. This paper implements the proposed intelligent service middleware as a prototype and then shows that the middleware can be used for a variety of USN applications through the performance evaluation.