• 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 Satellite, Information and Communications
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• v.10 no.1
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• pp.17-21
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• 2015

In this paper, we introduce satellite communication for new wireless disaster network to be built on the basis of amateur radio HR (HAM Radio) as a wireless package system, and channel environments of a D2D terminal that tries to connect and communicate with the wireless disaster network. In this disaster network, we propose a LOS component ratio based adaptive channel modeling approach to accurately estimate a variety of channels whose the D2D terminal could have and smoothly transfer to the level of multimedia data based on the Okumura-Hata channel model. As a result of computer simulation, performance of the proposed method was compared with the that of Okumura-Hata model of open area and urban area model and we were confirmed that there is a gain of BER performance from the results of the computer simulation.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.103-114
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• 2006

Now distribution centers include an ASRS (Automated Storage and Retrieving System) and automated transfer systems such as conveyors and AGV (Automated Guided Vehicle). These automated distribution centers have lots of parameters to be considered fur operating performance. The general basic parameters in the distribution centers are specifications of storage equipment, system operating rules, configuration of storage area and unit load features. In this paper, an approach using simulation and metamodeling with response Surface method to optimize the design parameters of an automated distribution center model is presented. The simulation based metamodel will constitute an efficient approximation of the system function, and the approximate function will be used to design rapid optimal parameters of the distribution center model. This paper provides a comprehensive framework for economical material flow system design using the simulation and metamodeling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.179-187
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• 2015

Spread of smartphone creates various contents. Among many contents, AR application using Location Based Service(LBS) is needed widely. In this paper, we propose error correction algorithm for location-based Augmented Reality(AR) system using computer vision technology in android environment. This method that detects the early features with SURF(Speeded Up Robust Features) algorithm to minimize the mismatch and to reduce the operations, and tracks the detected, and applies it in mobile environment. We use the GPS data to retrieve the location information, and use the gyro sensor and G-sensor to get the pose estimation and direction information. However, the cumulative errors of location information cause the mismatch that and an object is not fixed, and we can not accept it the complete AR technology. Because AR needs many operations, implementation in mobile environment has many difficulties. The proposed approach minimizes the performance degradation in mobile environments, and are relatively simple to implement, and a variety of existing systems can be useful in a mobile environment.

• Korean Chemical Engineering Research
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• v.48 no.4
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• pp.483-489
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• 2010

An image analysis-based soft sensor is designed and applied to automatic quality classification of product appearance with color-textural characteristics. In this work, multiresolutional multivariate image analysis (MR-MIA) is used in order to analyze product images with color as well as texture. Fisher's discriminant analysis (FDA) is also used as a supervised learning method for automatic classification. The use of FDA, one of latent variable methods, enables us not only to classify products appearance into distinct classes, but also to numerically and consistently estimate product appearance with continuous variations and to analyze characteristics of appearance. This approach is successfully applied to automatic quality classification of intermediate and final products in industrial manufacturing of engineered stone countertops.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.296-303
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• 2014

In this paper, we propose an algorithm to visualize radio wave environment based on the measured Received Signal Strength Indication( RSSI) and 3D geographic information. We estimate the source position using the circumcenter of the triangle and visualize the radio wave environment using the empirical propagation models. A mode seeking algorithm(mean-shift clustering) is used to seek the peak points and the center of gravity is utilized to reduce the estimation errors. Our approach finds its applications in the radio wave monitoring systems for the efficient utilization of radio resources.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.5 no.1
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• pp.85-105
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• 1981

Information is an essential factor leading the rapid progress which is one of the distinguished characteristics in modem society. As more information is required and as more is supplied by individuals, governmental units, businesses, and educational institutions, the greater will be the requirement for efficient methods of communication. One possibility for improving the information dissemination process is to use computers. The capabilities of such machine are beginning to be used in the process of Information storage, retrieval and dissemination. An important problems, that must be carefully examined is whether one technique for information retrieval is better for worse than another. This paper examines problem of how to evaluate an information retrieval system. One specific approach is a cost accounting model for use in studying how to minimize the cost of operating a mechanized retrieval system. Through the use of cost analysis, the model provides a method for comparative evaluation between systems. The general cost accounting model of the literature retrieval system being designed by this study are given below. 1. The total cost accounting model of the literature retrieval system. The total cost of the literature retrieval system = (the cost per unit of user time X the amount of user time) + ( the cost per unit of system time X the amount of system time) 2. System cost accounting model system cost = (the pre-search system cost per unit of time X time) + (the search system cost per unit of time X time) + (the post search system cost per unit of time X time) 1) Pre-search system cost per unit of time = cost of channel per unit time + cost of central processing unit per unit time + cost of storage per unit time 2) Search system cost per unit of time = comparison cost + document representation cost. 3) Post-search system cost per unit of time. = cost of channel per unit time + cost of central processing unit per unit time + cost of storage per unit time 3. User cost accounting model Total user cost = [pre-search user cost per unit of time X (time + additional time) ] + [search user cost per unit of time X (time + additional time) ] + [post-search user cost per unit of time X (time + additional time) ].

• Smart Structures and Systems
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• v.14 no.4
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• pp.595-615
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• 2014

This study aims to investigate the relationship between structural damage and sensitivity indices using the Hilbert-Huang transform (HHT) method. Two damage detection indices are proposed: the ratio of bandwidth (RB), and the ratio of effective stiffness (RES). The nonlinear four bays multiple degree of freedom models with various predominant frequencies are constructed using the SAP2000 program. Adjusted PGA earthquake data (Japan 311, Chi-Chi 921) are used as the excitations. Next the damage detection indices obtained using the HHT and the fast Fourier transform (FFT) methods are evaluated based on the acceleration responses of the structures to earthquakes. Simulation results indicate that, the column of the 1 st floor is the first yielding position and the RB value is changed when the RES<90% in all cases. Moreover, the RB value of the 1 st floor changes more sensitive than those from the top floor. In addition, when the structural response is nonlinear (i.e., RES<100%), the RB and the RES curves indicate the incremental change in the HHT spectra. However, the same phenomenon can be found from FFT spectra only when the stiffness reduction is large enough. Therefore, the RB estimated from the smoothed HHT spectra is an effective and sensitive index for detecting structural damage.