• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.263-265
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• 2003

The computation cost of image registration is affected by searching data size and space. This paper proposes an efficient image registration algorithm that uses multi-resolution wavelet decomposed image to reduce the data size search. The algorithm determines the correlation detection at low resolution on low-pass sub bands of wavelet and generate mask for higher resolution as part of a coarse to fine registration algorithm. The correlation matching is defined for coarse resolution similarity measurement, while mutual information (MI) is used at fine resolution. The results show that the new efficient mask-based algorithm improves computational efficiency and yields robust and consistent image registration results.

• Toxicological Research
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• v.25 no.1
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• pp.1-8
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• 2009

Validation specifies and coordinates all relevant activities to ensure compliance with good laboratory practices (GLP) according to suitable international standards. This includes validation activities of past, present and future for the best possible actions to ensure the integrity of non-clinical laboratory data. Recently, validation has become increasingly important, not only in good manufacturing practice (GMP) institutions but also in GLP facilities. In accordance with the guideline for GLP regulations, all equipments used to generate, measure, or assess data should undergo validation to ensure that this equipment is of appropriate design and capacity and that it will consistently function as intended. Therefore, the implantation of validation processes is considered to be an essential step in a global institution. This review describes the procedures and documentations required for validation of GLP. It introduces basic elements such as the validation master plan, risk assessment, gap analysis, design qualification, installation qualification, operational qualification, performance qualification, calibration, traceability, and revalidation.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.42-49
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• 2006

XML used rapid method of meta language representation in internet for information transmission. In addition to XML Schema used frequency specification to variety data type. This thesis designed to Simple Type meta model of XML schema using UML. But because structure of XML schema complicate and suppose variety data type we can recognize many difficult matter to user's apprehension and application of model properties that appeared UML. To way out of this matter this study could specified clearly to structured expression in XML schema meta model that is applied OCL specification and together, come up with method of detailed design to parse tree and token generation for lexical and symmentics analysis in compile step on this study foundation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.439-443
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• 2007

Nowadays, activity recognition becomes a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from labeled activity samples. Most of the existing work uses only one learning method for activity learning and is focused on how to effectively utilize the labeled samples by refining the learning method. However, not much attention has been paid to the use of multiple classifiers for boosting the learning performance. In this paper, we use two methods to generate multiple classifiers. In the first method, the basic learning algorithms for each classifier are the same, while the training data is different (ASTD). In the second method, the basic learning algorithms for each classifier are different, while the training data is the same (ADTS). Experimental results indicate that ADTS can effectively improve activity recognition performance, while ASTD cannot achieve any improvement of the performance. We believe that the classifiers in ADTS are more diverse than those in ASTD.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.367-374
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• 1999

This paper suggests an integrated method based on concept ascension and attribute reduction for efficient induction of decision rules from a large database. We study an automatic scheme to generate concept trees by a clustering technique, a method for generalizing databases by the concept ascension technique, an optimal reduction method by means of attributes reduction using the sibmificance of attributes, and an efficient way of reduction of attribute values applying the discernible matrix and functions. The method can be used for the decision making tasks such as an investment planning or price evaluation, the construction of knowledge bases for diagnosis of defects or medical diagnosis, data analysis such as marketing or experimental data, information retrieval for high level inquiries, and so on.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.483-491
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• 2005

SAR signal processing technique has been considered a crucial technical part in order to generate an image from radar signal data and ADD (Agency for Defense Development) has focused on this area for years to develope our own SAR Processor for various SAR systems (Radarsat, ERS, KOMSAR). In this paper, we investigated major techniques related to generation of SAR images and developed ASPR (ADD SAR Processor for Radarsat) practically using the commercial Radarsat-1 radar signal data (RAW). We demonstrated the performance of the ASPR in comparison with the image generated by MDA and Vexcel's SAR Processor (FOCUS).

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.1-11
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• 1994

The development of "Ship structural CAD system" has been performed in CSDP(Computerized Ship Design and Production) project to support ship structural design works. The procedures and contents of current design practice concerning the ship structural design were analyzed. To generate design information required at each design stage using the ship structural CAD system, the computerized model was created. To represent and implement the model information, a data structure which represents design concept as well as shape information was proposed using the concept of the product model. To embody the computerized model the object-oriented techniques were established to represent requirements of real world.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.182-185
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• 2012

In this paper, For 4th generation wireless communication systems, we propose a method to predict FH patterns in FH-OFDMA systems. OFDM is recognized as a promising modulation technique. Multi-user allocation in OFDM system can use FH that provides the spectrum-spread techniques. If one can generate more predictable FH sequences, then performance of the system can be easily improved. Current random FH and simple adaptive FH methods, however, are not considering predicting FH sequences. In this paper we show that the sampling of the wireless faded signal is not realized as a certain probability nature. With this regard, the proposed predictive FH allocation method is designed to embed the unknown probability models. Simulation study shows that the predictive FH method is more accurately predict FH sequences than the random or simple adaptive FH methods. We will further improve this proposed method to apply QoS control and MAC function development in OFDMA based wireless physical structures, especially maritime wireless data communications.

• Nuclear Engineering and Technology
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• v.16 no.3
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• pp.136-140
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• 1984

A new medal is presented in order to evaluate the risk from a nuclear facility following accidents directly combining the on-site meteorological data using the Monte Carlo Method. To estimate the radiological detriment to the surrounding population-at-large (collective dose equivalent), in this study the probability distribution of each meteorological element based upon on-site data is analyzed to generate atmospheric dispersion conditions. The random sampling is used to select the dispersion conditions at any given time of effluent releases. In this study it is considered that the meteorological conditions such as wind direction, speed and stability are mutually independent and each condition satisfies the Markov condition. As a sample study, the risk of KNU-1 following the large LOCA was calculated, The calculated collective dose equivalent in the 50 mile region population from the large LOCA with 50 percent confidence level is 2.0$\times$10$^2$ man-sievert.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.984-994
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• 2020

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries.