• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.147-158
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• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.

• Convergence Security Journal
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• v.8 no.3
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• pp.19-24
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• 2008

Common Criteria is a standard to estimate safety of information protection product such as network-level firewall system and intrusion detection system. Recently, CC version is changed from CC v.2.3 to CC v.3.1. CC v.3.1 estimation methodology requires a secured dictionary accomodation preparation for information protection product. In this research, progressed CC v3 base composition product test and research about vulnerability analysis method. Further, this paper presents specific plan sorting composition style information protection product examination methodology to existing principle and detailed methodology.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.91-94
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• 2003

In this paper, we achieve implementation of a Time-Frequency Domain Reflectometry(TFDR) system through comparatively low performance(100MS/s) PCI extensions for Instrumentation(PXI). The TFDR is the general methodology of Time Domain Reflectometry(TDR) and Frequency Domain Reflectometry(FDR). This methodology is robust in Gaussian noises, because the fixed frequency bandwidth is used. Moreover, the methodology can get more information of the fault by using the normalized time-frequency cross correlation function. The Arbitrary Waveform Generator(AWG) module generates the input signal, and the digital oscilloscope module acquires the input and reflected signals, while PXI controller module performs the control of the total PXI modules and execution of the main algorithm. The maximum range of measurement and the blind spot are calculated according ta variations of time duration and frequency bandwidth. On the basis of above calculations, the algorithm and the design of input signals used in the TFDR system are verified by real experiments. The correlation function is added to the TDR methodology for reduction of the blind spot in the TFDR system.

• Journal of Fashion Business
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• v.20 no.5
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• pp.30-44
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• 2016

In this study, we used the Q methodology, which is considered an effective way to identify and assess the characterization of the human subjective consciousness, and we intended to carry out a scientific approach to classify cosmetics consumers in a department store. The purpose of this study is to identify the dimension of recognition and the characterization of Korean women who use a department store, as well as to classify cosmetics consumers in a department store. The analyzed data was divided into the top 10 questions and 10 sub-items, and it was then classified into six consumer types, depending on typicality of three factors. The three factors were 'effectiveness', 'goal' and 'congestion of shopping'. We named and analyzed the features of each type through in-depth Q workshops in which 22 professionals participated. This study is meaningful as it used the Q-methodology instead of statistics which had been used before to classify the consumers, so that the 'subjective' estimation was analyzed into 'objective' types. The results of this study are expected to be useful for creating a marketing strategy for the cosmetics industry.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.884-893
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• 2019

Spent fuel racks are steel structures used in the storage of the spent fuel removed from the nuclear power reactor. Rack units are submerged in the depths of the spent fuel pool to keep the fuel cool. Their free-standing design isolates their bases from the pool floor reducing structural stresses in case of seismic event. However, these singular features complicate their seismic analysis which involves a transient dynamic response with geometrical nonlinearities and fluid-structure interactions. An accurate estimation of the response is essential to achieve a safe pool layout and a reliable structural design. An analysis methodology based on the hydrodynamic mass concept and implicit integration algorithms was developed ad-hoc, but some dispersion of results still remains. In order to validate the analysis methodology, vibration tests are carried out on a reduced scale mock-up of a 2-rack system. The two rack mockups are submerged in free-standing conditions inside a rigid pool tank loaded with fake fuel assemblies and subjected to accelerations on a unidirectional shaking table. This article compares the experimental data with the numerical outputs of a finite element model built in ANSYS Mechanical. The in-phase motion of both units is highlighted and the water coupling effect is detailed. Results show a good agreement validating the methodology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.129-145
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• 2017

This study proposes a methodology to estimate the financial damages by personal information breach of a company and to analyse risk systematically through a case study of a company which experiences private information breach. Using FAIR(Factor Analysis of Information Risk) model, estimate the loss amount and to analyse risk objectively of a company by personal information breach. This study estimates adequacy and importance of corresponding factors applying AHP(Analytic Hierarchy Process) on each factors for assessing loss amount. By adopting proposed methodology in this study, the person in charge of actual work can assess and prove the loss amount though the latest risk estimation methodology. In addition, the person in charge can select the proper parameters for the corresponding company and can obtain the objective quantitative estimation. Hence it can be reported to the management by accurately assessing loss amount caused by personal information breach.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.141-160
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• 2007

User interface has been regarded as a crucial issue to increase the acceptance of mobile services. In special, even though to what extent the machine as speaker communicates with human as listener in a timely and polite manner is important, fundamental studies to come up with these issues have been very rare. Hence, the purpose of this paper is to propose a methodology of estimating politeness level in a certain context-aware setting and then to design a context-aware system for polite mobile interface. We will focus on Korean language for the polite level estimation simply because the polite interface would highly depend on cultural and linguistic characteristics. Nested Minkowski aggregation model, which amends Minkowski aggregation model, is adopted as a privacy-preserving similarity evaluation for case retrieval under distributed computing environment such as ubiquitous computing environment. To show the feasibility of the methodology proposed in this paper, simulation-based experiment with drama cases has performed to show the performance of the methodology proposed in this paper.

• Informatization Policy
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• v.26 no.4
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• pp.85-106
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• 2019

Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.565-572
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• 2014

A systematically structured 3D information model can be effectively utilized in many application fields. This study presents the methodology of generation and application of the city information model, which is suited for the management of the flood damage information. To ensure the interoperability and re-usability of the information, this study develops application methodology to utilize the information attributes included in the CityGML as an open standard data schema and extension methodology for additional information attributes. Also, an effective combining method for topography and building model was proposed. Using the data extracted from the combined information model based on a real flood damage case, it was shown that the numbers of casualties and isolation during a flood can be predicted and as a result, the applicability of the data model on flood damage estimation is naturally verified.

• Journal of Korea Trade
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• v.25 no.5
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• pp.110-128
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• 2021

Purpose - The essential purpose of this study is to analyze the possibility of substitution of an individual job resulting from technological development represented by the 4th Industrial Resolution, considering the different effects of digital transformation on the labor market. Design/methodology - In order to estimate the substitution probability, this study used two data sets which the job characteristics data for individual occupations provided by KEIS and the information on occupational status of substitution provided by Frey and Osborne(2013). In total, 665 occupations were considered in this study. Of these, 80 occupations had data with labels of substitution status. The primary goal of estimation was to predict the degree of substitution for 607 of 665 occupations (excluding 58 with markers). It utilized three methods a principal component analysis, an unsupervised learning methodology of machine learning, and Ridge and Lasso from supervised learning methodology. After extracting significant variables based on the three methods, this study carried out logistics regression to estimate the probability of substitution for each occupation. Findings - The probability of substitution for other occupational groups did not significantly vary across individual models, and the rank order of the probabilities across occupational groups were similar across models. The mean of three methods of substitution probability was analyzed to be 45.3%. The highest value was obtained using the PCA method, and the lowest value was derived from the LASSO method. The average substitution probability of the trading industry was 45.1%, very similar to the overall average. Originality/value - This study has a significance in that it estimates the job substitution probability using various machine learning methods. The results of substitution probability estimation were compared by industry sector. In addition, This study attempts to compare between trade business and industry sector.