• Korean Journal of Remote Sensing
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• 제34권6_3호
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

• Convergence Security Journal
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• 제18권1호
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• pp.117-128
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• 2018

The purpose of this paper is to analyze the behavior of North Korea's cyber attack against South Korea since 2009 based on major international security theories and suggest South Korea's policy option. For this purpose, this paper applied the behavioral domain and characteristics of 'cyber power' and 'coercion dynamics' model, which are attracting attention in international security studies. The types of cyber attacks from North Korea are classified into the following categories: power-based incarceration, leadership attacks and intrusions, military operations interference, and social anxiety and confusion. In terms of types and means of cyber power, North Korean GPS disturbance, the Ministry of Defense server hacking and EMP are hard power with high retaliation and threat and cyber money cashing and ransomware are analyzed by force in the act of persuasion and incentive in the point of robbing or asking for a large amount of money with software pawns. North Korea 's cyber attack has the character of escape from realistic sanctions based on the second nuclear test. It is important for South Korea to clearly recognize that the aggressive cyberpower of North Korea is changing in its methods and capabilities, and to ensure that North Korea's actions result in far greater losses than can be achieved. To do this, it is necessary to strengthen the cyber security and competence to simultaneously attack and defend through institutional supplement and new establishment such as cyber psychological warfare, EMP attack preparation, and enhancement of security expertise against hacking.

• Proceedings of the Plant Resources Society of Korea Conference
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• 한국자원식물학회 2019년도 춘계학술대회
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• pp.62-62
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• 2019

Bacterial leaf blight(BLB), caused by X. oryzae pv. oryzae(Xoo), is one of the most destructive diseases of rice due to its high epidemic potential. Understanding BLB resistance at a genetic level is important to further improve the rice breeding that provides one of the best approaches to control BLB disease. In the present investigation, a collection of 192 accessions was used in the genome-wide association study (GWAS) for BLB resistance loci against four Korean races of Xoo that were represented by the prevailing BLB isolates under Xoo differential system. A total of 192 accessions of rice germplasm were selected on the basis of the bioassay using four isolated races of Xoo such as K1 and K2. The selected accessions was used to prepare 384-plex genotyping by sequencing (GBS) libraries and Illumina HiSeq 2000 pairedend read was used for GBS sequencing. GWAS was conducted using TASSEL 5.0. The TASSEL program uses a mixed linear model (MLM). The results of the bioassay using a selected set of 192 accessions showed that a large number of accessions (93.75%) were resistant to K1 race and K2 resistant germplasm proportion remained between 66.67. The genotypic data produced SNP matrix for a total of 293,379 SNPs. After imputation the missing data was removed, which exhibited 34,724 SNPs for association analysis. GWAS results showed strong signals of association at a threshold of [-log10(P-value)] more than 5 (K1 and K2) for nine of the 39 SNPs, which are plausible candidate loci of resistance genes. These SNP loci were positioned on rice chromosome 2, 9, and 11 for K1 and K2 races. The significant loci detected have also been illustrated and make the CPAS markers for NBS-LRR type disease resistance protein, SNARE domain containing protein, Histone deacetylase 19, NADP-dependent oxidoreductase, and other expressed and unknown proteins. Our results provide a better understanding of the distribution of genetic variation of BLB resistance to Korean pathogen races and breeding of resistant rice.

• Journal of the Korea Society of Computer and Information
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• 제26권4호
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Smart Structures and Systems
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• 제24권6호
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• Knowledge Management Research
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• 제21권4호
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• pp.287-300
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• 2020

We investigate empirically the impact of IT exploration & exploitation capability and operational capability upon organizational agility, especially small and medium sized firms in the logistics industry in South Korea. Based on literature on the bilateral relationship between organizational agility and IT capability, we follow the established research model and propose hypotheses. This work takes an empirical methodology to test the hypotheses: design survey questionnaires, collect data, test reliability and validity of data, and finally test the hypotheses. Our results based on the data collected in 2018 present that IT exploration & exploitation capability significantly increases operational capability, and operational capability increases organizational agility. We find our contribution in updating previous research findings with recent data and in expanding the domain of research more specifically into small and medium sized firms in logistics industry in South Korea. Practically our work suggests that managers and policy makers should consider both fostering newly emerging IT exploration and existing IT resource exploitation capability in order to enhance organizational agility of those small and medium sized firms in logistics industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제22권6호
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• pp.566-572
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• 2021

A methodology for the identification and coordinates estimation of air cavities under urban ground or sandy soil using its natural poles and natural resonant frequencies is presented. The potential of this methodology was analyzed. Simulation models of PEC (Perfect Electric Conductor)s with various shapes and dimensions were developed using an EM (Electromagnetic) simulator. The Cauchy method was applied to the obtained EM scattering response of various objects from EM simulation models. The natural poles of objects corresponding to its instinct characterization were then extracted. Thus, a library of poles can be generated using their natural poles. The generated library of poles provided the possibility of identifying a target by comparing them with the computed natural poles from a target. The simulation models were made assuming that there is an air cavity under urban ground or sandy soil. The response of the desired target was extracted from the electromagnetic wave scattering data from its simulation model. The coordinates of the target were estimated using the time delay of the impulse response (peak of the impulse response) in the time domain. The MP (Matrix Pencil) method was applied to extract the natural poles of a target. Finally, a 0.2-m-diameter spherical air cavity underground could be estimated by comparing both the pole library of the objects and the calculated natural poles and the natural resonant frequency of the target. The computed location (depth) of a target showed an accuracy of approximately 84 to 93%.

• Clean Technology
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• 제27권1호
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• pp.61-68
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• 2021

Selective catalytic reduction (SCR) is widely used as a method of removing nitrogen oxide in large-capacity thermal power generation systems. Uniform mixing of the injected ammonia and the inlet flue gas is very important to the performance of the denitrification reduction process in the catalyst bed. In the present study, a computational analysis technique was applied to the ammonia injection system design process of a denitrification facility. The applied model is the denitrification facility of an 800 MW class coal-fired power plant currently in operation. The flow field to be solved ranges from the inlet of the ammonia injection system to the end of the catalyst bed. The flow was analyzed in the two-dimensional domain assuming incompressible. The steady-state turbulent flow was solved with the commercial software named ANSYS-Fluent. The nozzle arrangement gap and injection flow rate in the ammonia injection system were chosen as the design parameters. A total of four (4) cases were simulated and compared. The root mean square of the NH3/NO molar ratio at the inlet of the catalyst layer was chosen as the optimization parameter and the design of the experiment was used as the base of the optimization algorithm. The case where the nozzle pitch and flow rate were adjusted at the same time was the best in terms of flow uniformity.

• Journal of the Korean GEO-environmental Society
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• 제23권8호
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• Clean Technology
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• 제28권4호
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• pp.316-322
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• 2022

The flow pattern at the inlet of the catalyst layer in a selective catalytic reduction (SCR) system is one of the key parameters influencing the performance of the denitrification process. In the curved diffusing parts between the ammonia injection grids and the catalyst layers, guide vanes are installed to improve flow uniformity. In the present study, a numerical simulation has been performed to investigate the effect of the geometrical configuration of the guide vanes on the aerodynamic characteristics of a denitrification facility. This application has been made to the existing SCR process in a large-scaled coal-fired power plant. The flow domain to be solved covers the whole region of the flow passages from the exit of the ammonia injection gun to the exit of the catalyst layers. ANSYS-Fluent was used to calculate the three-dimensional steady viscous flow fields with the proper turbulence model fitted to the flow characteristics. The root mean square of velocity and the pressure drop inside the flow passages were chosen as the key performance parameters. Four types of guides vanes were proposed to improve the flow quality compared to the current configuration. The numerical results showed that the type 4 configuration was the most effective at improving the aerodynamic performance in terms of flow uniformity and pressure loss.