• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.458-467
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• 2010

In this paper, a new audio reproduction system was developed in which the cross-talk signals would be reasonably cancelled at an arbitrary listener position. To adaptively remove the cross-talk signals according to the listener's position, a method of tracking the listener position was employed. This was achieved using the two microphones, where the listener direction was estimated using the time-delay between the two signals from the two microphones, respectively. Moreover, room reverberation effects were taken into consideration where linear prediction analysis was involved. To remove the cross-talk signals at the left-and right-ears, the paths between the sources and the ears were represented using the KEMAR head-related transfer functions (HRTFs) which were measured from the artificial dummy head. To evaluate the usefulness of the proposed listener tracking system, the performance of cross-talk cancellation was evaluated at the estimated listener positions. The performance was evaluated in terms of the channel separation ration (CSR), a -10 dB of CSR was experimentally achieved although the listener positions were more or less deviated. A real-time system was implemented using a floating-point digital signal processor (DSP). It was confirmed that the average errors of the listener direction was 5 degree and the subjects indicated that 80 % of the stimuli was perceived as the correct directions.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.585-590
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• 2024

In this study, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of engineers and simple measuring tools. With the recent enactment of the Track Diagnosis Act, a large budget has been invested and the volume of rail diagnosis is rapidly increasing, but it is difficult to secure the reliability of diagnosis results using labor-intensive visual inspection techniques. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the rail internal crack characteristics due to rail surface damage were studied. In field measurements, rail surface damage locations were selected, samples of various damage types were collected, and the rail surface damage status was evaluated. In indoor testing, we intend to analyze the correlation between rail surface defects and internal defects using a electron scanning microscope (SEM). To determine the crack growth rate of urban railway rails currently in use, the Gaussian probability density function was applied and analyzed.

• Journal of Platform Technology
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• v.12 no.1
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• pp.91-105
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• 2024

As the number of cases of applying IT systems to the existing isolated ICS (Industrial Control System) network environment continues to increase, security threats in the ICS environment have rapidly increased. Security threat scenarios help to design security strategies in cybersecurity training, including analysis, prediction, and response to cyberattacks. For successful cybersecurity training, research is needed to develop valid and reliable security threat scenarios for meaningful training. Therefore, this paper proposes a case-based security threat scenario development methodology for cybersecurity training in the ICS environment. To this end, we develop a methodology consisting of five steps based on analyzing actual cybersecurity incident cases targeting ICS. Threat techniques are standardized in the same form using objective data based on the MITER ATT&CK framework, and then a list of CVEs and CWEs corresponding to the threat technique is identified. Additionally, it analyzes and identifies vulnerable functions in programming used in CWE and ICS assets. Based on the data generated up to the previous stage, develop security threat scenarios for cybersecurity training for new ICS. As a result of verification through a comparative analysis between the proposed methodology and existing research confirmed that the proposed method was more effective than the existing method regarding scenario validity, appropriateness of evidence, and development of various scenarios.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.80-87
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• 2010

This study was conducted to develop a reservoir modelling workflow to reproduce the heterogeneous distribution of effective permeability that impacts on the performance of SAGD (Steam Assisted Gravity Drainage), the in-situ bitumen recovery technique in the Athabasca Oil Sands. Lithologic facies distribution is the main cause of the heterogeneity in bitumen reservoirs in the study area. The target formation consists of sand with mudstone facies in a fluvial-to-estuary channel system, where the mudstone interrupts fluid flow and reduces effective permeability. In this study, the lithologic facies is classified into three classes having different characteristics of effective permeability, depending on the shapes of mudstones. The reservoir modelling workflow of this study consists of two main modules; facies modelling and permeability modelling. The facies modelling provides an identification of the three lithologic facies, using a stochastic approach, which mainly control the effective permeability. The permeability modelling populates mudstone volume fraction first, then transforms it into effective permeability. A series of flow simulations applied to mini-models of the lithologic facies obtains the transformation functions of the mudstone volume fraction into the effective permeability. Seismic data contribute to the facies modelling via providing prior probability of facies, which is incorporated in the facies models by geostatistical techniques. In particular, this study employs a probabilistic neural network utilising multiple seismic attributes in facies prediction that improves the prior probability of facies. The result of using the improved prior probability in facies modelling is compared to the conventional method using a single seismic attribute to demonstrate the improvement in the facies discrimination. Using P-wave velocity in combination with density in the multiple seismic attributes is the essence of the improved facies discrimination. This paper also discusses sand matrix porosity that makes P-wave velocity differ between the different facies in the study area, where the sand matrix porosity is uniquely evaluated using log-derived porosity, P-wave velocity and photographically-predicted mudstone volume.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.243-246
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• 2012

The study was aimed at the development of the simple linear regression model to estimate the fruit yield of sweet pepper and to support decision-making management for growing sweet pepper crop in Korea. For quantitative analysis of relationship between environmental data and periodical yield of sweet pepper the data obtained from the commercial Venlo-type glasshouse for 2 years. Obtained periodical yield data of five different cultivars and radiation data were accumulated and fitted by linear regression. A significant linear relationship was found between radiation integral and fruit yield, whereas the production per unit of radiation was different between cultivars. The slope of linear regression could indicate as light use efficiency for fruit production ($LUE_F$, $g{\cdot}MJ^{-1}$). $LUE_F$ of 'Ferrari' was $5.85g{\cdot}MJ^{-1}$, 'Fiesta' 5.32 for first year and $4.75g{\cdot}MJ^{-1}$ and for second year, 'President' was $4.66g{\cdot}MJ^{-1}$, 'Cupra' was $3.86g{\cdot}MJ^{-1}$, and 'Boogie' was $6.48g{\cdot}MJ^{-1}$. The amount of light requirement for the unit gram of fruit was between $25.88J{\cdot}g^{-1}$, for 'Cupra' and $15.42J{\cdot}g^{-1}$ for 'Boogie'. Although we found the linear relationship between radiation and fruit yield, $LUE_F$ was varied between cultivars and as well as year. The linear relationship could describe the fruit yield as function of radiation, but it needed more variable to generalization of the production, such as cultivar specifications, temperature, and number of fruits set per plant or unit of ground.

• Journal of Radiation Protection and Research
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• v.41 no.1
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• pp.41-47
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• 2016

Background: For the accurate dose assessment in radiation therapy, energy spectrum of the photon beam generated from the linac head is essential. The aim of this study is to develop the technique to accurately unfolding the energy spectrum with the transmission analysis method. Materials and Methods: Clinical linear accelerator and Monet Carlo method was employed to evaluate the transmission signals according to the thickness of the observer material, and then the response function of the ion chamber response was determined with the mono energy beam. Finally the energy spectrum was unfolded with HEPROW program. Elekta Synergy Flatform and Geant4 tool kits was used in this study. Results and Discussion: In the comparison between calculated and measured transmission signals using aluminum alloy as an attenuator, root mean squared error was 0.43%. In the comparison between unfolded spectrum using HEPROW program and calculated spectrum using Geant4, the difference of peak and mean energy were 0.066 and 0.03 MeV, respectively. However, for the accurate prediction of the energy spectrum, additional experiment with various type of material and improvement of the unfolding program is required. Conclusion: In this research, it is demonstrated that unfolding spectra technique could be used in megavoltage photon beam with aluminum alloy and HEPROW program.

• Korean Journal of Poultry Science
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• v.44 no.4
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• pp.259-265
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• 2017

This study was to investigate the effect of chick weight in the early growth period on market-weight of Korean native chickens (KNCs). We measured the body weights of 1,087 chickens (male 479, female 608) of 13 KNC strains at 1-84 days of age at two week intervals. The growth performance of the 13 KNC strains was investigated. Correlation coefficients among the weights of chickens in each growth period and regression of market-weight on early chick weights were analyzed. The results showed that the average body weight of 70-day-old KNCs was 1,962g: 2,154g and 1,819.7g for males and females, respectively. The equation for regression of body weight on age was estimated as $\hat{Y}=0.1347X^2+18.738X-40.134$ ($R^2=0.9418$). Using this regression equation, the duration required to attain a KNC market-weight of 2 kg was estimated as 71.8 days. All the correlation coefficients between early chick weight and market-weight were significantly positive. Although the correlation coefficients among the chick weights in each growth period decreased with increase in age interval, early growth weight had a significant effect on late growth performance. The correlation coefficient between market-weight at 70-days and chick weight at 1-day was estimated to be a low as 0.10-0.13. In the estimations of market-weight correlation coefficients, correlation coefficient and coefficient of determination were high in the female and male chicks after 28-days and 42-days of age, respectively. The results of the analysis of correlation and regression between early chick weight and market-weight of KNCs showed that market-weight could be predicted based on the weights of 28-day-old females and 42-day-old males.

• Composites Research
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• v.15 no.4
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• pp.23-31
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• 2002

The two dimensional size effect of specimen gauge section ($length{\;}{\times}{\;}width$) was investigated on the compressive behavior of a T300/924 $\textrm{[}45/-45/0/90\textrm{]}_{3s}$, carbon fiber-epoxy laminate. A modified ICSTM compression test fixture was used together with an anti-buckling device to test 3mm thick specimens with a $30mm{\;}{\times}{\;}30mm,{\;}50mm{\;}{\times}{\;}50mm,{\;}70mm{\;}{\times}{\;}70mm{\;}and{\;}90mm{\;}{\times}{\;}90mm$ gauge length by width section. In all cases failure was sudden and occurred mainly within the gauge length. Post failure examination suggests that $0^{\circ}$ fiber microbuckling is the critical damage mechanism that causes final failure. This is the matrix dominated failure mode and its triggering depends very much on initial fiber waviness. It is suggested that manufacturing process and quality may play a significant role in determining the compressive strength. When the anti-buckling device was used on specimens, it was showed that the compressive strength with the device was slightly greater than that without the device due to surface friction between the specimen and the device by pretoque in bolts of the device. In the analysis result on influence of the anti-buckling device using the finite element method, it was found that the compressive strength with the anti-buckling device by loaded bolts was about 7% higher than actual compressive strength. Additionally, compressive tests on specimen with an open hole were performed. The local stress concentration arising from the hole dominates the strength of the laminate rather than the stresses in the bulk of the material. It is observed that the remote failure stress decreases with increasing hole size and specimen width but is generally well above the value one might predict from the elastic stress concentration factor. This suggests that the material is not ideally brittle and some stress relief occurs around the hole. X-ray radiography reveals that damage in the form of fiber microbuckling and delamination initiates at the edge of the hole at approximately 80% of the failure load and extends stably under increasing load before becoming unstable at a critical length of 2-3mm (depends on specimen geometry). This damage growth and failure are analysed by a linear cohesive zone model. Using the independently measured laminate parameters of unnotched compressive strength and in-plane fracture toughness the model predicts successfully the notched strength as a function of hole size and width.