• Sleep Medicine and Psychophysiology
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• v.27 no.2
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• pp.67-76
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• 2020

Objectives: Brain maturation involves brain lateralization and asymmetry to achieve efficient information processing and cognitive controls. This study elucidates normal brain maturation change during the gap between ages 6-9 and age 14-17 using resting EEG. Methods: An EEG dataset was acquired from open source MIPDB (Multimodal Resource for Studying Information Processing in the Developing Brain). Ages 6-9 (n = 24) and ages 14-17 (n = 26) were selected for analysis, and subjects with psychiatric illness or EEG with severe noise were excluded. Finally, ages 6-9 (n = 14) and ages 14-17 (n = 11) were subjected to EEG analysis using EEGlab. A 120-sec length of resting EEG when eyes were closed was secured for analysis. Brain topography was compartmentalized into nine regions, best fitted with brain anatomical structure. Results: Absolute power of the delta band and theta band in ages 6-9 was greater than that of ages 14-17 in the whole brain, and, also is relative power of delta band in frontal compartment, which is same line with previous studies. The relative power of the beta band of ages 14-17 was greater than that of ages 6-9 in the whole brain. In asymmetry evaluation, relative power of the theta band in ages 14-17 showed greater power in the left than right frontal compartment; the opposite finding was noted in the parietal compartment. For the alpha band, a strong relative power distribution in the left parietal compartment was observed in ages 14-17. Absolute and relative power of the alpha band is distributed with hemispheric left lateralization in ages 14-17. Conclusion: During the gap period between ages 6-9 and ages 14-17, brain work becomes more complicated and sophisticated, and alpha band and beta band plays important roles in brain maturation in typically developing children.

• Clean Technology
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• v.26 no.4
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• pp.329-335
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• 2020

Methanol synthesized from renewable hydrogen and captured CO2 has recently attracted great interest as a sustainable energy carrier for large-scale renewable energy storage. In this study, molten carbonate fuel cell's performance was investigated with the direct conversion of methanol into syngas inside the anode chamber of the cell. The internal reforming of methanol may significantly improve system efficiency since the heat generated from the electrochemical reaction can be used directly for the endothermic reforming reaction. The porous Ni-10 wt%Cr anode was sufficient for the methanol steam reforming reaction under the fuel cell operating condition. The direct supply of methanol into the anode chamber resulted in somewhat lower cell performance, especially at high current density. Recycling of the product gas into the anode gas inlet significantly improved the cell performance. The analysis based on material balance revealed that, with increasing current density and gas recycling ratio, the methanol steam reforming reaction rate likewise increased. A methanol conversion more significant than 90% was achieved with gas recycling. The results showed the feasibility of electricity and syngas co-production using the molten carbonate fuel cell. Further research is needed to optimize the fuel cell operating conditions for simultaneous production of electricity and syngas, considering both material and energy balances in the fuel cell.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.83-100
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• 2020

This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.307-317
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• 2021

In recent years, global warming has led to frequent climate change-related problems, and elevated temperatures, among adverse climatic factors, represent a critical problem negatively affecting crop growth and yield. In this context, the present study examined the physiological traits of wheat plants grown under high temperatures. Specifically, the effects of elevated temperatures on seed development after heading were evaluated, and the vegetation indices of different organs were assessed using hyperspectral analysis. Among physiological traits, leaf greenness and OJIP parameters were higher in the high-temperature treatment than in the control treatment. Similarly, the leaf photosynthetic rate during seed development was higher in the high-temperature treatment than in the control treatment. Moreover, temperature by organ was higher in the high-temperature treatment than in the control treatment; consequently, the leaf transpiration rate and stomatal conductance were higher in the control treatment than in the high-temperature treatment. On all measuring dates, the weight of spikes and seeds corresponding to the sink organs was greater in the high-temperature treatment than in the control treatment. Additionally, the seed growth rate was higher in the high-temperature treatment than in the control treatment 14 days after heading, which may be attributed to the higher redistribution of photosynthates at the early stage of seed development in the former. In hyperspectral analysis, the vegetation indices related to leaf chlorophyll content and nitrogen state were higher in the high-temperature treatment than in the control treatment after heading. Our results suggest that elevated temperatures after the booting stage positively affect wheat growth and yield.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.29-34
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• 2021

Purpose Sample reception environment system in nuclear medicine has not changed much compared to 20 years ago. When preparing sample for in vitro test, there was no significant change because the test was carried out by generating an own specimen from the parent specimen. In this study, We would like to introduce a method that automatically removes the sample cap using the automated decapper equipment and enables automatic reception at the same time. In addition, including a provisional reception system. Materials and Methods In 2019, it was intended to get a device that automatically removes the cap of a patient's blood sample. This equipment is the same as the equipment used in the Department of Laboratory Medicine (Vacuette Ⓡ Unicap Belt Decapper, Greiner bio-one, Austria). However, the purchase was delayed due to differences in tube size, budget, and space. In January 2020, we borrowed domestic automatic decapper equipment and modified it to suit our laboratory environment. After 9 months, we were able to introduce a system that automatically removes the lid of a patient's blood sample and at the same time automatically accepts the test. And, through the provisional reception system, it was possible to know the arrival of the specimen in a short time. Results With the use of an automatic decapper device, the sample cap was automatically removed, and the reception proceeded at the same time. So, it was very efficient at work because it shortened the sample preparation time by about 20 minutes. In addition, it was possible to prevent the examiner's musculoskeletal disorders caused by repeated wrist use. After using the provisional reception system, patients were able to be discharged quickly, and the number of phone calls to confirm the arrival of samples was reduced. Conclusion Most hospitals have about four employees in the nuclear medicine in vitro laboratory. It is effective to use automatic decapper equipment and a provisional reception system for organizations that perform work with the minimum number of personnel.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.85-93
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• 2021

The seventy percentage of Korean Peninsular is covered by the mountainous area, and the depth of west sea and south sea is relatively shallow. Therefore, a large scale land reclamation from the sea has been implemented for the construction of industrial complex, residental area, and port and airport facilities. The common problem of reclaimed land is consisted of soft ground, and hence it has low load bearing capacity as well as excessive settlement upon loading on the ground surface. The hollow concrete block has been used to reinforce the loose and soft foundation soil where the medium-high apartment or one-story industrial building is being planned to be built. Recently the earthquakes with the magnitude of 4.0~5.0 have been occurred in the west coastal and southeast coastal areas. Lee (2019) reported the advantages of hollow concrete block reinforced shallow foundation through the static laboratory bearing capacity tests. In this study, the dynamic behavior of hollow concrete block reinforced sandy ground with filling the crushed stone in the hollow space has been investigated by the means of shaking table test with the size of shaking table 1000 mm × 1000 mm. Three types of seismic wave, that is, Ofunato, Hachinohe, Artificial, and two different accelerations (0.154 g, 0.22 g) were applied in the shaking table tests. The horizontal displacement of structure which is situated right above the hollow concrete block reinforced ground was measured by using the LVDT. The relative density of soil ground are varied with 45%, 65%, and 85%, respectively, to investigate the effectiveness of reinforcement by hollow block and measured the magnitude of lateral movement, and compared with the limit value of 0.015h (Building Earthquake Code, 2019). Based on the results of shaking table test for hollow concrete block reinforced sandy ground, honeycell type hollow block gives a large interlocking force due to the filling of crushed stone in the hollow space as well as a great interface friction force by the confining pressure and punching resistance along the inside and outside of hollow concrete block. All these factors are contributed to reduce the great amount of horizontal displacement during the shaking table test. Finally, hollow concrete block reinforced sandy ground for shallow foundation is provided an outstanding reinforced method for medium-high building irrespective of seismic wave and moderate accelerations.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.167-176
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• 2022

Adaptive optics (AO) systems compensate for atmospheric disturbance, especially phase distortion, by introducing counter-wavefront deformation calculated from real-time wavefront sensing or prediction. Because AO system implementations are time-consuming and costly, it is highly desirable to estimate the system's performance during the development of the AO system or its parts. Among several techniques, we mostly apply statistical analysis, computational simulation, and optical-bench tests. Statistical analysis estimates performance based on the sum of performance variances due to all design parameters, but ignores any correlation between them. Computational simulation models every part of an adaptive optics system, including atmospheric disturbance and a closed loop between wavefront sensor and deformable mirror, as close as possible to reality, but there are still some differences between simulation models and reality. The optical-bench test implements an almost identical AO system on an optical bench, to confirm the predictions of the previous methods. We are currently developing an AO system for a 1.6-m ground telescope using a deformable mirror that was recently developed in South Korea. This paper reports the results of the statistical analysis and computer simulation for the system's design and confirmation. For the analysis, we apply the Strehl ratio as the performance criterion, and the median seeing conditions at the Bohyun observatory in Korea. The statistical analysis predicts a Strehl ratio of 0.31. The simulation method similarly reports a slightly larger value of 0.32. During the study, the simulation method exhibits run-to-run variation due to the random nature of atmospheric disturbance, which converges when the simulation time is longer than 0.9 seconds, i.e., approximately 240 times the critical time constant of the applied atmospheric disturbance.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.175-198
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• 2022

With the development of technology, the methods of digitally converting various forms of analog information have become common. As a result, the concept of recording, building, and reproducing data in a virtual space, such as digital heritage and digital reconstruction, has been actively used in the preservation and research of various cultural heritages. However, there are few existing research results that suggest optimal scanners for small and medium-sized relics. In addition, scanner prices are not cheap for researchers to use, so there are not many related studies. The 3D scanner specifications have a great influence on the quality of the 3D model. In particular, since the state of light reflected on the surface of the object varies depending on the type of light source used in the scanner, using a scanner suitable for the characteristics of the object is the way to increase the efficiency of the work. Therefore, this paper conducted a study on nine small and medium-sized buried cultural properties of various materials, including earthenware and porcelain, by period, to examine the differences in quality of the four types of 3D scanners. As a result of the study, optical scanners and small and medium-sized object scanners were the most suitable digital records of the small and medium-sized relics. Optical scanners are excellent in both mesh and texture but have the disadvantage of being very expensive and not portable. The handheld method had the advantage of excellent portability and speed. When considering the results compared to the price, the small and medium-sized object scanner was the best. It was the photo room measurement that was able to obtain the 3D model at the lowest cost. 3D scanning technology can be largely used to produce digital drawings of relics, restore and duplicate cultural properties, and build databases. This study is meaningful in that it contributed to the use of scanners most suitable for buried cultural properties by material and period for the active use of 3D scanning technology in cultural heritage.