• Convergence Security Journal
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• v.22 no.2
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• pp.115-120
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• 2022

This study analyzed the recent trends in the sports environment to which big data and AI technologies, which are representative technologies of the 4th Industrial Revolution, and approached them from the perspective of convergence of big data and AI technologies in the sports field. And the results are as follows. First, it is being used for player and game data analysis and team strategy establishment and operation. Second, by combining big data collected using GPS, wearable equipment, and IoT with artificial intelligence technology, scientific physical training for each player is possible through user individual motion analysis, which helps to improve performance and efficiently manage injuries. Third, with the introduction of an AI-based judgment system, it is being used for judge judgment. Fourth, it is leading the change in marketing and game broadcasting services. The technology of the 4th Industrial Revolution is bringing innovative changes to all industries, and the sports field is also in the process. The combination of big data and AI is expected to play an important role as a key technology in the rapidly changing future in a sports environment where scientific analysis and training determine victory or defeat.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1009-1014
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• 2023

Comprehensive observations of the Euler method and the Lagrangian method were performed in order to obtain high-resolution observation data in space and time for the complex environment of new city. The two radiosondes, which measure meteorological parameters using Lagrangian methods, produced air pressure, wind speed and wind direction. They were generally consistent with each other even if the observation points or times were different. The temperature measured by the sensor exposed to the air during the day was relatively high as the altitude increased due to the influence of solar radiation. The temporal difference in wind direction and speed was found in the comparison of Euler's wind profiler data with radiosonde data. When the wind field is horizontally in homogeneous, this result implies the need to consider the advection component to compare the data of the two observation methods. In this study, a method of using observation data at different times for each altitude section depending on the observation period of the Euler method is proposed to effectively compare the data of the two observation methods.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.65-71
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• 2024

To achieve high resolution and sensitivity of positron emission tomography (PET) for small animals, the detector is constructed using very thin and long scintillation pixels. Due to the structure of these scintillation pixels, spatial resolution deterioration occurs outside the system's field of view. To solve this problem, we designed a detector that could improve spatial resolution by measuring the interaction depth and improve sensitivity by using a quasi-block scintillator. A quasi-block scintillator size of 12.6 mm x 12.6 mm x 3 mm was arranged in four layers, and optical sensors were placed on all sides to collect light generated by the interaction between gamma rays and the scintillator. DETECT2000 simulation was performed to evaluate the performance of the designed detector. Flood images were acquired by generating gamma-ray events at 1 mm intervals from 1.3 mm to 11.3 mm within the scintillator of each layer. The spatial resolution and peak-to-peak distance for each location were measured in an 11 x 11 array of flood images. The average measured spatial resolution was 0.25 mm, and the average distance between peaks was 1.0 mm. Through this, it was confirmed that all locations were separated from each other. In addition, because the light signals of all layers were measured separately from each other, the layer of the scintillator that interacted with the gamma rays could be completely separated. When the designed detector is used as a detector in a PET system for small animals, it is considered that excellent spatial resolution and sensitivity can be achieved and image quality can be improved.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.41-54
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• 2024

Regular monitoring plays a crucial role in ensuring the safety of geotechnical structures. Currently, nondestructive methods are employed to monitor such structures to minimize the impact, e.g., sensor-based accelerometers, displacement meters, image-based lasers, and drone imaging. These technologies can observe surface changes; however, they frequently suffer difficulties in terms of identifying changes in internal properties. To monitor changes in internal properties, in situ geotechnical investigations can be employed. A nondestructive test that can be used for this purpose is the spectral analysis of surface wave (SASW) test using geophones. The SASW test is a nondestructive method; however, due to the time required for data interpretation and the difficulty in analyzing the data, it is challenging to use the SASW test for monitoring applications that require frequent observations. However, it is possible to apply the first-step analysis, which yields the dispersion curve, for monitoring rather than the complete SASW analysis, which yields the shear wave velocity. Thus, this paper presents a fundamental study on the phase difference that derives the dispersion curve to utilize the SASW test for monitoring. The reliability of each phase difference interval is examined to determine the boundary to the subjected monitor. The study used phase difference data obtained using a geophone from a single-layered, homogeneous ground site to evaluate reliable boundaries. The findings of this study are expected to improve the utility of monitoring by identifying the ideal boundary for phase difference data.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.388-398
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• 2020

Watermelon yield mainly depends on soil water content controlled by irrigation in a plastic greenhouse. In this study, we investigated the effect of different soil moisture contents affected by irrigation starting point on growth, yield, and physiological responses of small-sized watermelons. Irrigation was initiated at 5 different levels of soil water content as a starting point with soil moisture detecting sensor after 14 days of transplanting, and stopped at 7 ~ 10 days before harvest. These treatments were compared with the conventional periodic irrigation as control. When soil had the lowest moisture content (-50 kPa), the overall shoot growth was retarded, but the root length and root dry weight increased. The photosynthetic parameters (photosynthetic rate, stomatal conductance, and transpiration rate) of watermelon leaves decreased significantly in the lowest soil moisture content (-50 kPa). On the other hand, the photosynthetic rates of watermelon leaves grown with irrigation starting point between -20 and -40 kPa were observed to be higher than those of other treatments. Fruit set rate and marketable fruit yield increased significantly at -30 kPa and -40 kPa. Proline, abscisic acid (ABA), total phenol and citrulline, which are known to contribute to stress tolerance under drought condition, increased as soil water content decreased, particularly, the largest increases were recorded at -50 kPa. From these results, it was found that an appropriate water supply adjusted with an irrigation starting point between -30 and -40 kPa could help to keep favorable soil water content during the cultivation of small-sized watermelons, promoting the marketable fruit production as well as inducing the vigorous plant growth and reproductive development.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

• Korean Journal of Heritage: History & Science
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• v.48 no.3
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• pp.4-29
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• 2015

To protect cultural heritages from damage and destruction, evaluating the crime prevention environments is considered extremely important. This study analyzed the crime patterns related to cultural heritages, classified the crime environments by their types, and deduced the elements of the CPTED(Crime Prevention Through Environment Design), aiming to present the indices for evaluating the crime prevention environments. The results of this study can be summarized as follows. First, the crimes related to cultural heritages that must be prevented were identified as the night time trespassing and arson. According to the results of the analysis of external environments based on crime actions, the crime prevention environments of cultural heritages were classified into 10 types. Second, the important evaluation principles of the cultural heritage CPTED were the access control, surveillance reinforcement and the surrounding environment. Third, the access control that cover the internal region, boundary, external region and surroundings were classified into 22 indices. The surveillance reinforcement covers natural, organized and mechanical surveillance with 21 indices. Fourth, the applicability of the CPTED evaluation index was presented according to the types of the cultural crime prevention environments. The results confirmed that the maximum 43 indices were applicable to the seowon(lecture hall), hyanggyo(Confucian school), and gwana(district government office), and the minimum 10 indices, to the ramparts. Finally, the 43 indices were applied to Donam Seowon to validate their applicability. The results confirmed that most of the indices were applicable with the partial supplements. The evaluation index presented in this study is likely to contribute to studies in the cultural heritage CPTED field and to the protection of cultural heritages. Furthermore, this study is considered significant because it unleashed continuous concerns on and developments of CPTED. However, as the field survey to validate the applicability of the indices was limited to only one type, it may require further objective verification such as through an expert's examination of the validity and applicability of the evaluation index. In addition, to accommodate the index in related policies and systems, more precise verifications of the indices by type are considered necessary.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.258-267
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• 2020

The agrivoltaic can produce electricity and grow crops on fields at the same time. It is necessary to analyze the cultivation environment and evaluate the crop productivity under agrivoltaic because the shading point changes according to structure of agrivoltaic and sun's position. Two types of "fixing" and "tracing" agrivoltaic were installed, and a rice cultivation experiment was conducted in the fields under each agrivoltaic and without shading (control). "Hyunpoombyeo" was transplanted on June 7, 2019, and grown with fertilization of 9.0-4.5-5.7 kg/10a (N-P-K). Fifteen weather stations were installed under each agrivoltaic to measure solar radiation and temperature, and yield and yield-related elements were investigated by points. The accumulated solar radiation during the rice growing season in fixing was no much difference between points, and that in tracing was much difference between points. However, the average solar radiations of two agrivoltaics were similar. The mean temperature, yield, and yield-related elements showed a significant difference for the shading rate, and decreased with increasing the shading rate except ripening grain rate and 1000 grain weight of fixing agrivoltaic. In the relationship between shading rate and yield, fixing and tracing were fitted to a logistic equation and a simple linear equation, respectively, and showed a high correlation (tracing: R2 = 0.62, fixing: R2 = 0.73). The shading rate variation by point for two types was large despite similar yield variation. Thus, it needs to be more closely examined the relationship of the shading rate for a specific period rather than the shading rate during the whole growing season.