• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.244-255
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• 2022

This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.365-384
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• 2024

The development of scanning technology is accelerating for safer and more efficient automated inspection than human-based inspection. Research on automatically detecting facility damage from images collected using computer vision technology is also increasing. The pixel size, quality, and quantity of an image can affect the performance of deep learning or image processing for automatic damage detection. This study is a basic to acquire high-quality raw image data and camera performance of a mobile tunnel scanning system for automatic detection of damage based on deep learning, and proposes a method to quantitatively evaluate image quality. A test chart was attached to a panel device capable of simulating a moving speed of 40 km/h, and an indoor test was performed using the international standard ISO 12233 method. Existing image quality evaluation methods were applied to evaluate the quality of images obtained in indoor experiments. It was determined that the shutter speed of the camera is closely related to the motion blur that occurs in the image. Modulation transfer function (MTF), one of the image quality evaluation method, can objectively evaluate image quality and was judged to be consistent with visual observation.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.55-62
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• 2015

Purpose Various methods for reducing radiation exposure have been continuously being developed. The aim of this study is to evaluate effectiveness of dose reduction, image quality and PET SUV changes by applying combination of automatic exposure dose(AEC), automated dose-optimized selection of X-ray tube voltage(CAREkV) and sinogram affirmed iterative reconstruction(SAFIRE) which can be controled by user. Materials and Methods Torso, AAPM CT performance and IEC body phantom images were acquired using biograph mCT64, (Siemens, Germany) PET/CT scanner. Standard CT condition was 120 kV, 40 mAs. Radiation exposure and noise were evaluated by applying AEC, CAREkV(120 kV, 40 mAs) and SAFIRE(120 kV, 25 mAs) with torso phantom compare to standard CT condition. And torso, AAPM and IEC phantom images were acquired with combination of 3 methods in condition of 120 kV, 25 mAs to evaluate radiation exposure, noise, spatial resolution and SUV changes. Results When applying AEC, CTDIvol and DLP were decreased by 50.52% and 50.62% compare to images which is not applying AEC. mAs was increased by 61.5% to compensate image quality according to decreasing 20 kV when applying CAREkV. However, CTDIvol and DLP were decreased by 6.2% and 5.5%. When reference mAs was the lower and strength was the higher, reduction of radiation exposure rate was the bigger. Mean SD and DLP were decreased by 2.2% and 38% when applying SAFIRE even though mAs was decreased by 37.5%(from 40 mAs to 25 mAs). Combination of 3 methods test, SD decreased by 5.17% and there was no significant differences in spatial resolution. And mean SD and DLP were decreased by 6.7% and 36.9% compare to 120 kV, 40 mAs with AEC. For SUV test, there was no statistical differences(P>0.05). Conclusion Combination of 3 methods shows dose reduction effect without degrading image quality and SUV changes. To reduce radiation exposure in PET/CT study, continuous effort is needed by optimizing various dose reduction methods.

• Journal of the korean academy of Pediatric Dentistry
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• v.32 no.3
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• pp.416-426
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• 2005

Intravenous sedation have many advantages of rapid onset and recovery, ability of control sedation levels and duration through titration. Midazolam is most commonly used intravenous medication for sedation in pediatrics, endoscopy, oncologic procedures and so on. But in dentistry, midazolam intravenous sedation is usually for adult, and there are few reports for children. Todays, children who need sedation become more and older, intravenous sedation technique is going a matter of concern in pediatric dentistry. The purpose of this paper is to evaluate the efficacy of sedation and clinical success for different initial dosage of midazolam in intravenous sedation for pediatric dental patients. 16 healthy children (male 10, female 6), mean age $54.7{\pm}10.7$ months, who needed at least two separate treatment visits requiring local anesthesia were chosen for this study. Every children were taken 0.3mg/kg, maximum 5mg of midazolam by intramuscular route, and then 30~50% $N_2O-O_2$ for 10 minutes was given. On every visits, one of the following 2 different initial dosage was given by intravenous route : (1) Group I : 0.1mg/kg Midazolam (2) Group II : 0.2mg/kg Midazolam. Additional dosage was half of the first dose. Physiologic parameters (oxygen saturation, heart rate, respiratory rate, end-tidal carbon dioxide pressure) was recorded by ten procedure steps. Behavior was videotaped and rated using Ohio State University Behavioral Rating Scale and Automated Counting System by one investigator, blind to administered dosage. After the treatment, operator evaluated the clinical success. Physiologic parameters were stable and within normal range during treatment in both groups. The analyzed sedative effect, in behavioral evaluation, ratio of favorable Quiet was higher in group II, and clinical success rate of group II was better than group I. Induction time was rapid in group II, and recovery time was rapid in group I. And there was no statistically difference between two groups in every results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Journal of the Ergonomics Society of Korea
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• v.36 no.2
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• pp.87-108
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• 2017

Objective: The purpose of this study was to precede the acceptance study based on automation steps and user experience that was lacked in the past study on the core technology of autonomous vehicle, ADAS. The first objective was to construct the acceptance model of ADAS technology that is the core technology, and draw factors that affect behavioral intention through user experience-based evaluation by applying driving simulator. The second one was to see the change of factors on automation step of autonomous vehicle through the UX/UA score. Background: The number of vehicles with the introduction of ADAS is increasing, and it caused change of interaction between vehicle and driver as automation is being developed on the particular drive factor. For this reason, it is becoming important to study the technology acceptance on how driver can actively accept giving up some parts of automated drive operation and handing over the authority to vehicle. Method: We organized the study model and items through literature investigation and the scenario according to the 4 stages of automation of autonomous vehicle, and preceded acceptance assessment using driving simulator. Total 68 men and woman were participated in this experiment. Results: We drew results of Performance Expectancy (PE), Social Influence (SI), Perceived Safety (PS), Anxiety (AX), Trust (T) and Affective Satisfaction (AS) as the factors that affect Behavioral Intention (BI). Also the drawn factors shows that UX/UA score has a significant difference statistically according to the automation steps of autonomous vehicle, and UX/UA tends to move up until the stage 2 of automation, and at stage 3 it goes down to the lowest level, and it increases a little or stays steady at stage 4. Conclusion and Application: First, we presented the acceptance model of ADAS that is the core technology of autonomous vehicle, and it could be the basis of the future acceptance study of the ADAS technology as it verifies through user experience-based assessment using driving simulator. Second, it could be helpful to the appropriate ADAS development in the future as drawing the change of factors and predicting the acceptance level according to the automation stages of autonomous vehicle through UX/UA score, and it could also grasp and avoid the problem that affect the acceptance level. It is possible to use these study results as tools to test validity of function before ADAS offering company launches the products. Also it will help to prevent the problems that could be caused when applying the autonomous vehicle technology, and to establish technology that is easily acceptable for drivers, so it will improve safety and convenience of drivers.

• Journal of Periodontal and Implant Science
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• v.26 no.3
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• pp.771-778
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• 1996

The assessment of alveolar bone changes on dental radiographs to indicate progression of periodontal diseases or healing response to therapy is routine procedure. However, the diagnostic accuracy in detecting small alveolar bone changes is very limited. Recently, guided bone regeneration therapy is popular, but the quantification of new bone is somewhat difficult with conventional evaluation method. To quantificate the amount of new bone, various evaluating methods have been introduced including histomorphometry, radiomorphometry, biochemical analysis, X-ray probe microanalysis, scanning electron microscope backscatter method. In this study, guided bone regeneration using resorbable membrane with & without PDGF-BB is quatificated through histomorphmetry to evaluate the efficacy of histomorphometric analysis. 4 beagle dogs and 8 Sprague-Dawley rats were selected as experimental animals. In beagle dog experiment, $4{\times}4mm$ Class II defects were created in maxillary both second premolars, and biodegradable membrane containing PDGF-BB(experimental group) were covered over one defect, and same membrane without PDGF-BB(control group) were covered over the other defect. At 2 weeks, 5 weeks after surgery, each beagle dogs were sacrificed, and the tissues were treated by undecalcified fixation. In Sprague-Dawley rat experiment, 5mm round defect were created in temporal bone, the same membranes were covered on the defects. At 1 week, 2 weeks after surgery, each rats were sacrificed, and undecalcified fixation were taken. After grinding tissue specimen, we analyse them histomorphometrically using image analysis system. In beagle dog 2 weeks specimens, new bone formation area were $0.03123mm^2$ in experimental group,and $0.03012mm^2$ in control group. At 5 weeks specimens, $0.15324mm^2$ in experimental group, and $0.09123mm^2$ in control group. In Sprague-Dawley rat specimens, new bone fomation area were $0.20448mm^2$ in 1 week experimental group, $0.03604mm^2$ in 1 week control group. At 2 weeks specimens, $0.46349mm^2$ in experimental group, $0.17741mm^2$ in control group. The results indicated that histomorphometric analysis of new bone formation using image analysis system is very effective quantification method to evaluate the efficacy of treatment modalities.

• Journal of Environmental Health Sciences
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• v.42 no.2
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• pp.85-91
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• 2016

Objectives: The objective of this study was to assess heat stress, compare heat stress indices, and evaluate the usefulness of wet bulb globe temperature (WBGT) among outdoor workers exposed to heat during the summer season. Methods: WBGT, dry temperature, and heat index were measured using WBGT measurers (QUESTemp 32 model and QUESTemp 34 model, QUEST, WI, USA) by industrial hygienists from August 27 to September 16, 2015. Heat stress indices were measured at the workplaces of a shipbuilder in Ulsan and a construction site in Daegu. The dry temperature observed by the Automated Synoptic Observing System (ASOS) of the Korea Meteorological Administration was also compared. Results: Dry temperature measured by WBGT is different from that by ASOS. The temperature obtained from ASOS was less than $33^{\circ}C$, above which point a heat wave is forecast by the Korea Meteorological Administration. A heat index above $32.8^{\circ}C$ as a moderate risk was not observed during measurement. WBGT was consistently higher than $22^{\circ}C$, above which the risk of heat-related illness is increased in unacclimated workers involved in work with a high metabolic rate. WBGT was sometimes higher than $28^{\circ}C$, above which the risk of heat-related illness is increased in acclimated workers involved in work with a moderate metabolic rate in September. Conclusion: According to the measurement of heat stress indices, WBGT was more sensitive than heat index and temperature. Thus, general measures to prevent heat-related diseases should be implemented in workplaces during the summer season according to WBGT.