• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.3
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• pp.342-351
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• 2016

This study was carried out to develop an optimized analytical method using high-performance liquid chromatography (HPLC) applied to canthaxanthin, which is not yet designated as a food colorant in Korea, as well as to perform validation and uncertainty evaluation of this method. Official methods of AOAC, UK, and Japan with HPLC-UV detection were evaluated for the analysis of canthaxanthin by comparison of linearity, resolution, selectivity, limit of detection (LOD), limit of quantitation (LOQ), accuracy, precision, recovery, inter-laboratory tests, and uncertainty measurement. The calibration curves showed high linearity with an $R_2$ value of over 0.999 for canthaxanthin standard solutions in all three official methods. The official method of Japan exhibited the best results in terms of resolution and selectivity, including the lowest LOD and LOQ. The average coefficients of variation were calculated as less than five of three institutes with a precision value less than 1, accuracy near 100%, and recovery ratio between $100{\pm}10%$. The expanded uncertainty for canthaxanthin was estimated to be $39.5{\pm}5.29mg/kg$ (95% confidence level, k=2), and the uncertainty of measurement was 13.4%. In this study, official methods of canthaxanthin were compared and the validities verified. The results will be further applied to establish an authorized analytical method for canthaxanthin in Korea.

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.330-334
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• 2021

BACKGROUND: More recently, it has been shown that atmospheric ammonia (NH₃) plays a primary role in the formation of secondary particulate matter by reacting with the acidic species, e.g. SO₂, NOx, to form PM2.5 aerosols in the atmosphere. The Jeonbuk region is an area with high concentration of particulate matter. Due to environmental changes in the Saemangeum reclaimed land with an area of 219 km², it is necessary to evaluate the impact of the particulate matter and atmospheric ammonia in the Jeonbuk region. METHODS AND RESULTS: Atmospheric ammonia concentrations were measured from June 2020 to May 2021 using a passive sampler and CRDS analyzer. Seasonal and annual atmospheric ammonia concentration measured using passive sampler was significantly lower in Jangjado (background concentration), and the concentration ranged from 11.4 ㎍/m³ to 18.2 ㎍/m³. Atmospheric ammonia concentrations in Buan, Gimje, Gunsan, and Wanju regions did not show a significant difference, although there was a slight seasonal difference. The maximum atmospheric ammonia concentration measured using the CRDS analyzer installed in the IAMS near the Saemangeum reclaimed land was 51.5 ㎍/m³ in autumn, 48.0 ㎍/m³ in summer, 37.6 ㎍/m³ in winter, and 32.7 ㎍/m³ in spring. The minimum concentration was 4.9 ㎍/m³ in spring, 4.2 ㎍/m³ in summer, and 3.5 ㎍/m³ in autumn and winter. The annual average concentration was 14.6 ㎍/m³. CONCLUSION(S): Long term monitoring of atmospheric ammonia in agricultural areas is required to evaluate the formation of fine particulate matter and its impact on the environment. In addition, continuous technology development is needed to reduce ammonia emitted from farmland.

• Safety and Health at Work
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• v.10 no.2
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• pp.237-244
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• 2019

Background: Street vendors spend relatively more time near roadways and are vulnerable to air pollution related health disorders. However, there is limited information on the quality of the air they breathe. The objectives of this present study were to calculate the mass concentration of atmospheric particulate matter (PM) in eight size fractions ($PM_{0.4-0.7}$, $PM_{0.7-1.1}$, $PM_{1.1-2.1}$, $PM_{2.1-3.3}$, $PM_{3.3-4.7}$, $PM_{4.7-5.8}$, $PM_{5.8-9.0}$, and $PM_{9.0--0{\mu}m}$) at commercial (CML) and residential site (RSL) in Dehradun city from November 2015 to May 2016. To estimate the corresponding respiratory deposition dose (RDDs) in alveolar (AL), tracheobronchial (TB), and head airway (HD) region on street vendors working at CML and RSL. To find the association of atmospheric PM with RDDs and the incidence of respiratory related disorders among street vendors. Methods: Andersen cascade impactor was employed for calculating the PM mass concentration. Questionnaire based health survey among street vendors were carried out through personal interview. Results: A significant difference (p < 0.05; t-test) between the mean $PM_{0.4-10{\mu}m}$ mass concentration at CML and RSL was observed with ($mean{\pm}SD$) $84.05{\pm}14.5$ and $77.23{\pm}11.7{\mu}g\;m^{-3}$, respectively. RDDs in AL, TB and HD region at CML was observed to be 9.9, 7.8, and 7.3% higher than at RSL, respectively. Health survey revealed 1.62, 0.96, 0.04, and 0.57 times higher incidence of cold, cough, breathlessness, and chest pain, respectively with street vendors at CML compared to RSL. Conclusion: The site characteristics plays a major role in the respiratory health status of street vendors at Dehradun.

• Journal of Korean Society on Water Environment
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• v.34 no.6
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• pp.632-641
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• 2018

Algal dynamics is controlled by multiple environmental factors such as flow dynamics, water temperature, trophic level, and irradiance. Underwater irradiance penetrating from the atmosphere is exponentially decreased in water column due to absorption and scattering by water molecule and suspended particles including phytoplankton. As the exponential decrease in underwater irradiance affects algal photosynthesis, regulating their spatial distribution, it is critical to understand the light extinction characteristics to find out the mechanisms of algal dynamics more systematically. Despite the significance, the recent data have been rarely reported in the main stream areas of large rivers, Korea. In this study, the euphotic depths and light extinction coefficients were determined by monitoring the vertical variation of underwater irradiance and water quality in the main channel of Nakdong River near Dodong Seowon once a week during summer of 2016. The average values of euphotic depth and light extinction coefficient were 4.0 m and $1.3m^{-1}$, respectively. The degree of light extinction increased in turbid water due to flooding, causing an approximate 50 % decrease in euphotic depth. Also, the impact was greater than the self-shading effect during the periods of cyanobacterial bloom. The individual light extinction coefficients for background, total suspended solid and algal levels, frequently used in surface water quality modeling, were determined as $0.305m^{-1}$, $0.090m^{-1}/mg{\cdot}L^{-1}$, $0.013m^{-1}/{\mu}g{\cdot}L^{-1}$, respectively. The values estimated in this study were within or close to the ranges reported in literatures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.119-135
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• 2022

This paper used dynamic centrifuge tests to examine the seismic response for a deep temporary retaining wall with four input motions of 100, 1,000, and 2,400 years of return periods. The centrifuge model was designed based on an actual deep excavation design with a 50 m maximum excavation depth. The model backfill was prepared with dry silica sand at a relative density of 55%, and the retaining wall was modeled as a 24.8 m height diaphragm wall supported by struts. Acceleration response was amplified at the backfill surface, top of the wall, and near bedrock. However, in the middle of the model, input motion was de-amplified. The member forces of the wall and strut induced by the seismic load, which excited, were compared with the member force at rest condition. The wall's maximum negative and positive moments were increased to 36% and 10% compared to the maximum moment at rest. The maximum axial force increases to 70% of the at rest axial force on the bottom strut. The equivalent static analysis using Mononobe-Okabe (M-O) and Seed-Whitman (S-W) seismic earth pressures were compared to the centrifuge results. Considering the bending moment, the analysis results with the M-O theory underestimates but that with the S-W theory overestimates.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.585-596
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• 2022

This study determined major factors influencing landslide occurrence along a forest road near Sangsan village, Sancheok-myeon, Chungju-si, Chungcheongbuk-do, South Korea. Within a 2 km radius of the study area, landslides occur intensively during periods of heavy rainfall (August 2020). This makes study of the area advantageous, as it allows examination of the influence of only geological and tomographic factors while excluding the effects of rainfall and vegetation. Data for 82 locations (37 experiencing landslides and 45 not) were obtained from geological surveys, laboratory tests, and geo-spatial analysis. After some data preprocessing (e.g., error filtering, minimum-maximum normalization, and multicollinearity), structural equation model (SEM) and logistic regression (LR) analyses were conducted. These showed the regolith thickness, porosity, and saturated unit weight to be the factors most influential of landslide risk in the study area. The sums of the influence magnitudes of these factors are 71% in SEM and 83% in LR.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.243-248
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• 2022

The purpose of this paper is to etching SUS MASK by adding an additive (F300) to FeCl3. The equipment used in the experiment is a self-made automatic liquid management system. The automatic liquid management system is a device capable of controlling the Oxidation Reduction Potential (ORP) and specific gravity in real time and supplying FeCl3 and additives in a quantitative manner. SUS MASK was etched in units from 10 sheets up to 200 sheets for 1 minute. It was confirmed that when the initial SUS MASK was 10 sheets, the ORP value started with 628 mV and measured at 611 mV from the time of 40 sheets being injected, and maintained close to 610 mV up to 200 sheets. The specific gravity was maintained near 1.640. And the SUS MASK was measured close to 0.4 mm from 50 sheets to 200 sheets. The experimental conditions of ORP had a specific gravity of 610 mV, 1.463, an etching pressure of 3.0 kg/cm2, an additive (F300) ratio of 1.2%, and the hole size was measured by up to 200 sheets of 10 sheets at once etching. As a result, the diameter approached 0.4 mm from 20 sheets. Even if the number of SUS MASK was increased, the ORP and specific gravity were well controlled, and it was confirmed that the experimental target value was close to 0.4 mm.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.