• Journal of Preventive Medicine and Public Health
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• v.29 no.1 s.52
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• pp.1-14
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• 1996

To evaluate the health risk of the workplace environment of a general hospital toward the hospital workers, a questionnaire survey on the perception of risk at the workplace environment and environmental measurements at 27 locations with 240 workers in the hospital were made from October 25th, 1993 to October 30th, 1994. The results were as follows ; 1. By the environmental measurements, 86 workers(36%) were found to be exposed to poor or harmful degree of general illumination, 193 workers(80%) were exposed to poor or harmful local illumination, 34 workers(14%) were exposed to poor or harmful degree of thermal condition and 180 workers(75%) were exposed to poor or harmful noise level, but nobody was exposed to poor or harmful dust and toluene concentration. Also nobody was exposed to poor or harmful level of radiation or anticancer/antibiotic agents. 2. The subjective perceptions on the environmental conditions felt by the workers were different from the objective findings by the environmental measurements. The workers underscored the poor illumination state and overscored the dust concentrations. Also workers oversensitized about the thermal condition, the noise level, the radiation level, the toluene concentration and anticancer/antibiotic agents 3. The sources of noise were the dialogue(179 workers) and the office instruments(131 workers). The sources of dust came from the clothes(108 workers) and the building materials(79 workers). 4. The questionnaire survey showed that the 28 workers were exposed to poor or harmful level of the antibiotics, 10 workers to alkali or acid and 6 workers to drug dust in the pharmacy but the above findings could not be proved by the environmental measurements.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.188-201
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• 2005

This is the first part of a two-part paper which describes comparison of reliability design methods by application to Donghae Harbor Breakwaters. This paper, Part 1, is restricted to stability of armor blocks, while Part 2 deals with sliding of caissons. Reliability design methods have been developed fur breakwater designs since the mid-1980s. The reliability design method is classified into three categories depending on the level of probabilistic concepts being employed. In the Level 1 method, partial safety factors are used, which are predetermined depending on the allowable probability of failure. In the Level 2 method, the probability of failure is evaluated with the reliability index, which is calculated using the means and standard deviations of the load and resistance. The load and resistance are assumed to distribute normally. In the Level 3 method, the cumulative quantity of failure (e.g. cumulative damage of armor blocks) during the lifetime of the breakwater is calculated without assumptions of normal distribution of load and resistance. Each method calculates different design parameters, but they can be expressed in terms of probability of failure so that tile difference can be compared among the different methods. In this study, we applied the reliability design methods to the stability of armor blocks of the breakwaters of Donghae Harbor, which was constructed by traditional deterministic design methods to be damaged in 1987. Analyses are made for the breakwaters before the damage and after reinforcement. The probability of failure before the damage is much higher than the target probability of failure while that for the reinforced breakwater is much lower than the target value, indicating that the breakwaters before damage and after reinforcement were under- and over-designed, respectively. On the other hand, the results of the different reliability design methods were in fairly good agreement, confirming that there is not much difference among different methods.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.35 no.1
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• pp.83-89
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• 1990

A sweet corn hybrid, Golden Cross Bantam 70, was grown at 0, 5, 10, 15 and 20kg/10a of nitrogen (N) under the transparent P. E. film mulch to find the best yield evaluation method. Culm length, ear height, number of tillers increased and silking date was earlier by 1-2 days with increased N level. Leaf area index of main culm at harvest increased with increased N level. Marketable ears were divided into two classes according to the whole sale market price; the frist grade of which husked ear weight over 150g (unhusked ear weight 230g) and the second grade of which husked ear weight between 100 and 150g (unhusked ear weight between 180 and 230g). Average length, thickness, and weight of both grades of marketable ears were not different among the N levels. The proportion of the first grade increased with increased N level. However, total number and weight of marketable ears and gross income per 10a calculated considering weight and number of ears increased with increased N level. There were highly positive correlations between gross income and ear number or ear weight per l0a. The number and weight of marketable ears were underestimated at high N levels compared with gross income. Dry matter yield of stover ranged 740-963kg/10a and increased with increased N level with 20. 8-24.5% dry matter content. Rice black-streaked dwarf virus infection rate was 11.8-15.0%, but it was not related to N level. N concentration in ear was similar but that in stover increased with increased N level. Total N uptake increased but N recovery decreased with increased N level.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.18 no.2
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• pp.137-146
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• 2006

This is the second of a two-part paper which describes comparison of reliability design methods by application to Donghae Harbor Breakwaters. In this paper, Part 2, we deal with sliding of caissons. The failure modes of a vertical breakwater, which consists of a caisson mounted on a rubble mound, include the sliding and overturning of the caisson and the failure of the rubble mound or subsoil, among which most frequently occurs the sliding of the caisson. The traditional deterministic design method for sliding failure of a caisson uses the concept of a safety factor that the resistance should be greater than the load by a certain factor (e.g. 1.2). However, the safety of a structure cannot be quantitatively evaluated by the concept of a safety factor. On the other hand, the reliability design method, for which active research is being performed recently, enables one to quantitatively evaluate the safety of a structure by calculating the probability of failure of the structure. The reliability design method is classified into three categories depending on the level of probabilistic concepts being employed, i.e., Level 1, 2, and 3. In this study, we apply the reliability design methods to the sliding of the caisson of the breakwaters of Donghae Harbor, which was constructed by traditional deterministic design methods to be damaged in 1987. Analyses are made for the breakwaters before the damage and after reinforcement. The probability of failure before the damage is much higher than the allowable value, indicating that the breakwater was under-designed. The probability of failure after reinforcement, however, is close to the allowable value, indicating that the breakwater is no longer in danger. On the other hand, the results of the different reliability design methods are in fairly good agreement, confirming that there is not much difference among different methods.

• Geotechnical Engineering
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• v.2 no.1
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• pp.27-44
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• 1986

The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1475-1490
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• 2021

Detecting oil spill area using statistical characteristics of SAR images has limitations in that classification algorithm is complicated and is greatly affected by outliers. To overcome these limitations, studies using neural networks to classify oil spills are recently investigated. However, the studies to evaluate whether the performance of model shows a consistent detection performance for various oil spill cases were insufficient. Therefore, in this study, two CNNs (Convolutional Neural Networks) with basic structures(Simple CNN and U-net) were used to discover whether there is a difference in detection performance according to the structure of CNN and distribution characteristics of oil spill. As a result, through the method proposed in this study, the Simple CNN with contracting path only detected oil spill with an F1 score of 86.24% and U-net, which has both contracting and expansive path showed an F1 score of 91.44%. Both models successfully detected oil spills, but detection performance of the U-net was higher than Simple CNN. Additionally, in order to compare the accuracy of models according to various oil spill cases, the cases were classified into four different categories according to the spatial distribution characteristics of the oil spill (presence of land near the oil spill area) and the clarity of border between oil and seawater. The Simple CNN had F1 score values of 85.71%, 87.43%, 86.50%, and 85.86% for each category, showing the maximum difference of 1.71%. In the case of U-net, the values for each category were 89.77%, 92.27%, 92.59%, and 92.66%, with the maximum difference of 2.90%. Such results indicate that neither model showed significant differences in detection performance by the characteristics of oil spill distribution. However, the difference in detection tendency was caused by the difference in the model structure and the oil spill distribution characteristics. In all four oil spill categories, the Simple CNN showed a tendency to overestimate the oil spill area and the U-net showed a tendency to underestimate it. These tendencies were emphasized when the border between oil and seawater was unclear.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.