• Korean Journal of Social Welfare Studies
• /
• v.49 no.1
• /
• pp.191-219
• /
• 2018

Although several measurements of happiness at work have been developed as interest in it has grown, most of them only deal with hedonia, emotional pleasure, and there exists no measurement of eudaimonia, ultimate happiness through meaning and worthiness in Korea. This study aims to examine the validity of the Korean version of Global Hedonic and Eudaimonic Job Satisfaction (K-GHEJS) scale which covers both hedonia and eudaimonia at work. Considering the job characteristics of social work which emphasizes the values and meaning of the helping profession, online survey was performed among a total of 376 social workers. Exploratory factor analysis confirmed the goodness-of-fit of 10 items, and confirmatory factor analysis confirmed that classification as two factors of hedonic and eudaimonic job satisfaction is appropriate. The reliability was found to be high as reliability coefficient Chronbach's ${\alpha}$ was .936. This K-GHEJS scale which measures eudaimonic happiness for the first time in Korea, is expected to be useful for measuring job satisfaction of the helping professions such as social work that pursues the values and meanings of work.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.4
• /
• pp.459-466
• /
• 2018

Hazardous and Noxious Substances (HNS) are defined as substances that are likely to create a significant impact on human health and marine ecosystem when they are released into the marine environment. Recently, as the volume of HNS transported by ships increases, the rate of leakage accidents also increases. Therefore, research should be conducted to control and monitor sunken materials from the viewpoint of technology development for hazardous material leakage accident response. In this paper, acoustic detection experiments were carried out using HNS substitute materials in order to confirm the possibility of acoustic detection of sunken HNS on the sediment. The castor oil, which has a similar acoustic impedance with chloroform, is used as a substitute. 200 kHz high frequency signals were used to discriminate the reflected signals and measure reflection loss from the interface between water and castor oil. The reflection loss measured is in good agreement with the modeling results, showing a possibility of acoustic detection for sunken HNS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.4
• /
• pp.235-243
• /
• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_3
• /
• pp.1975-1984
• /
• 2021

Urban expansion results in raising the temperature in the city, which can cause social, economic and physical damage. In order to prevent the urban heat island and reduce the urban land surface temperature, it is important to quantify the cooling effect of the features of the urban space. Therefore, in order to understand the relationship between each object of land cover and the land surface temperature in Seoul, the land cover map was classified into 6 classes. And the correlation and multiple regression analysis between land surface temperature and the area of objects, perimeter/area, and normalized difference vegetation index was analyzed. As a result of the analysis, the normalized difference vegetation index showed a high correlation with the land surface temperature. Also, in multiple regression analysis, the normalized difference vegetation index exerted a higher influence on the land surface temperature prediction than other coefficients. However, the explanatory power of the derived models as a result of multiple regression analysis was low. In the future, if continuous monitoring is performed using high-resolution MIR Image from KOMPSAT-3A, it will be possible to improve the explanatory power of the model. By utilizing the relationship between such various land cover types considering vegetation vitality of green areas with that of land surface temperature within urban spaces for urban planning, it is expected to contribute in reducing the land surface temperature in urban spaces.

• Journal of Korea Water Resources Association
• /
• v.51 no.12
• /
• pp.1181-1194
• /
• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.7
• /
• pp.898-906
• /
• 2018

To investigate the effect of yellow dust on phytoplankton, a field survey and physiological experiments were carried out in the waters near Taean Peninsula from April 22 to 26, 2006, when yellow dust occurred. Phytoplankton populations during the yellow dust period were in the range of $26{\sim}290{\times}10^3cells{\cdot}L^{-1}$, a somewhat low standing crop. An increase in diatoms (a main taxonomic group), especially benthic diatoms such as Paralia sulcate, a typical species for active mixed sea water areas, was also remarkable. In addition, the Chl-a concentration after yellow dust exceeded the Chl-a concentration change range according to the tide before yellow dust. As the concentration of yellow sand increased in a yellow sand treatment experiment, primary productivity decreased, and the maximum assimilation number showed the same tendency. In the 48h culture experiment, primary productivity of the test group was lower than that of the control group at the early stage (T0) of yellow sand treatment, but after 48 hours (T48), the test group showed higher primary productivity than the control group. In particular, the primary productivity of the test group significantly increased to 321 % after 48 hours. Therefore, strong physical environment accompanied by yellow dust may temporarily inhibit the growth of phytoplankton in the waters adjacent to China in the early stage of yellow dust, but the formation of stable water mass has also been identified as a potential factor promoting the growth of phytoplankton.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.371-381
• /
• 2019

This study explored how retirement satisfaction or dissatisfaction influences on retirees' life satisfaction, comparing to workers and the gender differences were examined. The study sample was 2,609 persons (1,886 workers, 723 retirees) aged 45 or older who participated in the 1-2 waves of the Korean Longitudinal Study of Ageing (KLoSA), and the retirees were classified into continuously dissatisfied retirees and satisfied retirees during wave 1 and 2. Using SPSS 21.0, the multiple regression models were examined, and in order to clarify the gender difference, the multi-group analysis and the wald-test were conducted to test the difference of the regression coefficients according to gender using Mplus 7.3. According to the results, the life satisfaction of dissatisfied retirees was lower than that of the employed, but when satisfied with retirement, the life satisfaction was higher than that of the employed. In addition, the dissatisfied retirees in both gender were less satisfied with life than the employed, and this effect was greater in female group. However, the life satisfaction of female satisfied with retirement was higher than that of the employed, whereas the evidence of the male influence was not found to be significant. Based on the results of this study, discussion about heterogeneity of retirees and gender differences in life span were presented.

• Journal of Korean Society of Disaster and Security
• /
• v.12 no.1
• /
• pp.45-56
• /
• 2019

In this study, the seismic risk has been evaluated by setting the bedrock acceleration to 0.154g which, was taking into consideration that the earthquake return period for the buried electric power tunnels in the metropolitan area to be 1,000 years. In this case, the risk assessment during the earthquake was carried out in three stages. In the first stage, the site classification was performed based on the site investigation data of the target area. Then, the LPI(Liquefaction Potential Index) was applied using the site amplification factor. After, candidates were selected using a hazard map. In the second stage, risk assessment analysis of seismic response are evaluated thoroughly after the recalculation of the LPI based on the site characteristics from the boring logs around the electric power area that are highly probable to be liquefied in the first stage. The third Stage visited the electric power tunnels that are highly probable of liquefaction in the second stage to compensate for the limitations based on the borehole data. At this time, the risk of liquefaction was finally evaluated based off of the reinforcement method used at the time of construction, the application of seismic design, and the condition of the site.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.6
• /
• pp.384-395
• /
• 2020

Breaking waves generated by wave shoaling in coastal areas have a close relationship with various physical phenomena in coastal regions, such as sediment transport, longshore currents, and shock wave pressure. Therefore, it is crucial to accurately predict breaker index such as breaking wave height and breaking depth, when designing coastal structures. Numerous scientific efforts have been made in the past by many researchers to identify and predict the breaking phenomenon. Representative studies on wave breaking provide many empirical formulas for the prediction of breaking index, mainly through hydraulic model experiments. However, the existing empirical formulas for breaking index determine the coefficients of the assumed equation through statistical analysis of data under the assumption of a specific equation. In this paper, we applied a representative linear-based supervised machine learning algorithms that show high predictive performance in various research fields related to regression or classification problems. Based on the used machine learning methods, a model for prediction of the breaking index is developed from previously published experimental data on the breaking wave, and a new linear equation for prediction of breaker index is presented from the trained model. The newly proposed breaker index formula showed similar predictive performance compared to the existing empirical formula, although it was a simple linear equation.

• Journal of the Korea Convergence Society
• /
• v.12 no.1
• /
• pp.99-104
• /
• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.