• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1281-1293
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• 2021

The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (R_rs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for R_rs at 490 nm and 550 nm (RMSE~0), the underestimation of R_rs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II R_rs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.795-805
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• 2021

In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m³/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.109-121
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• 2021

As the global COVID-19 pandemic is prolonged, the Corona Blue phenomenon, combined with COVID-19 and blue, is intensifying. The purpose of this study is to analyze the current trend of Corona Blue in consideration of the possibility of increasing mental illness and the need for countermeasures, especially after COVID-19. This study tried to find out the relationship between stress and leisure activities before and after COVID-19 by using Corona Blue news article analysis through the topic modeling method, and questionnaire find out the help of stress and leisure activities. This study was compared and analyzed using two research methods. First, a total of 363 news articles were analyzed through topic modeling based on newspaper articles from January 2020, when COVID- 19 was upgraded to the "border" stage, until September, where the social distancing stage was strengthened to stage 2.5 in Korea. As a result of the study, a total of 28 topics were extracted, and similar topics were grouped into 7 groups: mental-demic, generational spread, causes of depression acceleration, increased fatigue, attitude to coping with long-term wars, changes in consumption, and efforts to overcome depression. Second, the SPSS statistical program was used to analyze the level of stress change according to leisure activities before/after COVID-19 and the main help according to leisure activities. As a result of the study, it was confirmed that the average difference in stress reduction according to participation in leisure activities before COVID-19 was larger than after COVID-19. Also, leisure activities were found to be effective in stress relief even after COVID-19. In addition, if the main help from leisure activities before COVID-19 was the meaning of relaxation and recharging through physical and social activities. After COVID-19, psychological roles such as mood swings through nature, outdoor activities, or intellectual activities were found to play a large part. As such, in this study, it was confirmed that understanding the current status of Corona Blue and coping with leisure in extreme stress situations has a positive effect. It is expected that this research can serve as a basis for preparing realistic and desirable leisure policies and countermeasures to overcome Corona Blue.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1143-1154
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• 2021

The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

• Publications of The Korean Astronomical Society
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• v.36 no.3
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• pp.47-63
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• 2021

Variability is one of the major characteristics of Active Galactic Nuclei (AGN), and it is used for understanding the energy generation mechanism in the center of AGN and/or related physical phenomena. It it known that there exists a time lag between AGN light curves simultaneously observed at different wavelengths, which can be used as a tool to estimate the size of the area that produce the radiation. In this paper, We present long term near-infrared variability of optically bright type 1 AGN using the Wide-field Infrared Survey Explorer data. From the Milliquas catalogue v6.4, 73 type 1 QSOs/AGN and 140 quasar candidates are selected that are brighter than 18 mag in optical and located within 5 degree around the ecliptic poles. Light curves in the W1 band (3.4 ㎛) and W2 band (4.6 ㎛) during the period of 2010-2019 were constructed for these objects by extracting multi-epoch photometry data from WISE and NEOWISE all sky survey database. Variability was analyzed based on the excess variance and the probability P_var. Applying both criteria, the numbers of variable objects are 19 (i.e., 26%) for confirmed AGN and 12 (i.e., 9%) for AGN candidates. The characteristic time scale of the variability (τ) and the variability amplitude (σ) were derived by fitting the DRW model to W1 and W2 light curves. No significant correlation is found between the W1/W2 magnitude and the derived variability parameters. Based on the subsample that are identified in the X-ray source catalog, there exists little correlation between the X-ray luminosity and the variability parameters. We also found four AGN with changing W1-W2 color.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.664-674
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• 2021

The relevance of this scientific research is determined by the negative impact of the COVID-19 pandemic on the current trends and dynamics of world tourism development. This article aims to identify patterns of development of the modern tourist market, analysis of problems and prospects of development in the context of the COVID-19 pandemic. Materials and methods. General scientific methods and methods of research are used in the work: analysis, synthesis, comparison, analysis of statistical data. The analysis of the viewpoints of foreign and domestic authors on the research of the international tourist market allowed us to substantiate the actual directions of tourism development due to the influence of negative factors connected with the spread of a new coronavirus infection COVID-19. Economic-statistical, abstract-logical, and economic-mathematical methods of research were used during the process of study and data processing. Results. The analysis of the current state of the tourist market by world regions was carried out. It was found that tourism is one of the most affected sectors from COVID-19, as, by the end of 2020, the total number of tourist arrivals in the world decreased by 74% compared to the same period in 2019. The consequence of this decline was a loss of total global tourism revenues by the end of 2020, which equaled $1.3 trillion. 27% of all destinations are completely closed to international tourism. At the end of 2020, the economy of international tourism has shrunk by about 80%. In 2020 the world traveled 98 million fewer people (-83%) relative to the same period last year. Tourism was hit hardest by the pandemic in the Asia-Pacific region, where travel restrictions are as strict as possible. International arrivals in this region fell by 84% (300 million). The Middle East and Africa recorded declines of 75 and 70 percent. Despite a small and short-lived recovery in the summer of 2020, Europe lost 71% of the tourist flow, with the European continent recording the largest drop in absolute terms compared with 2019, 500 million. In North and South America, foreign arrivals declined. It is revealed that a significant decrease in tourist flows leads to a massive loss of jobs, a sharp decline in foreign exchange earnings and taxes, which limits the ability of states to support the tourism industry. Three possible scenarios of exit of the tourist industry from the crisis, reflecting the most probable changes of monthly tourist flows, are considered. The characteristics of respondents from Ukraine, Germany, and the USA and their attitude to travel depending on gender, age, education level, professional status, and monthly income are presented. About 57% of respondents from Ukraine, Poland, and the United States were planning a tourist trip in 2021. Note that people with higher or secondary education were more willing to plan such a trip. The results of the empirical study confirm that interest in domestic tourism has increased significantly in 2021. The regression model of dependence of the number of domestic tourist trips on the example of Ukraine with time tendency (t) and seasonal variations (Turˆt = 7288,498 - 20,58t - 410,88∑5) it forecast for 2020, which allows stabilizing the process of tourist trips after the pandemic to use this model to forecast for any country. Discussion. We should emphasize the seriousness of the COVID-19 pandemic and the fact that many experts and scientists believe in the long-term recovery of the tourism industry. In our opinion, the governments of the countries need to refocus on domestic tourism and deal with infrastructure development, search for new niches, formats, formation of new package deals in new - domestic - segment (new products' development (tourist routes, exhibitions, sightseeing programs, special rehabilitation programs after COVID) -19 in sanatoriums, etc.); creation of individual offers for different target audiences). Conclusions. Thus, the identified trends are associated with a decrease in the number of tourist flows, the negative impact of the pandemic on employment and income from tourism activities. International tourism needs two to four years before it returns to the level of 2019.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• 한국노년학
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• v.38 no.4
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• pp.1035-1055
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• 2018

The purpose of this study is to investigate the relationship between public care and family care. Public care for older adults began in 2008 with the implementation of the Long-Term Care insurance in South Korea. Although the expansion of public care has the purpose of reducing the care burden for the family, it is not easy to say whether the developments of public care system reduce the amount of family care for older family members. Theoretically, public care and family care are expected to have various relationships depending on the degree of the role and function(substitution, hierarchical compensatory, task specific, supplementation, complementarity). And literatures have showed inconsistent results depending on the country, data, and methods. In this study, we analyzed the relationship between two care types focusing on home care services for older persons. Analyses were based on data from the second(2008) to sixth(2016) waves of Korean Longitudinal Study of Ageing(KLoSA). To investigate elderly care dynamics in the households, we pooled the data for four changes between two periods(2008-2010, 2010-2012, 2012-2014, and 2014-2016). This study used an analytic sample of 262 older adults, who are aged 55 over and experienced public care at least one point of time. We used Fixed-Effects(FE) model to analyze the differences within the same individuals under the condition that time-invariant unobserved factors are controlled. This study distinguished the cases of entry into public care and other cases of exiting public care. The results showed that older people who are dependent on public care are less dependent on family care than before. In both entry and exit groups, negative relations were maintained, but in the entering stage of public care, the degree of negative relations was relatively small, whereas in the stage of maintaining or departing from public care, relatively negative relations were strong. At the beginning periods, even though public care increased, family care did not decrease significantly. On the other hand, at the time of ending public care and relying on family care, family care increased significantly. The results of this study show that the relationship between public care and family care is close to hierarchical compensatory model and varies according to the stage of caring transition. Also, it was found that the cases of transition from public care to family care have the biggest burden of elderly care than other groups.

• 한국사회정책
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• v.25 no.3
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• pp.37-71
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• 2018

Since 2016, public and political interest on basic income has been increased beyond academic interest. The recent debate on basic income has expanded on issues regarding to the concrete implementation of basic income moving further than the debate on conception of the basic income in the abstract level. This study examines major critiques of basic income which was raised from social policy area and makes a counter-argument on these critiques. Major points summarized as follows. First, the problem of jobs and social insurance exclusion is not serious enough to call for basic income. Second, existing social security systems will be crowded out by excessive financial burden if basic income is introduced. Third, policies to cultivate citizens' capacities to cope with a technological change should be given priority over basic income. This study disputes these critiques by counter arguing four points. First, it is necessary to reconstruct welfare state based on basic income, given the labor market changes, such as long-term trend of employment change, newly emerging employment of platform companies, and inconsistency of platform labor and social insurance. Second, hypothesis of crowding-out effect on social security system is just a criticism that can be applied to the basic income initiative of the right-wing. Also, it is unable to find a logical basis or evidence of this hypothesis from the historical process of welfare state development or previous studies. Third, it is necessary to discuss how to reconfigure existing social security system and basic income which are complementary to each other and also have consistency with labor market as a configuration, not as a matter of choosing between basic income and social security system. Fourth, de-laborization does not mean a refusal to labor but a free choice, and the basic principle of social security is not needs but right. In conclusion, in order to develop more productive debate on basic income, it requires more sophisticated discussion and criticism from the point of view of the distributive justice; the debate on the sustainability of social insurance-centered welfare states; and debates on the political realization of basic income.

• 한국노년학
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• v.38 no.3
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• pp.569-592
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• 2018

This study purported to investigate the current state of human rights of older adults residing in rural areas of Korea. The study utilized, as an analytic framework, 4 priority directions (1. "older persons and development", 2. "rural area development", 3. "advancing health and well-being into old age", and 4. "ensuring enabling and supportive environments") with 13 task actions recommended by Madrid International Plan of Action on Ageing (MIPAA). Furthermore, the study examined gender differences in all items included in the analytic framework. Data was collected by the face-to-face survey on 800 subjects aged 65 and over. Statistical analyses were conducted using STATA 13.0 program. The main results were summarized in order of 4 priority directions as follows. First, average working hours per day were 6.2, and men reportedly participated in economic activities and needed job training more than women, while women participated in lifelong education programs more than men. Awareness of fire and disaster prevention facilities was low in both genders. Second, accessibility to the support center for the elderly living alone as well as protective services for the vulnerable elderly was found to be low. IT-based services and networking were used more by men than women, and specifically, IT-based financial transactions and welfare services were least used. Third, medical check-ups and vaccinations were well received, while consistent treatments for chronic illnesses and long-term care services were relatively less given. In addition, accessibility to mental health service centers was considerably low. Fourth, although old house structures and the lack of convenience facilities were found to be circumstantial risk factors for these elders, experiences of receiving housing support services were scarce. The elderly were found to rely more on informal care, and concerns for their care were higher in women than men. Plus, accessibility to elderly abuse services was markedly low. Based on these results, discussed were implications for implementing policies and practical interventions to raise the levels of the human rights for this population.