• Korean Journal of Ecology and Environment
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• v.47 no.spc
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• pp.48-56
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• 2014

Weekly changes of water environments and phytoplankton community with the salinity gradients were investigated at Gyoungpo Lake from April to November in 1998 and 2012. Underwater crossam in Gyoungpo Lake was removed in 2004. Thereafter, average salinity of Gyoungpo lake increased from 7.5 ppt in 1998 to 20 ppt in 2012. A total of 99 and 80 species of phytoplankton was observed from the sampled in 1998 and 2012, respectively. The number of common species during the 2 separate years was 40. Transparency, SS, $NO_3-N$ concentration and N/P ratio in 2012 were lower than those in 1998. During the period of water shortage (April, May) of 2012 transparency decreased due to decreased salinity and increased SS and Chl. a. Correlation coefficients between species and community scores of DCA ordination based on data matrix of the phytoplankton revealed larger variation among sampling seasons in 1998 than in 2012. The increase of seawater influx and conversion rates following the removal of the underwater crossbeam might explain such a differential variation. Gymnodium sp., Peridinium sp., Prorocentrum sp., Nitzschia longissima, Schroederia setigera, Lyngbya sp., Asterococcus limneticus, Asterococcus superbus and Cyclotella meneghiniana were found to well adapt at the high salinities in 2012. Comparatively, Asterrionella formosa, Nitzschia frustulum, Chlorella ellipsoidea, Scenedesmus bijuga and Scenedesmus ellipsoideus were observed at lower salinities in 1998. Two quite contrasting phytoplankton communities were found in the two seasons of a year, spring with limited precipitation and summer, the flood season.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.3
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• pp.352-359
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• 2016

White bread added with brown rice fiber was prepared by addition of 0.005, 0.010, 0.015, and 0.020% hemicellulase. Effects on product quality and sensory evaluation were examined. There were no significant differences in pH of dough before the 1st fermentation among the experiments. Dough made by addition of hemicellulase had a significantly higher pH after the 1st fermentation compared to the control group, whereas pH of bread had reverse effects. Fermentation power of dough expansion increased as incubation time increased. Addition of hemicellulase to samples significantly increased specific volume, baking loss, and water activity compared to the control sample. Moisture content was the lowest upon addition of 0.020% hemicellulase. For color, lightness was the highest in the control bread samples, greenness of the 0.015% addition sample was the lowest and yellowness of the 0.005% addition sample was the highest. For textural characteristics, hardness, gumminess, and chewiness were maximum in the control group. Cohesiveness and springiness were not significantly different between the samples. In the sensory evaluation, color, flavor, bran flavor, bitterness, astringency, and coarseness were not significantly different among the samples. Softness and overall acceptability were highest at the 0.020% addition level but lowest at the 0.010% level. The results indicate that addition of 0.020% hemicellulase to brown rice fiber white bread is optimal for quality and provides products with reasonably high overall acceptability.

• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.191-208
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• 2018

This paper focuses on the integration aspect of operators to determine an improvement strategy for the operating system to enhance competitiveness of Busan Port. This Study proposes the following alternatives: valuation standards for the integration of operators, the road map for the integration period, the scope and role setting of integrated operators' participation of Busan Port Authority(BPA), and the separation and linkage North Port and the New Port operators. First, the valuation standards for operator integration should be based on international standards. Additionally quantitative factors such as financial situation, business performance and participating companies' profitability, and the qualitative factors such as management ability, technology, and labor relations should be considered. Second, the timing of North Port's operator integration should be prioritized in the short term in conjunction with the commencement of its phase 2-4, 2-5, and 2-6. The integration of New Port operators should provide a road map for a relatively long-term perspective. Third, the participation of BPA' integrated operators should be considered in terms of publicity as a policy coordinator between terminals and by pursuing the profitability of entering into overseas business by fostering Korean global terminal operators. The scope and role of participation ensures that the experience and technology of the terminal operation business is maximized. Fourth, because physically intergrating the North Port' operator into a single corporate form is difficult, initially establishing a special purpose company to maximize the effect of the integrated operation is necessary. Then, the operators decided to convert to a holding company given the termination of the lease term contract with the State or BPA, and ultimately proposed a merger into a single corporation.

• Journal of Korea Water Resources Association
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• v.52 no.spc2
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• pp.811-822
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• 2019

Environmental flows in the downstream sections of Yongdam Dam, Wonju Stream Dam, and Hongcheon River were estimated with selected target fish species such as Nigra for the site of Yongdam Dam, Splendidus for the site of Wonju Stream Dam, and Signifer for the site of Hongcheon River by considering endangered and domestic species. Physical habitat analysis was performed to estimate environmental flows for the study sites by applying the Physical Habitat Simulation (PHABSIM) and RIVER2D which combined hydraulic and habitat models. Based on the monitored data for ecological environment, the Habitat Suitability Index (HSI) for the target species was estimated by applying the Instream Flow and Aquatic Systems Group (IFASG). In particular, based on the result of fish monitoring, the HSI for each stage of the growth for target species was analyzed. As a result, the Weighted Usable Area (WUA) was maximized at $4.9m^3/s$ of flow discharge during spawning, $5.8m^3/s$ during the period of juvenile, and $8.9m^3/s$ during the adult fish season at the downstream section of Yongdam Dam. The result of the Wonju Stream Dam showed an optimal environmental flow of $0.4m^3/s$, $1.0m^3/s$, and $1.5m^3/s$ during the period of spawning, juvenile, and adult. The habitat analysis for the site of Hongcheon River, which is a non-regulated stream, produced an optimum environmental flow of $5m^3/s$ in the spawning period, $4m^3/s$ in the juvenile stage and $6m^3/s$ in the adult stage.

• 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.

• 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.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1091-1103
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• 2018

Having knowledge regarding to which region is prone to drought or flood is a crucial issue in water resources planning and management. This could be more challenging when the occurrence of these hazards affected by climate change. In this study the future streamflow during the wet season (July to September) and dry season (October to March) for the twenty first century of South Korea was investigated. This study used the statistics of precipitation, maximum and minimum temperature of one global climate model (i.e., INMCM4) with 2 RCPs (RCP4.5 and RCP8.5) scenarios as inputs for The Precipitation-Runoff Modelling System (PRMS) model. The PRMS model was tested for the historical periods (1966-2016) and then the parameters of model were used to project the future changes of 5 large River basins in Korea for three future periods (2025s, 2055s, and 2085s) compared to the reference period (1976-2005). Then, the different responses in climate and streamflow projection during these two seasons (wet and dry) was investigated. The results showed that under INMCM4 scenario, the occurrence of drought in dry season is projected to be stronger in 2025s than 2055s from decreasing -7.23% (-7.06%) in 2025s to -3.81% (-0.71%) in 2055s for RCP4.5 (RCP8.5). Regarding to the far future (2085s), for RCP 4.5 is projected to increase streamflow in the northern part, and decrease streamflow in the southern part (-3.24%), however under RCP8.5 almost all basins are vulnerable to drought, especially in the southern part (-16.51%). Also, during the wet season both increasing (Almost in northern and western part) and decreasing (almost in the southern part) in streamflow relative to the reference period are projected for all periods and RCPs under INMCM4 scenario.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.30-36
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• 2022

A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.