• Journal of Soil and Groundwater Environment
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• v.26 no.4
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• pp.27-43
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• 2021

Since climate factors, such as precipitation, temperature, etc., show repeated patterns every year, it can be said that future changes can be predicted by analyzing past climate data. As with groundwater, seasonal variations predominate. Therefore, when a drought occurs, the groundwater level is also lowered. Thus, a change in the groundwater level can represent a drought. Like precipitation, groundwater level changes also have a high correlation with drought, so many researchers use Standard Groundwater Level Index (SGI) to which the Standard Precipitation Index (SPI) method is applied to evaluate the severity of droughts and predict drought trends. However, due to the strong interferences caused by the recent increase in groundwater use, it is difficult to represent the droughts of regions or entire watersheds by only using groundwater level change data using the SPI or SGI methods, which analyze data from one representative observation station. Therefore, if the long-term groundwater level changes of all the provinces of a watershed are analyzed, the overall trend can be shown even if there is use interference. Thus, future groundwater level changes and droughts can be more accurately predicted. Therefore, in this study, it was confirmed that the groundwater level changes in the last 5 years compared with the monthly average groundwater level changes of the monitoring wells installed before 2015 appeared similar to the drought occurrence pattern. As a result of analyzing the correlation with the water storage yields of 3,423 agricultural reservoirs that do not immediately open their sluice gates in the cases of droughts or floods, it was confirmed that the correlation was higher than 56% in the natural state. Therefore, it was concluded that it is possible to re-evaluate agricultural droughts through long-term groundwater level change analyses.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.71-78
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• 2023

In general, electric submersible pumps (ESPs), which have an average life of 1.0 to 1.5 years, experience a decrease in performance and a reduction in life of the pump depending on oil and gas reservoir characteristics and operating conditions in wells. As the result, the failure of ESP causes high well workover costs due to retrieval and installation, and additional costs due to shut down. In this study, a flow loop system was designed and established to predict the life of ESP in long­term operation of oil and gas wells, and the life cycle data of ESP from the time of installation to the time of failure was acquired and analyzed. Among the data acquired from the system, flow rate, inlet and outlet temperature and pressure, and the data of the vibrator installed on the outside of ESP were analyzed, and then the performance status according to long-term operation was classified into five stages: normal, advice I, advice II, maintenance, and failed. Through the experiments, it was found that there was a difference in the data trend by stage during the long­term operation of the ESP, and then the condition of the ESP was diagnosed and the failure of the pump was predicted according to the operating time. The results derived from this study can be used to develop a failure prediction program and data analysis algorithm for monitoring the condition of ESPs operated in oil and gas wells.

• Smart Media Journal
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• v.12 no.10
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• pp.93-101
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• 2023

Climate change has emerged as a global problem, with frequent temperature increases, droughts, and floods, and it is predicted that it will have a great impact on the characteristics and productivity of crops. Cnidium officinale is used not only as traditionally used herbal medicines, but also as various industrial raw materials such as health functional foods, natural medicines, and living materials, but productivity is decreasing due to threats such as continuous crop damage and climate change. Therefore, this paper proposes a model that can predict the physiologically active ingredient index according to the climate change scenario of Cnidium officinale, a representative medicinal crop vulnerable to climate change. In this paper, data was first augmented using the CTGAN algorithm to solve the problem of data imbalance in the collection of environment information, physiological reactions, and physiological active ingredient information. Column Shape and Column Pair Trends were used to measure augmented data quality, and overall quality of 88% was achieved on average. In addition, five models RF, SVR, XGBoost, AdaBoost, and LightBGM were used to predict phenol and flavonoid content by dividing them into ground and underground using augmented data. As a result of model evaluation, the XGBoost model showed the best performance in predicting the physiological active ingredients of the sacrum, and it was confirmed to be about twice as accurate as the SVR model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.525-535
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• 2023

In thi study, we unveil the intricate interplay among picophytoplankton (0.2-2 ㎛) communities, warming surface water temperatures, and major inorganic nutrients within the southwestern East Sea from 2003-2022. The observed surface temperature rise, reflecting global climate trends, defies conventional seasonal patterns in temperate seas, with highest temperatures in summer and lowest in spring. Concurrently, concentrations of major dissolved inorganic nutrient display distinct seasonality, with peaks in winter and gradually declining thereafter during spring. The time course of chlorophyll-a concentrations, a proxy for phytoplankton biomass, reveals a typical bimodal pattern for temperate seas. Notably, contributions from picophytoplankton exhibited a steady annual increase of approximately 0.5% over the study period, although the total chlorophyll-a concentrations declined slightly. The strong correlations between picophytoplankton contributions and inorganic nutrient concentrations is noteworthy, highlighting their competitively advantageous responsiveness to the shifting nutrient regime. These findings reflect significant ecological implications for the scientific insights into the marine ecosystem responses to changing climate conditions.

• The Journal of the Petrological Society of Korea
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• v.12 no.3
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• pp.119-134
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• 2003

Yuksipryeong two-mica granite presents strongly peraluminous characteristics in both mineralogy and geochemistry. It has high aluminum saturation index with 1.15∼l.20 and high corundum with 2.20∼2.98 wt% CIPW norm. As the color index is <16% and FeO$\^$T/+ MgO + TiO$_2$is average 1.9 wt％, it corresponds to leucogranite. Yuksipryeong two-mica leucogranite shows negative linear trend for TiO$_2$, Al$_2$O$_3$, FeO, Fe$_2$O$_3$, MgO, CaO, K$_2$O, P$_2$O$\_$5/, Rb, Ba, and Sr as SiO$_2$increases, and the positive relation of Zr and Th, which result from feldspar, biotite, apatite and zircon fractionation. Pegmatitic dike has higher SiO$_2$and P$_2$O$\_$5/, but lower another major elements. Yuksipryeong two-mica leucogranite has lower Rb, but higher Ba and Sr than Manaslu, Hercynian two-mica leucogranites, and S-type granites in Lachlan Fold Belt. Pegmatitic dike has higher Rb and Nb but lower Ba, Sr, Zr, Th, and Pb contents than Yuksipryeong two-mica leucogranite, resulting in removing or mobilizing for some trace elements from the granitic melt. Yuksipryeong two-mica leucogranite has total REEs with 95.7∼l23.3 ppm, and chondrite-normalized REE pattern is very steep ((La/Yb)$\_$N/ = 6.9∼24.8), light REEs (LREEs)-enriched End heavy REEs (HREEs)- depleted pattern with low to moderate Eu anomalies (Eu/Eu＊= 0.7∼0.9). While pegmatitic dike has low total REEs with 7.0 ppm, and chondrite-normalized REE pattern is flat-pattern ((La/Yb)$\_$N/ = 2.1) with strong negative Eu anomalies (Eu/Eu＊= 0.2). The melt compositions having formed two-mica leucogranites depend on not only the source rock but also the amounts of the residual remaining after melting of source rocks. The CaO/Na$_2$O and Rb/Sr-Rb/Ba ratios depend mainly on the composition of source rocks in the strongly peraluminous granite, that is, plagioclase/clay ratio of the source rocks. Yuksipryeong two-mica leucogranite has higher CaO/Na$_2$O and lower Rb/Sr-Rb/Ba ratios than Manaslu and Hercynian two-mica leucogranites (Millevaches and Gueret) derived from clay-rich, plagioclase-poor (polite), which suggest that the probable source rocks for Yuksipryeong two-mica leucogranite is clay-poor, plagioclase-rich quartzofeldspathic rocks. As the concentrations of Al$_2$O$_3$remain nearly constant but those of TiO$_2$increases as increasing temperature in the strong peraluminous melt, the Al$_2$O$_3$/TiO$_2$ratio may reflect relative temperature at which the melts have formed. Comparing the polite-derived Manaslu and Hercynian two- mica leucogranites, Manaslu two-mica leucogranite has higher Al$_2$O$_3$/TiO$_2$ratio than latter, and its melt have formed at relatively lower temperature ($\leq$ 875$^{\circ}C$) than Hercynian two-mica leucogranites. Likewise, comparing the quartzofeldspathic rock-derived granites, Yuksipryeong two-mica granite has higher Al$_2$O$_3$/TiO$_2$, ratio than S-type granites in Lachlan Fold Belt (>875$^{\circ}C$). The melt formed Yuksipryeong two-mica leucogranite are considered to have been formed at temperature at below the maximum 875$^{\circ}C$C$.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.396-402
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• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.24-35
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• 2016

To assess the relationship between environmental factors and seasonal phytoplankton community structure, we investigated abiotic and biotic factors in Ulsan Bay, Korea. We divided the bay into two areas based on geographical characteristics and compared the difference in each factor between inner and outer bay with t-test statistics. As a result, temperature in the outer bay was higher than that of the inner bay during winter (t = -5.833, p < 0.01) and autumn (p > 0.05). However, opposite trend was observed during spring (t = 4.247, p < 0.01) and summer (t = 2.876, p < 0.05). Salinity was significantly lower in the inner bay than in the outer bay in winter, spring, and summer (p < 0.01). However, the salinity was not significantly different between the inner and the outer bay in the autumn (p > 0.05). In particular, high nutrient concentration was observed in most stations during winter season due to vertical well mixing. The nutrient concentration was significantly higher in surface layers of inner bay after rainfall, particularly in the summer. The relative contribution (approximately 70%) of < $20{\mu}m$ (nano and pico) size phytoplankton was increased in all seasons with continuously low nutrients from the offshore water due to their adaption to low nutrient without other large competitors. Interestingly, high population of Eutreptiella gymnastica was kept in the inner bay during the spring and summer associated with high DIN (nitrate+nitrite, ammonium) after river discharge following rainfall, suggesting that DIN supply might have triggered the increase of Eutreptiella gymnastica population. In addition, high density of freshwater species Oscillatoria sp. and Microcystis sp. were found in several stations of the inner bay that were provided with large amounts of freshwater from the Tae-wha River. Diatom and cryptophyta species were found to be dominant species in the autumn and winter. Of these, centric diatom Chaetoceros genus was occupied in the outer bay in the autumn. Cryptophyta species known as opportunistic micro-algae were found to have high biomass without competitors in the inner bay. Our results demonstrated that Ulsan Bay was strongly affected by freshwater from Tae-wha River during the rainy season and by the surface warm water current from the offshore of the bay during dry season. These two external factors might play important roles in regulating the seasonal phytoplankton community structures.

• Korean Journal of Plant Resources
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• v.21 no.1
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• pp.36-40
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• 2008

To product grafts and construct its spread-system effectively, this study was carried out to investigate into effects on the survival percentage and growth in walnut trees(Juglans sinensis Dode) according to transplanting type and post-epicotyl grafting treatment. In the average survival percentage of the grafting according to post-epicotyl grafting transplanting type, TPGB1(transplanting in grafting bed) showing 89.02% was highest. Also, the survival percentage was different from appropriate temperature and humidity within treatment. As a result of the average survival percentage of the grafting by species, KWN-3 having 81.59% was highest with high survival percentage of total treatment in general. In addition, it is concluded that the nutrition condition of scions and collecting parts are strongly related to survival percentage on having significantly difference of its survival percentage by species. The growth rate of the survival grafts by transplanting type after grafting revealed that all of the investigation items(height and diameter growth of grafts, diameter growth of scions and etc.) resulted in same trend. TPGB1 having the highest tree height growth, 15.97cm($2.0{\sim}59.0cm$), showed the highest growth on diameter growth of shoots, 7.55mm($1.65{\sim}14.71mm$), and scions, 8.12mm($1.82{\sim}13.58mm$), as well. In the growth of each treatment according to different developing parts of shoots in grafts, the lateral bud, 12.05cm, was much superior to the terminal bud,9.57cm, on only graft height growth. However, the survival rate according to collecting parts of scions and developing parts of shoots with same treatment was not different with among-species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.