• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.1-13
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• 2009

Alkalinity and total carbon contents were measured by acid neutralizing titration (ANT), back titration (BT), gravitational weighing (GW), non-dispersive infrared-total carbon (NDIR-TC) methods for assessing precision and accuracy of alkalinity and total carbon concentration in $CO_2$-rich water. Artificial $CO_2$-rich water(ACW: pH 6.3, alkalinity 68.8 meq/L, $HCO_3^-$ 2,235 mg/L) was used for comparing the measurements. When alkalinity measured in 0 hr, percent errors of all measurement were 0~12% and coefficient of variation were less than 4%. As the result of post-hoc analysis after repeated measure analysis of variance (RM-AMOVA), the differences between the pair of methods were not significant (within confidence level of 95%), which indicates that the alkalinity measured by any method could be accurate and precise when it measured just in time of sampling. In addition, alkalinity measured by ANT and NDIR-TC were not change after 24 and 48 hours open to atmosphere, which can be explained by conservative nature of alkalinity although $CO_2$ degas from ACW. On the other hand, alkalinity measured by BT and GW increased after 24 and 48 hours open to atmosphere, which was caused by relatively high concentration of measured total carbon and increasing pH. The comparison between geochemical modeling of $CO_2$ degassing and observed data showed that pH of observed ACW was higher than calculated pH. This can be happen when degassed $CO_2$ does not come out from the solution and/or exist in solution as $CO_{2(g)}$ bubble. In that case, $CO_{2(g)}$ bubble doesn't affect the pH and alkalinity. Thus alkalinity measured by ANT and NDIR-TC could not detect the $CO_2$ bubble although measured alkalinity was similar to the calculated alkalinity. Moreover, total carbon measured by ANT and NDIR-TC could be underestimated. Consequently, it is necessary to compare the alkalinity and total carbon data from various kind of methods and interpret very carefully. This study provide technical information of measurement of dissolve $CO_2$ from $CO_2$-rich water which could be natural analogue of geologic sequestration of $CO_2$.

• Korean journal of applied entomology
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• v.58 no.2
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• pp.89-99
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• 2019

In total, 654,362 adult mosquitoes were captured using black light traps in Gangwon-do Province of the Republic of Korea from 2012 to 2017. The collected mosquitoes were identified to the species level, placed in pools of up to 50 mosquitoes each, by species and date of collection, and screened for flaviviruses using a reverse transcription-polymerase chain reaction assay. A total of 276,224 adult mosquitoes were grouped in 7,721 pools for virus testing, and 68 flavivirus positive pools (0.9%) were detected. Flavivirus-positive products were confirmed by DNA sequencing. Japanese encephalitis viruses were detected in single pools collected from Chuncheon (2012, 2017: Culex pipiens, 2,728 and 1,111 mosquitoes, respectively), Hoengseong (2013: Culex orientalis, 19), and Gangneung (2017: C. pipiens, 724). All the Japanese encephalitis viruses detected were revealed as genotype V. Chaoyang viruses were detected in 63 pools of 5,055 Aedes vexans nipponii and a single pool of 585 C. pipiens collected in Gangwon-do Province from 2012 to 2017. Chuncheon was the region with the highest minimum infection rates (MIR, 0.32) and maximum likehood estimate (MLE, 0.33; confidence interval (CI) 95%, 0.23-0.46) of A. vexans nipponii for Chaoyang virus, followed by Hoengseong (MIR 0.30, MLE 0.30, CI 0.16-0.52) and Gangneung (MIR 0.21, MLE 0.21, CI 0.13-0.31). Monthly MIR and MLE values of A. vexans nipponii for Chaoyang virus were the highest in October (MIR 0.38, MLE 0.38, CI 0.07-1.25).

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.285-294
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• 2022

In order to accurately calculate greenhouse gas emissions in the agricultural field, Korea has been developing national-specific emission factors through direct measurement of gas fluxes using the closed-chamber method. In the rice paddy, only national-specific emission factors for methane (CH₄) have been developed. It is thus necessary to develop those for nitrous oxide (N₂O) affected by the application of nitrogen fertilizer. However, since the concentration of N₂O emission from rice cultivation is very low, the QA/QC methods such as method detection and practical quantification limits are important. In this study, N₂O emission from a rice paddy was evaluated affected by the amount of nitrogen fertilizer, by taking into account both method detection and practical quantification limits for N₂O concentration. The N₂O emission from a rice paddy soils affected by the nitrogen fertilizer application was estimated in the following order. The method detection limit (MDL) of N₂O concentration was calculated at 95% confidence level based on the pooled standard deviation of concentration data sets using a standard gas with 98 nmol mol^-1 N₂O 10 times for 3 days. The practical quantification limit (PQL) of the N₂O concentration is estimated by multiplying 10 to the pooled standard deviation. For the N₂O flux data measured during the rice cultivation period in 2021, the MDL and PQL of N₂O concentration were 18 nmol mol^-1 and 87 nmol mol^-1, respectively. The measured values above the PQL were merely about 12% of the total data. The cumulative N₂O emission estimated based on the MDL and PQL was higher than the cumulative emission without nitrogen fertilizer application. This research would contribute to improving the reliability in quantification of the N₂O flux data for accurate estimates of greenhouse gas emissions and uncertainties.

• Korean Journal of Community Nutrition
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• v.28 no.1
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• pp.38-47
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• 2023

Objectives: This study examined the association between the experience of disease management education and the use of nutrition labels according to the sociodemographic characteristics and health behaviors of people diagnosed with hypertension and diabetes living in the community. Methods: Among the participants from the Community Health Survey (2018), 74,283 individuals diagnosed with hypertension or diabetes were included in the study population. According to gender, this study evaluated nutrition label use by the experience of disease management education, individual sociodemographic characteristics, and health behavior. Finally, using multiple logistic regression analysis, the association between disease management education and nutrition labels was calculated using the odds ratio (OR) and 95% confidence interval (CI). Results: Males (24.5%) experienced more disease management education than females (22.6%). In addition, younger age, higher education level, and higher equalized personal income experienced more disease management education (P < 0.001). The educational experience rate was higher in the male subjects who did not smoke or were involved in high-risk alcohol consumption (P < 0.001). In addition, the rate of disease management education experience was significantly higher for both men and women who exercised by walking (P < 0.001). The use of nutrition labels was higher in females (9.9%) than males (5.8%), and both males and females were significantly higher in young age, high education, high income, and professional and office positions (P < 0.001). The utilization rate of nutrition labels was high in non-smoking male subjects and high-risk-drinking female subjects. In addition, the utilization rate of nutrition labels was significantly higher in males and females who exercised by walking and those who experienced disease management education (P < 0.001). After adjusting for individual sociodemographic characteristics, health behavior, and disease management education, the use of nutrition labels was high among females (OR 3.19, 95% CI 2.85-3.58), high income (Q4; OR 1.62, 95% CI 1.41-1.87, Q5; OR 1.58, 95% CI 1.37-1.84) and highly educated (high school; OR 2.87, 95% CI 2.62-3.14, above college; OR 5.60, 95% CI 5.02-6.23) while it was low in the elderly (OR 0.43, 95% CI 0.40-0.47), and economically inactive (OR 0.86, 95% CI 0.76-0.96). The use of nutrition labels was high in non-smokers (OR 1.29, 95% CI 1.13-1.48), nonhigh-risk drinkers (OR 1.22, 95% CI 1.08-1.38), and subjects who exercised walking (OR 1.44, 95% CI 1.34-1.54). There was no difference in the utilization rate of nutrition labels according to obesity, and the utilization rate of nutrition labels was significantly higher in subjects who had experienced disease education (OR 1.34, 95% CI 1.24-1.44). Conclusions: Education on the use of nutrition labels, which contributes to food selection for healthy eating, might be a tool for dietary management. Moreover, the utilization rate can be a good indicator for predicting the proportion of the population practicing the guide for disease management. Improving the utilization rate of nutrition labels through disease management education can be a useful intervention for people with chronic diseases who need healthy eating habits for disease management and preventing complications, particularly those diagnosed with hypertension and diabetes.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.54-69
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• 2023

Purpose: Proteins are major components of the body and essential nutrients for proper growth and development. However, studies on protein intake in children and adolescents are insufficient. A few previous studies have reported the relationship with growth indicators, but results vary depending on the source of protein. Therefore, the current study investigates the relationship between protein intake and overweight and obesity among children and adolescents in Korea. Methods: Based on the 2014-2019 Korea National Health and Nutrition Examination Survey, 5,567 children and adolescents aged 6-18 years, who participated in a 24-hour dietary recall with information on height and weight, were included in this study. Protein intake was estimated as percentage of total energy (% of energy) and was classified into animal and plant protein according to the food source. Overweight and obesity were defined using the 2017 pediatric and adolescent growth chart. Results: Total protein intake of the subjects was estimated as 14.5% of total energy (animal protein 8.3% and plant protein 6.3%). The group with the highest total protein intake had a higher odds ratio (OR) of overweight/obesity than those with the least protein intake (OR, 1.36, 95% confidence interval (CI), 1.10-1.67, p for trend = 0.003). When classified by food source, the group with the highest animal protein intake had a significantly higher OR of overweight/obesity than subjects with the lowest intake (OR, 1.30, 95% CI, 1.05-1.61, p for trend = 0.016). However, plant protein was not significantly associated with overweight/obesity. Conclusions: These findings suggest that a high intake of animal protein in children and adolescents increases the risk of being overweight and obese. In order to develop normal growth and prevent obesity in the future, it is necessary to determine an appropriate protein intake level through nutrition education programs and prospective studies on balanced protein intake.

• Economic Analysis
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• v.27 no.4
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• pp.70-119
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• 2021

This paper analyzes the changes in financial reform during the Kim Jong-un era based on North Korean literature. We find that North Korea has systematically and functionally separated the central bank from commercial banks since the Kim Jong-un era began. In addition, enterprises have been allowed to withdraw cash from bank accounts and make inter-enterprise cash payments. In other words, nowadays non-cash currencies with passive money can partially serve as active money with purchasing power. With the systematic and functional separation of the central bank and the commercial bank, the issuance of the central bank changed to a money supply method through the commercial bank, and changes in the currency distribution structure have allowed commercial bank's credit creation function to be implemented. This means that the banking system and the monetary·payment system of the socialist planned economy are changing in the way of the market economy. Reforms in the financial sector are believed to have been necessary to support changes in the economic system and to restore the function of the public financial sector. These changes have progressed in terms of the level of reform, but they are still considered similar to the period of the former Soviet Union's Perestroika or to the early period of China's reform and opening. Although North Korea's financial reform is superior in terms of enacting the banking law, it is insufficient in terms of realizing the functions of commercial banks. In addition, it is assessed that institutional constraints such as maintaining a planned economy, and the lack of confidence in public finances limit the effectiveness and development of the financial system. It should be noted that these results are based on literature published in North Korea. In other words, there is a limit in the fact that such recent changes have been carried out on a trial basis in some areas, or have been carried out in a full-scale manner with a blueprint, since Kim Jong-un's inauguration.

• Journal of Gastric Cancer
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• v.23 no.2
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• pp.315-327
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• 2023

Purpose: Oxaliplatin, a component of the capecitabine plus oxaliplatin (XELOX) regimen, has a more favorable toxicity profile than cisplatin in patients with advanced gastric cancer (GC). However, oxaliplatin can induce sensory neuropathy and cumulative, dose-related toxicities. Thus, the capecitabine maintenance regimen may achieve the maximum treatment effect while reducing the cumulative neurotoxicity of oxaliplatin. This study aimed to compare the survival of patients with advanced GC between capecitabine maintenance and observation after 1st line XELOX chemotherapy. Materials and Methods: Sixty-three patients treated with six cycles of XELOX for advanced GC in six hospitals of the Catholic University of Korea were randomized 1:1 to receive capecitabine maintenance or observation. The primary endpoint was progression-free survival (PFS), analyzed using a two-sided log-rank test stratified at a 5% significance level. Results: Between 2015 and 2020, 32 and 31 patients were randomized into the maintenance and observation groups, respectively. After randomization, the median number of capecitabine maintenance cycles was 6. The PFS was significantly higher in the maintenance group than the observation group (6.3 vs. 4.1 months, P=0.010). Overall survival was not significantly different between the 2 groups (18.2 vs. 16.5 months, P=0.624). Toxicities, such as hand-foot syndrome, were reported in some maintenance group patients. Maintenance treatment was a significant factor associated with PFS in multivariate analysis (hazard ratio, 0.472; 95% confidence interval, 0.250-0.890; P=0.020). Conclusions: After 6 cycles of XELOX chemotherapy, capecitabine maintenance significantly prolonged PFS compared with observation, and toxicity was manageable. Maintenance treatment was a significant prognostic factor associated with PFS.