• Applied Chemistry for Engineering
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• v.32 no.1
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• pp.20-27
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• 2021

Effects of the etching treatment of SAPO-34 catalyst were investigated to improve the catalytic lifetime in DTO reaction. The aqueous NH3 solution was a more appropriate treatment agent which could control the degree of etching progress, compared to that of using a strong acid (HCl) or alkali (NaOH) solution. Therefore, the effect on characteristics and lifetime of SAPO-34 catalyst was observed using the treatment concentration and time of aqueous NH3 solution as variables. As the treatment concentration or time of aqueous NH3 solution increased, the growth of erosion was proceeded from the center of SAPO-34 crystal plane, and the acid site concentration and strength gradually decreased. Meanwhile, it was found that external surface area and mesopore volume of SAPO-34 catalyst increased at appropriate treatment conditions. When the treatment concentration and time were 0.05 M and 3 h, respectively, the lifetime of the treated SAPO-34 catalyst was the longest, and was significantly enhanced by ca. 36% (based on DME conversion of > 90%) compared to that of using the untreated catalyst. The model for the etching progress of SAPO-34 catalyst in a mild treatment process using aqueous NH3 solution was also proposed.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of Gastric Cancer
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• v.22 no.2
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• pp.135-144
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• 2022

Purpose: This study aimed to compare the surgical and oncological outcomes between totally laparoscopic pylorus-preserving gastrectomy (TLPPG) with intracorporeal anastomosis and laparoscopy-assisted pylorus-preserving gastrectomy (LAPPG) with extracorporeal anastomosis. Materials and Methods: A retrospective analysis was performed in 258 patients with cT1N0 gastric cancer who underwent laparoscopic pylorus-preserving gastrectomy using two different anastomosis methods: TLPPG with intracorporeal anastomosis (n=88) and LAPPG with extracorporeal anastomosis (n=170). The following variables were compared between the two groups to assess the postoperative surgical and oncological outcomes: proximal and distal margins, number of resected lymph nodes (LNs) in total and in LN station 6, operation time, postoperative hospital stay, and postoperative morbidity including delayed gastric emptying (DGE). Results: The average length of the proximal margin was similar between the TLPPG and LAPPG groups (2.35 vs. 2.73 cm, P=0.070). Although the distal margin was significantly shorter in the TLPPG group than in the LAPPG group (3.15 vs. 4.08 cm, P=0.001), no proximal or distal resection margin-positive cases were reported in either group. The average number of resected LN was similar in both groups (36.0 vs. 33.98, P=0.229; LN station 6, 5.72 vs. 5.33, P=0.399). The operation time was shorter in the TLPPG group than in the LAPPG (200.17 vs. 220.80 minutes, P=0.001). No significant differences were observed between the two groups in terms of postoperative hospital stay (9.38 vs. 10.10 days, P=0.426) and surgical complication rate (19.3% vs. 22.9%), including DGE (8.0% vs. 11.8%, P=0.343). Conclusions: The oncological safety and postoperative complications of TLPPG with intracorporeal anastomosis are similar to those of LAPPG with extracorporeal anastomosis.

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.167-194
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• 2020

In this study, we tested the hypothesis that a woman who claims sexual assault would be evaluated more negatively, and the suspected man would be judged more leniently, when the woman is agentic. In addition, we expected that this phenomenon would occur because the agentic accuser does not conform to the 'sexual crime victim' stereotype or feminine norms, and considered these as mediator variables. We also postulated that male (vs. female) participants would have a less positive regard of the agentic accuser and tested participant gender's moderating effects. Contrary to our hypothesis, participants criticized the agentic (vs. non-agentic) woman who claims sexual assault less and perceived her more positively and truthfully, and more likely to judged the suspected man to be guilty and recommended longer sentences. However, we observed the expected moderating effects of participant gender, so that male (vs. female) participants evaluated the agentic accuser more negatively. Mediation analyses yielded results on perceived truthfulness that were consistent with our hypothesis: Participants thought of agentic accuser as less feminine, which predicted less perceived truthfulness. Also, the less the agentic accuser was perceived to be feminine, male participants blamed her more while female participants had more positive impressions of her.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1191-1205
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• 2022

Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM_2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM_2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R² = 0.85 and XGB R² = 0.91, and it was confirmed that XGB was a more suitable model for PM_2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM_2.5 of Seoul was predicted using various factors, and an ensemble-based PM_2.5 prediction model showing good performance was constructed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1423-1431
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• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• 한국노년학
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• v.40 no.1
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• pp.33-49
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• 2020

This study was conducted to examine the latent classes in social exclusion and to analyse empirically the effects on the economic instability of old age by this type. And it also sought to look at whether the influence of old age anxiety varies with the subjective class consciousness of the elderly. Using the 14th data from the Korea General Social Survey (KGSS) in 2016, 1,041 adult males and females aged 18 years old were analyzed at the time of the survey. T-test, potential layer analysis (LCA), and multinomantic analysis of potential groups were conducted using the STATA14 and MPLUS 7 statistical programs. Finally, multi-regression analysis was performed to identify the moderate effect and effects among variables. According to the research, the types of social exclusion were three groups, followed by social exclusion group (49.3%), Multi-dimensional exclusion group (30.9%), and active social participation group (19.7%). The social exclusion group has the lowest possibility of economic, employment, and health exclusion, but the exclusion of formal and informal social activities seem to prominent, and the multi-dimensional exclusion group is more than 50% likely to experience exclusion in all areas. Active social participation are characterized by very active participation in informal social activities. By conducting multinominal logistic regression, it was observed that the social exclusion group included more young people than other groups, and that the multi-dimensional exclusion group included many elderly women without spouses. Finally, multiple regression analysis showed that social exclusion type interacts with subjective class consciousness and affects economic anxiety of old age.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.2
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• pp.65-81
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• 2022

Objectives This study aimed to assess the effects of oral administration of deer antler extracts on an osteoporosis-induced animal model. We analyzed the results of using deer antler single extracts on animal models with osteoporosis through a systematic review and meta-analysis. Methods We included osteoporosis studies in animal experiments that administrated deer antler extracts orally. We searched the following 13 databases without a language restriction: PubMed, EMBASE, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), Wanfang, Korean Medical Database (KMbase), National Digital Science Library (NDSL), Korean Traditional Knowledge (Koreantk), Oriental Medicine Advanced Searching Integrated System (OASIS), Research Information Sharing Service (RISS), Korea Institute of Science and Technology Information (KISTI), and Koreanstudies Information Service System (KISS). We used Systematic Review Centre for Laboratory Animal Experimentation's risk of bias tool for assessing the methodological quality of the included studies. Results A total of 299 potentially relevant studies were searched and 11 were included for a systematic review. Nine studies used a single deer antler extract. A study compared the effects of single extracts of deer antler and antler glue, while another study compared the effects of three single extracts of deer antler, old antler, and antler glue. For evaluating the intervention effect, bone mineral density (BMD) was measured as the primary outcome, while the histomorphometric indicators of the bone and serum alkaline phosphatase and osteocalcin levels were used as the secondary outcome variables. On conducting a meta-analysis of studies on single deer antler extract, BMD was observed to be significantly increased compared to that in control group (standardized mean difference [SMD]=2.11; 95% confidence interval [CI]=1.58~2.65; Z=7.75; p<0.00001; I²=56%). As a result of meta-analysis, according to the concentration of deer antler, the group with high concentration showed statistically significantly higher BMD than the group with low concentration (SMD=1.28; 95% CI=0.74~1.82; Z=4.63; p<0.00001; I²=9%). Conclusions The research shows that the deer antler extracts have significant anti-osteoporotic effects on the osteoporosis-induced animal model. However the studies included in this research had a high methodological risk of bias. This indicates the requirement of considerable attention in the interpretation of the study results.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.834-840
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• 2022

Objective : C-reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), and white blood cell (WBC) count are inflammatory markers used to evaluate postoperative infections. Although these markers are non-specific, understanding their normal kinetics after surgery may be helpful in the early detection of postoperative infections. To compliment the recent trend of reducing the duration of antibiotic use, this retrospective study investigated the inflammatory markers of patients who had received antibiotics within 24 hours after surgery according to the Health Insurance Review & Assessment Service guidelines and compared them with those of patients who had received antibiotics for 5 days, which was proven to be non-infectious. Methods : We enrolled 74 patients, divided into two groups. Patients underwent posterior lumbar interbody fusion (PLIF) at a single institution between 2019 and 2020. Group A included 37 patients who received antibiotics within 24 hours after the PLIF procedure, and group B comprised 37 patients who had used antibiotics for 5 days. A 1 : 1 nearest-neighbor propensity-matched analysis was used. The clinical variables included age, sex, medical history, body mass index, estimated blood loss, and operation time. Laboratory data included CRP, ESR, and WBC, which were measured preoperatively and on postoperative days (POD) 1, 3, 5, and 7. Results : CRP dynamics tended to decrease after peaking on POD 3, with a similar trend in both groups. The average CRP level in group B was slightly higher than that in group A; however, the difference was not statistically significant. Multiple linear regression analysis revealed operation time, number of fused levels, and estimated blood loss as significant predictors of a greater CRP peak value (r²=0.473, p<0.001) in patients. No trend (a tendency to decrease from the peak value) could be determined for ESR and WBC count on POD 7. Conclusion : Although slight differences were observed in numerical values and kinetics, sequential changes in inflammatory markers according to the duration of antibiotic administration showed similar patterns. Knowledge of CRP kinetics allows the assessment of the degree of difference between the clinical and expected values.