• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.113-141
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• 2011

The purpose of this study was to examine the effects of home economics instruction in food labeling using a motivational(ARCS-Attention, Relevance, Confidence, and Satisfaction) strategy to increase middle school students' learning motivation, recognition and use of food labels. To achieve this purpose, teaching-learning plans of food label instruction using a motivation(ARCS) strategy were developed over four class periods using a pretest-posttest experimental design. The experiment was conducted across two groups as follows: 4 experimental groups that received the motivation(ARCS) strategy instruction, and 3 comparative groups that received lecture type instruction. The pretest-posttest scores of the experimental and comparative groups were compared. The 203 data of questionnaires for the experiment were analyzed and evaluated by Analysis of Covariance(ANCOVA) using SPSS Win 12,0. The results of this study were as follows: First, teaching-learning plans, learning materials, and teacher reference materials for the home economics food label instruction that applied the motivation(ARCS) strategy were developed in five subject areas: nutrition labels, food additives, genetically modified food, irradiated food, and food quality verification labels. Second, students' learning motivation of the two groups showed statistically meaningful differences. Home economics instruction using a motivation(ARCS) strategy was more effective in increasing students' learning motivation than lecture type instruction. Third, as a result of ANCOVA which regulated the recognition of food labels in the pre-experimental design, the recognition of food labels in the post-experimental design showed the meaningful differences depending on the instruction style(motivation strategy and lecture type instruction). In addition, comprehensibility, practical use and educational necessity of food label details showed statistically meaningful differences. Home economics instruction using motivation(ARCS) strategy was more effective than lecture type instruction in improving students' recognition of food labeling. Fourth, as a result of ANCOVA which regulated the use of food labels in the pre-experimental stage, the use of food labels in the post-experimental stage showed meaningful differences between experimental and comparative groups depending on the instruction style. Therefore, home economics instruction in food labeling using motivation(ARCS) strategy was more effective than lecture type instruction in increasing students' use of food labels.

• Korean Journal of Cognitive Science
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• v.27 no.3
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• pp.441-467
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• 2016

This fMRI study is aim to investigate effects of competitive environment in cognitive empathic process in human brain. Empathy is known as a crucial factor for human's adaptive behavior in aspects of social cognition and it is almost automatic process, on the other hand competitive situation is psychologically devastated environment to win someone for getting rewards. We hypnotized that reading and understanding of other person's mind are a specific characteristic related to survival evolutionarily, however competition would have an effect on the empathic cognitive process because of mechanisms of competition. To manipulate the competitive atmosphere, one researcher took a role of competitor against participants and they were instructed to get monetary rewards when their performance was better than a competitor. 21 participants(9 males and 12 females) performed to judge the emotional valence of the empathic task consisted of illustrated images with various situation could be experienced in real world as on $1^{st}$ person perspective in both competitive and non-competitive condition, and did same performance with objects stimulus in control condition. In order to examine the competition effects on empathic process,, hemodynamic response were obtained during fMRI session and the imaging data were analyzed to identify brain regions where responses to each condition across the two consecutive runs. Participants' reaction time in competitive condition was faster statistically significant than non-competitive one. Activation for competitive condition increased in the following areas: ACC, mPFC, SMG, thalamus extended caudate and Nacc, parahippocampal gyrus, and for non-competitive condition increased paracingulate gyrus, temporal pole, vmPFC, superior occipital gyrus. As a result of regression analysis using empathic scores as covariance, the rSMG, IFG, fusiform gyrus, thalamus, putamen were correlated with higher empathic levels, and TPJ were correlated with lower empathic scores. We suggest that these observations could mean competitive environment have an effect on neural base of cognitive empathic process.

• The Korean Journal of Nuclear Medicine
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• v.32 no.3
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• pp.225-237
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• 1998

Purpose: We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Materials and Methods: Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq $H_2^{15}O$ at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). Results: All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. Conclusion: We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory.

• Journal of Gastric Cancer
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• v.5 no.3 s.19
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• pp.152-157
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• 2005

Purpose: A total gastrectomy is generally peformed for the treatment of upper third gastric cancer. However, the optimal extent of resection for early-stage upper third gastric cancer is still controversial. In this research, we compared the nutritional status and the quality of life in patients who underwent a total gastrectomy with uncut Roux en Y esophagojejunostomy with those in patients who underwent a proximal gastrectomy with esophagogastrostomy for treatment of upper third gastric cancer. Materials and Methods: We reviewed 50 patients with no evidence of recurrent disease following curative surgery for upper third gastric cancer. Among this group, 25 patients underwent a total gastrectomy (TG) and 25 patients a proximal gastrectomy (PG). 8 TG and 4 PG patients were excluded from this study because of death, refusal to interview etc. The nutritional status was assessed by measuring body weight, serum albumin, serum hemoglobin, and serum total protein. The gastrointestinal function and the quality of life were assessed by Cuschieri grading and modified Visick qrading. Results: In analysis of covariance of age and preoperative serum albumin, PG patients demonstrated lower weight loss (P=0.038), elevated serum albumin (P=0.049), and better outcome based on modified Visick grading (P=0.016) than TG, but there were no significant differences in the serum hemoglobin change (P=0.165), serum total protein change (P=0.435), and Cuschieri grading (P=0.064) between the preoperative and the postoperative data. Conclusion: In this study, a proximal gastrectomy led to a better nutritional status and quality of life than a total gastrectomy, as judged from the low weight loss, elevated serum albumin and better modified Visick grade.

• Journal of Science Education
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• v.35 no.1
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• pp.1-12
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• 2011

The purpose of this study was to examine the effects of science class using the multimedia materials on high school students' attitude toward science. The subjects were 222 high school students. For this study, 11th graders at a high school were assigned to a comparison group and an experimental group. The experimental group was received science class using multimedia materials for 3 months. The research design was pretest-posttest control group design, the data were analyzed using PASW statistics 18.0 program. The types of multimedia materials used in experimental group were science fiction movies, science documentaries, TV programs, and Power Point presentations created by students. Before and after treatment, the attitude toward science tests were administered. Pre-tests and post-test score differences between 2 groups were analyzed by ANCOVA. The differences of attitude toward science based on gender were compared by analysis of covariance. And the perception on science class with multimedia materials were also investigated. The results of this study were as follows: First, the attitude toward science was improved significantly after applying science classes using multimedia materials. Especially, there were significant difference between pre-test and post-test in the score of attitude toward science class and attitude toward science content which were sub-area of attitude toward science. Second, there was no significant difference between female and male students in total score of attitude toward science. However, the attitude toward science, scientists and society, which was a sub-area of attitude toward science, female students scored significantly higher than male students. Third, 84% student showed a positive perception that the science class enhanced their interest in science. 69% the students responded that we had thought about Science-Technology-Society. Multimedia material types which the students prefered were science fiction movie, science documentaries, science TV programs, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Korean Journal of Psychosomatic Medicine
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• v.29 no.2
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• pp.153-161
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• 2021

Objectives : The purpose of this study is to compare bleeding tendency of selective serotonin reuptake inhibitor (SSRI) and serotonin norepinephrine reuptake inhibitors (SNRI) using platelet function analyzer (PFA-100) in patients with major depressive disorder. Methods : This study is a prospective open-label study conducted by a single institution. A total of 41 subjects diagnosed with major depressive disorder under the DSM-5 diagnostic criteria participated in this study. The subjects were classified into SSRI (escitalopram) groups and SNRI (duloxetine) groups, respectively, according to random assignments. The closure time (CT) was measured using a platelet function analyzer (PFA-100) before each antidepressant was administered and after 6 weeks. Paired-sample t-test was conducted within each group to determine whether a specific antidepressant had an effect on closure time. In order to confirm the relative change in platelet function between the two groups, an independent sample t-test was conducted to compare and analyze the change in closure time between the two groups. Results : There was no significant changes in closure time (CEPI-CT, CADP-CT) before and 6 weeks after drug administration in the SSRI and SNRI groups, and there was no difference in the amount of changes in closure time between the two groups. Conclusions : Our results showed no difference in bleeding tendency between SSRI and SNRI. This study suggests that further large-scale studies on bleeding tendency for various antidepressants are needed in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.81-94
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• 2022

This study analyzed the effect of the entrepreneurship planning course provided by an women's university in Seoul on the enhancement of the core competencies of entrepreneurship of university students. To this end, pre- and post-test of core entrepreneurship competency were conducted on 63 female university students (32 in experimental group, 31 in control group) and then the results were analyzed. The course in which the experimental group participated was a team-based project learning course and it required a team of three people to draw an entrepreneurship plan containing social problem solving as the final result. The course was operated for a total of 8 weeks. To measure the level of entrepreneurship core competency in the pre- and post- test, the survey tool that was developed by the Ministry of Education and Korea Entrepreneurship Foundation (2020) was used. This tool composed by 'value creation', 'challenge', 'self-directed', and 'group creativity' competencies. As analyses methods, i) covariance analysis was performed using the pretest as a covariate, and then a two-way ANOVA was performed with treatment (experimental group, control group) and time point (pre test, post test) as two independent variables. Results show while there was no significant difference between the experimental group and the control group in the value creation competency, it significantly contributed to the enhancement of challenge, self-directed, and collective creativity competencies. Based on these results, implications and limitations were discussed, followed by future research direction.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.68-76
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• 2012

Objectives: Sleep disorders cause changes of autonomic nervous system (ANS) which affect cardiovascular system. Primary insomnia (PI) makes acceleration of sympathetic nervous system (SNS) tone by sleep deficiency and arousal. Obstructive sleep apnea syndrome (OSAS) sets off SNS by frequent arousals and hypoxemias during sleep. We aimed to compare the changes of heart rate variability (HRV) indices induced by insomnia or sleep apnea to analyze for ANS how much to be affected by PI or OSAS. Methods: Total 315 subjects carried out nocturnal polysomnography (NPSG) were categorized into 4 groups - PI, mild, moderate and severe OSAS. Severity of OSAS was determined by apnea-hypopnea index (AHI). Then we selected 110 subjects considering age, sex and valance of each group's size [Group 1 : PI (mean age=$41.50{\pm}13.16$ yrs, AHI <5, n=20), Group 2 : mild OSAS (mean age=$43.67{\pm}12.11$ yrs, AHI 5-15, n=30), Group 3 : moderate OSAS (mean age $44.93{\pm}12.38$ yrs, AHI 16-30, n=30), Group 4 : severe OSAS (mean age=$45.87{\pm}12.44$ yrs, AHI >30, n=30)]. Comparison of HRV indices among the four groups was performed with ANCOVA (adjusted for age and body mass index) and Sidak post-hoc test. Results: We found statistically significant differences in HRV indices between severe OSAS group and the other groups (PI, mild OSAS and moderate OSAS). And there were no significant differences in HRV indices among PI, mild and moderate OSAS group. In HRV indices of PI and severe OSAS group showing the most prominent difference in the group comparisons, average RR interval were $991.1{\pm}27.1$ and $875.8{\pm}22.0$ ms (p=0.016), standard deviation of NN interval (SDNN) was $85.4{\pm}6.6$ and $112.8{\pm}5.4$ ms (p=0.022), SDNN index was $57.5{\pm}5.2$ and $87.6{\pm}4.2$ (p<0.001), total power was $11,893.5{\pm}1,359.9$ and $18,097.0{\pm}1,107.2ms^2$(p=0.008), very low frequency (VLF) was $7,534.8{\pm}1,120.1$ and $11,883.8{\pm}912.0ms^2$ (p=0.035), low frequency (LF) was $2,724.2{\pm}327.8$ and $4,351.6{\pm}266.9ms^2$(p=0.003). Conclusions: VLF and LF which were correlated with SNS tone showed more increased differences between severe OSAS group and PI group than other group comparisons. We could suggest that severe OSAS group was more influential to increased SNS activity than PI group.