• Journal of Mushroom
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• v.21 no.3
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• pp.145-149
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• 2023

This study was conducted to reduce the phenomenon of the biased cultivation of certain mushroom varieties and to develop a competitive variety of Pleurotus nebrodensis. We have collected and tested characteristics of genetic resources from domestic and overseas varieties since 2015. We bred the domestic variety 'Boram'. The optimal temperature was 26~29℃ for mycelial growth and 15~18℃ for fruit body growth temperature. This variety was similar to the control variety (Uram) in terms of the number of cultivation days and yield per bottle. The shape of the new cultivar was round, whereas that of the control group was spatula-like. The yield was 181.1 g/bottle, which was statistically similar to that of the control variety. When incubating the parent and control varieties, the replacement line was clear. Moreover, polymerase chain reaction analysis of mycelial DNA resulted in different band patterns between the parent and control varieties, confirming the hybrid species.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.69-76
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• 2023

To improve the financial stability of the National Pension, an appropriate target rate of return should be established based on pension liabilities, and asset allocation policies should be formulated accordingly. The purpose of this study is to calculate the target rate of return considering the contributions of subscribers and the pension benefits, and based on this, derive an asset allocation. To do this, we utilized the internal rate of return methodology to calculate the target rate of return for each cohort. And then, we employed a Monte Carlo simulation-based re-sampling mean-variance model to derive asset allocation for each cohort that satisfy the target rate of return while minimizing risks. Our result shows that the target rate of return for each cohort ranged from 6.4% to 6.85%, and it decreased as the generations advanced due to a decrease in the income replacement rate of the National Pension. Consequently, the allocation of risky assets, such as stocks, was relatively reduced in the portfolios of future generations. This study holds significance in that it departs from the macroeconomic-based asset allocation methodology and proposes investments from an asset-liability management perspective, which considers the characteristics of subscribers' liabilities.

• Korean Circulation Journal
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• v.54 no.6
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• pp.325-335
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• 2024

Background and Objectives: The number of sensitized heart failure patients on waiting lists for heart transplantation (HTx) is increasing. Using the Korean Organ Transplantation Registry (KOTRY), a nationwide multicenter database, we investigated the prevalence and clinical impact of calculated panel-reactive antibody (cPRA) in patients undergoing HTx. Methods: We retrospectively reviewed 813 patients who underwent HTx between 2014 and 2021. Patients were grouped according to peak PRA level as group A: patients with cPRA ≤10% (n= 492); group B: patients with cPRA >10%, <50% (n=160); group C patients with cPRA ≥50% (n=161). Post-HTx outcomes were freedom from antibody-mediated rejection (AMR), acute cellular rejection, coronary allograft vasculopathy, and all-cause mortality. Results: The median follow-up duration was 44 (19-72) months. Female sex, re-transplantation, and pre-HTx renal replacement therapy were independently associated with an increased risk of sensitization (cPRA ≥50%). Group C patients were more likely to have longer hospital stays and to use anti-thymocyte globulin as an induction agent compared to groups A and B. Significantly more patients in group C had positive flow cytometric crossmatch and had a higher incidence of preformed donor-specific antibody (DSA) compared to groups A and B. During follow-up, group C had a significantly higher rate of AMR, but the overall survival rate was comparable to that of groups A and B. In a subgroup analysis of group C, post-transplant survival was comparable despite higher preformed DSA in a desensitized group compared to the non-desensitized group. Conclusions: Patients with cPRA ≥50% had significantly higher incidence of preformed DSA and lower freedom from AMR, but post-HTx survival rates were similar to those with cPRA <50%. Our findings suggest that sensitized patients can attain comparable post-transplant survival to non-sensitized patients when treated with optimal desensitization treatment and therapeutic intervention.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.2
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• pp.103-111
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• 2008

This study was carried out to investigate the optimal application rate and time of mixed expeller cake (MEC) for the replacement of chemical fertilizer. Dongjin-1, as cultivated rice was used at Fluvio-marine deposit in Honam plain paddy field. Soil chemical properties were improved by the application of MEC. Contents of total nitrogen and organic matter were higher in 70%, 100% plots of basal dressing than standard fertilizer application (SFA) plot. Cation exchangeable capacity was highly increased in 70% plot of basal dressing. Also, the content of organic matter in soil was increased with MEC application. Cation exchangeable capacity, total nitrogen and available phosphate were decreased according to late application time. The content of inorganic nitrogen in soil showed high tendency at more application rate of MEC, and nitrogen mineralization at harvest season have finished in 50%, 70% plots of basal dressing. The content of inorganic nitrogen in soil was increased according to late application time, however it was decreased in the late period of growth. Leaf color value became darker with increased application rate of MEC. Leaf color was dark green in MEC application plots at panicle formation stage, on the other hand, it was light green in 50%, 70% plots of basal dressing at heading stage. SPAD reading value of leaf-color was high during the whole growth stage in MEC application plots. More application rate of MEC showed higher tendency of fertilizer nitrogen absorption. Nitrogen use efficiency was the highest in 70% plot of basal dressing. Absorbed amount of fertilized nitrogen was increased in 10~15days before transplanting and nitrogen use efficiency was high according to the late application time. The ratio of perfect kernel and the content of protein on hulled rice showed high tendency at the less application rate of MEC. The ratio of head rice on milled rice showed high tendency at the less application rate of MEC. Rice yield increased 4% in 100% and 70% plots of basal dressing compare with SFA ($5.18Mg\;ha^{-1}$) plot respectively. Ear and culm length of rice were long according to the late application time, while the numbers of spikelet and ear were increased and the percentage of ripened grain was decreased. Rice yield was increased 2~5% in all MEC application plots compared to SFA plot and especially, increased 10~15days before transplanting in application plots. The optimal application rate and time of MEC on normal paddy field in plain were concluded that 70% basal dressing and 10~15days before transplanting

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1092-1099
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• 2022

Research on exhaust aftertreatment devices to reduce air pollutants and greenhouse gas emissions is being actively conducted. However, in the case of the particulate matters/nitrogen oxides (PM/NOx) simultaneous reduction device for ships, the problem of back pressure on the diesel engine and replacement of the filter carrier is occurring. In this study, for the optimal design of the integrated device that can simultaneously reduce PM/NOx, an appropriate standard was presented by studying the flow inside the device and change in back pressure through the inlet/outlet pressure. Ansys Fluent was used to apply porous media conditions to a diesel particulate filter (DPF) and selective catalytic reduction (SCR) by setting porosity to 30%, 40%, 50%, 60%, and 70%. In addition, the ef ect on back pressure was analyzed by applying the inlet velocity according to the engine load to 7.4 m/s, 10.3 m/s, 13.1 m/s, and 26.2 m/s as boundary conditions. As a result of a computational fluid dynamics analysis, the rate of change for back pressure by changing the inlet velocity was greater than when inlet temperature was changed, and the maximum rate of change was 27.4 mbar. This was evaluated as a suitable device for ships of 1800kW because the back pressure in all boundary conditions did not exceed the classification standard of 68mbar.

• Journal of Embryo Transfer
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• v.25 no.1
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• pp.15-20
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• 2010

This study was performed to identify the optimal timing for oocyte donor replacement during OPU procedure. OPU was carried out to collect oocytes from every donor at an interval of $3{\sim}4$ days (2 times a week). The collected oocytes were matured in vitro in TCM-199 supplemented with 10% FBS, 10 mg/ml of FSH and 1 mg/ml of estradiol for 24 h. After 24 h of exposure to sperm, the presumptive zygotes were cultured in CR1aa medium supplemented with 4 mg/ml of BSA for 3 days before being changed to CR1aa medium with 10% of FBS for another $3{\sim}4$ days. The mean numbers of retrieved oocytes were remained constantly up to 3 months ($6.0{\pm}0.5$, $6.2{\pm}0.7$, $5.2{\pm}0.6$), but significantly decreased at over 4 to 6 months ($3.7{\pm}0.5$, $2.8{\pm}0.4$, $1.2{\pm}0.2$) (p<0.05). The blastocyst development potential was also very similar rate from 1 to 3 months (37.2%, 40.4% and 44.6%), but significantly decreased from 4 to 6 months (24.8%, 29.3% and 28.6%, respectively) (p<0.05). The production of OPU derived embryos in periods of 1 to 3 months ($2.2{\pm}0.3$, $2.5{\pm}0.3$ and $2.3{\pm}0.4$) were significantly higher than those in 4 to 6 months ($0.9{\pm}0.2$, $0.8{\pm}0.2$ and $0.3{\pm}0.2$, respectively) (p<0.05). In conclusion, the efficient periods for the production of OPU derived embryos was until 4 months, twice per week to produce over 64 transferable embryos and then replace new donor after 3 months use. The best replacement time is 3 months and could be maximized production of OPU derived embryos.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Chest Surgery
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• v.36 no.6
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• pp.384-390
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• 2003

Background: Since Ross and Sormeville first reported the use of aortic homograft valve for correction of pulmonary atresia in 1966, homograft valves are widely used in the repair of congenital anomalies as conduits between the pulmonary ventricle and pulmonary arteries. On the basis of these results, we have used it actively. In this report, we describe our experience with the use of cryopreserved valved homograft conduits for infants and children requiring right ventricle to pulmonary artery connection in various congenital cardiac anomalies. Material and Method: Between January, 1996 and December 2001, 27 infants or children with a median age of 16 months(range 9days to 18years) underwent repair of RVOTO using homograft valved conduit by two surgeons. We studied 22 patients who have been followed up at least more than one year. The diagnosis at operation included pulmonary atresia with ventricular septal defect (n=13), truncus arteriosus (n=3), TGA or corrected TGA with RVOTO (n=6). Homograft valved conduits varied in size from 15 to 26 mm (mean, 183.82 mm). The follow-up period ranged from 12 to 80.4 months (median, 48.4 months). Result: There was no re-operation due to graft failure itself. However, early progressive pulmonary homograft valve insufficiency developed in one patient, that was caused by dilatation secondary to the presence of residual distal pulmonary artery stenosis and hypoplasia after repair of pulmonary atresia with ventricular septal defect. This patient was required reoperation (conduit replacement). During follow-up period, there were significant pulmonary stenosis in one, and pulmonary regurgitation more than moderate degree in 3. And there were mild calcifications at distal anastomotic site in 2 patients. All the calcified homografts were aortic in origin. Conclusion: We observed that cryopreserved homograft conduits used in infant and children functioned satisfactorily in the pulmonic position at mid-term follow-up. To enhance the homograft function, ongoing investigation is required to re-establish the optimal strategy for the harvest, preservation and the use of it.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.11-21
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• 2016

This study investigated the quality characteristics and retarding retrogradation of sponge cakes made with red yeast rice (RYR) flour. RYR (Monascus nuruk) is known to help digestion, smooth blood flow, and have anti-cancer, anti-microbial, and inhibitory effects against biosynthesis of cholesterol and blood pressure. This studys aim' was to find the optimal proportion of RYR flour in sponge cake. RYR sponge cakes were prepared with various levels (0, 5, 10, 15 and 20%) replacement of wheat flour and were designated as the control (without RYR), RYR5, RYR10, RYR15 and RYR20 respectively. Specific gravity was the lowest in RYR15 at 0.57, and the baking loss rate was not significantly different among the samples (p<0.05). The dough yield was the highest in RYR15 at 96.61. The moisture contents was highest in order, control, RYR5, and RYR15 at 28.67%, 28.18%, and 26.82% respectively. The L-value of crust tended to increase according to the level of RYR, but the L-value of crumb decreased in accorddance with the the content of RYR. The a-value of crust also decreased according to the level of RYR, although the a-value of crumb increased in response to higher levels of RYR. The b-value tended to decrease with increases of RYR (p<0.05). RYR5 exhibited the highest pH at 8.63, compared with RYR15 (8.57). The hardness, which was measured after cooling for 1 hour, was the lowest in RYR15 at $163.33g/cm^2$ and the springiness was not different significantly (p<0.05). Cohesiveness was the highest in RYR10 at 133.06%. The chewiness was the highest in RYR10 at $391.63g{\cdot}cm$ and lowest in RYR15 ast $169.62g{\cdot}cm$. Avrami equation showed that RYR15 and RYR20 had the lowest Avrami exponent (n) at 0.0664 and 0.4983 respectively. Time constant (1/k) was the highest in RYR15 at 200.00. Sensory evaluation revealed that RYR15 was the highest in color (5.50), flavor (4.95), sweetness (4.90), chewiness (4.75), and overall acceptability (4.60).