• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.4
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• pp.71-77
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• 2021

Several cooling techinques have been studied for protecting gas turbine blades from hot gas. In terms of film-cooling techniques, various shapes of film cooling holes have been studied including fan shaped holes, which are used on gas turbine blades. However, owing to increasing demands on smaller gas turbines, a research on film-cooling holes on thin walls is required. This study was conducted at blowing ratios of 1 and 2, using numerical analysis. Through the numerical analysis, the effect of geometrical parameters on the effectiveness of fan-shaped hole film cooling was studied. Moreover, optimization was performed on three geometrical parameters: metering length, lateral expansion angle and forward expansion angle. As a result, we realized that the optimal fan-shaped holes on each blowing ratio were found to have very similar geometry and cooling performance.

• Knowledge Management Research
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• v.22 no.4
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• pp.87-101
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• 2021

ESG Investment is emerging as a trend and common sense in the financial market. ESG Investment is an investment method that simultaneously pursue social sustainability and investment returns from a long-term perspective by reflecting non-financial factors such as environment, society and governance in addition to corporate financial performance in investment decisions. This study checked how the characteristics of ESG investment have been changed after Covid-19. Afterwards, it was confirmed that Covid-19 actually acted as a negative factor in the securities market by applying VAR model. At the same time, it was demonstrated that ESG indices of the US and Korea outperformed their benchmark in terms of return and risk during the pandemic regime. The result of this study hints that the importance of ESG investment will be unchanged after Covid-19. At the same time, it suggests that managers should avoid passive ESG management and engage in strategic ESG management based on knowledge management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.64-69
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• 2022

Commercialization of public technology is the transfer of government-led scientific and technological innovation and R&D results to the private sector, and is recognized as a key achievement driving economic growth. Therefore, in order to activate technology transfer, various machine learning methods are being studied to identify success factors or to match public technology with high commercialization potential and demanding companies. However, public technology commercialization data is in the form of a table and has a problem that machine learning performance is not high because it is in an imbalanced state with a large difference in success-failure ratio. In this paper, we present a method of utilizing CTGAN to resolve imbalances in public technology data in tabular form. In addition, to verify the effectiveness of the proposed method, a comparative experiment with SMOTE, a statistical approach, was performed using actual public technology commercialization data. In many experimental cases, it was confirmed that CTGAN reliably predicts public technology commercialization success cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.15-23
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• 2022

Among the learning methods for Continuous Learning environments, "Learning without Forgetting" has fixed regularization strengths, which can lead to poor performance in environments where various data are received. We suggest a way to set weights variable by identifying the features of the data we want to learn. We applied weights adaptively using correlation and complexity. Scenarios with various data are used for evaluation and experiments showed accuracy increases by up to 5% in the new task and up to 11% in the previous task. In addition, it was found that the adaptive weight value obtained by the algorithm proposed in this paper, approached the optimal weight value calculated manually by repeated experiments for each experimental scenario. The correlation coefficient value is 0.739, and overall average task accuracy increased. It can be seen that the method of this paper sets an appropriate lambda value every time a new task is learned, and derives the optimal result value in various scenarios.

• Journal of Microbiology and Biotechnology
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• v.31 no.12
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• pp.1624-1631
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• 2021

Prodigiosin as a high-valued compound, which is a microbial secondary metabolite, has the potential for antioxidant and anticancer effects. However, the large-scale production of functionally active Hahella chejuensis-derived prodigiosin by fermentation in a cost-effective manner has yet to be achieved. In the present study, we established carbon source-optimized medium conditions, as well as a procedure for producing prodigiosin by fermentation by culturing H. chejuensis using 10 L and 200 L bioreactors. Our results showed that prodigiosin productivity using 250 ml flasks was higher in the presence of glucose than other carbon sources, including mannose, sucrose, galactose, and fructose, and could be scaled up to 10 L and 200 L batches. Productivity in the glucose (2.5 g/l) culture while maintaining the medium at pH 6.89 during 10 days of cultivation in the 200 L bioreactor was measured and increased more than productivity in the basal culture medium in the absence of glucose. Prodigiosin production from 10 L and 200 L fermentation cultures of H. chejuensis was confirmed by high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS) analyses for more accurate identification. Finally, the anticancer activity of crude extracted prodigiosin against human cancerous leukemia THP-1 cells was evaluated and confirmed at various concentrations. Conclusively, we demonstrate that culture conditions for H. chejuensis using a bioreactor with various parameters and ethanol-based extraction procedures were optimized to mass-produce the marine bacterium-derived high purity prodigiosin associated with anti-cancer activity.

• Women's Health Nursing
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• v.27 no.4
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• pp.388-404
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• 2021

Purpose: The purpose of this study was to examine the effects of team-based learning (TBL) on nursing students' communication ability, problem-solving ability, self-directed learning, and nursing knowledge related to high-risk pregnancy nursing. Methods: This quasi-experimental study used a nonequivalent control group pretest-posttest design. The participants were 91 nursing students allocated to an experimental group (n=45) and a control group (n=46). The experimental group received TBL lectures three times over the course of 3 weeks (100 minutes weekly) and the control group received instructor-centered lectures three times over the course of 3 weeks (100 minutes weekly). Data were collected by questionnaires from September to November, 2019. Data were analyzed using the chi-square test, paired t-test, and independent t-test. Results: After the intervention, the mean scores of problem-solving ability (t=-2.59, p=.011), self-directed learning (t=4.30, p<.001), and nursing knowledge (t=3.18, p=.002) were significantly higher in the experimental group than in the control group. No significant difference in communication ability was found between the experimental and control group (t=1.38, p=.171) Conclusion: The TBL program was effective for improving nursing students' problem-solving ability, self-directed learning, and nursing knowledge. Thus, TBL can be considered an effective teaching and learning method that can improve the learning outcomes of high-risk pregnancy nursing in women's health nursing classes. The findings suggest that TBL will be helpful for future nursing students to develop the nursing expertise necessary for providing nursing care to high-risk pregnant women.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.70-75
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• 2022

Accurately measuring location is necessary to provide a variety of services. The data for indoor positioning measures the RSSI values from the WiFi device through an application of a smartphone. The measured data becomes the raw data of machine learning. The feature data is the measured RSSI value, and the label is the name of the space for the measured position. For this purpose, the machine learning technique is to study a technique that predicts the exact location only with the WiFi signal by applying an efficient technique to classification. Ensemble is a technique for obtaining more accurate predictions through various models than one model, including backing and boosting. Among them, Boosting is a technique for adjusting the weight of a model through a modeling result based on sampled data, and there are various algorithms. This study uses Xgboost among the above techniques and evaluates performance with other ensemble techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.134-139
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• 2022

Recently, interest in programming and artificial intelligence is continuously increasing, and software education is being implemented as a mandatory education from elementary school. For efficient programming education, it is basically necessary to build a lab environment suitable for students and teachers, but there are performance problems due to the inadequacy of old computers and network equipment. Therefore, in this paper, we propose a web page-based online practice environment and algorithm competition scoring system using React and Spring boot to solve the problem of the programming practice environment. Through this, it is thought that programming learning can be carried out using only a web browser even on low-spec computers. In addition, since various programming languages can be learned irrespective of the language to be learned, it is considered that the time cost for establishing a practice environment can be reduced.

• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.6
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• pp.527-545
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• 2021

The aim of this systematic review was to determine the success rate of nitrous oxide-oxygen procedural sedation (NOIS) in dentistry. A systematic digital search was conducted for publications or reports of randomized controlled trials evaluating the clinical performance of NOIS. Abstracts of research papers were screened for suitability, and full-text articles were obtained for those who met the inclusion and exclusion criteria accordingly. The quality of the studies was assessed using the revised Cochrane risk-of-bias tool (RoB 2). A total of 19 articles (eight randomized clinical trials with parallel intervention groups and 11 crossover trials), published between May 1988 and August 2019, were finally selected for this review. The studies followed 1293 patients reporting NOIS success rates, with a cumulative mean value of 94.9% (95% CI: 88.8-98.9%). Thirteen trials were conducted on pediatric populations (1098 patients), and the remaining six were conducted on adults (195 patients), with cumulative efficacy rates of 91.9% (95% CI: 82.5-98.1%) and 99.9% (95% CI: 97.7-100.0%), respectively. The difference was statistically significant (P = 0.002). Completion of treatment and Section IV of the Houpt scale were the most used efficacy criteria. Within the limitations of this systematic review, the present study provides important information on the efficacy rate of NOIS. However, further well-designed and well-documented clinical trials are required and there is a need to develop guidelines for standardization of criteria and definition of success in procedural sedation. Currently, completion of treatment is the most used parameter in clinical practice, though many others also do exist at the same time. To maximize NOIS efficacy, clinicians should strictly consider appropriate indications for the procedure.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.121-129
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• 2022

With the recent increase in international trade volume the trade volume through ships is also continuously increasing. The treatment of ballast water goes through the following five steps, samples are taken and analyzed at each step, and samples are obtained using a suction pump. These suction pumps have low efficiency and thus need to be improved. In this study, it is to optimize the form of the impeller which affects directly improvements of performance to determine the capacity of suction pump and to fulfill the purpose of this research. To do it, we have carried out parametric design as an input variable, geometric form for the impeller. By conducting the flow analysis for the optimum form, it has confirmed the value of improved results and achieved the purpose to study in this paper. It has selected the necessary parameter for optimizing the form of the pump impeller and analyzed the property using experiment design. And it can reduce the factor of parameter for local optimization from findings to analyze the property of form parameter. To perform MOGA(Multi-Objective Genetic Algorithm) it has generated response surface using parameters for local optimization and conducts the optimization using multi-objective genetic algorithm. with created experiment cases, it has performed the computational fluid dynamics with model applying the optimized impeller form and checked that the capacity of the pump was improved. It could verify the validity concerning the improvement of pump efficiency, via optimization of pump impeller form which is suggested in this study.