• Journal of the Korean Society of School Health
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• v.34 no.1
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• pp.76-86
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• 2021

Purpose: This study was conducted to describe the experience of school health teachers in regard to the COVID-19 pandemic in South Korea. Methods: We conducted a qualitative study using content analysis. Ten school health teachers were recruited from 6 elementary schools, 2 middle schools and 2 high schools in Seoul, using purposive sampling. They participated in semi-structured in-depth interviews in person or using an online communication system from January to February, 2021. Interviews were transcribed verbatim and analysed using qualitative content analysis. Results: Three main categories and nine generic categories emerged from the analysis. Firstly, it was discovered that school health teachers had psychological and physical stress to cope with COVID-19 due to the 1) fear of the unexpected infectious disease, 2) burden of having to deal with it alone, 3) breakdown of personal life and physical exhaustion and 4) heavy duty as a health teacher caused by the lack of an organic cooperation system with institutions related to school infectious diseases. Secondly, school health teachers had an increased sense of empowerment in regard to infectious disease management as a result of 1) feeling rewarded and appreciated and 2) gaining confidence and trust in infectious disease management. Finally, school health teachers experienced the urgent need for an effective response strategy for infection control because of the 1) confusion over infectious disease response due to lack of practical manuals applicable to the field as well as training, 2) disappointing response system without an expert response team dedicated to managing infectious diseases in schools, and 3) growing awareness of the need for change. Conclusion: It is expected that school health teachers' experience of COVID-19 will be used as important data for building effective and advanced school infectious disease response systems.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.27-27
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• 2019

본 연구는 멸종위기 아고산수종 구상나무의 보존 복원을 위한 유전다양성을 고려한 표본추출전략을 구명하는데 그 목적이 있다. 2019년 9월에 한라산 영실 집단($14,000m^2$)에서 총 152개체를 대상으로 선발된 10개의 nSSR 마커를 이용하여 유전다양성 및 공간적 유전구조를 분석하였다. 평균 유전다양성은 관찰된 대립유전자수(A)가 7.2개, 유효대립유전자수($A_e$)가 3.6개, 이형접합도 관찰치($H_o$)가 0.528, 이형접합도 기대치($H_e$)가 0.595이며, 고정지수(F)는 0.071 이었다. 조사구내 구상나무 성목 152개체는 평균 수고 3.6 m, 흉고직경 17.3 cm로 나타났다. 구상나무의 개체목간 평균거리는 3.94 m, 임분밀도는 700 본/ha 이며 개체의 공간적 분포는 임의분포 형태로 나타났다. 구상나무의 유전변이에 대한 공간적 자기상관성(spatial autocorrelation) 분석 결과, 조사구의 구상나무는 약 15 m 이내에서 분포하는 개체들 간 유전적 유사성이 있게 분포하는 것으로 나타났으며 임분밀도가 높고 수고가 낮은 특성으로 인하여 비교적 작은 유전군락이 형성된 것으로 사료된다. 결과적으로 영실의 구상나무 집단의 보존 복원을 위한 표본추출전략은 15 m의 간격을 두고 개체를 선발하는 것이 타당한 것으로 나타났다.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1295-1300
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• 2022

There has been increased interest in researching risk perception of radiation to implement successful risk communication, particularly given the recent worldwide nuclear policy movement regarding nuclear energy. This study aimed to investigate characteristics of risk perception among residents living near normally operating nuclear power plants in South Korea by identifying factors associated with risk perception. A survey was conducted with face-to-face interviews for 1200 residents aged 20e84 years by gender- and age-stratified random sampling. Risk perception was associated with trust perception in nuclear safety, but was not highly correlated with benefit perception for utilizing nuclear power. Relatively high risk perception was observed in women, older age groups, and residents not having experience of nuclear-related education or work. This association remained after adjusting for other factors including benefit perception, trust perception, and psychological distress. In addition to these individual characteristics, risk perception was also associated with a residential district's own unique context, indicating that a strategy of risk communication should be developed differently for residents facing nuclear-related circumstances. Given that risk perception can be changed, depending on social values such as safety culture and economic setting, further studies are required to understand the changing characteristics of radiation risk perception.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3054-3070
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• 2023

Nuclear Power Plants (NPP) are widely utilized around the globe from different base forms as it is one of the most dependable renewable resources that technological advancements have offered. However, different perceptions of the usage of NPPs emerged from different generations. The purpose of this study was to investigate the acceptance of nuclear energy as an alternative source of energy among Generation Z in the Philippines by utilizing an extended Theory of Planned Behavior (TPB) approach. An online questionnaire which consisted of 31 items was distributed using a purposive sampling approach and 450 respondents of Generation Z voluntarily answered. Structural Equation Modeling (SEM) showed that the knowledge regarding NPP had significant effects on risk perception and benefit perception which subsequently led to subjective norms. In addition, perceived behavioral control and subjective norms had significant effects on behavioral intention which led to nuclear acceptance. Interestingly, the respondents perceived the benefit of NPP as slightly higher than the perceived risk. With these, it was clear that the commissioning Nuclear Power Plant must consider as an alternative source of electric energy in the Philippines. Moreover, this study is one of the first studies that investigated the acceptance of NPP among Generation Z. Lastly, the model could be a basis to strengthen the acceptance strategy of opening NPP among Generation Z, particularly in developing countries.

• Journal of the Korean Applied Science and Technology
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• v.40 no.2
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• pp.189-198
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• 2023

This study aimed to identify the effects of nurses' interpersonal relationship ability on retention intention and turnover intention. The participants were 192 general duty nurses from a general hospital (95 with 36 months of experience or less, 97 with 37 months of experience or more) recruited using convenience sampling. Data were collected between February 15 and February 22, 2022. The data were analyzed by t-test, ANOVA, Pearson correlation coefficient, regression analysis, and more. The results demonstrated that turnover intention was higher among females. Also, a positive correlation between interpersonal relationship ability and retention intention was found to be significant among the nurses with at least 37 months of experience(r = .35, p < .001). The effect of interpersonal relationship ability on retention intention was found to be significant among the nurses with at least 37 months of experience(B = 0.71, t = 3.44, p < .001). However, the effect of interpersonal relationship ability on turnover intention was found to be nonsignificant. Based on these findings, this study concluded with the need for a strategy to strengthen interpersonal relation ability. during which the work experience should be considered, to promote nurses' retention intention.

• Women's Health Nursing
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• v.29 no.3
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• pp.229-238
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• 2023

Purpose: This study analyzed the effects of virtual reality simulation-based problem-based learning on nursing students' critical thinking ability, problem-solving ability, and self-efficacy in the nursing care of women undergoing induction of labor. Methods: A nonequivalent control group pretest and posttest design was employed. The study participants included 52 nursing students (24 in the experimental group and 28 in the control group). The experimental group took a problem-based learning (PBL) class in the first week, and then engaged in self-directed learning using virtual reality simulation. In the second week, lectures about emergency nursing care for induction of labor and drug administration were given. The control group participated in PBL in the first week and lectures in the second week. The study was conducted from April 17 to May 19, 2023. Data were analyzed using the chi-square test, Fisher exact test, analysis of variance, and the independent t-test. Results: Before-and-after differences between the two groups were statistically significant in problem solving ability (t=-5.47, p<.001) and self-efficacy (t=-5.87, p<.001). Critical thinking ability did not show a statistically significant difference between the two groups. The score for satisfaction with the virtual reality simulation program was 3.64±5.88 out of 5 in the experimental group. Conclusion: PBL education using a virtual reality simulation was found to be an effective way of teaching. Although convenience sampling was used, PBL education using virtual reality can be used as an educational strategy to enhance nursing students' problem-solving ability and self-efficacy.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1322-1329
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• 2023

This study attempted to verify how the selection attribute affects customer satisfaction and participation intention to provide basic data for the efficient operation strategy of domestic futsal fields. Therefore, people who used domestic futsal fields were selected as samples, and convenience sampling methods were used. The final analysis used 271 copies of data. The data processing was conducted with the SPSS (ver. 21.0) program, which conducted frequency analysis, factor analysis and reliability analysis, correlation analysis, simple and multiple regression analysis. First, the results of the study showed that domestic futsal field selection attributes had a significant impact on customer satisfaction in the order of service, convenience, price, and facility. Second, customer satisfaction had a significant effect on participation intention. Third, the optional attributes had a significant impact on participation intention in the order of facility, service, convenience, and price. Summarizing the above results, it is believed that domestic futsal courts need to provide facilities and services that allow consumers to enjoy futsal games more conveniently and safely.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2220-2238
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• 2024

As a typical active equipment, pump machinery is widely used in nuclear power plants. Although the mechanism of pump machinery in nuclear power plants is similar to that of conventional pumps, the safety and reliability requirements of nuclear pumps are higher in complex operating environments. Once there is significant performance degradation or failure, it may cause huge security risks and economic losses. There are many pumps mechanical parameters, and it is very important to explore the correlation between multi-dimensional variables and condition. Therefore, a condition monitoring model based on Deep Denoising Autoencoder (DDAE) is constructed in this paper. This model not only ensures low false positive rate, but also realizes early abnormal monitoring and location. In order to alleviate the influence of parameter time-varying effect on the model in long-term monitoring, this paper combined equidistant sampling strategy and DDAE model to enhance the monitoring efficiency. By using the simulation data of reactor coolant pump and the actual centrifugal pump data, the monitoring and positioning capabilities of the proposed scheme under normal and abnormal conditions were verified. This paper has important reference significance for improving the intelligent operation and maintenance efficiency of nuclear power plants.