• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.4
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• pp.361-368
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• 2021

The objective of this study was to establish technology for removing bacteria with human- and eco-friendly material. Staphylococcus aureus as an important component for balanced equilibrium among microbiomes, was cultured under various concentrations of phosphate. Experimental observation relating to physical properties was performed in an addition of phosphate buffer. Statistically minimum value of size and hardness using atomic force microscope was observed on the matured biofilm at 5 mM concentration of phosphate. As a result of absorbance for the biofilm tagged with dye, concentration of biofilm was reduced with phophate, too. To identify whether this reduction by phosphate at the 5 mM is caused by counter ion or not, sodium chloride was treated to the biofilm under the same condition. To elucidate components of the biofilm counting analysis of the biofilm using time-of-flight secondary ion mass spectrometry was employed. The secondary ions from the biofilm revealed that alteration of physical properties is consistent to the change of extracellular polymeric substrate (EPS) for the biofilm. Viscoelastic characterization of the biofilm using a controlled shear stress rheometer, where internal change of physical properties could be detected, exhibited a static viscosity and a reduction of elastic modulus at the 5 mM concentration of phosphate. Accordingly, bacteria at the 5 mM concentration of phosphate are attributed to removing the EPS through a reduction of elastic modulus for bacteria. We suggest that the reduction of concentration of biofilm induces dispersion which assists to easily spread its dormitory. In conclusion, it is elucidated that an addition of phosphate causes removal of EPS, and that causes a function of antibiotic.

• Korea Journal of Hospital Management
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• v.27 no.2
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• pp.53-66
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• 2022

Aim : The purpose of this study is to investigate the influence of the awareness level of the mandatory employment system for the disabled and the help of the employment increase on the health status of the disabled. Based on this, the purpose of this study is to raise awareness of the compulsory employment system for the disabled and to suggest a way to improve the health of the disabled. Methods : In this study, the first data of the second wave of the 2016-2018 Employment Panel Survey for the Disabled was used to analyze the participation of the disabled in economic activities. a total of 1,648 subjects were analyzed using the chi-square test and generalized estimating equation (GEE). Results : Compared to the group knowing about the compulsory employment system for the disabled, in the group who did not know about the compulsory employment system, the cognitive level was significantly higher for subjective health status (Odds Ratio [OR]: 1.573, 95% Confidence Interval [CI]: 1.252-1.977) and chronic diseases (OR: 1.407, 95% CI: 1.091-1.816), Compared to the group that the compulsory employment system for the disabled is helpful in increasing employment, the group that said it was not helpful at all had depression feel (OR: 2.330, 95% CI: 1.219-4.452) and subjective health status (OR: 2.052, 95% CI: 1.232. -3.416) significantly affected. Conclusion : It was found that the lower the level of awareness and help of the compulsory employment system for the disabled, the negative impact on their health status. Therefore, it is necessary to promote employment growth by raising awareness of the employment system for the disabled. Furthermore, in order to improve the health of the disabled, public relations plans to increase the understanding of the disabled on the system and policies to protect the disabled people who lose their will to work due to difficulties in accessing employment were enacted, and Changes to a disability-friendly working environment should be activated so that participants can participate.

• Journal of Applied Biological Chemistry
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• v.65 no.4
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• pp.261-267
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• 2022

The purpose of this study is to investigate the various functionalities of the peels, pulps, and seeds of passion fruit. Proximate composition, mineral contents, phenolic acid contents, total polyphenols, total flavonoids, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activities, 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activities, reducing power, α-glucosidase, and α-amylase inhibitory activities were measured for each part of passion fruit. Proximate composition analysis of the passion fruit indicated that moisture content contained (4.78-8.20%), carbohydrate (68.33-73.23%), protein (8.78-13.63%), fat (1.19-11.60%), and ash (1.51-8.80%). K, Ca, Na and Fe were the predominant mineral in the peels. P and Mg were the predominant mineral in the pulps. All the antioxidant activities (total polyphenols, total flavonoids, DPPH radical scavenging, ABTS radical scavenging, and reducing power) showed high results in the seeds. α-Glucosidase and α-amylase inhibitory activities IC₅₀ were in the peels (5.59 and 63.16 mg/mL), in the pulps (3.80 and 31.90 mg/mL), and in the seeds (0.06 and 1.02 mg/mL). These results indicated that the pulps, peels, and seeds of passion fruit have value as natural antioxidants with the high quality functional components.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.31-43
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• 2022

Startups are recognized as the vitality of the economy, and countries are competing to attract competitive overseas entrepreneurs and startups to their own startup ecosystem. In this global trend, entrepreneurs cross the border without hesitation, expecting abundant available resources and a startup friendly environment. Despite the increasing frequency of start-up migration between countries, studies related to this are very rare. Therefore, this study has chosen the cross-border migration of startups between countries as a research topic, and those who have been involved in the cross-border entrepreneurial migration to South Korea as a research sample. This study consists of two stages. The first research stage hires a Delphi method to collect expert opinions and find major factors related to the global startup migration. Drawing on the prior literature on the regional startup ecosystem at the national level, this stage is to conduct expert interviews in order to discover underlying factors and subfactors important for global migration of startups. The second stage measures the importance of the factors and subfactors using the AHP model. The priorities of factors and factors were identified hiring the overseas entrepreneurs who moved to Korea as the AHP survey samples. The results of this study suggest some interesting implications. First, a group of entrepreneurs with nomadic tendencies was found in the trend of global migration of entrepreneurs. They had already started their own businesses with the same business ideas in multiple countries before settling down in Korea. Second, important unique factors and subfactors in the context of global start-up migration were identified. A good example is the government's support package, including start-up visas. Third, it was possible to know the priority of the factors and subfactors that influence the global migration of startups This study is meaningful in that it preemptively conducted exploratory research focusing on a relatively new phenomenon of global startup migration, which recently catches attention in the global startup ecosystem. At the same time, it has a limitation in that it is difficult to generalize the meanings found in this study because the research was conducted based on the case of South Korea

• Journal of Life Science
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• v.20 no.2
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• pp.260-268
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• 2010

The lactate dehydrogenase (EC 1.1.1.27, LDH) isozymes in tissues from Channa argus were purified and characterized by biochemical, immunochemical and kinetic methods. The activity of LDH in skeletal muscle was the highest at 380.4 units and those in heart, eye and brain tissues were 13.4, 3,5 and 5.4 units, respectively. Citrate synthase (EC 4.1.3.7, CS) activity in heart tissue was the highest at 20.7 units. LDH/CS in skeletal muscle, heart, eye and brain tissues were 172.9, 0.6, 0.32 and 0.47. Protein concentration in skeletal muscle tissue was 14.7 mg/g and specific activities of LDH in skeletal muscle, heart, eye and brain tissues were 25.88, 0.79, 0.31 and 1.38 units/mg, respectively. Therefore, skeletal muscle tissue was anaerobic and heart tissue was aerobic. The LDH isozymes in tissues were identified by polyacrylamide gel electrophoresis, immunoprecipitation and Western blot with antiserum against $A_4$, $B_4$, and eye-specific $C_4$. LDH $A_4$, $A_3B$, $A_2B_2$. $AB_3$ and $B_4$ isozymes were detected in every tissue, $C_4$, $AC_3$, $A_2C_2$ and $A_3C$ were detected in eye tissue, and $A_3C$ was found in brain tissue. LDH $A_4$, $A_3B$, $A_2B_2$, $AB_3$, $B_4$, eye-specific $C_4$ isozymes were purified by affinity chromatography and Preparative PAGE Cells. The LDH $A_4$ isozyme was purified in the fraction from elution with $NAD^+$ containing buffer of affinity chromatography. Eye-specific $C_4$ isozyme was eluted right after $A_4$, after which $B_4$ isozyme was eluted with plain buffer. As a result, one part of molecular structures in $A_4$, $B_4$ and eye-specific $C_4$ were similar, but were different from each other in $B_4$ and $C_4$. Therefore the subunit A may be conservative in evolution, and the evolution of subunit B seems to be faster than that of subunit A. The activity of LDH $A_4$, $A_2B_2$, $B_4$, and eye-specific $C_4$ isozymes remained at 39.98, 21.28, 19.67 and 16.87% as a result of the inhibition by 10 mM of pyruvate, so the degree of inhibition was very high. The $Km^{PYR}$ values were 0.17, 0.27 and 0.133 mM in $A_4$, $B_4$ and eye-specific $C_4$ isozymes, respectively. The optimum pH of LDH $A_4$, $B_4$, eye-specific $C_4$, $A_2B_2$, $A_3B$, and $AB_3$ were pH 6.5, pH 8.5, pH 5.5, pH 6.0-6.5, pH 5.0 and pH 7.5. The $A_4$ and heterotetramer isozymes stabilized a broad range of pH. Especially, LDH activities in skeletal muscle tissue were high, resulting in a high degree of muscle activity.LDH metabolism in eye tissue seems to be converted faster from pyruvate to lactate by eye-specific $C_4$ isozyme as eye-specific $C_4$ have the highest affinity for pyruvate, and right after the conversion, oxidation of lactate was induced by $A_4$ isozyme. It was found that expression of Ldh-C, affinity to substrate and reaction time of $C_4$ isozyme were different according to the ecological environmental and feeding capturing patterns.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.33 no.4
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• pp.339-347
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• 2000

An algicidal bacterium, Micrococcus sp. LG-5 against the harmful dinoflagellate, Cochlodinium polykrikoides was isolated. The optimal conditions for the highest algicidal activity of bacterial culture filtrate showed in the range of $20{\~}30^{\circ}C$, at pH 7.0 and $3.0{\%}$ of NaCl concentration. In addition, $IC_(50)(mean of 50{\%} inhibitory concentration)$ of the culture filtrate against C. polykrikoides after incubation of 5 days was $0.482{\%}$. To investigate heat and pH stability of the culture filtrate of Micrococcus sp. LG-5, the culture filtrate ($pore size, 0.1 {\mu}m$) was heated to $121^{\circ}C for 15 min$ and adjusted pH from 2.0 to 10.0. There were no significant changes in algicidal activity by heat treatment and the pH change between pH from 5.0 to 10.0. The algicidal substances produced from Micrococcus sp. LG-5 were mainly detected in the fraction of $10,000{\~}1,000$ MWCO (molecular weight cut-off). The culture filtrate of Micrococous sp. LG-5 showed antimicrobial activity against Enterococcus faecalis, Escheiichia coli, Uebsiella pneunioniae and Vibrio altinolyticus, but did not show against Pseudomonas aeminosa, P. Buorescens, Salmonella typhi, Staphylococcus aureus, V. cholerae and V parahaemolyicus. The culture filtrate of Micrococcus sp. LG-5 was examined against 16 phytoplankton species and showed the algicidal activity against Ajexandzium tuarense, Eutreptiella Drnnastin, Gymnodinium catenatum, G. mikimotoi, G. sanguineum, eyodinium impuaicum, Heterocapsa triquetra, Heterosipa akashiwo, Prorocentrum micans and Pyraminonas sp.. However no algicidal effects of Micrococcus sp. LG-5 were observed against Chlamydomonas sp., Cylindrotheoa closterium, P. mininum, P. triestimum, Pseudonieschia sp. and Sczipuiella trochoidea. On the other hand, algicidal activity on the tested marinelivefood was not detected except for Isochrysis galbana. In addition, physiological responses of cultured olive flounder (Paralichthys oliraceus) exposed to $1 and 10{\%}$ of the culture filtrate of Micrococcus sp. LG-5 were measured. There were no clear changes in AST, GGT, creatinine, urea, total cholesterol, total protein, albumine, $Mg^(+2), Ca^(+2), Na^+, K^+, and Cl^-$. These results indicate that olive flounders were not affected when they were exposed to the culture filtrate of Micrococcus sp. LG-5.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Korean Home Economics Education Association
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• v.24 no.2
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• pp.117-134
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• 2012

The purpose of this study was to identify the stage of concern, the level of use, and the innovation configuration of Home Economics teachers regarding creativity and personality education in Home Economics(HE) classes. The survey questionnaires were sent through mails and e-mails to middle-school HE teachers in the whole country selected by systematic sampling and convenience sampling. Questionnaires of the stages of concern and the levels of use developed by Hall(1987) were used in this study. 187 data were used for the final analysis by using SPSS/window(12.0) program. The results of the study were as following: First, for the stage of concerns of HE teachers on creativity and personality education, the information stage of concerns(85.51) was the one with the highest response rate and the next high in the following order: the management stage of concerns(81.88), the awareness stage of concerns(82.15), the refocusing stage of concerns(68.80), the collaboration stage of concerns(61.97), and the consequence stage of concerns(59.76). Second, the levels of use of HE teachers on creativity and personality education was highest with the mechanical levels(level 3; 21.4%) and the next high in the following order: the orientation levels of use(level 1; 20.9%), the refinement levels(level 5; 17.1%), the non-use levels(level 0; 15.0%), the preparation levels(level 2; 10.2%), the integration levels(level 6; 5.9%), the renewal levels(level 7; 4.8%), the routine levels(level 4; 4.8%). Third, for the innovation configuration of HE teachers on creativity and personality education, more than half of the HE teachers(56.1%) mainly focused on personality education in their HE classes; 31.0% of the HE teachers performed both creativity and personality education; a small number of teachers(6.4%) focused on creativity education; the same number of teachers(6.4%) responded that they do not focus on neither of the two. Examining the level and type of performance HE teachers applied, the average score on the performance of creativity and personality education was 3.76 out of 5.00 and the mean of creativity component was 3.59 and of personality component was 3.94, higher than standard. For the creativity education, openness/sensitivity(3.97) education was performed most and the next most in the following order: problem-solving skill(3.79), curiosity/interest(3.73), critical thinking(3.63), problem-finding skill(3.61), originality(3.57), analogy(3.47), fluency/adaptability(3.46), precision(3.46), imagination(3.37), and focus/sympathy(3.37). For the personality education, the following components were performed in order from most to least: power of execution(4.07), cooperation/consideration/just(4.06), self-management skill(4.04), civic consciousness(4.04), career development ability(4.03), environment adaptability(3.95), responsibility/ownership(3.94), decision making(3.89), trust/honesty/promise(3.88), autonomy(3.86), and global competency(3.55). Regarding what makes performing creativity and personality education difficult, most HE teachers(64.71%) chose the lack of instructional materials and 40.11% of participants chose the lack of seminar and workshop opportunity. 38.5% chose the difficulty of developing an evaluation criteria or an evaluation tool while 25.67% responded that they do not know any means of performing creativity and personality education. Regarding the better way to support for creativity and personality education, the HE teachers chose in order from most to least: 'expansion of hands-on activities for students related to education on creativity and personality'(4.34), 'development of HE classroom culture putting emphasis on creativity and personality'(4.29), 'a proper curriculum on creativity and personality education that goes along with students' developmental stages'(4.27), 'securing enough human resource and number of professors who will conduct creativity and personality education'(4.21), 'establishment of the concept and value of the education on creativity and personality'(4.09), and 'educational promotion on creativity and personality education supported by local communities and companies'(3.94).

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.