• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.246-262
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• 2023

The purpose of this study is to identify the major peacekeeping activities that the Korean armed forces has performed from the past to the present. To do this, we collected 692 press releases from the National Defense Daily over the past 20 years and performed topic modeling and social network analysis. As a result of topic modeling analysis, 112 major keywords and 8 topics were derived, and as a result of examining the Korean armed forces's peacekeeping activities based on the topics, 6 major activities and 2 related matters were identified. The six major activities were 'Northeast Asian defense cooperation', 'multinational force activities', 'civil operations', 'defense diplomacy', 'ceasefire monitoring group', and 'pro-Korean activities', and 'general troop deployment' related to troop deployment in general. Next, social network analysis was performed to examine the relationship between keywords and major keywords related to topic decision, and the keywords 'overseas', 'dispatch', and 'high level' were derived as key words in the network. This study is meaningful in that it first examined the topic of the Korean armed forces's peacekeeping activities over the past 20 years by applying big data techniques based on the National Defense Daily, an unstructured document. In addition, it is expected that the derived topics can be used as a basis for exploring the direction of development of Korea's peacekeeping activities in the future.

• Health Policy and Management
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• v.33 no.4
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• pp.411-420
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• 2023

Background: The purpose of this study was to analyze the demand and supply status of patient beds by type of medical institution, categorized into 70 clinical privilege, in order to understand the regional bed supply situation. Methods: Utilizing the 70 clinical privilege defined by the Ministry of Health and Welfare, we calculated bed demand and supply quantities from 2019 to 2021 using data from Statistics Korea and the Health Insurance Statistical Yearbook. The bed demand calculation formula was based on the detailed guidelines for the medical sector by the Korea Development Institute and the 3rd edition of bed supply basic policies announced by the Ministry of Health and Welfare. Additionally, to mitigate distorted bed supply situations caused by factors such as regional levels and patient outflows, we classified bed supply types using the population decrease index indicator published by the Ministry of Public Administration and Security. Results: Among the 70 clinical privilege, it was analyzed that a relatively balanced bed supply situation exists overall, irrespective of the type of healthcare institution. However, in medical institutions at or above the level of hospitals, regions with bed supply ratios exceeding 20% compared to demand, particularly in institutions at or above the level of general hospitals, showed a relatively high rate of demand diversion. Conclusion: We have identified the bed supply types in the 70 clinical privilege in South Korea. Based on the results of this study, we emphasize the need for bed supply policies that consider regional characteristics. It is expected that this research can serve as fundamental data for future efforts aimed at managing or rectifying bed supply imbalances on a regional basis.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.27-35
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• 2024

We aimed to shed light on the issue of perpetuating societal disparities by analyzing the impact of inherent biases present in datasets used for training artificial intelligence models on the predictions generated by Artificial Intelligence(AI). Therefore, to examine the influence of data bias on AI models, we constructed an original dataset containing biases related to gender wage gaps and subsequently created a de-identified dataset. Additionally, by utilizing the decision tree algorithm, we compared the outputs of AI models trained on both the original and de-identified datasets, aiming to analyze how data de-identification affects the biases in the results produced by artificial intelligence models. Through this, our goal was to highlight the significant role of data de-identification not only in safeguarding individual privacy but also in addressing biases within the data.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.175-189
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• 2023

Purpose - The purpose of this study was to examine the relationship between CEO name uncommonness and R&D intensity while focusing on CEO ownership and CEO tenure as moderators of the relationship. Design/methodology/approach - This study collected data from various American databases such as national data on given names from Social Security Administration, COMPUSTAT, and Execucomp. The sample of this study includes 2,494 (firm-year) observations from U.S. firms between 2005-2011. This study conducts Feasible Generalized Least Square (FGLS) regression analysis to test the hypotheses. Findings - First, we found CEO name uncommonness was positively related to R&D intensity. In other words, CEOs with unusual names prefer being distinctive by increasing R&D investments. Second, we examine the moderating roles of CEO characteristics (i.e., CEO ownership and tenure). The results show that CEO tenure strengthens the positive relationship between CEO name uncommonness and R&D intensity. Research implications or Originality - First, this study extends the CEO characteristics and R&D literature by investigating how CEO name uncommonness affects R&D intensity. In addition, our study also supports the intitutionalization of CEO power arguments by showing that CEOs with unusual names are more likely to pursue distinctive strategies when they have longer tenure. For practical implications, our results allow the investors to better predict corporate future R&D expenses. It suggests that ceteris paribus, CEOs with unusual names, vis-a-vis CEOs with common names, are more likely to increase R&D expenses.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Journal of Microbiology and Biotechnology
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• v.34 no.5
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• pp.1017-1028
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• 2024

Lignocellulolytic enzymes play a crucial role in efficiently converting lignocellulose into valuable platform molecules in various industries. However, they are limited by their production yields, costs, and stability. Consequently, their production by producers adapted to local environments and the choice of low-cost raw materials can address these limitations. Due to the large amounts of olive stones (OS) generated in Morocco which are still undervalued, Penicillium crustosum, Fusarium nygamai, Trichoderma capillare, and Aspergillus calidoustus, are cultivated under different fermentation techniques using this by-product as a local lignocellulosic substrate. Based on a multilevel factorial design, their potential to produce lignocellulolytic enzymes during 15 days of dark incubation was evaluated. The results revealed that P. crustosum expressed a maximum total cellulase activity of 10.9 IU/ml under sequential fermentation (SF) and 3.6 IU/ml of β-glucosidase activity under submerged fermentation (SmF). F. nygamai recorded the best laccase activity of 9 IU/ml under solid-state fermentation (SSF). Unlike T. capillare, SF was the inducive culture for the former activity with 7.6 IU/ml. A. calidoustus produced, respectively, 1,009 ㎍/ml of proteins and 11.5 IU/ml of endoglucanase activity as the best results achieved. Optimum cellulase production took place after the 5th day under SF, while ligninases occurred between the 9th and the 11th days under SSF. This study reports for the first time the lignocellulolytic activities of F. nygamai and A. calidoustus. Furthermore, it underlines the potential of the four fungi as biomass decomposers for environmentally-friendly applications, emphasizing the efficiency of OS as an inducing substrate for enzyme production.

• Journal of Microbiology and Biotechnology
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• v.34 no.8
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• pp.1671-1679
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• 2024

Aspergillus flavus, the primary mold that causes food spoilage, poses significant health and economic problems worldwide. Eliminating A. flavus growth is essential to ensure the safety of agricultural products, and extracellular compounds (ECCs) produced by Bacillus spp. have been demonstrated to inhibit the growth of this pathogen. In this study, we aimed to identify microorganisms efficient at inhibiting A. flavus growth and degrading aflatoxin B₁. We isolated microorganisms from soil samples using a culture medium containing coumarin (CM medium) as the sole carbon source. Of the 498 isolates grown on CM medium, only 132 bacterial strains were capable of inhibiting A. flavus growth. Isolate 3BS12-4, identified as Bacillus siamensis, exhibited the highest antifungal activity with an inhibition ratio of 43.10%, and was therefore selected for further studies. The inhibition of A. flavus by isolate 3BS12-4 was predominantly attributed to ECCs, with a minimum inhibitory concentration and minimum fungicidal concentration of 0.512 g/ml. SEM analysis revealed that the ECCs disrupted the mycelium of A. flavus. The hydrolytic enzyme activity of the ECCs was assessed by protease, β-1,3-glucanase, and chitinase activity. Our results demonstrate a remarkable 96.11% aflatoxin B1 degradation mediated by ECCs produced by isolate 3BS12-4. Furthermore, treatment with these compounds resulted in a significant 97.93% inhibition of A. flavus growth on peanut seeds. These findings collectively present B. siamensis 3BS12-4 as a promising tool for developing environmentally friendly products to manage aflatoxin-producing fungi and contribute to the enhancement of agricultural product safety and food security.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.407-415
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• 2024

This study used data from the 9th main survey of the National Old Age Security Panel, the subjects were 1,923 elderly people aged 60 or older nationwide. As a result of analyzing the effect of demographic characteristics on Preparing for Oldage, 15.1% of explanatory power was shown in Preparing for Oldage. First, it was found that there was more Preparing for Oldage among men than among women. Age had a negative effect on Preparing for Oldage, with many respondents saying that the younger they were, the more likely they were to Preparing for Oldage. Education level also had a significant effect on Preparing for Oldage, and more respondents said that elementary, middle, and high school graduates were not doing Preparing for Oldage than those who graduated from vocational college or higher. Therefore, it was found that the lower the level of education, the less Preparing for Oldage was done. Next, as a result of examining the effect of life satisfaction on Preparing for Oldage, the higher the life satisfaction, the better the Preparing for Oldage was. In general, it was recognized that Preparing for Oldage would have an impact on life satisfaction, but through this study, it was confirmed that life satisfaction had an impact on Preparing for Oldage.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.65-72
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• 2013

In this study, the early suicide prevention program was applied to the elementary school students and compared the prior & post effect of the program, and verified the status of psychology change like emotional status, or temptation to take a suicide, and presented the possibility as a suicide prevention program. The period of adolescence is the very unstable period in the process of growth being cognitively immature, emotionally impulsive period. It is the period emotionally unstable and unpredictable possible to select the method of suicide as an extreme method to escape the reality, or impulsive problem solving against small conflict or dispute situation. Many stress of the student such as recent nuclear family, expectation of parents to their children, education problem, socio-environmental elements, individual psychological factor lead students to the extreme activity of suicide in recent days. In this study, the scope of stress experienced in the elementary school as well as idea and degree of temptation regarding suicide by the suicide prevention program were identified, and through prevention program such as meditation training, breath training and through experience of anger control, emotion-expression, self overcome and establish positive self-identity and make understanding Self-control, Self-esteem & preciousness of life based on which the effect to suicide prevention was analyzed. The study was made targeting 51 students of 2 classes of 6th grade of elementary school of Goyang-si and processed 30 minutes every morning focused on through experience & activity of the principle & method of brain science. The data was collected for 20 times before starting morning class by using Suicide Probability Scale(herein SPS-A) designed to predict effectively suicide Probability, suicide risk prediction scale, surveyed by 7 areas such as Positive outlook, Within the family closeness, Impulsivity, Interpersonal hostility, Hopelessness, Hopelessness syndrome, suicide accident. Analytical methods and validation was used the Wilcoxon's signed rank test using SPSS Program. Though the process of program in short period, but there was a effective and positive results in the 7 areas in the average comparison. But in the t-test result, there was a different outcome. It indicated changes in the 3 questionnaires (No.7, No.14, No.19) out of 31 SPS-A questionnaires, and there was a no change to the rest item. It also indicated more changes of the students in the class A than class B. And in case of the class A students, psychological changes were verified in the areas of Hopelessness syndrome, suicide accident among 7 areas after the program was processed. Through this study, it could be verified that different results could be derived depending on the Student tendency, program professional(teacher in charge, processing lecturer). The suicide prevention program presented in this article can be a help in learning and suicide prevention with consistent systematization, activation through emotion and impulse control based on emotional stress relief and positive self-identity recovery, stabilization of brain waves, and let the short period program not to be died out but to be continued connecting from childhood to adolescence capable to make surrounding environment for spiritual, physical healthy growth for which this could be an effective program for suicide prevention of the social problem.

• Journal of Service Research and Studies
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• v.9 no.2
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• pp.55-76
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• 2019

This study conducted empirical analyses to investigate the factors affecting the intention to use smart home services. Based on the previous relevant studies, the characteristics of smart home service were found to influence on the intention to use smart home service, and four variables(ubiquitous connectivity, reliability, context awareness, and security) concerning the service characteristics could be derived. And referring to the technology acceptance model(TAM), the updated TAM, IS success model, and the theory of reasoned action(TRA), three variables such as perceived ease of use, perceived usefulness and subjective norm were also likely to affect the intention to use smart home service, and the user innovativeness was inferred to play a role of moderating variable. In order to examine the research model and the hypotheses which could describe the relationship of the above mentioned variables, this study surveyed 447 people who were currently using or would use the smart home services, and then tested the hypotheses for 436 valid responses. The results of hypotheses testing showed that reliability, context awareness, and security have a significant effect on perceived usefulness and on perceived ease of use. However, it was found that ubiquitous connectivity significantly affected perceived usefulness but did not affect perceived ease of use. And perceived ease of use, perceived usefulness and subjective norm had significant effect on the intention to use smart home services. Also, user innovativeness as moderating variable was found to significantly influence on the magnitude of the relationship between ubiquitous connectivity and perceived usefulness and on that between reliability and perceived ease of use. This can be interpreted as the findings implying that innovative smart home-service users are likely to feel the smart home-services more useful than ordinary users when the degree of ubiquitous connectivity is higher, and are likely to perceive the use of smart home-services to be easier than ordinary ones when the degree of reliability is higher.