• Journal of Science Education
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• v.43 no.2
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• pp.207-226
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• 2019

The purpose of this study is to investigate how fusion science program for undergraduate general education influences the understanding of Nature of Science (NOS) and STEAM Literacy of students majoring in science and engineering in college. The students participated in the pre/post NOS survey(Lee, 2013) and the STEAM literacy survey(Choi et al., 2013) in the program. The results of this study are as follows. First, the fusion program was effective in understanding the NOS because there is a statistically significant difference between the pre/post tests.(p < 0.01). Second, while there were no significant differences between genders, however, there is a significant difference in students' majors in NOS understanding(p < 0.05). Third, it showed that improvement in STEAM Literacy in Convergence and Creativity domains is significant(p < 0.01). By contrast, the Caring domain of STEAM Literacy was decreased statically significant(p < 0.01). In the end, there is no difference in STEAM Literacy between genders as well as among students' major(p < 0.05).

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.349-355
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• 2019

The virtual reality training has been suggested as an intervention to improve physical function. But, the effects of virtual reality training focused on improving ADL in patients with acute stroke are unclear. Purpose of this study was to examine the effect of virtual reality training on hand function and activities of daily living (ADL) in patients with acute stroke. Sixteen patients with acute stroke were included in this study. The experimental group (VRA group) received 30 minutes of virtual reality training focused on ADL for each session, while the control group received 30 minutes of conventional virtual reality training. To examine the hand function and ADL of the subjects, the study used Jebsen-Tylor Hand Function Test (JTHFT) and Korean Modified Barthel Index (K-MBI), respectively. Both groups showed significant improvements in hand function of affected and unaffected sides, and in K-MBI total score before and after the intervention. The experimental group showed significantly greater improvements in the self-care domain of K-MBI after intervention than the control group. These findings suggest that the virtual reality training focused on ADL may have a better effect on self-care than conventional virtual reality training in patients with acute stroke.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.29-36
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• 2020

The background of this study is that machine learning administrative services are recently attracting attention as a major policy tool for non-face-to-face administrative services in the post-corona era. This study investigated the types of work expected to be effective when introducing machine learning administrative services for Seoul Metropolitan Government officials who are piloting machine learning administrative services. The research method is a machine that can be introduced by organizational unit by distributing and collecting questionnaires for Seoul administrative organizations that have performed machine learning-based administrative services for one month in July 2020 targeting Seoul public officials using machine learning-based administrative services. By analyzing the learning administration service and application service, the business characteristics of each machine learning administration service type such as supervised learning work type, unsupervised learning work type, and reinforced learning work type were analyzed. As a result of the research analysis, it was found that there were significant differences in the characteristics of administrative tasks by supervised and unsupervised learning areas. In particular, it was found that the reinforcement learning domain contains the most appropriate business characteristics for machine learning administrative services. Implications were drawn. The results of this study can be provided as a reference material to practitioners who want to introduce machine learning administration services, and can be used as basic data for research to researchers who want to study machine learning administration services in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.197-202
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• 2022

Gender neutral draft is the system that the level of manpower which military demands right now can be kept and the concept of gender equality can enlarge itself. This thesis draws implications on the necessity of optional review of draft and the amelioration of military organizational culture for the military through the example of Norway that has adopted gender neutral draft initially in Europe. The Military that is characterized by traditionally male led domain accelerates itself the openness to female by the aggrandizement of social participation and the improvement of human right for female. The various concerns about a necessary facilities, the period ofmilitary service, the level of salary, the keeping of combat power, etc just should be overcome in order to enlarge conscription to female in Korea. Situations such as the environment of national security, the level of social participation to female, the treatment to minority are different, so it is difficult for us to draw any conclusion whether the adoption of sex neutral conscription is right or not. Nonetheless, the national strategy that prepares for future may not be concluded easily and we can not stop it even though it is discomfortable truth. In Conclusion, we anticipate that the sound discourse on measures of including female in draft will be continued from the start with this thesis.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.339-350
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• 2022

The purpose of this study was to develop and investigate the validity and reliability of the Korean Version of Nurse's Job Crafting Scale. The Korean version of Job Crafting was translated and reverse-translated, and its content validity was verified by experts. Statistics were processed using SPSS/WIN 21.0 and AMOS 21.0 programs through self-report questionnaires for 151 nurses. Exploratory factor analysis and confirmatory actor analysis were performed to verify construct validity, and model fit, concentrated validity, and discriminant validity were confirmed through the analysis results.To verify the criterion validity, correlations with each domain were obtained using the calling scale. For reliability verification, the internal consistency reliability coefficient was calculated and confirmed. Reliability of all 20 job crafting tools was Cronbach's α = .93, with .91 for factor 1 (Increase in structural work resources, 5 questions) and .87 for factor 2 (Increase in structural work resources, 5 questions). The factor 3 (Increase in social work resources, 5 questions) was .83. The factor 4 (Increasing challenging business needs, 5 items) was .87, which was satisfactory for the reliability of internal consistency, and the Korean Version of Nurse's Job Crafting Scale was found to be an applicable tool. This study shows that the Korean Version of the Nurse's Job Crafting Scale is a valid and reliable instrument to assess nurses in Korea.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.57-70
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• 2020

Globally, cloud service is a core infrastructure that improves industrial productivity and accelerates innovation through convergence and integration with various industries, and it is expected to continuously expand the market size and spread to all industries. In particular, due to the global pandemic caused by COVID-19, the introduction of cloud services was an opportunity to be recognized as a core infrastructure to cope with the untact era. However, it is still at the preliminary stage for market expansion of cloud service in Korea. This paper aims to empirically analyze how cloud services can be accepted by users by each industry through extended Technology Acceptance Model(TAM), and what factors influence the acceptance and avoidance of cloud services to users. For this purpose, the impact and factors on the acceptance intention of cloud services were analyzed through the hypothesis test through the proposed extended technology acceptance model. The industrial sector selected four industrial sectors of education, finance, manufacturing and health care and derived factors by examining the parameters of TAM, key characteristics of the cloud and other factors. As a result of the empirical analysis, differences were found in the factors that influence the intention to accept cloud services for each of the four industry sectors, which means that there is a difference in perception of the introduction or use of cloud services by industry sector. Eventually it is expected that this study will not only help to understand the intention of using cloud services by industry, but also help cloud service providers expand and provide cloud services to each industry.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.785-796
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• 2023

In this study, a methodology for real-time classification and prediction of defects that may appear in PVDF(Polyvinylidene fluoride) sensors, which are widely used for structural integrity monitoring, is proposed. The types of sensor defects appearing according to the sensor attachment environment were classified, and an impact test using an impact hammer was performed to obtain an output signal according to the defect type. In order to cleary identify the difference between the output signal according to the defect types, the time domain statistical features were extracted and a data set was constructed. Among the machine learning based classification algorithms, the learning of the acquired data set and the result were analyzed to select the most suitable algorithm for detecting sensor defect types, and among them, it was confirmed that the highest optimization was performed to show SVM(Support Vector Machine). As a result, sensor defect types were classified with an accuracy of 92.5%, which was up to 13.95% higher than other classification algorithms. It is believed that the sensor defect prediction technique proposed in this study can be used as a base technology to secure the reliability of not only PVDF sensors but also various sensors for real time structural health monitoring.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.83-90
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• 2023

The purpose of this study is a descriptive research study to confirm the difference in health empowerment according to the current status and general characteristics of North Korean women defectors residing in South Korea. The subjects of the study were 201 North Korean women defectors living in the local community, and data were collected from September 16 to September 21, 2020 using a structured questionnaire. The collected data were analyzed by descriptive statistics, t-test, ANOVA, pearson's correlation coefficients using the SPSS/WIN 23.0 program. As a result of the study, the domain with the lowest score in the health empowerment of North Korean women defectors was "I know a positive method to cope with stress related to my health care." in the stress management question. Statistically significant differences were found in North Korean repatriation experience(t=3.77, p<.001), education(F=4.56, p=.012), economic status(t=-2.95, p=.004), subjective health status(t=-4.75, p<.001) and subjective stress(t=-2.47, p=.015). Based on the results of this study, alternatives should be prepared to strengthen the health empowerment of North Korean women defectors according to their individual characteristics.