The Society of Convergence Knowledge Transactions ISSN:2287-8920(Print) 융복합지식학회논문지

In the era of the Fourth Industrial Revolution, future-oriented educational programs are needed to foster creative and professional nursing talent. This study was done to verify the effect of Design Thinking-based nursing learning program on nursing students’ critical thinking, everyday creativity. Data were collected from May to July 2020, with 59 fourth grade of nursing students at one university in G Metropolitan City. Design Thinking-based nursing learning program was applied D-school’s five stage process that composed of empathize, define, ideate, prototype and test. this program was conducted total 4 times in 2 weeks, each session lasted 40~50 minutes. The collected data were analyzed as descriptive statistics and paired t-test with SPSS 20.0 program. After applying the Design Thinking-based nursing learning program, critical thinking(t=-6.65, p=.000) and everyday creativity(t=-2.17, p=.037) increased which was statistically significant. Based on the above results, the design thinking-based nursing learning program is very useful in improving the critical thinking and creativity of nursing students, so it is expected that it will be actively utilized in the educational field.

In the Arctic and the surrounding regions of the Arctic, the limitations such as extreme cold environment and isolation lead to difficulties such as manpower management and supply. As a result, a reliability-based system is required to minimize operational resources from the facility design stage. SINTEF, NTNU published an OREDA-handbook to evaluate availability of plant based on data from oil and gas production facilities. However, most field data are based on data collected in the mid-latitude region, making it unsuitable for assessing the availability of plants operating in cold environments in high-altitude regions. In this study, the methodology for extending the application limit of OREDA-handbook as a basic database for evaluating the operation rate of oil sand plant was presented. In addition, the change in availability was predicted and evaluated using the design example of the oil sand plant function module.

We pursue innovative construction technology that finds a path for local coexistence by optimizing environment-based plant facilities that are treated only as resident-hating facilities and constructing them underground and providing the upper space as resident-friendly facilities. In this study, a study was conducted on the safety when installing an underground complex plant composed of only section steel. In consideration of the area of the underground space and the devices arranged, the spacing of the columns was set to 10m in width and length, and braces were also modeled and performed to distribute the self-load on the material. As the boundary conditions, the conformity of the standard was confirmed through the structural analysis results applying the device load, self load, earth pressure, and earthquake load. As a result, in Cases 1 and 2, the same sag phenomenon occurred due to the fixed load, but in case 3, it was confirmed that the sag phenomenon occurred in the brace as the fixed load was distributed to the brace. SM460 was selected as the applied material, and the analysis result confirmed that design is possible stably. Using this analysis method, it is believed that it can be used as basic data when designing an underground complex exterior frame.

In this paper, we make a study on the language model based on attention. The representative attention model is a transformer model, which enables a self-attention. Even though the transformer model consists of encoder and decoder, decoder is usually used for language model. We build a sentence-piece model for tokenizing. The experimental result yields that the token unit number of 5000 gets the perplexity(ppl) reduction of 33.4% compared with that of 10,000 when AI-Hub corpus (https://www.aihub.org.kr) is used in the sentence-piece model. In order to prove the performance of language model with regard to perplexity, we make an experiment of speech recognition that the model with low perplexity yields better performance than that with high perplexity.

Among the sunscreen products that are important for protecting the skin from Ultraviolet (UV) rays, consumption of sun stick formulation has increased recently. To evaluate the stability of the developed sun stick, the cutting strength of the sun stick and the content of the ultraviolet absorber were analyzed four weeks after storage, with different storage temperature and solar conditions. Ethylhexylmethoxy cinnamate (Parsol MCX), Butylmethoxy dibenzoylmethane (Parsol 1789), Diethylaminohydroxybenzoylhexyl benzoate (Uvinul A Plus), Ethylhexyl Salicylate (Escalol 587), Octocrylene (Uvinul N539T)) were used as ultraviolet absorber. The five ingredients of UV absorbers were simultaneously quantitatively analyzed using gas chromatography (GC). As a result of the stability evaluation of the sun absorbent using the GC analysis method, the recovery rate of the sun absorbent in the product was 90 to 110%. As a result of measuring the cutting strength, there is little change in cutting strength due to temperature change, and the change in cutting strength is large under sunlight, so the product should be stored away from direct sunlight.

Mobile cloud storage services are used to efficiently share or synchronize users’ multimedia content data across multiple mobile devices. This mobile cloud storage provides flexibility and scalability to solve various heterogeneities to store various content data, so security issues must be addressed in the sharing process. Currently, cloud storage services generally encrypt and use content data for security purposes. However, this method is not secure because it identifies rogue users by managing simple IDs, passwords and encryption keys by software. This paper presents a data access management model and technique for sharing and security of multimedia contents based on EMRA on mobile cloud storage. It supports hardware-based key management, proof of client software integrity, and secure key sharing. In addition, the proposed model stores/manages different types of multimedia contents, so that problems arising during search can be solved by establishing a metadata relationship based on EMRA to increase the reliability of the search. And this paper presents a prototype using ARM TrustZone and a TPM emulator running in the secure world of TrustZone environment.

This study included anthropomorphism, service diversity, ease of use, and perceived privacy invasion in independent variables in order to be able to explain well by applying an Extended Technology Acceptance Model in relation to the intention of artificial intelligence speakers, which are recently attracting attention as a next-generation platform. In addition, a model including perceived usefulness and perceived enjoyment as parameters was designed. The results of this study are as follows. First, the anthropomorphism, diversity of services, and ease of use of artificial intelligence speakers had positive(+) effects on perceived usefulness, and the perceived privacy invasion had a negative(-) effects on perceived usefulness. Second, the anthropomorphism, diversity of services, and ease of use of artificial intelligence speakers had positive(+) effects on perceived enjoyment, and perceived privacy invasion did not significantly affect perceived enjoyment. Third, the perceived usefulness and perceived enjoyment by using the artificial intelligence speaker had positive(+) effects on the intention to use, and the perceived enjoyment had a much stronger effect on the intention to use than the perceived usefulness. Finally, as a result of path analysis, It was found that the most influential path for the intention to use artificial intelligence speakers was ‘service diversity → perceived enjoyment → intention to use’.

This study was to investigate creativity, compassionate competency, self-leadership and problem-solving ability and to identify factors influencing problem-solving ability in nursing students, This study population consisted of 127 students in the 4th grade of nursing at one university in G metropolitan city. The data were collected at september 2020 and analyzed using t-test, ANOVA, Mann-Whitney U test, Kruskal waillis test, Pearson correlation coefficient, multiple regression analysis with SPSS WIN 22.0 program. The results, the mean score of problem-solving ability in nursing students was 3.76±0.58, problem-solving ability explained 70.0% of the variance in self-leadership(β=.52, p<.001), compassionate competency(β=.33, p<.001), and creativity(β=.15, p<.001) in oder. The results of our research suggest that self-leadership is most important variable influencing problem-solving ability in nursing students. Therefore, to promote problem-solving ability in clinical situation, must to develop multidisciplinary nursing education program that can improve self-leadership, compassionate competency, and creativity.

As the World Wide Web becomes more common as a medium for publishing information, the volume of web documents is exploding. In web documents, HTML tables are widely used as a means of expressing important information because related information can be expressed in various ways in a two-dimensional logical structure. For this reason, interest in the method of automatically extracting data from HTML tables is increasing. This study proposes a method of complying with the coding conventions of HTML tables when creating web documents as a solution to the problem of automatic data extraction of HTML tables. The purpose of commonly used HTML coding conventions is to improve the readability of HTML code and make it easier to understand among developers when creating web documents. The purpose of the HTML coding convention proposed in this study is to facilitate automatic extraction of data from HTML tables in web documents. It is expected that the proposed HTML coding convention will be utilized to facilitate automatic data extraction from HTML tables.

As industrial sites and public buildings become larger and more complex, indoor residents are exposed to various indoor air pollution. In order to maintain a pleasant indoor environment, taking appropriate measures by periodically measuring CO₂ and Volatile Organic Compounds(VOC), which are highly harmful organic gases to the human body, as well as lighting, temperature and humidity, is an essential factor for creating a better living environment for human health. In this study, an IoT gateway system, which acts as a hub based on the Message Queuing Telemetry Transport(MQTT) protocol, was developed to collect data from MQTT client sensors associated with indoor air quality and control devices for decontamination. The reliable system was implemented by measuring indoor air quality at local and remote industrial sites and public buildings and sending messages to the MQTT server to control related devices such as air purifiers, air conditioners, and ventilators at the site according to the monitoring results in the event of abnormalities beyond a certain level. In the future, it is expected that the collected information will be used for industrial IoT and disaster prevention services by building ontology-based semantic database to provide situation awareness functions.

In the past, research on basic income has been conducted on a wide range of subjects in various academic fields, but studies in the government or administrative fields have been insufficient. Therefore, the purpose of this paper is to analyze the priorities by deriving core recognition frames for priorities by setting feasibility factors according to the expected issues when introducing the future basic income policy in Korea. In this study, first, the logic of basic income is investigated through the concept and principle of basic income. Second, through in-depth interviews, detailed forecasting issues on feasibility were derived from text-mining on the feasibility factors of basic income. Third, the expected issues for each category on the feasibility based on the identified expected issue data are schematically illustrated. In the issue-based Analytic Hierarchy Process(AHP), the priorities for feasibility was selected as a dependent variable and the priority of feasibility according to basic income policy was analyzed. The existing research on basic income mainly focused on philosophical and moral principles, the theory of distribution justice, the argument for and against basic income, and the single-line principle of feasibility, but this study analyzes the issues that are actually being discussed at the policy level. The policy implications expressed by deriving priorities for the feasibility of basic income will be a great foundation for establishing a more effective basic income policy in the future.

The purpose of this study is to compare and analyze the nine-year change in perception of pre-service early childhood teachers’ on Confucian values as Korean traditional values, and to find out the Confucian values as Korean traditional values recognized by pre-service early childhood teachers as of 2020. To this end, 215 students in the early childhood education department of the college located in J city and 187 students in the department of the same school were used to find out the change in perception of Confucian values by using the tool for measuring Confucian values as Korean traditional values. The research results according to the analysis results are as follows. First, the recognition of the importance of Confucian values ​​was found to have a significant correlation with the subject satisfaction of pre-service early childhood teachers in both 2012 and 2020. Second, in recognizing the importance of Confucian values, pre-service early childhood teachers recognized it as normal in 2012, but in 2020 pre-service early childhood teachers were statistically changed. In 2012 and 2020, Korean traditional values also changed the ranking of important perceptions of the 29 Items of Confucian values as Korean traditional values.

In a rapidly changing business environment, it is necessary for public organizations to change the types of leadership and to rethink continuous improvement and organizational effectiveness through innovative behavior and knowledge sharing. Therefore it is meaningful that the organizations quest empowering leadership and analyze the impacts on innovative behavior and knowledge sharing by the self-efficacy of members. It was surveyed employees in public organizations to achieve the goal of this study. The main analysis result shows that the empowering leadership gives positive influence on the organizational members’ self-efficacy, knowledge sharing and innovative behavior. It also brings mediation effects on self-efficacy. Public organizations are required to be flexible in responding in a rapidly changing business environment increasing diversity and complexity. It is also necessary for the organizations to strengthen the competitiveness and to improve the effectiveness increasing self-efficacy by empowering leadership and linking knowledge sharing and innovative behavior.

In 2020, when the world became non-face-to-face due to the unprecedented corona pandemic situation, BTS, which turned the whole world upside down, was nominated for the American Grammy Awards following the Billboard Music Awards, proving the importance of fandom as well as musicality. The number of PC and mobile game users has increased significantly due to measures such as social distancing and self-isolation to prevent the spread of the corona pandemic. The domestic game market is focused on mobile and PC games, but the console market is also growing every year. In particular, we can expect the appearance of the 9th-generation consoles XBOX Series X and PlayStation 5 to be released in 2020, changes in game platforms such as “Let’s Get Together Animal Forest” and changes in game users’ culture and game market according to the killer title. In this paper, we analyze the characteristics of game users and game fandom culture according to the change of the game platform, derive a competitive plan that the Korean game industry should have in the post-corona era, and suggest the direction for the game industry.

Big issues of the Fourth Industrial Revolution are big data and artificial intelligence. Various types of data that are automatically created, stored, processed and analyzed from IoT sensors, SNS, and financial transactions are using for accurate prediction . However, data analysis using incomplete data containing missing values results in biased estimates and resulting erroneous analyses. In this study, the missing values mechanism and the missing values pattern were explored and the classical method of replacing missing values and the multiple imputation methods were considered. Empirical studies conducted simulations of 48,192 fine dust (PM10) and ultrafine dust (PM 2.5) time series data containing missing values, varying the number of data sets replaced by the MICE package of R, the statistical language. As a result, the mutiple imputation method using 20 imputed datasets was judged to be appropriate and were compared with the original datasets that removed missing values to show that the parameters of the original datasets were consistent.