• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.7-12
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• 2024

The development of artificial intelligence technology changes the social structure and educational environment, and the importance of artificial intelligence capabilities continues to increase. This study was conducted with the purpose of developing a checklist of questions to measure AI capabilities of elementary school students. To achieve the purpose of the study, a Delphi survey was used to analyze literature and develop questions. For literature analysis, two domestic studies, five international studies, and the Ministry of Education's curriculum report were collected through a search. The collected data was analyzed to construct core competency measurement elements. The core competency measurement elements consisted of understanding artificial intelligence (6 elements), artificial intelligence thinking (4 elements), artificial intelligence ethics (4 elements), and artificial intelligence social-emotion (3 elements). Considering the knowledge, skills, and attitudes of the constructed measurement elements, 19 questions were developed. The developed questions were verified through the first Delphi survey, and 7 questions were revised according to the revision opinions. The validity of 19 questions was verified through the second Delphi survey. The checklist items developed in this study are measured by teacher evaluation based on performance and behavioral observations rather than a self-report questionnaire. This has the implication that the measurement results of competency are raised to a reliable level.

• Information Systems Review
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• v.26 no.1
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• pp.315-335
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• 2024

This study analyzes the digital business environment in Korea and predicts the digital business trends to be noted in 2024. The study comprehensively reviews the domestic and international ICT market outlook and provides objective and in-depth analysis by compiling opinions from various experts. In particular, through a multi-dimensional approach, it derives practical trends applicable to the local business environment, provides strategic implications considering the characteristics of digital business in Korea, and suggests directions for Korean companies to adapt to the global business environment and strengthen their competitiveness. During the research process, 20 preliminary candidate trends were initially identified by collecting and analyzing reports from major domestic and international market research institutes. We then conducted in-depth interviews with 10 experts from industry and academia to select 15 shortlisted trends from these 20 trends and 10 trends selected from the previous year. Finally, we conducted a large-scale survey of 209 experts from academia and industry, and we selected 11 domestic digital business trends to focus on in 2024. This study, which presents an outlook of digital business trends suitable for the Korean business environment based on a variety of opinions scientifically gathered from Korean digital business leaders, will contribute to understanding IT trends in Korea from a business perspective and their differences from global trends.

• Information Systems Review
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• v.26 no.2
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• pp.45-57
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• 2024

This study develops a deep learning-based methodology for predicting Crude Palm Oil (CPO) prices. Palm oil is an essential resource across various industries due to its yield and economic efficiency, leading to increased industrial interest in its price volatility. While numerous studies have been conducted on palm oil price prediction, most rely on time series forecasting, which has inherent accuracy limitations. To address the main limitation of traditional methods-the absence of stationarity-this research introduces a novel model that uses the ratio of future prices to current prices as the dependent variable. This approach, inspired by return modeling in stock price predictions, demonstrates superior performance over simple price prediction. Additionally, the methodology incorporates the consideration of lag values of independent variables, a critical factor in multivariate time series forecasting, to eliminate unnecessary noise and enhance the stability of the prediction model. This research not only significantly improves the accuracy of palm oil price prediction but also offers an applicable approach for other economic forecasting issues where time series data is crucial, providing substantial value to the industry.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.287-297
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• 2024

The purpose of this study is to develop a design thinking-based program to enhance the core competencies of creative problem-solving, collaboration, and communication for college students and to verify its effectiveness. To this end, a design thinking-based program was developed according to the instructional systems design (ISD) model consisting of learning content analysis, class activity design, evaluation tool development, implementation, evaluation and revision. After applying to the target (88 college students), competencies in creative problem-solving, collaboration, and communication were tested to verify quantitative effectiveness and the collected data was analyzed by t-test. In order to verify the qualitative effectiveness, the reflective logs submitted by each group as a final project report were analyzed. The results of the t-test conducted to verify the change in students' means in the pre-post competency test, showed that there were statistically significant increase in creative problem solving skill (t=-4.955, p<.01), collaboration skill (t=-3.179, p<.01), and communication skills(t=- 4.293, p<.01). And the design thinking-based program enabled students to have optimal learning experiences. Especially, learners in the program positively appreciated the experience of sharing various ideas with other members, strengthening cognitive flexibility, and acquiring performance.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.29-39
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• 2024

This study attempted to determine the effect of job stress, job involvement, and goal orientation on work-life balance for shift nurses. The subjects of the study were 128 shift nurses working at a hospital in city C of province G. Date were conducted from April 01 to April 15, 2024 using a Google questionnaire. The collected data were analyzed by correlation and multiple regression analysis. The total explanatory power was 28.0%. The results of this study showed significant differences in job stress(β=.405, p<.001), goal orientation(β=-265, p=.002), and job involvement(β=.174, p=.037) as factors affecting the work-life balance of shift nurses. Therefore, it is expected to have a positive impact on patient health by contributing to the improvement of the quality of nursing services by forming an organizational culture that avoids excessive goal setting and allows employees to concentrate on their work with appropriate stress management. This suggests that nurses are not only individuals but also professional medical practitioners, and that maintaining a healthy work-life balance is crucial for the country's human resources, which requires institutional support at the government level.

• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.382-392
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• 2024

This study aimed to identify differences in soil properties and geological characteristics between slow-moving landslide prone areas and areas without landslide (control areas) in the Republic of Korea. During this 3-year field surveys (2019-2021), 11 soil and geological parameters were measured at 300 sites, i.e., 107 slow-moving landslide prone areas and 193 control areas. T-tests were conducted to identify differences in field-observed parameters between the two areas, followed by χ²-tests and density plots considering distribution patterns of the sample groups. We identified statistically significant differences between the areas in terms of soil internal friction angle, weathered rock thickness, bedrock thickness, and number of major geological anomaly zones. In conclusion, slow-moving landslide prone areas exhibited significant differences in geological characteristics, such as stratum thickness and presence of anomaly zones, compared with the control areas. To better understand the relationship between the geological characteristics identified in this study and the occurrence of slow-moving landslides, further field data collection and systematic analyses are warranted.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.425-436
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• 2023

In Korea, the U.S. Tier-4 Final emission standards have been applied to agricultural machinery since 2015. This study was conducted to analyze the emission characteristics of agricultural tractors during plow tillage operations using PEMS (portable emissions measurement systems). The tractor working speed was set as M2 (5.95 km/h) and M3 (7.60 km/h), which was the most used gear stage during plow tillage operation. An engine idling test was conducted before the plow tillage operation was conducted because the level of emissions differed depending on the temperature of the engine (cold and hot states). The estimated level of emissions for the regular area (660 m²), which was the typical area of cultivation, was based on an implement width of 2.15 m and distance from the work area of 2.2 m. As a result, average emission of CO (carbon monoxide), THC (total hydrocarbons), NOx (nitric oxides), and PM (particulate matter) were approximately 6.17×10-2, 3.36×10^-4, 2.01×10^-4, and 6.85×10^-6 g/s, respectively. Based on the regular area, the total emission of CO, THC, NOx, and PM was 2.62, 3.76×10^-2, 1.63, and 2.59×10^-4 g, respectively. The results of total emission during plow tillage were compared to Tier 4 emission regulation limits. Tier 4 emission regulation limits means maximum value of the emission per consumption power (g/kWh), calculated as ratio of the emission and consumption power. Therefore, the total emission was converted to the emission per power using the rated power of the tractor. The emission per power was found to be satisfied below Tier 4 emission regulation limits for each emission gas. It is necessary to measure data by applying various test modes in the future and utilize them to calculate emission because the emission depends on various variables such as measurement environment and test mode.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.819-826
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• 2024

This study aims to examine the correlations between self-control, time management behavior, and SNS addiction proneness among university students, and to analyze their impact on academic procrastination. The goal is to explore intervention strategies to improve academic procrastination behaviors. The subjects of this study were 167 students from a university located in City D, who agreed to participate and responded to the survey between February 6, 2024, and April 19, 2024. The collected data were analyzed using the SPSS 21.0 statistical program, employing t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. Academic procrastination showed significant negative correlations with self-control (r=-.570, p<.001) and time management behavior (r=-.544, p<.001), and a significant positive correlation with SNS addiction proneness (r=.367, p<.001). The factors influencing academic procrastination were time management behavior (β=-.461, p<.001), self-control (β=-.359, p<.001), and SNS addiction proneness (β=.199, p<.001), with an explanatory power of 52%. To reduce academic procrastination among university students, it is necessary to implement various extracurricular programs aimed at improving time management behavior.

• Journal of the Korean Regional Science Association
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• v.40 no.3
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• pp.23-42
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• 2024

This study examines changes in housing insecurity among young adults from a longitudinal perspective, recognizing the dynamic nature of young adulthood. The objective of the study is to explore shifts in housing insecurity and to identify the factors affecting entry into and exit from housing insecurity. Using data from the Seoul Youth Panel in 2021 and 2022, housing insecurity is measured across three dimensions, and changes over one year are categorized. The sample consists of 40% of individuals experiencing persistent security, 33% experiencing persistent insecurity, 14% exiting insecurity, and 13% entering security, indicating that the transition into and out of housing insecurity is quite dynamic. Empirical results from the logistic regression models reveal several key findings. Firstly, crises in employment and social domains significantly correlate shifts in housing insecurity among young people. Unstable employment and unsatisfactory job conditions increase the risk of entering, and decrease the likelihood of exiting housing insecurity. Social isolation and lower social support increase the risk of entry into housing insecurity, while higher social support enhances the likelihood of exiting housing insecurity. Secondly, residential characteristics play a pivotal role in the transition of housing insecurity. Those living in non-apartments and renters are considerably less likely to exit housing insecurity compared to those living in apartments and homeowners, respectively. Furthermore, residing in rooftop or semi-subterranean location, or undergoing residential moves, significantly elevate the risk of entering housing insecurity. Thirdly, external supports appear to have a limited role in achieving housing security for young adults. Parental economic resources significantly facilitate exiting housing insecurity, whereas governmental housing policy benefits show no significant effect. These findings provide important implications for policy-making aimed at addressing and preventing housing insecurity among young adults.

• Journal of the Korean Applied Science and Technology
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• v.41 no.4
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• pp.929-938
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• 2024

This study examined the effects of a 12-week combined exercise program on blood lipids, albumin, and free fatty acid (FFA) levels in obese, middle-aged women, aged 55-64, who were within five years post-menopause. The participants were divided into two groups: a moderate-intensity exercise group (MIG, n=10) and a high-intensity exercise group (HIG, n=10). Both groups performed resistance exercises using elastic bands and aerobic walking on treadmills three times a week for 60 minutes per session. Data analysis involved calculating the mean (M) and standard deviation (SD) for each measurement item. A two-way repeated measures ANOVA was used to assess interaction effects between groups and periods. Paired t-tests were conducted to evaluate within-group differences over time, and independent t-tests were used to compare between-group differences. The statistical significance level was set at .05 for all analyses. Results showed a significant interaction effect for triglycerides (TG) among the blood lipids (p<.05). No statistically significant difference was found in albumin levels. FFA levels significantly decreased in both groups due to the interaction effect (p<.05), with a more pronounced decrease in the MIG group. These findings indicate that regular exercise is effective in improving and preventing obesity in post-menopausal, obese middle-aged women. Notably, moderate-intensity exercise had a more substantial impact on TG and FFA levels compared to high-intensity exercise. Therefore, continuous moderate-intensity exercise is recommended to improve obesity and promote a healthy lifestyle before transitioning into old age.