• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.75-83
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• 2022

Most of the courses that teach the Python programming language are liberal arts courses that all students in general universities must complete. Through this, non-major students who have learned the basic programming process based on computational thinking are strengthening their convergence capabilities to apply SW in various major fields. In the previous research results, various evaluation methods for understanding the concept of computational thinking and writing code were suggested. However, there are no examples of evaluation problems, so it is difficult to apply them in actual course operation. Accordingly, in this paper, a Python basic programming curriculum that can be applied as a liberal arts subject for non-majors is proposed according to the ADDIE model. In addition, the case of evaluation problems for each Python element according to the proposed detailed curriculum was divided into 1st and 2nd phases and suggested. Finally, the validity of the proposed evaluation problem was analyzed based on the evaluation scores of non-major students calculated in the course to which this evaluation problem case was applied. It was confirmed that the proposed evaluation problem case was applied as a real-time online non-face-to-face evaluation method to effectively evaluate the programming competency of non-major students.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.5
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• pp.98-104
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• 2022

When processing parts, the cutting oil can improve the cooling performance of the workpiece and tool to increase the precision of the workpiece or extend the life of the tool and facilitate chip extraction. Since such cutting oil has a harmful effect on the environment and the human body due to additives such as sulfur, research on a minimum lubrication supply method using an eco-friendly oil is recently underway. The minimum lubrication supply method minimizes the amount of cutting oil used during processing and processes it, which can reduce the amount of cutting oil used, but has a problem in that cooling performance efficiency is poor. Therefore, this study conducted a study on mist cooling of lubricants to reduce the amount of cutting oil used and maximize the cooling effect of processing heat generated during tapping processing. Spray pressure, processing speed, direction, and lubricant spray amount, which are considered to have an effect on cooling performance, were set as process conditions, and the effect on temperature was analyzed by performing an experiment using the box benquin method among experiments were analyzed. Through the experimental analysis results, the optimal conditions for mist and processing that maximize the cooling effect were derived, and the validity of the results derived through additional experiments was verified. In the case of processing by applying the mist lubrication method verified through this study, it is considered that high-precision processing is possible by improving the cooling effect.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.69-74
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• 2022

Big data related analysis techniques, the prescriptive analytics methodology improves the performance of passive learning models by ensuring that active learning secures high-quality learning data. Prescriptive analytics is a performance maximizing process by enhancing the machine learning models and optimizing systems through active learning to secure high-quality learning data. It is the best subscription value analysis that constructs the expensive category data efficiently. To expand the value of data by collecting research field, research propensity, and research activity information, customized researcher through prescriptive analysis such as predicting the situation at the time of execution after data pre-processing, deriving viable alternatives, and examining the validity of alternatives according to changes in the situation Provides research information service.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.453-458
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• 2022

The Republic of Korea Army(ROKA) has carried out a deep change to prepare for the future war since 2017. For this, Korea Army Research Center for Future & Innovation(KARCFI) established in 2018 tried to spread out boom of innovation toward the whole ROKA. A number of ROKA members mentioned the necessity of research methodology creating future crucial capabilities, weapons, combat concepts, structures, etc. KARCFI researchers established a thinking process for revolution in military affairs(RMA) to rapidly respond field requests and optimized it through validity assessment of professionals and experiment in Army Innovation School. As a result, a thinking process for RMA provided creative ideas with the Army's vision and strategy, was included in its education system. Simultaneously, it became one of methodologies for the Army's research tasks and KCI journals. From now on, a thinking process for RMA will be able to signpost for RMA of the Army through diverse following studies.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.95-102
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• 2023

This study was to identify the factors affecting nurses' use intention of digital healthcare and the moderating effect of clinical career based on the UTAUT model. The items were composed by performance expectancy 3 items, facilitation condition 3tiems, and perceived risk 3 items. CFA was performed to verify the construct validity. As a results, average variance extracted (AVE) was .5 or higher, and construct reliability (CR) was .7 or higher. Model fit was confirmed as CMIN/df=1.797, GFI=.955, CFI=.979, TLI=.968, IFI=.979, and RMSEA=.063. The internal reliability was .93 for performance expectancy, .84 for facilitating conditions, and .64 for perceived risk. Performance expectancy, facilitating condition, and perceived risk had a significant effect on use intention, and clinical career showed a moderating effect(t=-2.159, p=.032). Therefore, in order to enhance the use intention of digital health care, performance expectancy, and facilitating conditions should be raised and perceived risk should be reduced.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.1-12
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• 2023

The era of digital transformation is rapidly emerging in industries and academia, including finance and logistics, and the consulting market for digital transformation is also growing. According to previous studies, the need for digital transformation is also mentioned in consulting institutions. In this process, the role of consultants should be changed according to the times, and customer relationship management and attitude toward customers are emphasized. However, consulting research has the point that research on this has not been studied in depth. Therefore, the purpose of this study is to develop an element of attitude focusing on consultant attitudes in the field of digital transformation. As a result of research using literature analysis and modified Delphi techniques, 'customer orientation', achievement orientation', professional dignity', 'maintenance of expertise', and 'ethics' were found to be key attitude factors. This study is meaningful in that consultant attitude elements in the digital transformation field were explored and developed by verifying content validity, and consultants in the digital transformation field can recognize the importance of attitude and use it as a basic tool for capacity improvement.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.17 no.2
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• pp.145-156
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• 2021

Ultrasonic Nanocrystal Surface Modification (UNSM) is a peening technology that generates elastic-plastic deformation on the material surface to which a static load of a air compressor and a dynamic load of ultrasonic vibration energy are applied by striking the material surface with a strike pin. In the UNSM-treated material, the structure of the surface layer is modified into a nano-crystal structure and compressive residual stress occurs. When UNSM is applied to welds in a reactor coolant system where PWSCC can occur, it has the effect of relieving tensile residual stress in the weld and thus suppressing crack initiation and propagation. In order to quantitatively evaluate the compressive residual stress generated by UNSM, many finite element studies have been conducted. In existing studies, single-path UNSM or UNSM in a limited area has been simulated due to excessive computing time and analysis convergence problems. However, it is difficult to accurately calculate the compressive residual stress generated by the actual UNSM under these limited conditions. Therefore, in this study, a minimum finite element peening analysis area that can reliably calculate the compressive residual stress is proposed. To confirm the validity of the proposed analysis area, the compressive residual stress obtained from the experiment are compared with finite element analysis results.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.129-136
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• 2023

The study aims to examine the determinants that affect satisfaction, revisit intention, and recommendation intention with foreign tourists who visited Korea despite the threat of COVID-19. This study employs the survey data collected by the Korea Tourism Organization from 8,135 foreign tourists who visited Korea in 2020. As the survey data contains a mixture of continuous and categorical variables, decision tree analysis can ensure analytical validity for the research. According to the analytical results, the determinants affecting satisfaction are the purpose of the visit and acceptance of self-quarantine during their stay. The factors influencing revisit intention are the purpose of the visit, frequency of the visit, and acceptance of self-quarantine during their stay. The determinants affecting recommendation intention are the purpose of the visit, length of stay, and gender. Based on the results of this analysis, this study not only explains the relationship between these determinants and tourism satisfaction, revisit intention, and recommendation intention, but also suggests implications for revitalizing tourism activities.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.13-20
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• 2023

In this paper, the actual data of VOC reduction facilities was analyzed through a model that detects and predicts data anomalies. Using the USAD model, which shows stable performance in the field of anomaly detection, anomalies in real-time data are detected and sensors that cause anomalies are searched. In addition, we propose a method of predicting and warning, when abnormalities that time will occur by predicting future outliers with an auto-regressive model. The experiment was conducted with the actual data of the VOC reduction facility, and the anomaly detection test results showed high detection rates with precision, recall, and F1-score of 98.54%, 89.08%, and 93.57%, respectively. As a result, averaging of the precision, recall, and F1-score for 8 sensors of detection rates were 99.64%, 99.37%, and 99.63%. In addition, the Hamming loss obtained to confirm the validity of the detection experiment for each sensor was 0.0058, showing stable performance. And the abnormal prediction test result showed stable performance with an average absolute error of 0.0902.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.297-302
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• 2022

The purpose of this study is to develop the management innovation scale for public institution and apply scale through examination of relationship between management innovation and innovation performance. As a result, we developed management innovation scale with 7 categories and verified its validity and reliability. Also we found positive effect of management innovation on innovative performance. Based on theses findings, implications of the research findings are discussed, and recommendations for future research are provided.