• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.95-106
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• 2005

Road accidents are considered as the result of a complex interplay between road, vehicle, environments, and human factors. Little study, however, has been carried out on the attributes of human factor compared to the road geometric conditions and traffic conditions. The previous researches focused on mainly both traffic and geometric conditions on specific location. Therefore, it's hard to explain phenomenon of the high traffic accident rates where road and traffic conditions are good. Because of these reasons, accident analysis has contributed on geometric improvement and has not contributed on traffic management such as selection of attention section, driver napping alert, etc. The freeway incident management is also associated with reliable prediction of incident occurrences on freeway sections. This paper presents a method for estimating the effect of trip length on freeway accident rate. A PAR (Potential Accident Ratio), the new concept of accident analysis, considering TLFDs (Trip Length Frequency Distributions) is suggested in this paper. This approach can help to strengthen freeway management and to reduce the likelihood of accidents.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.416-428
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• 2019

The purpose of this study is to provide basic data for the development of pre-parent education program by grasping parent role recognition, educational needs and readiness of unmarried men and women. The subjects were 196 unmarried male and female students from K-do. Data were collected from November 1st to 20th, 2018, and analyzed using IBM SPSS WIN/21.0 to get frequency, percentage, average, standard deviation, t-test, ANOVA, sheffe-test, paired t-test, and IPA matrix. The average score of recognition of social pre-parent role was $3.41{\pm}0.27$ (out of 5 points), educational needs was $3.48{\pm}0.41$ points (out of 4 points), and educational readiness was $2.65{\pm}0.57$ points (out of 4 points). educational needs being higher than educational readiness. Through IPA matrix analysis, the area to be strengthened was 'family relation or parent role', and 'self understanding' was the area to encourage putting effort into other evaluation attributes. The area where no further effort is needed and needs improvement in the future was 'spouse selection and marriage', and 'pregnancy and childbirth' and 'child rearing' were the areas to intensively improve. Therefore, there is a need for establishing a standardized strategy in the area A, which has high degree of readiness and needs. Also, it is necessary to take strategies and countermeasures to raise the readiness of area C with low degree of readiness and needs, rather than accepting it as an unnecessary area of further effort input.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.485-494
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• 2021

This study aimed to examine the effect of selected factors on confidence in nursing performance among new operating room nurses, with a focus on the mediating effect of learning flow. Data was collected from July to August 2019 using structured questionnaires. The participants were 250 new operating room nurses from university hospitals located in Incheon and Gyeonggi. The collected data was analyzed using the IBM SPSS Statistics 25.0 and AMOS 24.0. Structural equation modeling was performed to examine the effect of the selected factors namely web-based video programs on confidence in nursing performance, and the mediating effect of learning flow. Results: The factors of 'hygiene & safety' and 'patient care' from the web-based video programs had a positive effect on the learning flow. The higher the learning flow of the nurses, the greater their confidence in nursing performance. Just the 'hygiene & safety' factor significantly increased nursing performance. Conclusion: The study results suggest that new nurses perceive that 'hygiene & safety' is an important factor in building their confidence in nursing performance, even without the learning flow. Therefore, it is necessary to develop web-based video programs based on nurses' needs and to emphasize the importance of postoperative care.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.65-74
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• 2021

Since 2020, the GuangXi government of China has focused on the deep integration of tea industry with leisure and cultural tourism, popular science education, health care and elderly care industries. Among the output value targets of the tertiary industry, the GuangXi government plans to achieve 25 billion yuan, and the tea industry is developing rapidly. Through questionnaire survey, field research and interview, this paper studies the differences of demand behavior and selection attributes of tea products among consumers in different years, and finally studies the evolution pattern of service mode of tea industry in GuangXi. The results show that there are obvious differences in life and work style, shopping habits, service design, user experience, social needs and personality needs of each generation consumers in different years. Based on the analysis of demand and behavior habits of tea products, the evolution pattern of service mode of tea industry in GuangXi is studied. Based on the above results, according to the differences of consumers' choice of tea products in different years, the service mode of tea industry in GuangXi is improved The development of tea industry in service design, user experience level is worthy of in-depth attention.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• Smart Media Journal
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• v.9 no.4
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• pp.66-72
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• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.222-235
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• 2022

The Government provides a financial assistance to stimulate firm R&D and innovation activities. Previous papers on the impact of public subsidies on firm R&D investments mainly had a focus on an individual policy tool regardless of potential impacts of other policy instruments. This study addresses this gap by examining the effects of policy mix regarding a subsidy and a tax credit. The empirical analyses from fixed effect model using Survey on Technology of SMEs 2015-2017 revealed valuable points. First, policy mix induces more R&D investment of SMEs, which in turn, shows a complementary relationship between two instruments. Second, even if impact of tax credit controlled, subsidy is positively associated with SMEs R&D investment. These findings justify policy mix interventions to promote SME R&D activity. Moreover, grants can be applied as a more useful policy tool for SMEs that are constrained by resources and capabilities.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.169-192
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• 2024

This study was conducted with the aim of providing a foundation for high-quality national place name authority data by developing Korean-specific guidelines for place name authority data in response to the need for systematic construction and standardization of authority databases. To this end, a survey of domestic and international trends and cases related to place name authority data was conducted, and the rules and guidelines of each country for establishing place name authority data were analyzed. Based on these surveys and rule analyses, the scope of concepts and terminology required to build a place name authority database were defined and the direction for the development of place name authority data guidelines was set. The analysis also determined the scope and framework of the guidelines, and how they should be referenced to existing rules. The structure of the guidelines proposed in this study is based on the original RDA and NCR. Based on the implications derived from the analysis process, the guidelines were organized and presented in terms of scope of construction, selection and recording of preferred place names, recording of variant place names, and attributes of place names to propose a technical guideline for place name authority data that fits the Korean situation. Future discussions were revealed accordingly.