• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.421-426
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• 2024

The Analytic Hierarchy Process (AHP) converts people's judgment criteria into objective numerical values using pairwise comparisons. However, the need for an excessive number of pairwise comparisons poses a problem. To mitigate this issue, most existing studies have utilized the process separation approach. The method of process separation devised in this study is a "separation and integration approach," where 1) the standard AHP process is used for evaluating judgment criteria, and 2) the Multi-Attributive Utility Technique (MAUT) is applied for comparing alternatives. This AHP-MAUT Hybrid model was applied to a real analysis case, specifically analyzing the transportation choices of commuters between Bundang and Gangnam Station in Gyeonggi Province. The results showed that the computational process was reduced by 42.03% when applying the Hybrid model compared to using the AHP model alone. Furthermore, the choice results of residents using the Hybrid model were compared with those using the standard AHP. The consistency between the two models' choices was 82.1%, indicating a significant level of consistency. In conclusion, this study contributes by presenting a simpler, more convenient, yet equally effective Hybrid model as a new decision-support system alternative to AHP.

• Journal of dental hygiene science
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• v.24 no.2
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• pp.115-123
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• 2024

Background: The population of Gangneung City in South Korea has shown a gradual increase in the proportion of individuals aged 65 years and older, and the most frequently reported diseases for several years have consistently been periodontal diseases, including gingivitis and periodontitis. The regional imbalance in the distribution of dental personnel and resources has emerged as a problem of inequality in the use of dental care. It has been advocated to identify areas with disadvantages in dental care and develop public dental policies based on that. This study aimed to develop a customized oral healthcare program for local seniors based on a Public-Private-Academic Partnership, and to evaluate the oral health status of older adults in Gangneung City. Methods: The participants were residents aged 60 years and above in Gangneung City. A questionnaire including general information, systemic health status, and oral health status was administered to the participants. In addition, oral healthcare and education tailored to each individual's health status were provided once or twice based on their oral health status. The collected data were analyzed using IBM SPSS Statistics 25 for descriptive statistical analysis. Results: Among the older adults in Gangneung City, 75% had at least one prosthesis and exhibited symptoms of gingivitis or periodontitis. Additionally, the modified sulcus bleeding index decreased among participants who underwent the program twice. Over 90% of the participants expressed satisfaction with the program. Conclusion: The program appeared to contribute positively to the oral health promotion among local seniors. Further oral healthcare programs should focus on seniors in rural and old urban areas to reduce disparities in oral health across regions.

• Annals of Occupational and Environmental Medicine
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• v.34
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• pp.23.1-23.14
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• 2022

Background: The musculoskeletal disease (MSD) burden is an important health problem among Korean fishers. We aimed to investigate the indicators of the prevalence of MSD and contributions of significant indicators to MSD in Korean fishers. Methods: This cross-section study included 927 fishers (male, 371; female, 556) aged 40 to 79 years who were enrolled from 3 fishery safety and health centers. The outcome variable was one-year prevalence of MSD in 5 body parts (the neck, shoulder, hand, back, and knee). Independent variables were sex, age, educational attainment, household income, job classification, employment xlink:type, hazardous working environment (cold, heat, and noise), ergonomic risk by the 5 body parts, anxiety disorder, depression, hypertension, diabetes, and hyperlipidemia. The adjusted odds ratio of MSDs by the 5 body parts were calculated using multiple logistic regression analysis. We computed the population attributable fraction (PAF) for each indicators of MSDs using binary regression models. Results: The one-year prevalence of MSD in the neck, shoulder, hand, back, and knee was 7.8%, 17.8%, 7.8%, 27.2%, and 16.2% in males vs. 16.4%, 28.1%, 23.0%, 38.7%, and 30.0% in females, respectively. The ergonomic risk PAF according to the body parts ranged from 22.8%-59.6% in males and 22.8%-50.3% in female. Mental diseases showed a significant PAF for all body parts only among female (PAF 9.1%-21.4%). Cold exposure showed a significant PAF for the neck, shoulder, and hand MSD only among female (25.6%-26.8%). Age was not a significant indicator except for the knee MSD among female. Conclusions: Ergonomic risk contributed majorly as indicators of MSDs in both sexes of fishers. Mental disease and cold exposure were indicators of MSDs only among female fishers. This information may be important for determining priority risk groups for the prevention of work-related MSD among Korean fishers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.577-586
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• 2024

As new technologies are developed, new security threats such as the emergence of AI technologies that create ransomware are also increasing. New security equipment such as XDR has been developed to cope with these security threats, but when using various security equipment together rather than a single security equipment environment, there is a difficulty in creating numerous regular expressions for identifying and classifying essential data. To solve this problem, this paper proposes a method of identifying essential information for identifying threat information by introducing artificial intelligence-based entity name recognition technology in various security equipment usage environments. After analyzing the security equipment log data to select essential information, the storage format of information and the tag list for utilizing artificial intelligence were defined, and the method of identifying and extracting essential data is proposed through entity name recognition technology using artificial intelligence. As a result of various security equipment log data and 23 tag-based entity name recognition tests, the weight average of f1-score for each tag is 0.44 for Bi-LSTM-CRF and 0.99 for BERT-CRF. In the future, we plan to study the process of integrating the regular expression-based threat information identification and extraction method and artificial intelligence-based threat information and apply the process based on new data.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.274-280
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• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.

• Journal of Korean Home Economics Education Association
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• v.35 no.4
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• pp.1-12
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• 2023

At a time when interest in the educational use of ChatGPT is increasing, it is necessary to investigate the perception of ChatGPT among college students. A survey was conducted to compare the current status of internet and interactive artificial intelligence use and perceptions of ChatGPT after using it in the following courses in Spring 2023; 'Family Life and Culture', 'Fashion and Museums', and 'Fashion in Movies' in the first semester of 2023. We also looked at comparative analysis reports and reflection diaries. Information for coursework was mainly obtained through internet searches and articles, but only 9.84% used interactive AI, showing that its application to learning is still insufficient. ChatGPT was first used in the Spring semester of 2023, and ChatGPT was mainly used among conversational AI. ChatGPT is a bit lacking in terms of information accuracy and reliability, but it is convenient because it allows students to find information while interacting easily and quickly, and the satisfaction level was high, so there was a willingness to use ChatGPT more actively in the future. Regarding the impact of ChatGPT on education, students said that it was positive that they were self-directed and that they set up a cooperative class process to verify information through group discussions and problem-solving attitudes through questions. However, problems were recognized that lowered trust, such as plagiarism, copyright, data bias, lack of up-to-date data learning, and generation of inaccurate or incorrect information, which need to be improved.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.76-86
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• 2024

This study sought to introduce smart urban regeneration to solve the problem of aging and substandard housing in large cities that occurred during the rapid industrialization and urbanization of local cities in Korea. Accordingly, this study aims to activative the old downtown through the convergence of the existing urban regeneration project and smart city project and to improve the physical, social, and economic aspects. As a research method, the literature related to smart cities and urban regeneration was systematically reviewed, and the possibility of introducing smart city services in the Samho-dong district of Yangsan City was explored through domestic and foreign case analysis. As a result of the research, the necessity of smart urban regeneration was highlighted, and the conclusion was reached that it is important to improve the efficiency of urban regeneration projects by using information and communication technology and strengthen sustainability by urban regeneration. This study is expected to contribute to the activative the old downtown and the improvement of the quality of life of citizens, and it is necessary to strengthen the interaction between smart city and urban regeneration in the future, and the introduction of smart city services suitable for local characteristics is judged to play an important role in sustainable urban development through local community and citizen participation.

• Journal of Korean Home Economics Education Association
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• v.36 no.2
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• pp.15-31
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• 2024

This study employs photovoice research methodology to investigate adolescents' experiences in sibling relationships and to analyze the impact of sibling interactions on their development and growth. The participants comprised eight high school students with one sibling (four males and four females) residing in the Incheon region. The research process encompassed several stages: participant recruitment, orientation, photovoice activity (focus group interviews), data analysis, and conclusion derivation. During the photovoice activity, participants engaged in a narrative process of photographing, interpreting, and discussing their experiences. The narratives were categorized into four primary themes: structure and environment, emotional interactions, roles, and parental subsystems. The conclusions drawn from the study are as follows: First, the similarity formed in sibling relationships during adolescence contributes to psychological stability. Second, roles and expectations based on birth order can cause stress for adolescents, indicating the need for equitable role adjustments within the family. Third, conflict in sibling relationships is crucial for enhancing problem-solving and social relationship skills. Lastly, consistent parenting attitudes significantly affect the emotional well-being of siblings. This study emphasizes the significance of fostering a deeper understanding of human development and family relationships through an exploration of adolescent sibling dynamics within home economics education.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.1-8
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• 2024

As technology advances, Internet of Things (IoT) technology is rapidly evolving as well. Various protocols, including Message Queuing Telemetry Transport (MQTT), are being used in IoT technology. MQTT, a lightweight messaging protocol, is considered a de-facto standard in the IoT field due to its efficiency in transmitting data even in environments with limited bandwidth and power. In this paper, we propose a method to improve the message transmission method in MQTT 5.0, specifically focusing on the shared subscription feature. The widely used round-robin method in shared subscriptions has the drawback of not considering the current state of the clients. To address this limitation, we propose a method to select the optimal transmission method by considering the current state. We model this problem based on Markov decision process (MDP) and utilize Q-Learning to select the optimal transmission method. Through simulation results, we compare our proposed method with existing methods in various environments and conduct performance analysis. We confirm that our proposed method outperforms existing methods in terms of performance and conclude by suggesting future research directions.

• Communications of Mathematical Education
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• v.38 no.3
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• pp.379-400
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• 2024

This study aims to propose a method for analyzing mathematics assessment data that integrates both content and cognitive domains, utilizing the multidimensional two-parameter logistic model with a Q-matrix (M2PL-Q; da Silva, 2019). The method was applied to the TIMSS 2019 8th-grade mathematics assessment data. The results demonstrate that the M2PL-Q model effectively estimates students' ability levels across both domains, highlighting the interrelationships between abilities in each domain. Additionally, the M2PL-Q model was found to be effective in estimating item characteristics by differentiating between content and cognitive domain, revealing that their influence on problem-solving can vary across items. This study is significant in that it offers a comprehensive analytical approach that incorporates both content and cognitive domains, which were traditionally analyzed separately. By using the estimated ability levels for individual student diagnostics, students' strengths and weaknesses in specific content and cognitive areas can be identified, supporting more targeted learning interventions. Furthermore, by considering the detailed characteristics of each assessment item and applying them appropriately based on the context and purpose of the assessment, the validity and efficiency of assessments can be enhanced, leading to more accurate diagnoses of students' ability levels.