• Journal of Korean Home Economics Education Association
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• v.35 no.2
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• pp.1-20
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• 2023

The purpose of this study is to extract and analyze ecological citizenship elements in the middle school home economics textbook used in the 2015 national curriculum for the introduction of ecological transformation education in the 2022 national curriculum. As a result of the analysis, the content analysis of the ecological citizenship factor was validated by six experts who are incumbent middle school home economics teachers, and the S-CVI value was 0.97, ensuring the validity of the ecological citizenship factor analysis. The results of analyzing 242 ecological citizenship factors extracted from home economics textbooks are as follows. According to the content area of the 2015 national home economics curriculum, the 'human development and family' area had the highest presence of ecological citizenship factors followed by the 'resource management and self-reliance' area and the 'home life and safety' area. Among the categories of ecological citizenship factors, 'value⋅attitude' was the most frequent, followed by 'process⋅function' and 'knowledge⋅understanding'. For each textbook composition system, ecological citizenship elements were extracted in the order of pictures, text, activities, and supplementary materials. There was a significant variation in the number of ecological citizenship factors among publishers, indicating the importance of the textbook writers' perception, interpretation, and direction of writing. Based on these analysis results, ecological citizenship teaching and learning activities applicable to home economics education were presented. This study highlights the potential for practicing ecological citizenship education in line with the new orientation of the curriculum on ecological transformation education through home economics education. Furthermore, it provides valuable baseline data for the development and implementation of textbooks for the 2022 national curriculum.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Journal of Industrial Convergence
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• v.21 no.5
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• pp.1-13
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• 2023

Carbon neutrality is the concept of reducing greenhouse gases emitted by human activities and making actual emissions zero through removal of remaining gases. It is also called "Net-Zero" and "carbon zero". Korea has declared a "2050 Carbon Neutrality policy" to cope with the climate change crisis. Various carbon reduction legislative processes are underway. Since carbon neutrality requires changes in industrial technology, it is important to prepare a system for carbon zero. This paper aims to understand the status and trends of global carbon neutrality technology. Therefore, ROK's web platform "www.naver.com." was selected as the data collection scope. Korean online articles related to carbon neutrality were collected. Carbon neutrality technology trends were analyzed by future signal methodology and Word2Vec algorithm which is a neural network deep learning technology. As a result, technology advancement in the steel and petrochemical sectors, which are carbon over-release industries, was required. Investment feasibility in the electric vehicle sector and technology advancement were on the rise. It seems that the government's support for carbon neutrality and the creation of global technology infrastructure should be supported. In addition, it is urgent to cultivate human resources, and possible to confirm the need to prepare support policies for carbon neutrality.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.33-39
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• 2022

This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.

• Research in Community and Public Health Nursing
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• v.33 no.1
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• pp.13-31
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• 2022

Purpose: This study conducted a job analysis of visiting nurses in the process of change. Methods: Participants were the visiting nurses working for the Seoul Metropolitan city. On the basis of the Public Health Intervention Wheel model, two times of the focus group interview (FGI) with seven visiting nurses and one time of the Developing a Curriculum (DACUM) with 34 visiting nurses were performed. A questionnaire survey of 380 visiting nurses was conducted to examine the frequency, importance and difficulty levels of the tasks created by using the FGI and DACUM. Results: Visiting nurses' job was derived as the theme of present versus transitional roles. The present role was categorized as 'providing individual- and group-focused services' and 'conducting organization management', while the transitional role was categorized as 'providing district-focused services' and 'responding to new health issues'. The job generated 13 duties, 28 tasks, and 73task elements. The tasks showed the levels of frequency (3.65 scores), importance (4.27 scores), and difficulty (3.81 scores). All the tasks were determined as important, exceeding the average 4.00 scores. The group- and district-focused services of the tasks were recognized as more difficult but less frequent tasks. Conclusion: The visiting nurses exert both present and transitional roles. The transitional roles identified in the present study should be recognized as an extended role of visiting nurses in accordance with the current changing healthcare needs in South Korea. Finally, the educational curriculum for visiting nurses that reflects the transitional roles from the present study is needed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Trans-
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• v.14
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• pp.35-63
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• 2023

Parkinson's disease is a degenerative neurological disease that affects even basic daily life movements due to impairment of body function caused by a lack of dopamine, which is charge of the body movement. Presently, it is hard to cure Parkinson's disease entirely with medical technology, so movement therapy as a solution to delay and prevent disease is getting more attention. Therefore, this study aims at desiging and disseminating a body movement program that concentrates on individual self-care and balacing the state of body and mind by applying the Feldenkrais Method® to patients with Parkinson's disease. The Feldenkrais Method® is a mind-body perceptual learning method using body movements. It is a methodology that re-educates the nervous system by connecting the brain and behavior as a function of neuroplasticity. In this study, the body movement program developed and verified by the researcher was modified and supplemented with a focus on the self-awareness of the Feldenkrais Method®. A 24-session physical exercise program was composed of 5 stages to improve the self-management ability of patients with Parkinson's disease. The stages include self-awareness, self-observation, self-organization, self-control, and self-care. The overall changes recognize one's condition and improve one's ability to detect modifications in the internal sense and external environment. In conclusion, the body movement program improves the body movement program improves mental and physical functions and self-care for Parkinson's disease patients through the Feldenkrais method. The availability of the program's on-site applicability remains a follow-up task. Furthermore, it is necessary to establish a systematic structure to spread it more widely through convergent cooperation with the scientific field applied with metaverse as a reference for the wellness of the elderly.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.90-103
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• 2023

The purpose of this study is to examine the anxiety arising from the budgetary and mental problems of graduate school students. Three graduate students majoring in Earth science examined conflict situations by using a narrative inquiry technique. First, participants become psychologically unstable due to a lack of knowledge in the field of Earth science, lack of mentors, lack of information related to academic schedules, late start compared to others, financial difficulties, and discrimination in the scholarship system. Second, participants felt hope from the perception that their lives are valuable, that they can change students for the better, and that they are developing themselves. Third, with their hope, the study participants bore the previously mentioned inferior situation mentioned above. They are, however, torn between becoming secondary school teachers and attempting to reroute their career path due to certain circumstances. Based on the results of the examination, the following conclusions were drawn. First, there should be improvements from graduate school management based on collecting and scrutinizing the demands of students in the to fulfill their needs. Second, providing psychological counseling for students who have problems overcoming their anxieties. This study expects graduate schools to not only emphasize training of incumbent teachers, but also suggest ways that can satisfy students to make better learning environment for all its members.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.123-132
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• 2023

Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.