• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.499-505
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• 2022

This study aims to provide basic data for the development of educational programs for effective gender equality education in elementary schools by confirming the consciousness of gender equality in the 5th and 6th graders of elementary school. In this study, 5th and 6th graders attending three elementary schools located in G and A cities explained the research and collected data using questionnaires from 190 people who wished to participate in the research. Frequency analysis and percentage were used for general characteristics of subjects, and t-test and ANOVA were used for differences in gender equality awareness according to subjects' sex, grade, and number of siblings. Consciousness of gender equality showed an average of 3.47 points out of 4, with an average of 3.51 points in the social and cultural life area, 3.49 points in the home life area, 3.47 points in the school life area, and 3.38 points in the vocation life area. Various activities should be conducted to raise students' consciousness of gender equality, and families, schools, and society should jointly strive to create a gender-equal cultural climate. Future study is needed to identify the factors affecting the gender equality awareness of elementary school students.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.391-398
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• 2022

The aim of this study was to identify the factors affecting the mental health of high school students. The participants comprised 216 students in general high school. Data collection was conducted from May 1, 2020 to May 20, 2020. The data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and a multiple regression analysis. The average score for self-esteem was 3.75±0.64(1-5), perceived stress was 2.86±0.58(1-5), emotional regulation ability was 3.43±0.65(1-5) and mental health was 1.91±0.71(1-5). Mental health had a statistically significant relationship with self-esteem(r=-.64, p<.001), emotional regulation ability(r=-.61, p<.001) and perceived stress(r=.54, p<.001). The factors affecting mental health were self-esteem(β=.46, p<.001), emotional regulation ability(β=-.37, p<.001), negative perceived stress(β=.17, p=.001) ; the explanatory power of the model was 60.0%. Therefore, it will be necessary to develop a program that can help high school students improve their self-esteem and control their negative emotions in order to promote their mental health.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.47-61
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• 2023

Satisfaction on the residential environment is a major factor influencing the choice of residence and migration, and is directly related to the quality of life in the city. As online services of real estate increases, people's evaluation on the residential environment can be easily checked and it is possible to analyze their satisfaction and its determining factors based on their evaluation. This means that a larger amount of evaluation can be used more efficiently than previously used methods such as surveys. This study analyzed the residential environment reviews of about 30,000 apartment residents collected from 'Zigbang', an online real estate service in Seoul. The apartment review of Zigbang consists of an evaluation grade on a 5-point scale and the evaluation content directly described by the dweller. At first, this study labeled apartment reviews as positive and negative based on the scores of recommended reviews that include comprehensive evaluation about apartment. Next, to classify them automatically, developed a model by using Bidirectional Encoder Representations from Transformers(BERT), a deep learning-based natural language processing model. After that, by using SHapley Additive exPlanation(SHAP), extract word tokens that play an important role in the classification of reviews, to derive determining factors of the evaluation of the residential environment. Furthermore, by analyzing related keywords using Word2Vec, priority considerations for improving satisfaction on the residential environment were suggested. This study is meaningful that suggested a model that automatically classifies satisfaction on the residential environment into positive and negative by using apartment review big data and deep learning, which are qualitative evaluation data of residents, so that it's determining factors were derived. The result of analysis can be used as elementary data for improving the satisfaction on the residential environment, and can be used in the future evaluation of the residential environment near the apartment complex, and the design and evaluation of new complexes and infrastructure.

• Journal of Science Education
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• v.46 no.2
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• pp.195-211
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• 2022

In this study, we explored the meaning of astronomical observation activities of five earth science teachers through in-depth interviews. Semi-structured interviews were conducted after providing a questionnaire based on Seidman's three-step process of interview. By analyzing the interview transcript, the educational implications inherent in astronomical observation activities were extracted. Teachers have constructed systematic basis of observation and astronomy in the observational astronomy and laboratory class during their course in the teacher education institute. After they became in-service teachers, practical know-hows of astronomical observation activities in schools were developed with the help of colleagues. By designing and executing astronomical observation activities for students, teachers notice positive changes in the cognitive domain, affective domain, and career perception of the students. Hence, teachers consider that astronomical observation activities have great educational effects. In addition, astronomical activities appear to be very rewarding and satisfying experiences to teachers, by providing opportunities for having pride as an earth science teacher. However, teachers tend to find difficulties in operating astronomical observation activities in fields, due to both internal and external obstacles. It is found that the removal of internal obstacles is more important for teachers to attempt or to continue astronomical observation activities. In this sense, it is necessary to support teachers by providing timely training courses with related content, as well as opportunities to share their experiences within a peer group such as teachers' research society.

• Journal of Science Education
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• v.47 no.1
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• pp.1-10
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• 2023

In this study, we investigated the perception of STEAM (science, technology, engineering, arts, and mathematics) education consultants (SEC) about the requirements to achieve actual results and the improvements for STEAM education consulting. Data were collected from teachers who have had previous SEC experience or have extensive experience in STEAM education. First, an open-ended questionnaire was used to conduct a survey on the requirements and improvements for the STEAM education consulting, and items were composed by analyzing the contents of these free responses, and then statistical analysis was performed by asking them to respond on the Likert scale to how much they agreed to each item. As a result of the analysis, the SEC recognized that "formation of consensus between consultants and teachers", "consultant feedback on reflection of previous consulting results" and "encouragement and support for teachers" are appeared to be the most required for STEAM education consulting to achieve actual results. As the improvements of STEAM education consulting, "sharing cases and opinions among consultants", "selection and sharing of consulting best practices", and "development of various consulting types such as open classes" received the highest agreement. Based on these results, a support plan to increase the effectiveness of STEAM consulting was proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.83-89
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• 2023

The clustering technique using RF fingerprint extracts the characteristic signature of the transmitters which are embedded in the transmission waveforms. The output of the RF-Fingerprint feature extraction algorithm for clustering identical DMR(Digital Mobile Radios) is a high-dimensional feature, typically consisting of 512 or more dimensions. While such high-dimensional features may be effective for the classifiers, they are not suitable to be used as inputs for the clustering algorithms. Therefore, this paper proposes a dimension reduction algorithm that effectively reduces the dimensionality of the multidimensional RF-Fingerprint features while maintaining the fingerprinting characteristics of the DMRs. Additionally, it proposes a clustering algorithm that can effectively cluster the reduced dimensions. The proposed clustering algorithm reduces the multi-dimensional RF-Fingerprint features using t-SNE, based on KL Divergence, and performs clustering using Density Peaks Clustering (DPC). The performance analysis of the DMR clustering algorithm uses a dataset of 3000 samples collected from 10 Motorola XiR and 10 Wintech N-Series DMRs. The results of the RF-Fingerprinting-based clustering algorithm showed the formation of 20 clusters, and all performance metrics including Homogeneity, Completeness, and V-measure, demonstrated a performance of 99.4%.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.87-98
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• 2023

In this study, we investigated the change in science core competency perception of high school students and the reason for change when science inquiry classes were conducted using eight 'skills' of the 2015 revised science curriculum. Fifteen first-year high school students in Jeollanam-do participated in the science inquiry class of this study, and the class was conducted for 20 hours (5 hours a day for four days). The inquiry activities used in the class consisted of four activity stages (research problems, research methods, research results, and conclusions) and each stage was constructed to include at least one 'skill (Problem Recognition, Model Development and Use, Inquiry Design and Performance, Data Collection, Analysis and Interpretation, Mathematical Thinking and Computer Application, Conclusion and Evaluation, Evidence-based Discussion and Demonstration, and Communication)'. As a result of the study, students' perception of the five science core competencies increased statistically significantly at the significance level of 0.01 through inquiry classes and more than 93% of students recognized that their science core competencies improved through the classes. However, since the class of this study was conducted for a small number of students, it is difficult to generalize the effect of the class, and so it is necessary to conduct a quantitative study for many students.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.171-177
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• 2022

The retirement of the Korean baby boomer generation has become a major factor in an aging society as a large proportion of the population has moved from the middle-aged to the elderly. In addition, after being busy working at a structured workplace for over 30 years, after retirement, they could not adapt to the unstructured environment, causing depression and leading to social problems such as the risk of suicide. research was needed. This study uses photovoice to in-depth research on the research question of how retirees' perception of death preparation, who wants to live a life prepared until death, is used. This is the purpose of this study. The study participants were 7 baby boomer retirees, the data were collected for 2 months, and the perception derived as a result of analyzing the photos, explanations, and in-depth interviews taken by the subject analysis method was used to prepare It was a necessity for education. In the discussion of this study, it is urgent to develop a death preparation education program that can help the baby boomer retirees, and I would like to suggest that the cooperation of local organizations in charge of the program is necessary. This study is meaningful in that it presents basic data in preparing social welfare policy measures for the elderly after retirement through the awareness of death preparations of baby boomer retirees.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.