• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.261-268
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• 2024

This study developed a pattern design that is highly useful in the modern culture and tourism industry based on various formative elements that appeared in the cloud-treasure pattern on fabrics from the Joseon Dynasty. The cloud-treasure pattern has an auspicious meaning. Therefore, the wrapping cloth with this pattern symbolizes the meaning of giving a precious gift. There are many aesthetic and formative elements in royal culture that can be utilized in the development of various cultural products. Therefore, it has very high utility value even in modern times. We examined rare royal wrapping cloth and applied its formative characteristics to develop a popular package design. Through this, another possibility was presented in the convergence of traditional culture and design. In particular, we actively combined the pattern of wrapping cloth with the 2024 fashion trend to develop a unique and trendy pattern design. The main source of the pattern design is the silk jacquard wrapping cloth with cloud-treasure pattern, a relic of Princess Myeong-an owned by the Seoul Museum of Craft Art. The researcher directly examined the wrapping cloth to extract 14 design motifs and developed 6 types of trendy patterns by combining them with dot and ribbon patterns, which are pattern trends for 2024. Afterwards, the pattern was mapped onto a box package similar to a wrapping cloth and expressed virtually.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.163-171
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• 2024

This study applies neural network analysis techniques to examine the factors influencing the purchasing decisions of fashion eyewear among women in their 30s and 40s, comparing these findings with traditional parametric analysis methods. In the fashion area, machine learning techniques are utilized for personalized fashion recommendation systems. However, research on such applications in Korea remains insufficient. By reanalyzing a study conducted in 2017 using traditional quantitative methods with these new techniques, this study aims to confirm the utility of neural network methods. Notably, the study finds that the classification accuracy of preferred sunglasses design is highest, at 86.2%, when the L-BFGS-B neural network is activated using the hyperbolic tangent function. The most critical factors influencing purchasing decisions were consumers' occupations and their pursuit of new styles. It is interpreted that Korean sunglasses consumers prefer "safe changes." These findings are consistent for selecting both the frames and lenses of sunglasses. Traditional quantitative analysis suggests that the type of sunglasses preferred varies according to the group to which a consumer belongs. In contrast, neural network analysis predicts the preferred sunglasses for each individual, thereby facilitating the development of personalized sunglasses recommendation systems.

• Journal of Korean Home Economics Education Association
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• v.26 no.3
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• pp.35-52
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• 2014

This study analyzed the 12 different technology home economics textbooks I, II for middle school students and the content systems of the textbooks by 7 instructional strategies in Reigeluth's elaboration theory. The units analyzed were 'Clothing and self-expression' and 'Eco-friendly clothing life and recycling by reform'. The purpose of this study was to provide basic information for the development of textbooks and teaching materials by analyzing current textbooks. Researchers analyzed the textbooks individually using pre-developed analysis frame using Reigeluth's elaboration theory. The results of the study were as follows. The conceptual elaboration process was used in the unit of 'Clothing and self-expression' of all the textbooks used in this study, and procedural elaboration process was mostly used in the unit of 'Eco-friendly clothing life and recycling by reform'. The strategies of advance learning ability were presented mostly in the forms of 'Learning Objective', 'Thought Opening', 'Key terms' in either unit and sub unit. The strategies of summarizer were presented as 'Unit Summary', 'Cleanup' and 'Assessment'. The strategies of synthesizer were used in all the textbooks as the 'Exploration' to increase the students interest through the promotion of the learning content in a variety of activities and projects. The cognitive activator strategies were shown in all of the textbooks using mostly 'Figure,' and others such as 'Table,' 'Diagram', and 'Explanation of Terms'. The strategies of learner control were used to guide the supplement and deepen the learning by various forms. However the analogy strategies were hardly used in units of textbooks analyzed in this study. As a result, the technology home economics textbooks I, II for middle school students applied the Reigeluth's elaboration theory, except the analogy strategies. It is recommended to utilize th analogy strategies and various activities to enhance the students' understanding and participation.

• Journal of the Korean Geotechnical Society
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• v.25 no.4
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• pp.91-103
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• 2009

Slope failure depends upon the climatic features related to related rainfall, structural geology and geomorphological features as well as the variation of the mechanical behaviors of soil constituting a slope. In this paper, among many variables, effects of soil layer thickness on the slope failure process, and variations of matric suction and volumetric water content were observed. When the soil layer is relatively thick, the descending wetting front decreases matric suction and the observed matric suction reaches to "0" value. When the wetting front reaches to the impermeable boundary, the bottom surface of steel soil box, ascending wetting front was observed. This observation can be postulated to be the effects of various sizes of pores. When macro size pores exist, the capillary effects can be reduced and infilling of pore will be limited. The partially filled pores would be filled with water during the ascending of the wetting front, which bounces from the impermeable boundary. This assumption has been assured from the observation of variation of the volumetric water contents at different depth. When the soil layer is thick (thickness = 20 cm), for granular material, erosion is a cause triggering the slope failure. It has been found that the initiation of erosion occurs when the top soil is fully saturated. Meanwhile, when the soil layer is shallow (thickness = 10 cm), slope slides as en mass. The slope failure for this condition occurs when the wetting front reaches to the interface between the soil layer and steel soil box. As the wetting front approaches to the bottom of soil layer, reduction of shear resistance along the boundary and increase of the unit weight due to the infiltration occur and these produce complex effects on the slope failure processes.

• Journal of Practical Engineering Education
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• v.16 no.5_spc
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• pp.747-756
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• 2024

The purpose of this study was to discover the desirable ESG direction of public institutions and obstacles to promoting ESG management as perceived by members within public institutions. To this end, three research questions were set and FGI was conducted on eight groups of public institution members. As a result of the FGI data analysis, 9 subfactors and 43 meaning units in 3 dimensions corresponding to the answers to the 3 research questions were derived. The first dimension, public institution members' awareness of ESG, consisted of three subfactors: ESG was recognized as an environmental protection trend related to the climate change crisis, and as a marketing tool used by companies to enhance their image. In addition, it was recognized as a newly included public institution management evaluation index. The second dimension, obstacles to the promotion of ESG in public institutions, appeared to be four subfactors: a government-dependent management system strongly influenced by the government, a rigid internal communication system in a top-down manner, the possibility of lack of sincerity in promoting ESG management, limitations of the internal human resource management system, etc. The third dimension, the desirable ESG direction of public institutions, was found to be two subfactors, including priority promotion of activities that meet the unique purpose of public institutions and ESG activities that can grow together with the region as a member of the local community. This study is significant in that, unlike existing studies that discovered positive antecedent factors that affect a company's ESG management performance, it identified factors that impede performance achievement from the perspective of the members who drive ESG.

• Journal of The Korean Association For Science Education
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• v.32 no.10
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• pp.1502-1523
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• 2012

Recently, there have been growing interest in teachers' professional development since teachers were regarded as a critical factor in the context of the reform efforts. Along with these efforts, educational researchers have continued to implement various programs to improve teachers' subject matter knowledge, beliefs, and their practices. Although considerable researches have been done regarding the efficiency of these programs, most of them have focused on individual teacher's change. However, a "teacher's mind is socially formed" (Edwards, 2001). This perspective indicates that teacher change is necessarily viewed in terms of social mediational process between individual and the social context. This study examines the interactions between teachers and researchers in order to explore the mediational processes and the aspects of collective understanding, which has emerged from the collaborative workshop. The data were collected from small group activities in a workshop and then analyzed using interactional sociolinguistic approach. Futhermore, activity system was employed to describe the social mediational process. The findings show that participating teachers constructed knowledge through conflict regarding collective understanding. This process of collective understanding was mediated by object, rules, and roles within each activity system. Findings from the study suggest that the sociocultural perspectives to teacher education are essential in understanding how teachers learn to teach and that teachers' professional discourse can play a significant role in teachers' professional development.

• 한국노년학
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• v.38 no.3
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• pp.409-433
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• 2018

The purpose of this study is to examine the effect of contact with the elderly in a daily life on children's ageist attitude. Acknowledging the people's tendency to report in socially appropriate ways to the explicit attitude measurement, implicit measurement is introduced, and relation with the daily contact with elderly(DCE) is analyzed. The research question are as follows: 1) Are these two attitudes explained by different factors? 2) Can DCE alleviate both children's implicit and explicit ageist attitude? 3) How do the contact with grandparent and neighboring elderly affect the children's explicit and implicit ageist attitude? Data was collected from 503 fourth to sixth grade elementary school children. Child-Age Implict Association Test is used to measure implicit ageist attitude. Multinominal logistic analysis and ordered logistic analysis was applied. Followings are the main results: First, explicit and implicit ageist attitudes are found to be related with different predictors. Second, Elderly contact seems to lighten children's ageist attitude overall. Third, the effects of grandparental contact and the neighboring elderly contact on two different ageism were different. While the effect of elderly neighbor contact is limited to the expression of ageism, grandparental contact has a influence not only on the explicit but also on the implicit ageism, even though the effect on implicit attitude is limited in extent. Forth, not the quality of contact but the quantity of it was related to implicit ageist attitude. This result contradicts conventional idea of Intergroup Contact Theory. In the further research, the predictor of implicit ageist attitude need to be throughly examined.

• Journal of Korean Society of Forest Science
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• v.32 no.1
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• pp.29-35
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• 1976

In order to estimate sawmill productivities, rates of technical change and optimum combination of production factors, Cobb-Douglas production functions have been derived using data obtained from 96 sample mills in Busan-Incheon, southwestern and northeastern areas. The results may be summarized as follows: 1. There is a tendency of expanding average sawmill size in the areas. The horse-power holdings per mill have been increased at the rates of 91 percent in Busan-Incheon, 7.7 percent in southwestern and 16.9 percent in northeastern areas. This implies that the mills around log-importing ports have made rapid development, compared with those in forest regions. 2. The regression coefficients (production elasticities) of the functions for the year of 1967 in the above three areas are much similar each other, but significant differencies are found in the production functions of 1975. In other words, sawmill productivity was mainly restricted by capital deficiencies in all areas in 1967, but this situation was succeeded only by N-E area in 1975. The range of sum of regression coefficients is 1.0437-1.4214, this indicates increasing rates of return to scale. 3. The annual rates of technical changes in B-I, S-W and N-E areas for the observed period are 17.6, 7.6 and 2.2 percents respectively. Busan-Incheon is the only area where labor productivity is higher than that of capital. 4. The best combination of production factors for maximizing firm's profit is subject to the changes of input and output prices. With some assumptions of prices and costs, the optimum levels of power and labor input in B-I, S-W and N-E areas are 57:17, 427:94 and 192:27.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.89-96
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• 2016

By reviewing preceding studies of big data and spatial big data, spatial big data was defined as one part of big data, which spatialize location information and systematize time series data. Spatial big data, as one part of big data, should not be separated with big data and application methods within the system is to be examined. Therefore in this study, services that spatial big data is required to provide were suggested. Spatial big data must be available of various spatial analysis and is in need of services that considers present and future spatial information. Not only should spatial big data be able to detect time series changes in location, but also analyze various type of big data using attribute information of spatial data. To successfully provide the requirements of spatial big data and link various type of big data with spatial big data, methods of forming sample points and extracting attribute information were proposed in this study. The increasing application of spatial information related to big data is expected to attribute to the development of spatial data industry and technological advancement.