The purposes of this study are to develop the standardized tests of career preparation behavior of career preparation behavior for college students. For these, the 'Career Preparation Behavior Scale for College Students' which was developed in 2011 was reviewed and revised. After 609 students were involved and analyzed for the pretest, 1,244 subjects were collected by taking into account gender, grade, major, and location of colleges for developing a standardized test. The Career Preparation Behavior Scale consisted of 3 subareas and 30 items: 11 items for learning area, 12 items for counseling and information collecting area, 7 items for employment action area. The levels of reliabilities, construct validity, discriminant validity, and the concurrent validity were relatively high. Also, the suitability index of the structural model was analyzed to check the structural significance. The degree of career reparation behavior among norm groups was increased in general according to the grades. Scores of students majoring in humanities and social sciences received significantly high scores compared with those of majoring in science and technology or in art and music. But the levels of satisfaction on career preparation behavior were no difference according to gender, grade, and major. 'The Standardized Career Preparation Behavior Scale for College Students' would be used for conducting career education or programs for college students in the future.
In this study, the statistical characteristics of the resistance bias factors were analyzed using a high-quality field load test database, and the total resistance bias factors were estimated considering the soil uncertainty and construction errors for the application of the limit state design of aggregate pier foundation. The MLR model by Bong and Kim (2017), which has a higher prediction performance than the previous models was used for estimating the resistance bias factors, and its suitability was evaluated. The chi-square goodness of fit test was performed to estimate the probability distribution of the resistance bias factors, and the normal distribution was found to be most suitable. The total variability in the nominal resistance was estimated including the uncertainty of undrained shear strength and construction errors that can occur during the aggregate pier construction. Finally, the probability distribution of the total resistance bias factors is shown to follow a log-normal distribution. The parameters of the probability distribution according to the coefficient of variation of total resistance bias factors were estimated by Monte Carlo simulation, and their regression equations were proposed for simple application.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.1
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pp.184-188
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2019
The purpose of this paper is to investigate the effectiveness of Google Classroom (GC) and to examine the satisfaction of professors using GC as an online environment at a Mongolian University. Fourteen professors designed the lecture model and provided lessons using GC at D University for four weeks. GC provides new learning opportunities that are more efficient than face-to-face learning, because it can overcome the limitations of time and space. The results of the survey conducted with the professors who participated in the class to explore the effectiveness of GC show that the system provides: cooperation: 100% (strongly agree=7, Agree=7), personal learning opportunity: 100% (strongly agree=10, Agree=4), ease in learning: 100% (strongly agree=11, Agree=3), suitability: 100% (strongly agree=8, Agree=6), feedback opportunities: 100% (strongly agree=7, Agree=7), connection: 100% (strongly agree=7, Agree=7), accessibility: 100% (strongly agree=7, Agree=7), learning effectiveness: 100% (strongly agree=9, Agree=5), paperless experience: 100% (strongly agree=8, Agree=6). The professors who attended the class reacted positively to the use of GC, proving that the application of GC at this Mongolian University was appropriate and efficient. The use of GC is expected to help educational institutions strengthen and improve online learning, especially by breaking from traditional learning, and opening new paths for professors and students in Mongolia.
Journal of the Korean Society of Earth Science Education
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v.12
no.1
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pp.27-39
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2019
The purpose of this study is to develop a STEAM program for teaching climate change through CLAMP (Climate-Leaf Analysis Multivariate Program) paleoclimate inquiry in connection with high school 'Integrated Science' subject. In order to do so, we analyzed the 2015 revised national curriculum and science textbook in terms of the PDIE instructional design model, and developed the teaching-learning materials for 10 class hours through expert panel discussion and pilot test. According to the STEAM class procedure, in the situation presentation stage, the fossil leaves were collected from the dicotyledon plants near school, and the LMA (Leaf Margin Analysis) climate inquiry activity. was presented as the learning goal. During the creative design stage, students were taught about geology and leaf fossils in the study region, and CLAMP input data (31 characteristics of morphotype and leaf architectural of fossil leaves) were given. In the emotional experience and new challenge stage, we collected leaf fossils for outdoor learning, explored paleoclimate with CLAMP method, and promoted climatic literacy in the process of discussing tendencies and causes of Cenozoic's climate change. The validity of the development program was assessed (CVI .84) as being suitable for development purpose in all items through the process of establishing reliability among expert panel. In order to apply the program to the high school, a pilot test was conducted to supplement the discrepancies and to review the suitability. The satisfaction rate of the participants was 4.48, and the program was complemented with their opinions. This study will enable high school students to have practical knowledge and reacting volition for climate change, and contribute to fostering students' climate literacy.
In the present paper, the dynamic force-moment equilibrium equations, driving power and energy equations are analyzed to formulate the equation for fuel economy(km/liter) equivalent to the driving distance (km) divided by the fuel volume (liter) of the vehicle, a selected model of gasoline powered KIA K3 (1.6v). In addition, the effects of the dynamic parameters such as speed of vehicle (V), vehicle total weight(M), rolling resistance ($C_r$) between tires and road surface, inclined angle of road (${\theta}$), as well as the aerodynamic parameters such as drag coefficient ($C_d$) of vehicle, air density(${\rho}$), cross-sectional area (A) of vehicle, wind speed ($V_w$) have been analyzed. And the possibility of alternative materials such as lightweight metal alloys, fiber reinforced plastic composite materials to replace the conventional steel and casting iron materials and to reduce the weight of the vehicle has been investigated by Ashby's material index method. Through studies, the following results were obtained. The most influencing parameters on the fuel economy at high speed zone (100 km/h) were V, the aerodynamic parameters such as $C_d$, A, ${\rho}$, and $C_r$ and M. While at low speed zone (60 km/h), they are, in magnitude order, dynamic parameters such as V, M, $C_r$ and aerodynamic ones such as $C_d$, A, and ${\rho}$, respectively.
Journal of the Korean Society of Environmental Restoration Technology
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v.21
no.6
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pp.95-113
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2018
We studied the change of wetland vegetation structure to understand ecological restoration process of wetlands through the field survey of ecological restoration projects in Incheon, Iksan and Busan. We compared the vegetation plan at the time of planted with the results of the vegetation monitoring in 2018, and analyzed the changes in wetland vegetation structure. Based on results, we attempted to understand the restoration process of those wetlands and discuss the management measures for sustainable wetland restoration. As a result, in the Incheon Yeonhee restoration wetland, the number of plant species was increased, from 18 species in 2016 to 29 in 2018. The dominant species, Myriophyllum verticillatum, covered the wetland most and its occupied area was increased. On the other hand, the distribution area of the planted emergent hydrophytes was reduced. The area of open water decreased from 71.7% in 2016 to 48.8% in 2018. In Busan Igidae restoration wetland, the number of plant species was increased, from 6 species in 2014 to 31 in 2018. The dominant species was Myriophyllum verticillatum and its occupied area was increased. The area of floating plant communities that planned has decreased. The open water area decreased from 83.9% in 2014 to 31.8% in 2018. In Iksan Sorasan restoration wetland, the number of plant species was increased, from 13 species in 2016 to 36 in 2018. The dominant species was Phragmites communis Trin. and its occupied area was increased. The other planted species showed a tendency to be decreased by Phragmites communis Trin. and its terrestrialization. The open water area decreased from 86.6% in 2016 to 6.7% in 2018. These results suggest that wetlands should be managed by considering the change of vegetation structure and open water areas based on the following succession process, because it affects the habitat suitability of wetland organisms and biodiversity as well. Thus, the continuous monitoring for the ecological structure of restored wetland is important, and it could be possible step to develop sustainable wetland ecological restoration model.
Yang, Hee Gun;Ha, Gwangsu;Ryu, Myeong Seon;Park, Se Won;Jeong, Ho Jin;Yang, Hee-Jong;Jeong, Do-Youn
Journal of Life Science
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v.31
no.8
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pp.761-770
/
2021
In this study, the optimal medium composition for enhancing protease production was established by the Bacillus strain isolated from Makgeolli, a traditional fermented food, using the response surface methodology. B. amyloliquefaciens SRCM115785 was selected as the protease producer by productivity analysis and identified by 16S rRNA gene sequencing. Plackett-Burman design (PBD) was introduced to analyze the effect of each component on protease production among the 11 selected medium components. As a result, glucose, yeast extract, and beef extract were finally selected as factors for enhancing protease production. Central composite design (CCD) analysis was designed as a method to determine the optimal concentration of each component for protease production and the concentration of each medium composition for maximum protease production was predicted to glucose 6.75 g/l, yeast extract 12.42 g/l and beef extract 17.48 g/l. The suitability of the experimental model was proved using ANOVA analysis and as a result of quantitative analysis to prove this, the amount of increase was 230.47% compared to the LB medium used as a control. Through this study, the optimization of medium composition for enhancing protease production was established, and based on this, it is expected that it can be efficient use of protease as an industrial enzyme.
Visual communication based on socio-cultural context, such as emoticons on social media, is increasing. Therefore, it is necessary to study the visual expression of metonymy as a means to correctly understand the communication method in the age of visual culture. The purpose of this study is to explore how metonymy is visualized within a cultural context. Specifically, , a typical underlying phenomenon of metonymy expression, and the expression principles of various reproduced through it are identified by pairing them with the cultural context. Based on context theory, which is a representative discourse in the social science field, emoticons from in high context and emoticons in in low context were selected and compared as case study subjects. The major findings are: First, a visual application model of metonymy was proposed regarding the process through which metonymy is reproduced as a visual result. Second, the types of metonymy and their salience attribute applied to the emoticon expression method was identified in detail. Third, based on the contextual theory, how the characteristics of high-context visual metonymy differ from that of low-context visual metonymy were presented. In the future, the results of this study can be used as a criterion for judging the local acceptability and local suitability of design results in the design development process that requires the use of localization strategies.
Kang, Sang In;Kim, Ye Jin;Lee, Ji Un;Park, Si Hyeong;Choi, Kwan Su;Song, Ho-Su;Choi, Jung-Mi;Heu, Min Soo;Lee, Jung Suck
Korean Journal of Fisheries and Aquatic Sciences
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v.54
no.6
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pp.880-889
/
2021
The home meal replacement (HMR) market has attracted significant attention due to COVID-19 pandemic and products that utilize the combination of different processed ingredients are now being developed. In this study, Broughton's ribbed ark Scapharca broughtonii was soaked in seasoned soy sauce with the incorporation of mustard leaf Brassica juncea (M-BRA), which is known to have a unique texture as well as excellent functional properties such as antioxidation, to develop a regional specialty product. The optimal conditions for manufacturing M-BRA from the seasoned soy sauce (the sauce to be added [X1] and the soaking time [X2]), were examined using response surface methodology (RSM) to analyze the significance of the salinity (Y1), amino-N content (Y2), and overall acceptance (Y3). The coefficient of determination (R2) between X1-X2 and Y1-Y3 were close to 1, thereby confirming the suitability of the RSM model. The optimal conditions were seasoned soy sauce addition of 140% and soaking time of 156 min. The M-BRA manufactured under these conditions exhibited superior overall acceptance compared to seasoned commercial soy sauce, which was used as a control. We expect that the market for M-BRA manufactured by combining marine and agricultural materials will expand owing to superior overall acceptance compared with commercial products.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.39
no.6
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pp.363-369
/
2021
High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.
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