• 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.

• Korea Trade Review
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• v.43 no.3
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• pp.1-26
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• 한국체육학회지인문사회과학편
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• v.54 no.2
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• pp.299-312
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• 2015

The purpose of this study was to find the effects of user experience on flow and satisfaction of electronic hogu system in the taekwondo game. The subjects were players who had experience using electronic hogu system in the taekwondo game for 2014 year 7month~10month. 652 samples out of 750 samples through convenient sampling method were adopted as a final data. We confirmed the goodness of fit test of the model, utilizing SPSS WIN Ver 18.0, and AMOS 7.0, and after which we tested each hypothesis. The results were as follows; First, sentient, emotional, cognitive, behavioral, relational experience of user experience did not have a significant influence on cognition flow. Second, sentient, emotional, relational experience of user experience did not have a significant influence on behavioral flow. Third, cognitive, behavioral experience of user experience had a significant influence on behavioral flow. Fourth, cognition, behavioral flow had a significant influence on satisfaction. Fifth, factor between native and foreigner taekwondo players had significantly different. This paper is a meaningful to figure out user satisfaction of electronic hogu system in taekwondo games and maximize athletic performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Journal of Christian Education in Korea
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• v.73
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• pp.117-137
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• 2023

This is a case study of an extra-curricular program that designed and implemented maker education based on design thinking to foster a Christian worldview. The program was designed at K university in the course of 10 sessions as following stages; tinkering, providing a special lecture for motivation, finding issues, empathizing, making, sharing and reflecting. A total of 15 students in 5 teams participated in the program, progressed through each stage in the process of solving the problems they found around them so that their neighbors and the creative world could become better. As a result of operating this program, the participants became concerned about their neighbors and community and reflected on the change of perspective of the world from a Christian worldview. As a suggestion for follow-up research and projects, to develop a model of maker education based on design thinking for cultivating a Christian view of the world is proposed in order to support to easy design and management of the program even if there is a lack of professional related knowledge and experience. In addition, it is needed to develop a manual and guide book including a facilitator's role and an assessment tool like a rubric that can give feedback on the performance of the program and make improvement.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.57-65
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• 2023

This study examined the obstacles of important factors involved in the start-up decision process for prospective entrepreneurs and plans after graduation while attending hair and beauty colleges and analyzed them in a phenomenological way to establish countermeasures. The subjects of the study agreed to collect data from 10 prospective entrepreneur doctors and plans after graduation while attending hair and beauty college located in G, and were in-depth from December 15 to December 30, 2022. The collected data were analyzed using the Colaizzi method. The results of this study were extracted with 13 topics and two subject collections that represent the characteristics of the experience in the preliminary start-up process of the participants. Based on the results of this study, it is meaningful to examine the obstacles of the factors that are importantly involved in the start-up decision process and establish countermeasures accordingly. In conclusion, at a time when the market for start-ups is expanding and government support is increasing, the factors affecting the will of college students, who are potential professional managers in the future, and effective implications for enhancing the university's start-up infrastructure, start-up difficulties, and start-up motivation were obtained. Therefore, it is urgent to develop efficient performance counseling research or program counseling that can promote and support mental and environmental growth through career development required for the difficulties of the decision process of prospective entrepreneur hair college students and the situations they face. It is necessary to develop various measurement tools in consideration of the level of career development and development of a start-up decision-making process model that can fully grasp the status of start-ups of prospective start-ups.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.217-228
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• 2023

Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.