• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.81-94
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• 2022

This study analyzed the effect of the entrepreneurship planning course provided by an women's university in Seoul on the enhancement of the core competencies of entrepreneurship of university students. To this end, pre- and post-test of core entrepreneurship competency were conducted on 63 female university students (32 in experimental group, 31 in control group) and then the results were analyzed. The course in which the experimental group participated was a team-based project learning course and it required a team of three people to draw an entrepreneurship plan containing social problem solving as the final result. The course was operated for a total of 8 weeks. To measure the level of entrepreneurship core competency in the pre- and post- test, the survey tool that was developed by the Ministry of Education and Korea Entrepreneurship Foundation (2020) was used. This tool composed by 'value creation', 'challenge', 'self-directed', and 'group creativity' competencies. As analyses methods, i) covariance analysis was performed using the pretest as a covariate, and then a two-way ANOVA was performed with treatment (experimental group, control group) and time point (pre test, post test) as two independent variables. Results show while there was no significant difference between the experimental group and the control group in the value creation competency, it significantly contributed to the enhancement of challenge, self-directed, and collective creativity competencies. Based on these results, implications and limitations were discussed, followed by future research direction.

• Journal of Gifted/Talented Education
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• v.24 no.3
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• pp.421-444
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• 2014

In STEAM education, contents that has been extracted from a variety of areas, so it can work closely and systematically. Therefore STEAM education requires systems thinking that can be grasped effectively these different disciplines. The purposes of this study are to develop a STEAM program based on systems thinking, and apply the program to the secondary science gifted student in order to investigate the educational effect. A model of the Program developed from previous research and theoretical contents of systems thinking and STEAM. A draft of the STEAM program was developed on the theme of "rocket". A total of 113 students was participated in this study. 100 seventh and 13 eighth graders were enrolled at seigy. A single group pre-post test paired t-test was conducted on them in systems thinking skills. Result of applying the program to the students as follows. The systems thinking ability was improved after the application of the program. 'Mental Model', 'Personal Skill', 'Team Learning', and 'System Analysis', 'Shared Vision' emerged for both improved significantly. In conclusion, the STEAM program based on system thinking improves students' systems thinking skills. This program of results can be helpful in cultivate human resources with the problem solving ability based on system thinking and STEAM literacy by used in public education curriculum.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.51-70
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• 2022

This study examined whether learner-customized start-up education, such as business consulting, functions effectively as part of universities' start-up support and whether business consulting positively strengthened start-up capabilities compared to consulting from other institutions. Furthermore, it explored the direction of universities' start-up support development by harnessing customized education, such as business consulting. The results of the study are as follows. First, business consulting had a positive impact. It informed the shortcomings of individual founders (teams) and identified the direction for improvement. Second, compared to consulting from other institutions, the fact that it formed a relationship between the consultant and the student beyond the business relationship and that it was conducted for free on campus have a relative advantage. Such business consulting enabled university students to see the world more maturely. Third, this study argues that customized start-up businesses can generate synergy with school curriculum and other non-curricular subjects. Based on this perception, it designed a method to build a co-curriculum education system. This study is significant because it investigated satisfaction and the possibility of a customized start-up business with business consulting as a representative case, exploring the direction of support for start-up education students want.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.427-434
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• 2022

This study aims to develop design elements for cultural convergence between rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities, which is a key area in the practical support system for independent life support for individuals with developmental disabilities. As for the research method, a procedure for conducting FGI by forming two teams for professors majoring in special education and rehabilitation science was formed. The research was presented in three upper categories (universal cultural convergence elements, field-centered cultural convergence elements, and policy-centered cultural convergence elements) that should be designed for cultural convergence between rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities. In addition, subcategories were specifically composed for each upper category. First, as a universal cultural element, "open creative convergence" was presented in principle, which can be explained as a principle of exploring and practicing the validity of convergence between related fields for rehabilitation for individuals with developmental disabilities and lifelong education for individuals with disabilities. Second, field-centered cultural factors included development of joint practice model between fields of rehabilitation science and special education, subject matter education knowledge and skills, teaching and learning methods, learning career roadmaps, employment and job career development roadmaps, and the formation of an independent life development history certification system. Third, as policy-centered cultural elements, the formation of a curriculum integration composition system between local related institutions, the establishment of a qualification development path for coordinator-professional teacher-type personnel, and the organizational systematization between school-center types were presented. The study concluded that independent life support for individuals with developmental disabilities should not only be guaranteed for the entire life of adulthood, but also a lifelong education for individuals with disabilities based rehabilitation support system for individuals with developmental disabilities should be established through cultural convergence.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.481-496
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• 2013

The purpose of this study was to make a basic research on college cultural contents education in an effort to step up the manifestation of the creativity of cultural contents experts in line with the development of the fast-changing era of creative economy. It's basically meant to analyze the characteristics of cultural contents education in relation to creative idea to seek practical ways of improving that education. What problems there were with cultural contents education and how that education was actually provided were analyzed to suggest some of the right directions for client-centered cultural contents education. Earlier studies were analyzed, and the results of a survey that was conducted on students whose major was linked to cultural contents were analyzed as well. As a result, current cultural contents education was considered not to be satisfactory due to existing teaching methods, learning process and curriculums that were devoid of creativity. To rectify the situation, interdisciplinary attempts should be made such as multi-major, interdisciplinary programs or convergence education, and plenty of experiments, sufficient practice and an increase in the number of faculty members are all required. In terms of education, existing curriculums and courses should urgently be revamped to strengthen field placement and creative discussions. As for educational methods, the lecture method should be avoided, and specialized education should be offered instead, which should strike a balance between discussion, team play and project education. It is expected to produce good results if there are appropriate connection among different major fields of study and the harmonious implementation of diverse internship, convergence and field placement programs.

• Journal of the Korean Applied Science and Technology
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• v.39 no.2
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• pp.246-260
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• 2022

This study was conducted to analyze the creativity education contents of dance activities in physical education textbooks for the 3rd and 4th grades of elementary school. For this purpose, 16 types of textbooks and auxiliary data for physical education in the 3rd and 4th grades of elementary school were collected and analyzed using the creative education content analysis frame of the physical education textbook based on the 4P model. In order to secure the integrity of the research, expert consultation was operated. The results of this study are as follows. First, from the viewpoint of creative person, 'inquiry' was the most common in creative mind, and the rest of the elements appeared relatively evenly. As for the subject of activity, 'individual' and 'colleague (team)' showed similar frequencies. Second, from the viewpoint of the creative process, all activity areas appeared as 'learning', and most of the elements of the activity purpose appeared evenly, and the creative process was explored. Third, from the viewpoint of creative output, physical activity performance was the most common activity method, and two or three activity methods were used together. In the creativity factor, all factors appeared evenly, and sensitivity and sophistication were the most common with 4 factors. Fourth, from the viewpoint of the creative environment, most of the activity spaces were no restrictions, and the activity media consisted of many educational contents using the body. Through this study, it was requested that creativity education in dance activities should be expanded quantitatively and intensified in quality, and the necessity of spreading creativity education contents of dance activities to other areas was explored.

• Korean Journal of Communication Studies
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• v.22 no.2
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• pp.89-121
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• 2014

In order to suggest a strategy for continuous growth of webtoon, this article examined webtoon usage motivation and tried to make a prediction about culture content products and services connected with webtoon, including intention for viewing movies, based on webtoon; intention for switching to paid webtoon content, and intention for buying webtoon character products. From the point of view of Uses and Gratification Theory intentions for using webtoon and human sociocultural behavior intention are already predicted but with the usefulness of Theory of Planned Behavior Integrated Model this study extended the explanation power of prediction about webtoon related behavioral intention. Results found 5 motivational factors for webtoon usage i.e. 'seeking information', 'entertainment and access availability', 'webtoon genre characteristics', 'influence from a friend or acquaintance', and 'escapism and tension release'. Among them the ones that influenced the intention for viewing movies, based on webtoon, were found to be 'webtoon genre characteristics', 'escapism and tension release' and the 3 variables from Theory of Planned Behavior. 'Seeking information', 'entertainment and access availability', 'webtoon genre characteristics', and all the 3 variables from Theory of Planned Behavior were found to influence the intention for switching to paid webtoon content. The intention for buying webtoon based character products was affected by the motivational factors 'seeking information', 'escapism and tension release' and the behavior and subjective norms variables from Theory of Planned Behavior. Based on the uncommon results from the research several suggestions were made for the continuous growth of webtoon.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.