Journal of Korea Entertainment Industry Association
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v.14
no.2
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pp.51-62
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2020
The study was conducted to verify the causality of the ability of high school and college dance majors to influence the successful goal orientation and how the change in goal affects the sense of dance performance self-confidence. In this regard, 172 dance majors were collected to collect data on their belief in dance ability, the direction of mastery goal of approach and avoidance, and the measure of confidence in dance performance, and the results of their studies were derived through correlation and structural equation analysis and path analysis. The analysis results showed reasonable factor structure and reliability based on the preceding study of feasibility analysis results between variables. Thus, the structural equation for the study variables confirmed that the theoretical hypothesis was suitable, and the path of each variable was verified through the path analysis. The analysis showed that the increased belief that ability can be improved by effort has been found to improve the effort and consequently the confidence in dancing. Also, the fixed belief that ability is not changing in a fixed sense has been found to affect the avoidance goal and reduce confidence. It can be interpreted that the more one believes that one can change one's ability by effort, the more one strengthens one's actions to achieve one's goal, thereby improving one's dance confidence. Therefore, it is deemed necessary for subsequent studies to explore whether the paths of these models differ by their major or dance careers, and to apply variables that can measure the success or failure of actual performances to enhance the explanatory power of these research variables.
Journal of Korea Entertainment Industry Association
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v.15
no.4
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pp.349-357
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2021
Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.
Journal of Korea Entertainment Industry Association
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v.15
no.3
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pp.183-192
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2021
This study was purposed to explore the learning culture through the related literature and research review in Jewish Havruta which has interaction, critical reflection, and the driving force creating a better world. The prior researches on Havruta mainly tend to as ways to increase learners' interest in learning and studies as curriculum or teaching methods such as creativity, understanding, and problem-solving skills. However, Havruta is not just method to study subjects, but rather a process of developing thinking through dialogue and discussion. Therefore, Havruta's essential meaning as a lifelong learning should be explored. Studies showed that Jews embody the thinking process from interpreting, analyzing, setting up logic, questioning, discussing, and debating Talmud with others anytime, anywhere, and anyone throughout their learning culture. It develops basic skills for life, forms an integrated personality in relationships with others, and continuously conducts lifelong learning to shape one's own beings. Therefore, lifelong learning culture would be sharing information that one has in the process of discussion through dialogue between two or more people, and supporting and encouraging the other's failure or fear rather than attacking them. The embodiment of thinking process in which people teach and learn eachother, accept the difference, and expand thought would be significant foundation to create lifelong learning culture.
Journal of Korea Entertainment Industry Association
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v.15
no.4
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pp.359-367
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2021
This study tried to examine the factors that affect the entrepreneurial intentions in the field of culture and tourism industry. Through this, it was attempted to present strategic implications for start-up plans to prospective entrepreneurs in the cultural tourism industry. As a result of the study, the following implications were drawn. First, prospective entrepreneurs in the field of culture and tourism industry need to analyze the start-up items they want to start and systematically design a start-up plan based on market research. Also, by analyzing various start-up cases, it is necessary to secure various prior experiences of failure and success. Second, prospective entrepreneurs in the field of culture and tourism industry will need to increase their interest in starting a business by completing various entrepreneurship education conducted by more diverse institutions and schools than now, and they will have to increase the sense of achievement and willpower that can appear in education. In addition, by making efforts to create human relationships through various entrepreneurship education, efforts should be made to show the utilization of human networks and information sharing when starting a business. Lastly, prospective entrepreneurs in the field of culture and tourism industry should visit startup-related institutions and receive education and advice from experts in order to acquire various information. In addition, efforts should be made to provide more diverse start-up support by obtaining information on start-ups implemented by the state.
Journal of Korea Entertainment Industry Association
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v.15
no.4
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pp.299-307
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2021
This study is a research study to identify the recognition, experiences, needs of convergence education in occupational therapy students. Therefore, it is intended to provide basic data when developing convergence subjects and non-regular programs within the occupational therapy (department) curriculum. From December 03, 2020, a web questionnaire consisting of 14 questions in 4 areas was distributed over a month, and the data of 130 people were finally analyzed. The results are as follows. First, the recognition and experiences of occupational therapy students in convergence education were low. Second, 57.7% of students recognized that occupational therapy majors need convergence education, and the expected effect of convergence education was 'improvement of occupational therapy job-related knowledge'. Third, it was recognized that 'natural science', 'prosthesis and assistive technology, activity of daily living(ADL)', and 'ADL training' convergence education was necessary for the students of occupational therapy department. The results of this study are expected to be used as basic data in the future development of occupational therapy curriculum and non-regular programs for convergence education. In the future, I think that the demand for convergence education and program development in preparation for the 4th industrial revolution will increase in the occupational therapy curriculum. It is expected that the data of this study will be used meaningfully by professors in charge of occupational therapy education at universities.
Journal of Korea Entertainment Industry Association
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v.15
no.4
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pp.255-265
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2021
The purpose of this study was to examine the effects of Kahoot!(Game-based Student Response System) on nursing education. This study used an one group Pretest-posttest design. Participants were 179 nursing students from one D university located in Gwangju, Korea. The Kahoot!(Game-based Student Response System) was provided for 6 times. Data were collected between August 26 and October 25, 2019. The collected data was analyzed by descriptive statistics, paired t-test, pearson's correlation coefficient and stepwise multiple regression using IBM SPSS 21.0 program. The results showed that learning engagement(t=-6.257, p=.000) was significantly higher than levels before Kahoot!(Game-based Student Response System), critical thinking disposition(t=-2.163, p=.032) was significantly higher than levels before Kahoot!(Game-based Student Response System), problem solving ability(t=-3.032, p=.003) was significantly higher than levels before Kahoot!(Game-based Student Response System). Significant relationships were found among learning engagement(r=.375, p=.000), critical thinking disposition(r=.286, p=.000), problem solving ability(r=.291, p=.000) and learning satisfaction. The results of stepwise multiple regression indicates that learning engagement(β=.307, p=.000), problem solving ability(β=.158, p=.041) predicts 15.2% in learning satisfaction(F=16.905, p=.000). In conclusion, Kahoot!(Game-based Student Response System) is effective in improving learning engagement and problem solving ability to nursing education.
Journal of Korea Entertainment Industry Association
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v.15
no.4
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pp.89-100
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2021
Comedy has been popular since ancient Greece. In order to visualize comedy more effectively, the actor's acting acts as an important factor. Then active discussion is needed on how actors can actually shape their comedic performance. I would like to approach comedic acting methods, focusing on the character of Kim Seo-young in the play . This researcher played the character of Kim Mi-young, and the characteristics of comedic acting include exaggeration, repetition, fast tempo, changing tone, and exaggerated physical behavior. Comedic acting comes from a dissonance of reactions. This is because unexpected reactions to stimuli can cause audience laughter. Comedic acting is also important in exaggeration and repetition, which must be based on true acting. The fast tempo of the act and the changing tone of the words also affect comedic acting expressions, and the embodiments of 'slapstick' and 'group dance', which are characteristics of farce acting, play an important role in causing audience laughter. In order for these characteristic elements to show comic effects, the actor's true acting must be the basis. What is important in comedic acting is understanding the narrative flow and features of the text and expressing it accurately. Comedic effects can be sufficiently represented if an actor truly expresses his means and faithfully demonstrates what the text requires. It is hoped that such research will help explore various acting arts, the acting education field, and the theater creation process.
In this paper, we propose a post-processing method through interpolation of hole regions that occur when extracting point clouds. When image matching is performed on stereo image data, holes occur due to occlusion and building façade area. This area may become an obstacle to the creation of additional products based on the point cloud in the future, so an effective processing technique is required. First, an initial point cloud is extracted based on the disparity map generated by applying stereo image matching. We transform the point cloud into a grid. Then a hole area is extracted due to occlusion and building façade area. By repeating the process of creating Triangulated Irregular Network (TIN) triangle in the hall area and processing the inner value of the triangle as the minimum height value of the area, it is possible to perform interpolation without awkwardness between the building and the ground surface around the building. A new point cloud is created by adding the location information corresponding to the interpolated area from the grid data as a point. To minimize the addition of unnecessary points during the interpolation process, the interpolated data to an area outside the initial point cloud area was not processed. The RGB brightness value applied to the interpolated point cloud was processed by setting the image with the closest pixel distance to the shooting center among the stereo images used for matching. It was confirmed that the shielded area generated after generating the point cloud of the target area was effectively processed through the proposed technique.
Kim, Daesun;Kim, Jinsoo;Jang, Seonwoong;Bak, Suho;Gong, Shinwoo;Kwak, Jiwoo;Bae, Jaegu
Korean Journal of Remote Sensing
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v.38
no.6_1
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pp.1329-1341
/
2022
Destroying the marine environment and marine ecosystem and causing marine accidents, marine debris is generated every year, and among them, submerged marine debris is difficult to identify and collect because it is on the seabed. Therefore, deep-learning-based semantic segmentation was experimented on waste fish nets and waste ropes using underwater images to identify efficient collection and distribution. For segmentation, a high-resolution network (HRNet), a state-of-the-art deep learning technique, was used, and the performance of each optimizer was compared. In the segmentation result fish net, F1 score=(86.46%, 86.20%, 85.29%), IoU=(76.15%, 75.74%, 74.36%), For the rope F1 score=(80.49%, 80.48%, 77.86%), IoU=(67.35%, 67.33%, 63.75%) in the order of adaptive moment estimation (Adam), Momentum, and stochastic gradient descent (SGD). Adam's results were the highest in both fish net and rope. Through the research results, the evaluation of segmentation performance for each optimizer and the possibility of segmentation of marine debris in the latest deep learning technique were confirmed. Accordingly, it is judged that by applying the latest deep learning technique to the identification of submerged marine debris through underwater images, it will be helpful in estimating the distribution of marine sedimentation debris through more accurate and efficient identification than identification through the naked eye.
Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.
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