• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.39-60
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• 2021

In the field of deep learning, there are many algorithms mainly after GAN in research related to generation, but in terms of generation, there are similarities and differences with art. If the generation in the engineering aspect is mainly to judge the presence or absence of a quantitative indicator or the correct answer and the incorrect answer, the creation in the artistic aspect creates a creation that interprets the world and human life by cross-validating and doubting the correct answer and incorrect answer from various perspectives. In this paper, the video generation ability of deep learning was interpreted from the perspective of collage and compared with the results made by the artist. The characteristic of the experiment is to compare and analyze how much GAN reproduces the result of the creator made with the collage technique and the difference between the creative part, and investigate the satisfaction level by making performance evaluation items for the reproducibility of GAN. In order to experiment on how much the creator's statement and purpose of expression were reproduced, a deep learning algorithm corresponding to the statement keyword was found and its similarity was compared. As a result of the experiment, GAN did not meet much expectations to express the collage technique. Nevertheless, the image association showed higher satisfaction than human ability, which is a positive discovery that GAN can show comparable ability to humans in terms of abstract creation.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.253-264
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• 2022

The purpose of this study is to examine the practice of scientists from the perspective of Ian Hacking's 'creation of phenomena'. Scientific phenomena, according to Hacking, are regular and do not exist in nature without the intervention of scientists or experimental tools. This study tries to derive scientific educational meaning by analyzing the thoughts and episodes of the 'Sontanda (inter-individual variability)' phenomenon experienced by four life scientists. The Sontanda phenomenon is a common term used by scientists to describe phenomena in which findings do not appear consistently even when studies are carried out using the same experimental procedure and materials. The following four educational implications were discovered as a result of the research. First, we confirmed the importance of embodied knowledge, or non-verbal knowledge, which solves issues by making appropriate judgments and reactions at all times, rather than simply becoming accustomed to the experimental method. This argues that propositional knowledge and non-verbal knowledge should be handled equally in order to provide students with a practical scientific inquiry. Second, we tried to reconsider the picture of the experiment. The phenomenon revealed in the interviews of scientists is rare, and it takes a long time to stabilize the phenomenon. On the other hand, the image of school experiments is always positive and consistent, necessitating a shift in perspective. Third, the precise meaning of scientific practice could be confirmed. This study confirms that scientists use their knowledge effectively in line with the circumstances, and we examined strategies to apply scientific practice to school instruction based on this. Finally, by provoking uncertainty, the Sontanda phenomena may give students with an opportunity to engage in meaningful scientific involvement. By breaking away from the cookbook experiment, this study expects school experimental education to help in efforts to experience scientific practice.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.378-390
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• 2022

With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of Christian Education in Korea
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• v.68
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• pp.175-216
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• 2021

This essay aims to seek an alternative model of catechesis, as this form of education faces various challenges from the Korean Church especially during COVID-19 pandemic. For a long time, catechesis in the Korean Church narrowly focused on the act of producing Christians who would be loyal to the local church, rather than focusing on nurturing members loyal to Christ, an issue that has been problematized in recent publications on catechesis. Thus, the loss of social trust in the Korean Church and the decline of its public image exemplify how this type of catechesis as disciple-making for local church's benefit, mostly nurtures a vertical dimension of faith. The current teaching and learning method mostly employs a unilateral transfer of doctrine from the teacher to the learner and emphasizes the memorization of doctrine. This type of instruction renders the catechesis as the most lackluster and outdated form of Christian education. This essay aims to reconceptualize the traditional model of catechesis. This essay first critically evaluates current situations of catechesis and presents several alternative meanings on the concept of doctrine. Then it explores the theories of catechesis through different models posed by Christian educators such as John Westerhoff III and Richard Osmer. The final section is devoted to presenting an alternative form of catechesis that focuses on seeking holistic faith.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.101-110
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• 2019

The actor's art work is to build and create a role on stage based on the writer's drama. The actor's role creation is possible by analyzing the role of the writer in the drama logically and acting it actively. This is how an actor who practices practical acts goes beyond a stereotypical role-building and performs live acting skills. A case study in the field work for the application of Etude is absolutely necessary at present, where Etude of Stanislavsky is operated in Korean university education and field. This study will be a case in which Etude, which is a scientific and systematic acting methodology of Stanislavsky, is recognized and applied in the field as a methodology for more extended actor training methodology rather than making a judgment about the value of Etude as applied to theater education and the field as an acting training method. The researcher will introduce the methodology of using Etude as an acting method of Stanislavsky through the use of Etude in the creative play , and would like to give an example of an acting creation process model about 'how to apply Etude'. Through these studies and applications, actors can avoid falling into stereotypes and mannerism, and prepare the foundations for a living actor's art, the acting guide for creating a practical role.

• Journal of Korea Entertainment Industry Association
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• v.13 no.1
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• pp.89-98
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• 2019

Performing arts, for instance, theatre and dance that perform on the stage, should recognize the contemporary characters and also emphasize the trend of the times. Thus, the subject of those varies and provides the audience diversity contents and style. People who perform those try to put the contemporary characteristic and sociality into their stage by utilizing new technology for their stage to be more sophisticated in aesthetic and philosophic aspects. According to the trend of the times, science and technology have been making great progress. As a result, the stage technology continues to develop, contributing to enhance the aesthetic and philosophical completeness of the performing arts. Also, there are technical and formal researches or methods constantly that make the performing arts new and diverse. Therefore, it can be said that it is very important to widen a category of the performing arts that amplify the actor's acting and emotions on the stage and then give the audience an experience. This paper will analyze in the way which various image techniques utilize to widen the actor's technique in the performing arts and the actor's technique progresses in the era called the Fourth Industrial Revolution era that grafts the art onto new media. Through this paper, in the era of the Fourth Industrial Revolution, a new paradigm in actor's acting which is becoming a hot topic in performing arts is predicted and anticipated.

• Journal of Korean Foot and Ankle Society
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• v.26 no.1
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• pp.22-29
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• 2022

Purpose: Despite continuous updates of standard treatment guidelines for acute ankle sprain and chronic ankle instability (CAI), in practice preferred treatment protocols vary widely. Based on a Korean Foot and Ankle Society (KFAS) member survey, this study reports current trends in the management of ankle ligament injuries. Materials and Methods: A web-based questionnaire containing 34 questions was sent to all KFAS members in September 2021. Questions mainly addressed clinical experience and preferences for the diagnosis and treatment of ankle ligament injuries. Answers with a prevalence of ≥50% among respondents were considered to reflect tendencies. Results: Eighty-four of the 550 members (15.3%) responded. Answers that showed a tendency were as follows: commonest additional image study (ultrasound), conservative treatment modality (immobilization, oral medication), frequency of surgical treatment (<5 cases per annum), most important factor when deciding on surgical treatment (activity level, e.g., occupation or sport), and commonest surgical procedure (open ligament repair). Answers that showed a tendency for CAI were as follows: most important symptom (repeated sprain, giving way), radiological factors (talar tilt, osteochondral lesion, anterior talar translation), and patient factors (occupation, sports activities, recurrent instability after surgery, etc.). For decision making regarding surgical treatment and method, the most preferred surgical procedure was the modified Broström procedure, and the most common repair technique was suture anchor technique. The following were considered poor prognostic factors; generalized laxity, failed previous surgery, cavovarus, severe mechanical instability, heavy work, obesity, and dissatisfaction after surgery because of residual pain. Conclusion: This study updates information regarding current trends in the management of ankle ligament injuries in Korea, and reveals consensus opinions and variations in approaches to patients with an acute or chronic injury. The divergence of approaches identified indicates the need for further studies to determine standard guidelines and long-term results.