• 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 the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.200-208
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• 2022

In this study, an automatic information collection system and geographic information construction algorithm for the transportation disadvantaged using electric mobility aids are implemented using an object recognition model. Recognizes objects that the disabled person encounters while moving, and acquires coordinate information. It provides an improved route selection map compared to the existing geographic information for the disabled. Data collection consists of a total of four layers including the HW layer. It collects image information and location information, transmits them to the server, recognizes, and extracts data necessary for geographic information generation through the process of classification. A driving experiment is conducted in an actual barrier-free zone, and during this process, it is confirmed how efficiently the algorithm for collecting actual data and generating geographic information is generated.The geographic information processing performance was confirmed to be 70.92 EA/s in the first round, 70.69 EA/s in the second round, and 70.98 EA/s in the third round, with an average of 70.86 EA/s in three experiments, and it took about 4 seconds to be reflected in the actual geographic information. From the experimental results, it was confirmed that the walking weak using electric mobility aids can drive safely using new geographic information provided faster than now.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.248-252
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• 2022

The environment refers to what is surrounded by something during human life. This environment is related to the way humans live, and presents various problems on how to perceive the surrounding environment and how the behaviors that constitute the environment support the elements necessary for human life. Humans have an interest in the supportability of the environment as the interrelationship increases as humans perceive and understand the environment and accept the factors supported by the environment. In space, human movement starts from one space to the next and exchanges stimuli and reactions with the environment until reaching a target point. These human movements start with subjective judgment and during gait movement, the spatial environment surrounding humans becomes a collection of information necessary for humans and gives stimulation. will do. In this process, in particular, humans move along the movement path through movement in space and go through displacement perception and psychological changes, and recognize a series of spatial continuity. An image of thinking is formed[1]. In this process, spatial experience is perceived through the process of filtering by the senses in the real space, and the result of cognition is added through the process of subjective change accompanied by memory and knowledge, resulting in human movement. As such, the spatial search behavior begins with a series of perceptual and cognitive behaviors that arise in the process of human beings trying to read meaning from objects in the environment. Here, cognition includes the psychological process of sorting out and judging what the information is in the process of reading the meaning of the external environment, conditions, and material composition, and perception is the process of accepting information as the first step. It can be said to be the cognitive ability to read the meaning of the environment given to humans. Therefore, if we can grasp the perception of space while moving and human behavior as a response to perception, it will be possible to predict how to grasp it from a human point of view in a space that does not exist. Modern people have the theme of reminiscing dog-friendly hotels for the healing of petloss syndrome, and this thesis attempts to approach the life of companions.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Korean Association for Visual Culture
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• v.17
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• pp.65-92
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• 2011

This thesis investigates the complex functions of the magic lantern in illusionism and enlightment which was the most popular visual media and the direct ancestor of cinema. Especially, the thesis focuses on the characteristics of magic lantern's images which had been varied with the scientific and technological development. During the early period of the magic lantern, from the late 18th century to the beginning of the 19th century, it frightened viewers by showing magic images with ghosts and spectres, 'phantasmagoria', and wondered with images of natural catastropes and interesting stories like fables and fairy tales, which fulfilled the entertainment function. Since the mid 19th century the magic lantern began to show not only pictures of the 'scientific themes' on the earth, nature and human, but also them of the ethnological on the far, exotic worlds like Africa, Amazon and Syberia etc. from the European perspective. These contents conducted the educative function and contributed to the process of Enlightment to the peoples in the pre-modern age. The two functions of the magic lantern such as entertainment and education had been neither historically followed, nor clearly divided, but the one was predominant according to the development of lantern techniques as well as the changes of the world view and the culture of the time. The entertainment function of the magic lantern based on the visual fantacy did exist in the late 19th century further, and also in the late industrial society, even in the age of highly developed science and technology, viewers want rather 're-enchantment' by illusionism than facts and truths on the reality. This is an essential characteristic of the moving image media, as it had already been presented in the images of the magic lantern.

• Journal of the Daesoon Academy of Sciences
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• v.46
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• pp.33-68
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• 2023

Simwudo (尋牛圖), known as Ox Seeking Pictures, originated in the 11th-12th century and have consistently played a guiding role in the teachings of various religions in East Asia. Some Korean religions that emerged during modern times conveyed their teachings through depictions of ox seeking or herding. Among them, Daesoon Jinrihoe stands out as a representative religion. The belief system of this particular religion elucidates its distinct doctrine and worldview by reimagining Simwudo, into a new set of six panels (seven or nine panels in some variations). The Simwudo of Daesoon Jinrihoe differs from that of Buddhism, particularly in its treatment of meditation (禪), both in terms of context and significance. While they share similarities in the aspect of ox-seeking, the Buddhist Simwudo symbolizes human nature, whereas the Simwudo of Daesoon Jinrihoe represents the great Dao of Heaven and Earth propagated by Kang Jeungsan and brought into completion by Jo Jeongsan. In the Buddhist context, the subject of the search is the Ox, signifying the restoration of a deluded human's pure nature in order to achieve personal salvation and in some version of Simwudo, reenter society to perform salvific actions for others. On the other hand, in the Simwudo of Daesoon Jinrihoe depicts the process of a human attaining immortality and following the teachings of Jeungsan and Jeongsan. This culminates in the final image which is the redemption of the world. The final phase of the Buddhist Simwudo, depending on the version, is either enlightenment (personal salvation) or reentering society to perform salvific actions (as a bodhisattva), whereas the Simwudo of Daesoon Jinrihoe show the simultaneous achievement of the perfection of humanity and the redemption of the world. This distinction highlights the fundamental differences between the Simwudo of these two distinctly different religious traditions. These differences arise from the contrasting purposes pursued by Buddhism and Daesoon Jinrihoe.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.

• Journal of Christian Education in Korea
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• v.75
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• pp.103-125
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• 2023

This study aims to explore the direction and tasks of Christian unification education as peace education. To this end, after examining the historical trend of peace education and unification education in Korea, the tasks of peaceful unification education are reviewed. Peace education has expanded with the activation of peace movements and educational discourse starting from civil society, while unification education has been planned in accordance with the government's unification and North Korea policy and is moving toward the field of education practice. However, due to the nature of unification education that aspires for peace, the combination of the two fields has continued steadily, and research on peace unification education has been continuously conducted. The direction and tasks of Christian unification education as peace education were proposed based on the tasks of peace unification education derived through prior research analysis and the trend of the times in the two areas to carry out the research purpose. For the sustainability of peace on the Korean Peninsula, Christian unification education as a peace education should aim to foster peaceful citizens who take the lead in transitioning from a culture of violence to a culture of peace. To this end, first, it is necessary to seek the direction of Christian education for the dissolution of the antagonist image. Second, activities that guarantee learners' subjectivity and autonomy should be carried out away from the top-down method in teaching and learning. Third, a curriculum connected to daily life should be formed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.