• Journal of architectural history
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• v.3 no.1
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• pp.101-122
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• 1994

This paper is one of the sequels from 'A Survey of Villages and Dwellings of Korean Immigrants in the North-Eastern Part of China'. It is the result of the extensive survey of Ch'ang-ts'ai-tsun village and covers several architectural characteristics of the dwellings. This paper alma to identify the 'double file' dwelling type, which is believed as one of the main stream of Korean folk dwelling. In this type, 'Chung-ju-kan' forms the central open space, where main household functions are carried out. This type originates from climatic reasons and functional reasons as well. This paper also aims to clarify how the dwelling forms are changed according to the life styles of various periods. The Korean immigrants in this village have experienced rapid changes in modern times like other Chinese. Through various political movements, the original dwelling type of this village has changed to adapt various needs and functions, which shows the simple truth : dwelling form changes according to the changes of life style and social structure. In this paper the directions of chimney through various periods are analyzed to verify the differences of the house layout methods and concepts of the time. The village had grown through 3 main periods before liberation period(1946), communization period(1946 - 1966) and contemporary period (1967 - ). It is concluded as follows: 1. The village was originated in late 19th century along the east-west street, which was a major routes of Korean Immigrants to China. In this area there was no regularity in its site plan. The direction of chimney, which was usually westward, was not determined according to the location of gate. This type was kept until liberization of this area, 1946. The plans of dwellings followed Ham-kyong-do 'double file' dwelling type, '6-kan dwelling' or '8-kan dwelling'. 2. The 'New Village' area, which was formed in the communization period, has a strict regularity in its site plan. The direction of chimney was determined as opposite direction of the gate. This method was maintained until 1976, when Mao died and new 'open' policy was held by Chinese government. In this area the 'dwelling house' plan type was not changed, but its layout and size were restricted. The general form of the dwelling in this village was shaped in this period. 3. The contemporary dwellings were built in random site location. The dwelling type was changed because of the reduction of family size and the permissin of private ownership. The number of rooms was reduced but the storage rooms and domestic animal hutches were added. But the 'Chung-ju-kan', the major chacteristics of north-eastern Korea dwelling is still kept. It becomes one large 'Chtin-ju-kan' room like 'open plan' type.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.360-366
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• 2022

This paper presents a AI model structure for restoring Korean traditional palace photographs, which remain only black-and-white photographs, to color photographs using Pix2Pix, one of the adversarial generative neural network techniques. Pix2Pix consists of a combination of a synthetic image generator model and a discriminator model that determines whether a synthetic image is real or fake. This paper deals with an artificial intelligence model by adjusting a receptive field of the discriminator, and analyzes the results by considering the characteristics of the ancient palace photograph. The receptive field of Pix2Pix, which is used to restore black-and-white photographs, was commonly used in a fixed size, but a fixed size of receptive field is not suitable for a photograph which consisting with various change in an image. This paper observed the result of changing the size of the existing fixed a receptive field to identify the proper size of the discriminator that could reflect the characteristics of ancient palaces. In this experiment, the receptive field of the discriminator was adjusted based on the prepared ancient palace photos. This paper measure a loss of the model according to the change in a receptive field of the discriminator and check the results of restored photos using a well trained AI model from experiments.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.157-168
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• 2023

Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

• Information Systems Review
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• v.23 no.3
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• pp.201-223
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• 2021

Smart home is an advanced Internet of Things (IoT) service that enhances the convenience of human daily life and improves the quality of life at home. Recently, with the emergence of smart home products and services to which artificial intelligence (AI) technology is applied, interest in smart home is increasing. To gain a competitive edge in the smart home market, companies are providing "personalized service" to users, which is a key service that can promote smart home use. This study investigates the factors affecting the value awareness of personalized service and intention to use smart home. This research focuses on four-dimensional motivated innovativeness (cognitive, functional, hedonic, and social innovativeness) and privacy risk awareness as key factors that influence the value awareness of personalized service of smart home. In particular, this study conducts a comparative analysis between the generation MZ (young people in late teens to 30s), who are showing socially differentiated characteristics, and the generation X and baby boomers in 40s to 50s or older. Based on the analysis results, this study derives the distinctive characteristics of generation MZ that are different from the older generation, and provides academic and practical implications for expanding the use of smart home services.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.137-142
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• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.

• The Journal of Korean Medicine
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• v.35 no.3
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• pp.155-165
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• 2014

Objectives: The pulse diagnosis to identify the symptoms has been considered important in Korean medicine. The position and character of disease would be confirmed by pulse diagnosis of left and right radial artery. This paper is to analyze the characteristics and differences of left and right blood vessels. Methods: In this study, left and right radial artery and dorsalis pedis artery was measured and analyzed by using condenser typed pulse analyzer. Commercially available pulse analyzer was used to measure the radial artery. The pulse wave was measured in 20 laboratory healthy men and women. The blood vessel aging degree and index of augmentation of blood vessel was obtained from the measured pulse wave graph and the characteristics and differences of the left and right blood vessel was analyzed. Results: The significant difference of pulse transit time between the right handed and non-right handed was not found. The correlation of radial artery and dorsalis pedis artery had no significant difference. By obtaining the blood vessel aging index (AGI) and augmentation index (AI) of blood vessel at the left and right radial artery, the significant difference between right handed and non-right handed was not found. Conclusions: The result of this study would help to explain the characteristic of blood vessel with respect to the left and right handed. We suggest that research of pulse wave of the left and right blood vessel using pulse analyzer should be needed in further study.

• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.31-41
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• 2006

This study is to analyze the effect of compatibility of information characteristics and information technology structure on AIS performance. This used financial and non-financial factors as the characteristics of management accounting information and used information technology structure as centralization and decentralization classified by Ahtuv et.(1989) and Fiedler et.(1996). 425 sampling companies are selected randomly and 137 of them were used in this study. The results of this study are as follows. First, In compatibility analysis between the characteristics of management accounting information and information technology structure, in case of companies which have centralized data process system, AIS performance of companies which use financial information is higher than that of companies which use non-financial information. However, no meaningful results show statistically. in case of companies which have decentralized data process system, AIS performance of companies which use non-financial information is higher than that of companies which use financial information. Also the statistical results show the meaning at the p. < 0.01.