• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.41-68
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• 2019

Multi-view learning considers data from various viewpoints as well as attempts to integrate various information from data. Multi-view learning has been studied recently and has showed superior performance to a model learned from only a single view. With the introduction of deep learning techniques to a multi-view learning approach, it has showed good results in various fields such as image, text, voice, and video. In this study, we introduce how multi-view learning methods solve various problems faced in human behavior recognition, medical areas, information retrieval and facial expression recognition. In addition, we review data integration principles of multi-view learning methods by classifying traditional multi-view learning methods into data integration, classifiers integration, and representation integration. Finally, we examine how CNN, RNN, RBM, Autoencoder, and GAN, which are commonly used among various deep learning methods, are applied to multi-view learning algorithms. We categorize CNN and RNN-based learning methods as supervised learning, and RBM, Autoencoder, and GAN-based learning methods as unsupervised learning.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.271-278
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• 2020

Modern financial services go beyond the stage of internet banking, and new concepts of financial transactions such as Internet of Things, mobile banking, electronic payments, and fintech have emerged. As a result, banks are less influential in financial transactions, and changes are being demanded. In the present era, the basic business of banks has decreased, and it is transforming into a space where both consumer finance work and reside. The bank office stands for the brand image of the bank, and it is represented by trust with customers in the basic business of financial transactions, and the rise in real estate value is a natural social phenomenon due to the nature of the location and location of real estate owned by the bank. The business method and space of the bank office that meets the new paradigm of the modern society is an inefficient space only for the convenience and rest of consumers, but it must be used as a variety of spaces suitable for the region to increase the functional value of the bank office. Through this study, as a convenience space for consumers, various service facilities should be introduced to understand the characteristics of the region as a convenience space for consumers, and various service facilities should be introduced to meet the needs of consumers, and the bank office should be improved as a complex service space for local residents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1463-1469
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• 2020

Multimedia information, including video and voice, is highly utilized in that it is easily understood by people. For this reason, applications have been studied which store multimedia information in IoT devices and transmit information in conjunction with smartphones. The problem is that the size of information can be larger than the capacity of IoT devices due to video and image. In this paper, the multimedia content design technique, which takes into account the limitations of storage capacity, was studied when there is a limit of storage capacity. Considering that the video has a higher understanding of information than text, while the capacity is larger, the solution between information comprehension and capacity is sought. The size of static and dynamic media is a variable and the harm is solved in accordance with the linear planning method. Case studies have shown that the design techniques of this paper are useful.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.17-26
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• 2021

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.1-10
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• 2022

Visually impaired people have very difficulty using retail stores due to the absence of braille information on products and any other support system. In this paper, we propose a basic algorithm for a system that recognizes products in retail stores and explains them as a voice. First, the deep learning model detects hand objects and product objects in the input image. Then, it finds a product object that most overlapping hand object by comparing the coordinate information of each detected object. We determine that this is a product selected by the user, and the system read the nutritional information of the product as Text-To-Speech. As a result of the evaluation, we confirmed a high performance of the learning model. The proposed algorithm can be actively used to build a system that supports the use of retail stores for the visually impaired.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.405-414
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• 2022

The purpose of this study is to discover the possibility to expand the aesthetic interpretation of dance works. For this purpose, this study analyzes Maguy Marin's (1981) because it shows Sigmund Freud's concept of uncanny and grotesque images well. The theoretical framework of this study was centered on previous academic studies, and Hoffman's Der Sandmann(1816) was presented as an example to help the conceptual understanding of uncanny and grotesque. The analysis of of Magi Marin was divided into stage space, dancer's movements, costumes, and voice. As a result of this study, it was discovered that is a work with an experimental spirit that deviated from the stereotypes of traditional stage aesthetics. And it was implemented as uncanny and grotesque images in the choreography structure. In addition, as the changes of the times have a great influence on the creation of dance works, it is thought that the discourse of various aesthetic interpretation methods in dance works can provide various directions for dance creation in the future. Therefore, this study will be helpful in raising the aesthetic value and status of dance art.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.351-356
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• 2023

The purpose of this study is to analyze how the movie <The Book of Fish> (2021) represents Joseon, which is slowly collapsing with the Neo-Confucian order of the 19th century shaking, and to discuss its meaning. Prior to the analysis, the analysis framework of the historical drama was presented considering the narration characteristics of the historical drama. Using the analysis framework of historical dramas, we confirmed that <The Book of Fish> is representing the image of Jeong Yak-jeon and Jang Chang-dae living their lives as independent individuals between the limitations and possibilities of the times based on the plot structure of the narrative of exile. Through the central memory and surplus memory created through plot and style elements such as contrast between black and white and color images, voice-over narration, chinese poetry subtitles and music, the film asks us universal questions about what it takes to live as an independent individual.

• Asia Marketing Journal
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• v.11 no.3
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• pp.167-184
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• 2009

In the ever competitive world airline industry, Korean Air has been seeking on the one hand to streamline its operations through cost control and at the same time to boost customer loyalty and retention through a strong service differentiation strategy. As part of their service differentiation strategy, Korean Air has been actively engaging in culture marketing campaign. Their main activity involves entering into an alliance with the three leading museums of the world. Beginning with the Luvre of France, Korean Air supported the development of voice narration system that included the Korean language. This case describes the efforts of Korean Air to go beyond simply being a company that transports people and packages, to a global leading carrier that links the cities, cultures, and arts of the world. In the process, the case introduces the strategies and detailed actions behind Korean Air's culture marketing efforts.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.919-928
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• 2023

Deep learning technology is used in various fields such as self-driving cars, image creation, and virtual voice implementation, and deep learning accelerators have been developed for high-speed operation in hardware devices. However, several side channel attacks that recover secret information inside the accelerator using side-channel information generated when the deep learning accelerator operates have been recently researched. In this paper, we implemented a DNN(Deep Neural Network)-based MNIST digit classifier on a microprocessor and attempted a correlation power analysis attack to confirm that the weights of deep learning accelerator could be sufficiently recovered. In addition, to counter these power analysis attacks, we proposed a Node-CUT shuffling method that applies the principle of misalignment at the time of power measurement. It was confirmed through experiments that the proposed countermeasure can effectively defend against side-channel attacks, and that the additional calculation amount is reduced by more than 1/3 compared to using the Fisher-Yates shuffling method.