• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권4호
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• pp.291-297
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• 2013

Chaotic dynamics have been studied by many researchers in the fields of biology, physics, and engineering. Interest in chaos is also expanding to the social sciences such as politics, economics, and others, including the prediction of societal events. The concept of leisure has developed from a passive concept correlated with relaxation, entertainment, and ideology formation into a positive concept that assumes a more active role. As information and communications technology develops, digital leisure activity is expected to continue spreading. This expansion of digital leisure function correctly, as well as. Traditional leisure activity functions correctly more, whereas digital leisure activity is predicted to function incorrectly more often. In this paper, we propose a mathematical addiction model of digital leisure that deals with its dysfunctions such as addiction to digital leisure, including computer games, internet search, internet chatting, and social media. Herein, to solve addiction to digital leisure, we propose a model derived from a nicotine addiction.

• 디지털산업정보학회논문지
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• 제8권3호
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• pp.23-31
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• 2012

With the advance of Smart TV technologies, TV watchers can enjoy the Internet and games while watching TV programs. Besides retrieving with some keywords in the Internet, people may want to access local information such as notifications from town, messages from children's schools, shopping information from local marts, and even reminder messages for visiting from hospitals while watching TV without using web-browser. In this paper, we introduce the daily life notification service scenarios and its functional and non-functional requirements. Furthermore, we also propose a system that provides the notification services, consists of smart TV apps and server systems. We also introduce the system architecture and the component design of the system. Our work will help smart TV service developers because this paper will give them some service scenarios, requirements, and system architecture and its component design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.1015-1029
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• 2021

Modern technology offers many ways to enhance teaching and learning that in turn promote the development of tools for educational activities both inside and outside the classroom. Many educational programs using the augmented reality (AR) technology are being widely used to provide supplementary learning materials for students. This paper describes the potential and challenges of using GeoGebra AR in mathematical studies, whereby students can view 3D geometric objects for a better understanding of their structure, and verifies the feasibility of its use based on experimental results. The GeoGebra software can be used to draw geometric objects, and 3D geometric objects can be viewed using AR software or AR applications on mobile phones or computer tablets. These could provide some of the required materials for mathematical education at high schools or universities. The use of the GeoGebra application for education in Laos will be particularly discussed in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3498-3512
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• 2021

This article describes how events that make up text stories can be represented and extracted. We also address the results from our simple experiment on extracting and clustering events in terms of emotions, under the assumption that different emotional events can be associated with the classified clusters. Each emotion cluster is based on Plutchik's eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion. While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy. The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4624-4644
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• 2019

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권12호
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• pp.4835-4848
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• 2020

The recent expansion of the digital content market is increasing the technical demand for various facial image transformations within the virtual environment. The recent image translation technology enables changes between various domains. However, current image-to-image translation techniques do not provide stable performance through unsupervised learning, especially for shape learning in the face transition field. This is because the face is a highly sensitive feature, and the quality of the resulting image is significantly affected, especially if the transitions in the eyes, nose, and mouth are not effectively performed. We herein propose a new unsupervised method that can transform an in-wild face image into another face style through radical transformation. Specifically, the proposed method applies two face-specific feature loss functions for a generative adversarial network. The proposed technique shows that stable domain conversion to other domains is possible while maintaining the image characteristics in the eyes, nose, and mouth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1486-1501
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• 2021

The removal of accessories from the face is one of the essential pre-processing stages in the field of face recognition. However, despite its importance, a robust solution has not yet been provided. This paper proposes a network and dataset construction methodology to remove only the glasses from facial images effectively. To obtain an image with the glasses removed from an image with glasses by the supervised learning method, a network that converts them and a set of paired data for training is required. To this end, we created a large number of synthetic images of glasses being worn using facial attribute transformation networks. We adopted the conditional GAN (cGAN) frameworks for training. The trained network converts the in-the-wild face image with glasses into an image without glasses and operates stably even in situations wherein the faces are of diverse races and ages and having different styles of glasses.

• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.12-16
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• 2021

Soccer is one of the popular sports globally, and South Korea is no exception; the professional domestic soccer tournament has been held in South Korea since 1983. The national soccer team in South Korea has shown outstanding performances, hosting the 2002 World Cup and achieving a bronze medal at the London 2012 Olympic Games and second place at the 2019 U-20 World Cup. In addition, one of the South Korean soccer players, Heung-min Son, has played a remarkable role in the English Premier League. Like other global soccer clubs, South Korean domestic soccer clubs create and manage their own YouTube channel to interact with fans and keep them updated. In this study, we explore how and why Seoul E-Land Football Club (SEFC) utilizes its YouTube channel. SEFC is distinctive in that they are playing at the second division, their home ground is based in Seoul, and they are sponsored by a company run on Christian values. We analyze one of the soccer club's YouTube channels multi-dimensionally and discover the roles of YouTube.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.853-873
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• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• International Journal of Internet, Broadcasting and Communication
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• 제15권1호
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• pp.211-221
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• 2023

After COVID-19, various metaverse platforms for online lectures are being provided. Most of the classrooms are tiered type, and they are divided into intensive classrooms and open classrooms depending on the shape of the classrooms. Intensive classrooms provide a one-sided lecture format, so there are many difficulties in conducting communication-based classes that carry out team missions like PBL classes. In this study, we propose a metaverse classroom that applies the functions of a multiplayer online role-playing game (MMORPG), one of the game genres suitable for PBL classes. The proposed system provides various interaction techniques for PBL classes. We evaluated user satisfaction when this was applied to actual classes. As a result of the evaluation, it was found that users preferred text and voice chatting more than video chatting and solving missions like games was very helpful in online classes.