• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.289-294
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• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.43-53
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• 2021

Super-realistic content technology has recently attracted attention as a core of the "new normal" that can overcome the spatial constraints caused by pandemics. It is moreover the core that allows users in remote locations to meet and engage in various social, cultural, and economic activities based on a network. Content technology is rapidly spreading beyond the existing entertainment area to various industries as an innovative tool that can be used to overcome space-time constraints and improve the productivity of industrial sites, because reality and virtual reality are now super-connected with ultra-low latency. However, existing services such as teleconferencing and tele-collaboration do not provide a level of realism that replaces face-to-face services, and various technical requirements have been proposed to overcome this. The trends in core technologies such as XR twins, hyper-realistic reproduction, sensory interaction, and emotional recognition technology, which are necessary for interactive realistic content that leads to feelings, from reproduction to experience and emotion, are explained. In this article, our aim is to present the future of realistic content that enables human care and can even overcome psychological difficulties such as the "Corona blues".

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.71-79
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• 2018

Recently, Korean traditional foods have been commercialized and exported to the world because they can be conveniently and easily ingested. In particular, it is necessary to study and develop recipe for representative foods with high preference in China and Japan which are geographically close to Korea. Therefore, this paper retrieves and collects recipes for representative foods of Korean traditional foods in China and Japan using country portal sites in China and Japan. The recipe collected for each country is constructed with a recipe database to analyze and visualize what materials are used for each type of recipe. The recipe analyzed by country will be used as basic data for commercializing Korean traditional food in China and Japan in the future.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.516-524
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• 2022

The construction industry is considered the most hazardous industry globally. Therefore, safety education is crucial for raising the safety awareness of construction workers working at construction sites and creating a safe working environment. However, the current safety education method and tools cannot provide trainees with realistic and practical experiences that might help better safety awareness in practice. A metaverse, a real-time network of 3D virtual worlds focused on social connection, was created for more interactive communication, collaboration, and coordination between users. Several previous studies have noted that the metaverse has excellent potential for improved safety education performance, but its required functions and practical applications have not been thoroughly researched. In order to fill the research gap, this paper reviewed the potential benefits of a metaverse based on the current research and suggested its application for safety education purposes. This paper scrutinized the metaverse's key functions, particularly its information and knowledge sharing function and reality capture function. Then, the authors created a metaverse prototype based on the two key functions described above. The main contribution of this paper is reviewing the potential benefits of a metaverse for safety education. A realistic and feasible metaverse platform should be developed in future studies, and its impact on safety education should be quantitatively verified.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.209-217
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• 2024

The purpose of this study is to explore development plans by analyzing social interests and perceptions of jiu-jitsu using big data analysis. Network analysis, centrality analysis, and CONCOR analysis were conducted by collecting data for the last 10 years of major domestic portal sites. First, 'judo' was found to be the most important related word in network analysis, and 'judo' was also an important word in the analysis of dgree centrality. In the closeness centrality analysis, "defender" was the most important word, and "sports" was the most important word in betweenness centrality. Finally, as a result of CONCOR analysis, four clusters (related sports and marketing, jiu-jitsu competitions, belt test, supplies and expenses) were formed. As a conclusion of the study, first, words such as 'judo', 'exercise', 'competition', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu.As a conclusion of the study, first, words such as 'judo', 'exercise', 'contest', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu. Second, it is necessary to share information on training costs through various routes, to make awareness of the graduation process or method common, and to develop safety products and create a safe training culture. Third, it is necessary to find ways to continuously increase the influx of new trainees by attracting steady competitions.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.275-282
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• 2020

Social interest on high-quality specialty coffee is increased due to customers' growing experience upon coffee and recent change of coffee culture, which is taking one step further from putting emphasis on not just price and quality but also psychological satisfaction. As a culture of drinking coffee and giving much value on its taste and flavor, a number of customers increasingly demand coffee which is probable to suit one's taste. Likewise, the number of specialty coffee shops is increasing with growing qualities of their coffee. Therefore, the purpose of this study is to analyze the main attributes of specialty coffee and to build a marketing system for specialty coffee shops. The text mining on domestic web portal sites by online big-data analysis is used to extract components of properties of specialty coffee and analyze the degree of how the elements affect the properties. According to the result of the study, words related to coffee taste, coffee beans and baristas were found to play a central role in the properties of specialty coffee.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.87-95
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• 2016

Considerable research over the years has been devoted to ascertaining the impact of social media on political settings.In recent days, Social Network Sites (SNS) such as Facebook allowed users to share their political beliefs, support specific candidates, and interact with others on political issues. This study examines the role of SNS as the means of political campaign. The study tasks the case of the 2015'sspecial election, Seoul Korea. The analysis aims to identify how candidates use Facebook or Twitter to interact with voters by applying functional theory of political campaign discourse developed by Benoit. In this study, we analyzed the candidates' SNS messages in terms of political behavior such as self-expression, informing policy, asking voters to participate in political events. Among them the results indicated that two candidates, Jung, Dong Young and Byun, Hee Jae, both of them used SNS to express themselves the most. The study also found that two candidates used mainly the strategy called 'acclaim' which praises their own strengths. In terms of topics of SNS messages (policy versus character) there was different between two candidates. Jung, sent message in relation to 'character' the most, while Byun contained 'policy' message on SNS the most. Based on these findings implications and directions for future studies are discussed.

• The Korean Journal of Franchise Management
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• v.11 no.2
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• pp.23-39
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• 2020

Purpose: Social Network Sites(SNS) have been grown up as a public communication channel consumer frequently participate in. Most of food service brands are utilizing social media for advertising recently. As a result of SNS marketing, food service brands anticipate positive outputs from SNS engagement and consumer brand engagement so that we need to verify structural relationship among SNS characteristics, SNS engagement and consumer brand engagement. Research design, data, and methodology: This study identifies that SNS characteristics have effects on SNS engagement and examines relationship between SNS engagement and behavioral engagement. We conceptualize SNS characteristics as information quality, hedonic level and interaction. Furthermore, SNS engagement is composed of SNS participation, positive word of mouth(WOM). In order to verify the purposes of this research, research model and hypotheses were developed. All constructs were measured with multiple items developed and tested in the previous studies. Sample data were collected from 433 online survey panels and analyzed by using SmartPLS 3.2.9. Result: The findings of this research are as follows. First, information quality is positively related with SNS participation. Hedonic level and interaction have impacts on SNS participation and positive WOM respectively. Second, SNS participation has positive effects on positive WOM. Third, both SNS participation and WOM influence behavioral engagement respectively. Conclusions: The implications demonstrate that SNS characteristics such as information quality and hedonic level and interaction exert effects for consumer to participate in SNS brand page. Meanwhile, hedonic level and interaction influence on positive WOM but information quality doesn't. SNS participation and positive WOM affect consumer to engage in specific brand behaviorally as well. Therefore, food service brand marketer is required to manage SNS information quality and hedonic level and interaction among members to encourage SNS participation and positive WOM. As SNS participation and positive WOM increases behavioral engagement of consumer, marketer needs to incentivize SNS participation and look after situation of positive WOM and respond swiftly.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.