• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1272-1278
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• 2022

The government enacted and promulgated the 'Severe Accident Punishment Act' in January 2021 and is implementing this law. However, the number of occupational accidents in 2021 increased by 10.7% compared to the same period of the previous year. Therefore, safety measures are urgently needed in the industrial field. In this study, BLE Mesh networking technology is applied for safety management of high-risk industrial sites with poor communication environment. The complex sensor AIoT device collects gas sensing values, voice and motion values in real time, analyzes the information values through artificial intelligence LSTM algorithm and CNN algorithm, and recognizes dangerous situations and transmits them to the server. The server monitors the transmitted risk information in real time so that immediate relief measures are taken. By applying the AIoT device and safety management system proposed in this study to high-risk industrial sites, it will minimize industrial accidents and contribute to the expansion of the social safety net.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.168-170
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• 2022

The government enacted and promulgated the 'Severe Accident Punishment Act' in January 2021, and is enforcing the law for workplaces with 50 or more full-time workers. However, the number of industrial accident accidents in 2021 increased by 10.7% compared to the same period of the previous year, and chemical gas Safety accidents due to leaks and explosions also occur frequently. Therefore, in high-risk industrial sites, comprehensive Safety measures are urgently needed. In this study, BLE Mesh networking in industrial sites with poor communication environment apply technology. The complex sensor AIoT device recognizes a dangerous situation as a gas sensing value, voice, and motion value, and transmits it to the server. The server monitors the risk situation in real time through information value analysis and judgment through artificial intelligence LSTM algorithm and CNN algorithm for AIoT transmission information. Through this study, through the development of AIoT devices capable of gas sensing, voice and motion recognition, and AI-applied safety management systems, It will contribute to the expansion of the social safety net by expanding its application.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.39-51
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• 2024

To effectively implement the integrated water management policy outlined in the National Water Management Act, it is essential to analyze agricultural water supply and demand at both basin and water district levels. Currently, agricultural water is primarily distributed through open canal systems and controlled by floodgates, yet the utilization-to-supply ratio remains at a mere 48%. In the case of agricultural water, when analyzing water balance through existing national basin water resource models (K-WEAP, K-MODISM), distortion of supply and regression occurs due to calculation of regression rate based on the concept of net water consumption. In addition, by simplifying the complex and diverse agricultural water supply system within the basin into a single virtual reservoir, it is difficult to analyze the surplus or shortage of agricultural water for each field within the basin. There are limitations in reflecting the characteristics and actual sites of rural water areas, such as inconsistencies with river and reservoir supply priority sites. This study focuses on the development of a model aimed at improving the deficiencies of current water balance analysis methods. The developed model aims to provide standardized water balance analysis nationwide, with initial application to the Anseo standard watershed. Utilizing data from 32 facilities within the standard watershed, the study conducted water balance analysis through watershed linkage, highlighting differences and improvements compared to existing methods.

• Journal of the Society of Disaster Information
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• v.10 no.4
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• pp.518-527
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• 2014

Our society is changed and diversified rapidly and such tendency is accelerated day after day and has made a lot of problems in the many fields. The important thing we have to recognize is such tendency has a bad effect recently on the safety system in Korea. So it is time to enhance the national safety system and moreover recently Sewol-ho(passenger ship) went down in the sea, it made people remind the importance of national safety system. With this incident, Korean government decided to establish the national safety communication network against the disaster. At this time, I will propose several ideas about the national safety communication network. 1. It must to be established an unified network to contact people who is on a disaster site anytime and anywhere. This is most important element on all disaster sites. 2. PS-LTE technology must to be adopted to the network because it has many advantages including various multimedia services compared to the TETRA in the past. 3. 700MHz is the most efficient band for the network because it has wide cell sites coverage compared to 1.8GHz. 4. Satellite communication system is needed to the network for back-up. 5. It will be effective to adopt Social Media to the communication network system like a Twitter or Facebook for sharing many kinds of information and notifying people of warning message. 6. It can make the network more useful to introduce the latest technology like a sensor network. And Korean government has to improve the system related to the disaster including law and operating organization.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.15-26
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• 2010

Social Networks such as 'Facebook' and 'Myspace' are regarded as useful tools for people to share interests and maintain or expand relationships with other people. However, they pose the risk that personal information can be exposed to other people without explicit permission from the information owner. Therefore, we need a solution for this problem. Although existing social network sites allow users to specify the exposing range or users who can access their personal information, this cannot be a practical solution because the information can still be revealed to third parties through the permitted users albeit unintentionally. Usually, people allow the access of unknown person to personal data in online social networks and this implies the possibility of information leakage. We could use an access control method based on trust value, but this has the limitation that it cannot reflect the quantitative risk of information leakage. As a solution to this problem, this paper proposes an access control method based on a synthesized metric from trust and risk factors. Our various experiments show that the risk of information leakage can play an important role in the access control of online social networks.

• The Journal of Bigdata
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• v.1 no.1
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• pp.67-75
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• 2016

The study analyzed big data extracted from Google and social media to identify factors related to searches on cyber bullying in Korea and America. Korea's cyber bullying analysis was conducted social big data collected from online news sites, blogs, $caf{\acute{e}}s$, social network services and message for between January 1, 2011 and March 31, 2013. Google search trends for the search words of stress, exercise, drinking, and cyber bullying were obtained for January 1, 2004 and December 22, 2013. The main results of this study were as follows: first, the significant factors stress were cyber bullying that Korea more than America. Secondly, a positive relationship was found between stress and drinking, exercise and cyber bullying both Korea and America. Thirdly, significant differences were found all path both Korea and America. The study shows that both adults and teenagers are influenced in Korea. We need to develop online application that if cyber bullying behavior was predicted can intervene in real time because these actual cyber bullying-related exposure to psychological and behavioral characteristic.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.205-210
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• 2011

This paper is implemented new styled site to combine community of blog style for SNS and shopping mall. Especially, this site is included simulation of coordination in fashion with avatar model. It makes indirect experience of clothing and user-friendly user interface that is different to other Web sites or shopping malls. So this avatar is designed and implemented by using flash animation technique that makes confirm possible coordination styles with eyes of client instantly and review goods very easily. Additionally, it makes pay attention to connect shopping malls and service convenience by SNS.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.139-157
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• 2019

This study is intended for demonstrating the impacts of different factors on the formation of online consumer engagement behavior of young Chinese moviegoer in Korea. Based on Value-Exchange Model [Itani et al., 2019], we build research model to reveal the relationships among perceived enjoyment, perceived movie information value, multiplex-audience relationship quality, multiplex usage satisfaction, and online consumer engagement through experiments on valid data we collected from 186 participants who had lived in Korea and experienced the multiplex pages of top 3 movie theaters, where Smart PLS 3.0 is the tool used for statistical analysis. The experimental results show that both perceived enjoyment and perceived movie information value positively correlate to multiplex-audience relationship quality, and multiplex audience relationship quality significantly influences multiplex usage satisfaction and online consumer engagement. In addition, it is found that relationship quality plays the role of mediator between perceived enjoyment and satisfaction. The findings from this study offer both academic and managerial implications for movie distributors who are interested in developing potential Chinese consumer market in Korea.

• Fashion, Industry and Education
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• v.14 no.1
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• pp.40-49
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• 2016

This study examined students' perceived importance of the benefits derived from an international multi-course collaborative (IMCC) project and how these perceptions impact students' extrinsic and intrinsic motivations for using the project Facebook (i.e., perceived usefulness and enjoyment), attitude toward the project, and intent to participate in future IMCC projects. The data were collected from 96 students who participated in the IMCC project and were enrolled in four different fashion merchandising courses in two different countries, the U.S. and South Korea. This study found that perceived enjoyment of the project Facebook influenced attitude toward the project and intent to participate in future IMCC projects. Perceived usefulness and enjoyment were predicted by the perceived importance of cultural understanding and feedback exchange among international group members. Attitude was influenced by the perceived importance of networking through the IMCC project, while intent to participate in future IMCC projects was predicted by perceived importance of cultural understanding and networking through the IMCC project. This study provides educators in the related disciplines insights about how to incorporate social network sites into course curricula to motivate students' project participation and learning.

• 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.