• Fire Science and Engineering
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• v.30 no.6
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• pp.92-98
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• 2016

This study evaluated thermal image real-time estimation and fire alarm using by a CCD camera, which has been a seamless feature-point analysis method, according to the angle and position and image fusion by a vector coordinate point set-up of equal shape. The system has higher accuracy, fixing data value of temperature sensing and fire image of 0~255, and sensor output-value of 0~5,000. The operation time of a flame specimen within 500 m, 1000 m, and 1500 m from the test report specimen took 7 s, 26 s, and 62 s, respectively, and image creation was proven. A diagnosis of fire accident was designated to 3 steps: Caution/Alarm/Fire. Therefore, a series of process and the transmission of SNS were identified. A light bulb and fluorescent bulb were also tested for a false alarm test, but no false alarm occurred. The possibility that an unwanted alarm will be reduced was verified through a forecast of the fire progress or real-time estimation of a thermal image by the change in the image of a time-based flame and an analysis of the diffusion velocity.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.367-374
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• 2017

The purpose of this study was to examine brand reliability, product attitude, and purchase intention attitude on a difference in a type between information source (General person / Company) in Sina Weibo. A questionnaire survey was conducted targeting 160 people. Questionnaire was conducted from April 3-7, 2017. The analysis was used 77 people for the General posting without error and 70 people for the Corporate posting. As a result of the research, general person posting is higher preference than public posting in brand reliability(General person M=2.5455/Company M=2.1306), product attitude(General person M=2.4589/Company M=1.9690), and purchase intention(General person M=2.5974/Company M=2.2750) according to type of posting information in Sina Weiboo. The outcome of this study will help to understand consumers' attitudes according to types of sources in China SNS.

• Journal of the Korean Society of Radiology
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• v.13 no.6
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• pp.865-872
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• 2019

The purpose of this study was to analyze the correlation between radiation information sources and major selection satisfaction in radiologic science students of Korean and American. The subjects of this study were first-grade and second-grade at one university in Chungbuk, Korea and one university in Texas, USA. The survey study investigated from May 7, 2019 to May 28, 2019. As a result, first, these college students in both countries used the internet the most as them, but the percentage of information collected through textbooks was significantly higher among American college students. Second, Korean college students had a higher level of reliability in information sources than American college students in the order of internet, newspapers, and social network service (SNS), except government prints. Third, American college students had significantly higher satisfaction in major selection than Korean college students. Fourth, Korean college students were helped to select majors through various information sources, especially, the correlation coefficient between SNS was significantly higher.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.133-142
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• 2021

This study aims to expand the effect of online education into the aspect of active exploration and sharing of class-related issues by learners. Based on theoretical discussions, Two types of motivation (personal and social) to explore issues, engagement, attitude toward issue content, and eWOM model were verified. As a result of the study, it was found that the impact of personal and social motivations that online education has on engagement on specific issues, and the positive(+) influence on attitudes toward issue content and word of mouth intentions on SNS, considering engagement as a parameter. In this study, the role of engagement in inducing the next learning by oneself was confirmed, and it can be seen that social and personal motives for issues and class content should be utilized to increase engagement.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.3
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• pp.41-50
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• 2019

Purpose : The goal of this descriptive research study was to identify the relationship between t relative deprivation, absolute deprivation, self-esteem, self-efficacy, and social support of university students and their show-off behavior on social network services (SNSs), as well as to identify the influencing factors. Methods : The research tools consisted of 8 items for general characteristics, a measure of deprivation (9 items for relative deprivation and 8 items for absolute deprivation), 15 items for show-off behavior on SNSs, 10 items for self-esteem, 25 items for social support, and 20 items for self-efficacy. Data analysis was performed using the SPSS 22.0 program for the descriptive statistics, t-test, ANOVA, Pearson's correlation, and stepwise multiple regression. Results : The results showed relative deprivation (B=.102, t=4.060, p<.001) was the most important factor in show-off behavior on SNSs for university students. Furthermore, social support (B=-.178, t=-3.099, p=.002), absolute deprivation (B=-.175, t=-4.284, p<.001), and self-esteem (B=-.212, t=-2.490, p=.014) accounted for 21.5% of the explanatory power (F=14.215, p<.001). Conclusion : The study findings revealed that relative deprivation is the most important factor in the show-off behavior of university students on SNSs. Social support, absolute deprivation, and self-esteem were also identified as factors that affect their show-off behavior on such services. This study aims to contribute to the effective program progress by providing basic data for the development of the show-off behavior on SNSs intervention and prevention programs to reduce the side effects of various the show-off behaviors on SNSs of university students.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.201-207
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• 2019

In this paper, we propose an effective method to block illegal gambling advertisement on social media. With the increase of smartphone and internet usage, users can easily access various information while sharing information such as text and video with a large number of others. In addition, illegal sports gambling advertisements are also continue to be transmitted on SNS. To avoid most surveillance networks, users are easily exposed to illegal sports gambling advertisement images by including phrases in the images that indicate illegal sports gambling advertisements. In order to cope with these problems, we proposed a method to actively block illegal sports gambling advertisements in a way different from the conventional passive methods. In this paper, we select words frequently used for illegal sports gambling, classifies them into three groups according to their importance, calculate WF for each word using weighted formula by degree of relevance and frequency, and then sum the WF of the words in the image. Blocking, warning, and passing were determined by cv, the total of WF. Experimenting with the proposed method, 193 out of 200 experimental images were correctly judged with 96.5% accuracy, and even though 7 images were illegal sports gambling advertisements. Further research is needed to block 3.5% of illegal sports betting ads that cannot be blocked in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.915-929
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• 2023

Improvements in people's quality of life, diversification of leisure activities, and changes in population structure have led to an increase in the demand for tourism and an expansion of the diversification of tourism activities. In particular, for coastal cities where land and marine tourism elements coexist, various factors influence their tourism demands. Tourism requires the construction of infrastructure and content development according to the demand at the tourist destination. This study aims to improve the prediction accuracy and explore influencing factors through time series analysis of tourism scale using agent-based data. Basic local governments in the Busan area were examined, and the data used were the number of tourists and the amount of tourism consumption on a monthly basis. The univariate time series analysis, which is a deterministic model, was used along with the SARIMAX analysis to identify the influencing factor. The tourism consumption propensity, focusing on the consumption amount according to business types and the amount of mentions on SNS, was set as the influencing factor. The difference in accuracy (RMSE standard) between the time series models that did and did not consider COVID-19 was found to be very wide, ranging from 1.8 times to 32.7 times by region. Additionally, considering the influencing factor, the tourism consumption business type and SNS trends were found to significantly impact the number of tourists and the amount of tourism consumption. Therefore, to predict future demand, external influences as well as the tourists' consumption tendencies and interests in terms of local tourism must be considered. This study aimed to predict future tourism demand in a coastal city such as Busan and identify factors affecting tourism scale, thereby contributing to policy decision-making to prepare tourism demand in consideration of government tourism policies and tourism trends.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.925-933
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• 2018

In this paper, we propose a new smart ordering application system for granting the customer numbers. The proposed system assigns sequence number of customers who visit at offline store as using speaker and microphone of smart device. This system has more advantage than the existing ordering system. Because the proposed system does not need any customer information like as phone number or SNS ID, it can protect customer privacy information. In this system, we use high frequency which is inaudible to the human ear as communication signal between speaker and microphone. To confirm performance evaluation, we perform a test with ten smart devices like as iPhone 6, 7, 8, Galaxy s8 and the result shown a success rate of 98.7 percent. Therefore, the proposed system can be useful service technology at the various offline store which need to assign a sequence number for customers, because many customers visit at the store.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.187-193
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• 2019

In this study, we attempted to identify the personality traits that influence one's likelihood to stalk an ex-partner on Facebook. Specifically, we focused on self-concept-related traits, given that the motivations for using social network sites (SNS) are highly associated with the concept of self. These include self-esteem, narcissism, and self-efficacy. To assess these factors, we controlled for extraneous variables while assessing the predictive power of personality traits, such as Facebook usage, length of the relationship, and time since the break-up. The results of a self-administered, web-based survey (N=207) showed that self-esteem, narcissism, and self-efficacy are all traits that can predict the stalking of an ex-partner on Facebook. More specifically, we showed a negative association between self-esteem and one's likelihood to stalk an ex-partner on Facebook, while it showed positive relationships between Facebook stalking and both narcissism and self-efficacy.