• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.17-23
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• 2015

Due to the development of information and communication technology as health care service is popular variety utilizing bioinformatics patient information services are being provided to the patient. In particular, the healthcare utilizing bioinformatics information, and change in a variety of healthcare trends. However, healthcare services using bioinformatics information of the patient and the complexity of the disease, new diseases (SARS, AIDS, etc .) due to the emergence of increasing health care costs and health promotion services provided to patients may not be smooth. In this paper, we propose a model for low-cost health services and medical care of patients bioinformatics fast access to information. The proposed model can be so big a bioinformatics data formation by the patient's patient information anytime / anywhere providing medical services in the home or the nearest hospital for their own disease management. In particular, the proposed model of health care services is characterized improve work efficiency, reducing the burden on hospitals by passing a medical illness to easily analyze patient information.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.3069-3085
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• 2018

In this study, we examined the effect of non-cognitive factors on job tenure and tenure using KLIPS. We examine the internal consistency of the big5 personality trait and of the locus of control, and use the parameterized proportional hazards model. As a result, we confirmed that non-cognitive skill such as personality traits and locus of control affect individual labor market performance. Conscientiousness has shown that the job seeking period of adult job seekers is lengthened, thereby lowering the unemployment rate. It can be understood that high attentiveness under uncertainty can misinterpret information, and that lack of decision restricts escape from unemployment. In the tenure analysis, people with internal locus of control tendency were less likely to leave the job due to longer tenure. Those who have internal control can not only be preferred by the organization but also the internal control tendency seems to be the factor that maintains the long-term job because of the motivation and self-control of their actions.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.593-604
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• 2022

The purpose of this study is to analyze the flow of change in perception of metaverse before and after COVID-19 through big data analysis. This research method used Textom to collect all data, including metaverse for two years before COVID-19 (2018.1.1~2019.11.30) and after COVID-19 outbreak (2020.1.11~2021.12.31), and the collection channels were selected by Naver and Google. The collected data were text mining, and word frequency, TF-IDF, word cloud, network analysis, and emotional analysis were conducted. As a result of the analysis, first, hotels, weddings, and glades were commonly extracted as social issues related to metaverse before and after COVID-19, and keywords such as robots and launches were derived, so the frequency of keywords related to hotels and weddings was high. Second, the association of the pre-COVID-19 metaverse keywords was platform-oriented, content-oriented, economic-oriented, and online promotion-oriented, and post-COVID-19 clusters were event-oriented, ontact sales-oriented, stock-oriented, and new businesses. Third, positive keywords such as likes, interest, and joy before COVID-19 were high, and positive keywords such as likes, joy, and interest after COVID-19. In conclusion, through this study, it was found that metaverse has firmly established itself as a new platform business model that can be used in various fields such as tourism, travel, festivals, and education using smart technology and metaverse.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.18-24
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• 2020

Recently, research on Society 5.0 has been actively carried out in Japan. The Society 5.0 is used in various areas using IoT sensors. This paper proposes a privacy approach model of multiple approaches to IoT users based on Society 5.0. The proposed model used multiple methods of synchronizing important information of IoT devices with one another in the virtual environment. The proposed model improved the efficiency of IoT information by accumulating the weight of IoT information on a probability-based basis. Further, it improves the accuracy of IoT information by segmenting it so that attribute information is linked to IoT information. As a result of the performance evaluation, the efficiency of IoT devices has improved by an average of 5.6 percent, depending on the number of IoT devices and the number of IoT hub devices. Accuracy has improved by an average of 15.9% depending on information collection and processing.

• Journal of The Korean Astronomical Society
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• v.28 no.1
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• pp.61-65
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• 1995

We discuss a model4-dimensional Friedmann cosmology which may have evolved from a model of 4+D dimensions which admits spontaneous compactification of D dimensions (or N-dimensional variants of the Brans-Dicke (BD) theory). The BD parameter appearing in dimensional reduction is negative $-1<\omega<0$ (for the N-dimensional variants of the BD theory, $-1.5{\leq}{\omega})$. We find that if there had been inflationary transtion to the standard big-bang model, the Universe can undergoe a polar-type expansion during when the gravitational coupling becomes negative. The unique feature is that for the negative w, the density parameter of the post-inflationary Universe falls in a range 0<0<1 even if the Universe is geometrically flat (k = 0).

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.392-399
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• 2013

Due to the development of IT technology and the information age, a dependency of the network over the most of our lives have grown to a greater extent. Although it provides us to get various useful information and service, it also has negative effectiveness that can provide network intruder with vulnerable roots. In other words, we need to urgently cope with theses serious security problem causing service disableness or system connected to network obstacle with exploiting various packet information. Many experts in a field of security are making an effort to develop the various security solutions to respond against these threats, but existing solutions have a lot of problems such as lack of storage capacity and performance degradation along with the massive increase of packet data volume. Therefore we propose the packet analysis model to apply issuing Big Data technology in the field of security. That is, we used NoSQL which is technology of massive data storage to collect the packet data growing massive and implemented the packet analysis model based on K-means clustering using MapReudce which is distributed programming framework, and then we have shown its high performance by experimenting.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.95-106
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• 2016

The purpose of this study was to examine how college students use Facebook and the ways in which they feel of commitment while using Facebook. The Big Five Personality Model has been considerably used in the psychology fields, and the researchers have started to explore the role of characteristic factors in influencing an individual's use of social media, such as Facebook which has become one of the most popular social networking site in the world. Therefore, the current study aims to specify the links between The Big Five Personality Model and usage patterns as well as commitment of Facebook. Two hundreds thirty five college students participated in a survey and the results are as follows: First, participants who were high in extraversion and agreeableness were more likely to do information sharing activities such as sharing posts to their friends, writing comments on the other's posts. In addition, participants who were high in openness to experience, conscientiousness, and neuroticism were more likely to do information producing activities including offering events, group, or public pages to meet people both on and offline. Second, in terms of the relationship between personality traits and commitment to the Facebook, the study found that extraversion and neuroticism were related to users' commitment to Facebook. These findings are consistent with the existing literature regarding extraversion and neuroticism were representative personality factors when it comes to commitment of media. Specifically, the study found that those who were high in neuroticism were more likely to produce information such as posting photos repeatedly or tagging their friends on posts, and also more likely to feel commitment on Facebook. These findings confirm that personality is a highly relevant factor in determining individual's behavior and the degree of commitment on Facebook. Based on these findings implications and limitations of the study are discussed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.5
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• pp.231-239
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• 2014

This paper represents a method of existing building energy simulation using energy audit data. Energy audit must be carried out for reasonable analysis, because characteristics of existing buildings such as efficiency of fan, pump, flow rate, pressure, COP and operating schedule could be changed during the building operation. These building characteristics should be measured to estimate actual energy consumption of the existing building. In this study, we conducted energy audit and calculated energy savings for a 7-stories building as a case-study. The energy audit data were used to calibrate the building model of EnergyPlus simulation. Baseline model validated according to M&V guideline index. As a result, building characteristics are significant parameters making a big impact on energy savings in existing buildings.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.