• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.374-383
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• 2015

The purpose of this study was to clarify differences between adolescents from multicultural and ordinary Korean families in subjective oral symptoms. Moreover, this will be provide information in the policy making process that enhancing health equity. Data of 66,857 adolescents aged 12 to 18 years were derived from the 10th Korean Youth's Risk Web-based Study, which was conducted in 2014. Multiple logistic regression analysis revealed that subjective oral symptoms were related with sex, age, academic achievement, paternal education, maternal education, subjective economic status, residential type, smoking, alcohol consumption, drinking soft drink, eating fruits, eating snacks, and tooth brushing frequency. In conclusion, welfare and health services for multicultural family should be expanded and those ought to focus on increasing multicultural youth at the same time.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.102-110
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• 2010

H.264 SVC(Scalable Video Coding) provides the advantages of low disk storage requirement and high scalability. However, a streaming server or a user terminal has to extract a bit stream from SVC file. This paper proposes a bit stream extraction method which can get the maximum PSNR value while date bit rate does not exceed the available network bandwidth. To do this, this paper obtains the information about extraction points which can get the maximum PSNR value offline and decides the spatial/temporal resolution of a bit stream at run-time. This resolution information along with available network bandwidth is used as the parameters to a bit stream extractor. Through experiment with JSVM reference software, we proved that proposed bit stream extraction method can get a higher PSNR value.

• Journal of Radiation Protection and Research
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• v.20 no.2
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• pp.117-122
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• 1995

Meteorological Data Acquisition System (MDAS) and Meteorolocical Information Processing System (MIPS) have been developed for the measurement of the meteorological parameters at the Korea Atomic Energy Research Institute site. MIPS represents the measured meteorological data graphically on a computer screen. MDAS and MIPS are interfaced with real-time radiological dose assessment system (FADAS), which has been developed to rapidly assess the radiological consequences and to support decision-making under radiological emergencies.

• Informatization Policy
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• v.25 no.2
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• pp.84-96
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• 2018

The right to be forgotten means the right of people to request information and communication providers to delete their information online. As the number of people asking for deletion of their past embarrassing or negative online activities is increasing, discussions are being raised on the introduction of the right to be forgotten in South Korea. However, previous research on the right to be forgotten mainly deals with the legal concept, with insufficient consideration of economic value. The main purpose of this research is to examine social perception towards the right to be forgotten and to estimate its economic value quantitatively. According to the results, there are concerns about disclosure of personal information, but with lack of awareness on the right to be forgotten. The monthly average amount that a person is willing to pay to be forgotten is 1,218 Korean won (11 US dollars) and the total economic value is estimated to be about 540 billion won (490 million dollars) per year in 2017. Especially, those who have experienced leakage of personal information put higher value to the right to be forgotten. These results can be useful for making decisions about the right to be forgotten in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.65-80
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• 2019

With the advent of the ICT-based 4th industrial revolution, the convergence of the manufacturing industry and ICT seems to be the new breakthrough for achieving the company's competitiveness and play a role on the key element for accelerating the revival of the manufacturing industry. When the smart factory is implemented, each plant can analyze the quantity of data collected, build the data-driven operation systems which can make decisions, and ultimately discover the correlation among many events in the manufacturing sites. As the customers' needs become diversified more and more, it is required for the company to change its operating method from large quantity batch production systems to customizable and flexible manufacturing systems. For performing this requirements, it is essential for the company to adopt the smart factory. Based on technology acceptance model (TAM), this study investigates the factors influencing continuous use intention and switching intention of the smart factory. To do so, a questionnaire survey is conducted both online and offline. 122 samples are used for the study analysis. The results of this study will provide many implications with many researchers and practitioners relevant smart factories.

• The Korean Journal of Archival Studies
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• no.55
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• pp.235-273
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• 2018

The National September 11 Memorial is the institution that collects, assesses, arranges, uses, exhibits, and preserves collections related to the terror attack on September 11, 2001 (9/11), and the explosion incident at the World Trade Center (WTC) on February 26, 1996. After the 9/11 incident, various groups, including the LMDC and the PANYNJ, have participated in the establishment of this organization. Since its initial establishment, the necessity for memorial institutions and detailed characteristics had been discussed in meetings to gather citizens' opinions. Furthermore, the enactment of the 9/11 Memorial Act has secured the institution's stable operation and management. To properly manage disaster-related collections, a just agreement among the citizens and the government should be made to arrive at rational decision-making. This instution can provide answers regarding those ways. Moreover, managing disaster-related collections should be discussed as an important means of remembering, preserving memories, educating, revealing the truth, and preparing academic information and sources. As a result, collaborative governance in records management after a disaster is expected.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.391-404
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• 2019

Customers' fixed characteristics have often been used to predict customer behavior. It has recently become possible to track customer web logs as customer activities move from offline to online. It has become possible to collect large amounts of web log data; however, the researchers only focused on organizing the log data or describing the technical characteristics. In this study, we predict the decision-making time until each customer makes the first reservation, using Airbnb customer data provided by the Kaggle website. This data set includes basic customer information such as gender, age, and web logs. We use various methodologies to find the optimal model and compare prediction errors for cases with web log data and without it. We consider six models such as Lasso, SVM, Random Forest, and XGBoost to explore the effectiveness of the web log data. As a result, we choose Random Forest as our optimal model with a misclassification rate of about 20%. In addition, we confirm that using web log data in our study doubles the prediction accuracy in predicting customer behavior compared to not using it.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.53-63
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• 2011

An SNS(Social Network Service) enables people to form a social network on online as in the real world. With the rising popularity of the service, side effects of SNSs were issued. Therefore we propose and implement a policy-based privacy protection module and access control policy language for ensuring the right of control of personal information and sharing data among SNSs. The policy language for protecting privacy is based on an attribute-based access control model which grants an access to personal information based on a user's attributes. The policy language and the privacy protection module proposed to give the right of control of personal information to the owner, they can be adopted to other application domains in which privacy protection is needed as well as secure sharing data among SNSs.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.19-33
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• 2022

With the explosive growth of social media, its abundant text-based data generated by web users has become an important source for data analysis. For example, we often witness online movie reviews from the 'Naver Movie' affecting the general public to decide whether they should watch the movie or not. This study has conducted analysis on the Naver Movie's text-based review data to predict the actual ratings. After examining the distribution of movie ratings, we performed semantics analysis using Korean Natural Language Processing. This research sought to find the best review rating prediction model by comparing machine learning and deep learning models. We also compared various regression and classification models in 2-class and multi-class cases. Lastly we explained the causes of review misclassification related to movie review data characteristics.