• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.99-108
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• 2008

This paper entirely explains the Korean astronaut program from astronaut selection to launch and return and introduces technology and results through this program in detail. The Korean astronaut program launched Nov. 2005 with the objectives to develop the manned space technology such as astronaut selection, training and space experiment and to disseminate concerns to the public about the science and space. In 2006 to select the Korean astronauts, the standards for selecting astronauts were set and then the selection processes from 1st stage to 4th stage were performed. In 2007, the 2 Korean astronauts took the astronaut training and the 18 domestic science experiments and 3 international experiments which the Korean astronaut, Dr. Yi, performed in ISS last April were developed. In April 2008, the Korean astronaut was transported to ISS by Soyuz in Baikonur in Kazakhstan and returned to the ground with performing the mission and space experiments. This paper will explain these processes as the above(astronaut's selection, training, space experiment, etc.) in detail.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.117-128
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• 2016

The growing socio-economic effect caused by science and technology requires public to participate in policy-making process, which makes government to boost public understanding of science(PUS). Government has also exerted to construct infra for PUS. However results are not so meaningful. The government-funded science museum has mainly provided the program for students. Besides, science broadcasting channel has recorded the worst viewing rate. Meanwhile, some of the private sector-manufactured contents have attracted public attention in recent years, which is realized by considering elements such as an interesting topic selection, use of outside experts, two-way communication system, level adjusting for public through flexible running system. This study analyze podcast based program, face to face lectures, display contents by private industry, fab lab etc. on the base of the reciprocal PUS model to sort out the reason they have successful results. Futhermore, it argues that government should intensify support for private sector and create synergy effect by cultivate collaboration system between government and private sector to enhance the efficiency of PUS and offers public policy to realize the plan.

• IE interfaces
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• v.25 no.3
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• pp.309-318
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• 2012

Forecasting probability or likelihood of technology development success has been a crucial factor for critical decisions in technology management such as R&D project selection and go or no-go decision of new product development (NPD) projects. This paper proposes an analytic network process (ANP) approach to forecasting of technology development success. Reviewing literature on factors affecting technology development success has constructed the ANP model composed of four criteria clusters : R&D characteristics, R&D competency, technological characteristics, and technological environment. An alternative cluster comprised of two elements, success and failure is also included in the model. The working of the proposed approach is provided with the help of a case study example of MRAM (magnetic random access memory) technology.

• Nuclear Engineering and Technology
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• v.38 no.6
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• pp.489-504
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• 2006

A review has been made for the previous studies on safety of a geologic repository for high-level radioactive wastes (HLW) related to autocatalytic criticality phenomena with positive reactivity feedback. Neutronic studies on geometric and materials configuration consisting of rock, water and thermally fissile materials and the radionuclide migration and accumulation studies were performed previously for the Yucca Mountain Repository and a hypothetical water-saturated repository for vitrified HLW. In either case, it was concluded that it would be highly unlikely for an autocatalytic criticality event to happen at a geologic repository. Remaining scenarios can be avoided by careful selection of a repository site, engineered-barrier design and conditioning of solidified HLW. Thus, criticality safety should be properly addressed in regulations and site selection criteria. The models developed for radiological safety assessment to obtain conservatively overestimated exposure dose rates to the public may not be used directly for the criticality safety assessment, where accumulated fissile materials mass needs to be conservatively overestimated. The models for criticality safety also require more careful treatment of geometry and heterogeneity in transport paths because a minimum critical mass is sensitive to geometry of fissile materials accumulation.

• Journal of Information Technology Services
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• v.8 no.1
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• pp.47-58
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• 2009

The information protection security diagnosis institution was applied services since 2004, for the leveling up of public information protection and the establishment of the stability and reliability of information communication. And this security diagnosis was implemented actually on the 142 firms in 2005, the 160 firms in 2006 and the 205 firms in 2007. But this is recognized by the some firms as one of the unnecessary regulations. And there are some difficulties with collecting the subjective and reliable source data for establishing the information protection security diagnosis target. In this research, the enhanced model on the selection of information protection security diagnosis target firms was suggested by the interview with some expert and the analysis for the related actual data. By the model which are introduced from the statistical analysis of the related data and the summary of some expert's suggestions, information protection security diagnosis target can include the information telecommunication service providers taking 5 billion won as sales in a year, and web service providers like as shopping mall site, with the personal records of 2 million subscribers.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.413-420
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• 2019

The purpose of the present study is to develop a model for predicting hypercholesterolemia using an integrated set of body fat mass variables based on machine learning techniques, beyond the study of the association between body fat mass and hypercholesterolemia. For this study, a total of six models were created using two variable subset selection methods and machine learning algorithms based on the Korea National Health and Nutrition Examination Survey (KNHANES) data. Among the various body fat mass variables, we found that trunk fat mass was the best variable for predicting hypercholesterolemia. Furthermore, we obtained the area under the receiver operating characteristic curve value of 0.739 and the Matthews correlation coefficient value of 0.36 in the model using the correlation-based feature subset selection and naive Bayes algorithm. Our findings are expected to be used as important information in the field of disease prediction in large-scale screening and public health research.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.339-345
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• 2022

Cardiovascular diseases is one of the leading causes of death in the world. The objectives of this study were to build various models using sociodemographic variables based on three variable selection methods and seven machine learning algorithms for the identification of hypertension and dyslipidemia and to evaluate predictive powers of the models. In experiments based on full variables and correlation-based feature subset selection methods, our results showed that performance of models using naive Bayes was better than those of models using other machine learning algorithms in both two diseases. In wrapper-based feature subset selection method, performance of models using logistic regression was higher than those of models using other algorithms. Our finding may provide basic data for public health and machine learning fields.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.444-445
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• 2006

The proposed site selection for transmission system construction is applied by KEPCO's regulation of the site selection criteria and it is confirmed through the deliberation of site selection committee and talking with local authority, by means of study on Present status and site survey, to verify impediment of national land use and development plan. Therefore, it is true that KEPCO has difficulty in timely completion of power facility construction because of civil appeals due to insufficiently evaluate resistance factor of stakeholder and stubborn resistance of inhabitants. This paper describes the PEES(power effect estimation system) which contributed to timely completion of transmission system construction to solve the above difficulty by utilizing IT(Information Technology) such as GIS(Geographic Information System) and LiDAR for the proposed site section. PIES evaluates project impacts on commencement of construction and finds out counter measures then makes public construction information after prediction and analysis of stakeholder's resistance factor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4658-4679
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• 2017

Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

• Journal of the Korean Society of Safety
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• v.20 no.4 s.72
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• pp.63-70
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• 2005

It has been used so many kinds of architectural materials and interior products in current building construction, and use of composite architectural materials is increasing with the development of chemical technology. As the green architecture has become the center of public interest, much effort is conducted in advanced countries on the LCA point of view, such as restriction of architectural materials that emitting pollution substances, developing of Non-Toxic architectural materials, and recycling of used materials, etc. with the cooperation of related organizations, material manufacture companies, and construction companies. Because the kinds of materials to be used in building constructions are so various, there might be some possibility of personal and subjective choice at the time of materials selection resulting the missing the requirements of building components and the choice of harmful materials to human. One way to resolve the material problem is to present the green architectural materials which coincide with the quality performance at service and not harmful to man and nature. At this point of view, this study aims to develop the material classification model by investigating the major labelling system about green architectural materials in both domestic and abroad and to implement an efficient material selection system by making a powerful database of environmental standard and quality basis of building requirements.