• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.748-751
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• 2005

This paper introduces the testbed configuration for telematics wireless communications using terrestrial digital multimedia broadcasting (T-DMB) network. The testbed for telematics wireless communications is consisted of indoor laboratory testbed and outdoor field testbed. As a result of research, are derived testbed configurations for individual function verification at the indoor laboratory and performance test at the outdoor test road. In addition, a return channel configuration is described for interactive protocol as necessary for telematics services using T-DMB.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.131-141
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• 2012

In this paper, we propose a new method for collaborative filtering (CF)-based recommender systems. Traditional CF-based recommendation algorithms have applied constant settings such as a reference group (neighborhood) size and a significance level to all users. In this paper we develop a new method that identifies optimal personalized settings for each user and applies them to generating recommendations for individual users. Personalized parameters are identified through iterative simulations with 'training' and 'verification' datasets. The method is compared with traditional 'constant settings' methods using Netflix data. The results show that the new method outperforms traditional, ordinary CF. Implications and future research directions are also discussed.

• Journal of Power Electronics
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• v.10 no.6
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• pp.604-610
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• 2010

Experiments in electrical engineering should mirror the key components of successful research and development: Understand the basic theory needed, test the resulting concepts by simulation and verify these, finally, in the experiment. For optimal learning outcome continuous monitoring of the progress of each individual student is necessary, immediately repeating those subjects which have not been learned successfully. Classically, this is the task of the teacher. In case of remote-controlled experiments this monitoring process and the repetition of subjects should be automated for optimal learning outcome. This paper describes a remote-controlled experiment combining theory, simulation and the experiment itself with an automated monitoring process. Only the evaluation of the experimental results and their comparison to the simulation results has to be checked by a teacher. This paper describes the details of the educational structure for a remote-controlled experiment introducing active filtering of harmonics. For better understanding the content of the learning material (theory and simulation) as well as the results of the experiment and the underlying booking system are shortly presented.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.916-919
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• 2003

In this paper, we deal with a development of measurement system to apply the leakage rates test of primary containment in nuclear power plant. The measurement test about leakage rates in primary containment is one sort of test to prove safety of nuclear power plant. The parameters which are measured to calculate leakage rates are drybulb temperature, dew point temperature(or relative humidity), absolute pressure and flow. Overall, the measurement system consists of sensor module for data acquisition of the parameters, transfer module for wireless data communication and control module to control system and to calculate leakage rates. Because existing measurement systems are difficult to set in field, we pursued convenience of use, we applied wireless data communication and individual form module using battery. We also changed for the better in confidence. Recently, we are developing a drybulb temperature and a dew point temperature sensor module. We describe about function of developed measurement system, its standard and an plan for verification of measurement system.

• Journal of Life Science
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• v.13 no.4
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• pp.412-415
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• 2003

The purpose of this present study was to investigate the polymorphism of esterase locus for individual identification and parentage verification in Jeju native horse (JNH). Seventy three random JNH samples were studied by polyacrylamide gel isoelectric focusing(IEF) at pH 3.5 ∼ 6.0. We detected international recognized alleles, F, G, H, I, M, and an silent allele $I^o$. Gene frequencies of allele I showed 0.479 the highest, while allele H and M($I^o$) with relatively low frequencies were 0.027 and 0.014, respectively.

• Coupled systems mechanics
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• v.8 no.1
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• pp.1-17
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• 2019

The present paper deals with delamination fracture analyses of the multilayered functionally graded non-linear elastic Symmetric Split Beam (SSB) configurations. The material is functionally graded in both width and height directions in each layer. It is assumed that the material properties are distributed non-symmetrically with respect to the centroidal axes of the beam cross-section. Sine laws are used to describe the continuous variation of the material properties in the cross-sections of the layers. The delamination fracture is analyzed in terms of the strain energy release rate by considering the balance of the energy. A comparison with the J-integral is performed for verification. The solution derived is used for parametric analyses of the delamination fracture behavior of the multilayered functionally graded SSB in order to evaluate the effects of the sine gradients of the three material properties in the width and height directions of the layers and the location of the crack along the beam width on the strain energy release rate. The solution obtained is valid for two-dimensional functionally graded non-linear elastic SSB configurations which are made of an arbitrary number of lengthwise vertical layers. A delamination crack is located arbitrary between layers. Thus, the two crack arms have different widths. Besides, the layers have individual widths and material properties.

• The Journal of Economics, Marketing and Management
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• v.7 no.3
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• pp.1-12
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• 2019

Purpose - This study aims to investigate the major capabilities of airline cabin crew to improve the performance of the organization by identifying how they are affected by turnover and customer orientation. Research, design, data, and methodology -The survey participants were limited to all airline cabin crew members in Korea to look at the component measurement items. To verify the validity of the questionnaire, the final questionnaire for this survey was prepared by modifying and supplementing the questionnaire by analyzing factors and validating the questionnaire through reliability verification Results - The analysis on the impact of personal capacity of the airline cabin crew on turnover revealed that some factors had an effect of the positive and the personal capacity of the airline cabin crew has a statistically positive effect on the customer orientation relationship, which is a sub-factor of the cabin crew Conclusions -The capacity of the cabin crew of the airline was defined and the components were established as technical capacity, knowledge capacity and expertise capacity. It was found that the intangible performance of the individual capabilities and customer orientation were very closely related. Airline cabin crew have verified the importance of good talent selection and capacity development training, which are essential requirements for securing the airline's competitiveness.

• The Journal of Information Systems
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• v.30 no.2
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1149-1160
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• 2021

Lack of sleep time increases risks of fatigue, hypomnesis, decreased emotional stability, indigestion, and dementia. The risks can be reduced by providing eyelid-warming, inducing sleep and improving sleep quality. However, effective warming temperature to an person varies depending on physical condition and the individual. The various types of frequencies can be identified in brain wave from a person and amount of frequencies is also changed continuously before and after sleep. Therefore we can identify the user's sleep stage with brain wave, namely EEG. Effective sleep induction is possible if warming temperature to a person is controlled based on EEG. In this paper, we propose customized warming control techniques based on EEG for a efficient and effective sleep induction. As an experiment, sleep induction effects of standard sleep mask and customized temperature control techniques sleep mask are compared. EEG data and warming temperature were measured in 100 experiments. At customized warming control techniques, experiments showed that the ratio of alpha and theta waves increased by 3.21%p and the time to sleep decreased by 85 seconds. It will contribute to effective sleep induction and performance verification methods in customized sleep mask systems.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.1935-1946
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• 2022

The investigations of the coated-particles of nuclear fuel samples are carried out in three stages: front-end, irradiation in the reactor core, and post-irradiation examination. The front-end stage is the initial analysis of the failures rates of produced samples before they are placed in the reactor core. The purpose of the verification is to prepare the particles for an experiment that will determine the degree of damage to the coated particles at each stage. Before starting experiments with the samples, they must be properly prepared. Polishing the samples in order to uncover the inner layers is an important, initial experimental step. The authors of this paper used a novel way to prepare samples for testing - by applying an ion polisher. Mechanical polishing used frequently for sample preparations generates additional mechanical damages in the studied fuel particle, thus directly affecting the experimental results. The polishing methods were compared for three different coated particles using diagnostic methods such as Raman spectroscopy, scanning electron microscopy, and confocal laser scanning microscopy. Based on the obtained results, it was concluded that the ion polishing method is better because the level of interference with the structures of the individual layers of the tested samples is much lower than with the mechanical method. The same technique is used for the fuel particles undergone ion implantation simulating radiation damage that can occur in the reactor core.