• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6C
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• pp.506-515
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• 2010

In this paper, we compare and analyze the spectral efficiency of representative adaptive MIMO algorithms in indoor environments. We first briefly investigate the modulation and demodulation schemes of MIMO algorithms to be compared and then implement adaptive algorithms by using BPSK and square QAM schemes up to 256QAM. We finally compare the spectral efficiency of adaptive MIMO algorithms employing (2$\times$2) or (4$\times$4) antenna array through the computer simulation in indoor environments.

• Journal of the Korean Home Economics Association
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• v.40 no.6
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• pp.53-67
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• 2002

The purpose of this study is to examine consumer characteristics according to the recycling behavior and analyze the affected variables on recycling behavior. For the empirical analysis, the data was collected 585 consumers from May 14 to June 8,2001. The statistical methods for this study were descriptive statistics, t-tests, cross tables, ANOVA and multiple regression analysis using SPSS PC program. The major findings of this study were as follows: 1. Convenience was important variables to explain the recycling behavior of household trash between two groups, but extrinsic incentives of rewards for undertaking the behavior was not significant. 2. Intrinsic motivation like as perceived consumer difficulties(PCD), perceived consumer effectiveness(PCE), recycling altitude, and ethic was significant variables to compare two groups. 3. Recycling knowledge was important to explain the recycling behavior, but no impact on recycling behavior. 4. Except age, all of socially demographic variables were significant to compare the recycling behavior of two groups. 5. Recycling attitude and convenience had influence on recycling behavior. Especially, ethic had influence on low level recycling behavior of consumer group.

• Sleep Medicine and Psychophysiology
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• v.2 no.1
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• pp.31-43
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• 1995

Recently, the methods that measure and analyze brain electrical activity quantitatively have been available with the rapid development of computer technology. The quantitative electroencephalography(QEEG) is a method of computer-assisted analyzing brain electrical activity. The QEEG allows for a more sensitive, precise and reproducible examination of EEG data than that can be accomplished by conventional EEG. It is possible to compare various EEG parameters each other by using QEEG. Neurometrics, a kind of the quantitative EEG. is to compare EEG characteristics of the patient with normative data to determine in what way the patient's EEG deviates from normality and to discriminate among psychiatric disorders. Nowadays, QEEG is far superior to conventional EEG in its detection of abnormality and in its usefulness in psychiatric differential diagnosis. The abnormal findings of QEEG in various psychiatric disorders are also discussed.

• Journal of Fisheries and Marine Sciences Education
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• v.18 no.3
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• pp.272-282
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• 2006

The purpose of this study was a compare analysis on the counseling of testing and interview for problem of adolescent. The subjects were 20 adolescents who had randomly assigned to an experimental group(10) and a control group(10). To obtain the data, relation of counseling, awareness of self, motivation of self, identity of career questionaries were used. To analyze data, ANCOVA, MANOVA were executed. The results were follows. First, the counseling of testing affected significantly on improvement of experimental group's awareness of self, motivation of self. Second, the counseling of testing affected significantly on improvement of experimental group's identity of career.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.52.1-52.1
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• 2013

We present new analyses of FLS 1718+59, a galaxy-galaxy gravitational lens system in the Spitzer First Look Survey (FLS) Field. A background galaxy (z = 0.245) is severely distorted by a nearby elliptical galaxy (z = 0.08), which can be interpreted as a result of gravitational lensing. We analyze this system by multiple methods, including ELLIPSE fitting, gravitational lens modeling, and surface brightness fitting. From this analysis, we obtain parameters of the lens galaxy using varying approaches and compare them. In the future, we will conduct SED fitting for the lens galaxy and estimate the stellar mass, and compare this with the total mass of the lens to check the M-L relation.

• International Journal of Contents
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• v.6 no.3
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• pp.19-24
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• 2010

Task scheduling is an integrated component of computing with the emergence of grid computing. In this paper, we address two different task scheduling models, which are static Round-Robin (RR) and dynamic Fastest Site First (FSF) task scheduling method, using extended timed marked graphs, which is a special case of Stochastic Petri Nets (SPN). Stochastic reward nets (SRN) is an extension of SPN and provides compact modeling facilities for system analysis. We build hierarchical SRN models to compare two task scheduling methods. The upper level model simulates task scheduling and the lower level model implements task serving process for different sites with multiple servers. We compare these two models and analyze their performances by giving reward measures in SRN.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.215-226
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• 2023

Deep learning has made great strides in the field of unstructured data such as text, images, and audio. However, in the case of tabular data analysis, machine learning algorithms such as ensemble methods are still better than deep learning. To keep up with the performance of machine learning algorithms with good predictive power, several deep learning methods for tabular data have been proposed recently. In this paper, we review the latest deep learning models for tabular data and compare the performances of these models using several datasets. In addition, we also compare the latest boosting methods to these deep learning methods and suggest the guidelines to the users, who analyze tabular datasets. In regression, machine learning methods are better than deep learning methods. But for the classification problems, deep learning methods perform better than the machine learning methods in some cases.

• 기술발표회
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• s.2006
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• pp.66-72
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• 2006

The ground anchoring has been utilized over 40 years. It is growing the application of the removal ground anchor with tension force for holding earth retaining constructions in the city. It transmits tension stress of prestressed steel wire through grouting to fixed the ground that is of great advantage adjacent ground stability. Nowadays, we can find the compression dispersion anchor on many site. But, it has some problems in behavior of anchors because of impossible to tense p.c strand uniformly under the existing equipment due to different length of p c strand. Hence, motive of this research was to study the application of the newly developed tension system, that analyze and compare with the current anchoring method build on the data of in-site test and laboratory test. As a result, in case of auto back tension system, it became clear that tension pressure was equally distributed among the steal wires but the existing tension system showed sign of instability by indicating stress deflection of about 30% compare with design load. This can cause an ultimate failure of the concentrated p.c strand and a shear failure of ground.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.621-630
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• 2020

This study compared and analyzed the contents of secondary earth science curriculum in Mongolia and South Korea to check the contents of earth science education in both countries and to prepare basic data necessary for future earth science curriculum revisions. The research questions of this study are: first, to understand the changes and current operating conditions of earth science curriculum in both countries, to compare and analyze with other foreign cases, and second, to compare and analyze the contents of earth science and curriculum in both countries. The TIMSS evaluation framework is used to compare and analyze the earth science-related contents included in the science curriculum of middle schools. For analyzing the contents of high school, the contents of NGSS in the United States and the earth science curriculum contents of high schools in South Korea were mixed and the analysis frameworks were created and validated by experts. As a result of the study, countries that follow the Russian-style education system did not organize and operate earth science as an independent science subject, and deal with earth science-related content in the natural geography area of the geography subject. The earth science contents covered in middle school science curriculum in both countries, 18 of the 27 content elements of the TIMSS content analysis framework were matched in Mongolia and 20 in South Korea. In high school curriculum, the contents of earth science in Mongolia were described more briefly and not covered than in South Korea. In particular, the Mongolian geography curriculum dealt with many environmental issues. The emphasis on the operation method of the earth science curriculum in Mongolia and the contents related to the environment can be used as a reference when developing an interdisciplinary integrated curriculum of science and social studies in South Korea.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.331-352
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• 2008

The person information is a database given free most lively. This study investigates the construction of the domestic person information database and the service present situation. And I compare a search item and a search method with problems for the biographical database construction process and analyze it. I analyze the problems of the person information database and show the person idea who can solve this. I use term relations and the attribute data of the person which used thesaurus by biographical database construction with this purpose.