• Journal of Distribution Science
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• v.13 no.9
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• pp.103-112
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• 2015

Purpose - This paper aims to provide a step-by-step approach to factor analytic procedures, such as principal component analysis (PCA) and exploratory factor analysis (EFA), and to offer a guideline for factor analysis. Authors have argued that the results of PCA and EFA are substantially similar. Additionally, they assert that PCA is a more appropriate technique for factor analysis because PCA produces easily interpreted results that are likely to be the basis of better decisions. For these reasons, many researchers have used PCA as a technique instead of EFA. However, these techniques are clearly different. PCA should be used for data reduction. On the other hand, EFA has been tailored to identify any underlying factor structure, a set of measured variables that cause the manifest variables to covary. Thus, it is needed for a guideline and for procedures to use in factor analysis. To date, however, these two techniques have been indiscriminately misused. Research design, data, and methodology - This research conducted a literature review. For this, we summarized the meaningful and consistent arguments and drew up guidelines and suggested procedures for rigorous EFA. Results - PCA can be used instead of common factor analysis when all measured variables have high communality. However, common factor analysis is recommended for EFA. First, researchers should evaluate the sample size and check for sampling adequacy before conducting factor analysis. If these conditions are not satisfied, then the next steps cannot be followed. Sample size must be at least 100 with communality above 0.5 and a minimum subject to item ratio of at least 5:1, with a minimum of five items in EFA. Next, Bartlett's sphericity test and the Kaiser-Mayer-Olkin (KMO) measure should be assessed for sampling adequacy. The chi-square value for Bartlett's test should be significant. In addition, a KMO of more than 0.8 is recommended. The next step is to conduct a factor analysis. The analysis is composed of three stages. The first stage determines a rotation technique. Generally, ML or PAF will suggest to researchers the best results. Selection of one of the two techniques heavily hinges on data normality. ML requires normally distributed data; on the other hand, PAF does not. The second step is associated with determining the number of factors to retain in the EFA. The best way to determine the number of factors to retain is to apply three methods including eigenvalues greater than 1.0, the scree plot test, and the variance extracted. The last step is to select one of two rotation methods: orthogonal or oblique. If the research suggests some variables that are correlated to each other, then the oblique method should be selected for factor rotation because the method assumes all factors are correlated in the research. If not, the orthogonal method is possible for factor rotation. Conclusions - Recommendations are offered for the best factor analytic practice for empirical research.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.49-55
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• 2015

In cognitive radio network (CRN), spectrum sensing is an elementary level of technology for non-interfering to licensed user. Required sample number for spectrum sensing is directly related to the throughput of secondary user and makes the tradeoff between the throughput of secondary user and interference to primary user. Required spectrum sensing sample is derived from required false alarm, detection probability and minimum required SNR of primary user (PU). If we make clustering and minimize the required transmission boundary of secondary user (SU), we can relax the required PU SNR for spectrum sensing because the required SNR for PU signal sensing is related to transmission range of SU. Therefore we can achieve efficient throughput of CRN by minimizing spectrum sensing sample. For this, we design the tradeoff between gain and loss could be obtained from clustering, according to the size of cluster members through game theory and simulation results confirm the effectiveness of the proposed method.

• Korean Journal of Materials Research
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• v.31 no.10
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• pp.576-581
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• 2021

To improve the shortcomings and expand the advantages of the single-roll melt drag method, which is a type of continuous strip casting method, the melt drag method with a molding belt is applied to AZ31 magnesium alloy. By attaching the forming belt to the melt drag method, the cooling condition of the thin plate is improved, making it possible to manufacture thin plates even at high roll speed of 100 m/min or more. In addition, it is very effective for continuous production of thin plates to suppress oxidation of the molten metal on the roll contact surface by selecting the protective gas. As a result of investigating the relationship between the contact time between the molten metal and the roll and the thickness of the sheet, it is possible to estimate the thickness of the sheet from the experimental conditions. The relationship between the thin plate thickness and the grain size is one in which the thinner the thin plate is, the faster the cooling rate of the thin plate is, resulting in finer grain size. The contact state between the molten metal and the roll greatly affects the grain size, and the minimum average grain size is 72 ㎛. The thin plate produced using this experimental equipment can be rolled, and the rolled sample has no large cracks. The tensile test results show a tensile strength of 303 MPa.

• Journal of Preventive Medicine and Public Health
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• v.55 no.5
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• pp.464-474
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• 2022

Objectives: We introduced the cohort studies included in the Korean Cohort Consortium (KCC), focusing on large-scale cohort studies established in Korea with a prolonged follow-up period. Moreover, we also provided projections of the follow-up and estimates of the sample size that would be necessary for big-data analyses based on pooling established cohort studies, including population-based genomic studies. Methods: We mainly focused on the characteristics of individual cohort studies from the KCC. We developed "PROFAN", a Shiny application for projecting the follow-up period to achieve a certain number of cases when pooling established cohort studies. As examples, we projected the follow-up periods for 5000 cases of gastric cancer, 2500 cases of prostate and breast cancer, and 500 cases of non-Hodgkin lymphoma. The sample sizes for sequencing-based analyses based on a 1:1 case-control study were also calculated. Results: The KCC consisted of 8 individual cohort studies, of which 3 were community-based and 5 were health screening-based cohorts. The population-based cohort studies were mainly organized by Korean government agencies and research institutes. The projected follow-up period was at least 10 years to achieve 5000 cases based on a cohort of 0.5 million participants. The mean of the minimum to maximum sample sizes for performing sequencing analyses was 5917-72 102. Conclusions: We propose an approach to establish a large-scale consortium based on the standardization and harmonization of existing cohort studies to obtain adequate statistical power with a sufficient sample size to analyze high-risk groups or rare cancer subtypes.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.2
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• pp.281-289
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. Accordingly a more sophiscated classification of the human morphological characteristics is strongly required for the effective clothing construction. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. Data were collected by the direct anthropometric measurement. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the trunk, 19 variables from the data were applied to classify the bodytypes of trunk by Ward's minimum variance method. The groups forming a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical culster analysis. Type 3 and 4 in trunk were composed of the majority of 55.6% of the subjects. The Korean adult males had relatively well-balanced bodytypes in trunk.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.959-968
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• 2020

Tourist loyalty is created through good tourism service quality and the availability of tourism products. This study discussed the various attributes of tourism service quality, namely, tour agents, efficient personnel, accessible transportation, and information service quality. Whereas for tourism product availability attributes were varieties of product availability, wide selection of tour agents and tourist products, and wide variety of amenity services. As a general rule, the minimum is to have at least five times as many observations as the number of variables to be analyzed, and the more acceptable sample size would have a 10:1 ratio. A total of 424 questionnaires were returned, with 35 removed due to errors. Finally, 389 questionnaires respondents were used via accidental sampling method through the distribution of questionnaires to foreign tourists at Soekarno Hatta International Airport. In addition, AMOS 7.0 software is used to test models in confirmatory factor analysis (CFA) as well as hypothetical testing using structural equation modeling (SEM). The results showed that all hypotheses were accepted, except for the effect of tourism service quality on tourist loyalty in Indonesia. This research aims to contribute significantly to the existing knowledge of tourism, specifically from a foreign tourist perspective in Indonesia.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.17-26
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• 1999

We present the first speech coarticulation database of Korean, English and Konglish/sup 3)/ named "SORIDA"/sup 4)/, which is designed to cover the maximum number of representations of coarticulation in these languages [1]. SORIDA features a compact database which is designed to contain a maximum number of triphones in a minimum number of prompts. SORIDA contains all consonantal triphones and vowel allophones in 682 Korean prompts of word length and in 717 English prompt words, spoken five times by speakers of balanced genders, dialects and ages. Korean prompts are synthesized lexicons which maximize their coarticulation variation disregarding any stress phenomena, while English prompts are natural words that fully reflect their stress effects with respect to the coarticulation variation. The prompts are designed differently because English phonology has stress while Korean does not. An intermediate language, Konglish has also been modeled by two Korean speakers reading 717 English prompt words. Recording was done in a controlled laboratory environment with an AKG Model C-100 microphone and a Fostex D-5 digital-audio-tape (DAT) recorder. The total recording time lasted four hours. SORIDA CD-ROM is available in one disk of 22.05 kHz sampling rate with a 16 bit sample size. SORIDA digital audio-tapes are available in four 124-minute-tapes of 48 kHz sampling rate. SORIDA′s list of phonetically-rich-words is also available in English and Korean.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.543-552
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• 2020

This study is aimed at determining an algorithm capable of estimating the erosion index of rainfall for the region of Maceió-Alagoas in the northeast of Brazil. The sample of the truncated data from 2003 to 2006 counts 26,889 droplet size distributions integrated per minute, with 680 rain events with duration longer than 10 minutes. The equation proposed to estimate erosion index used as a dependent variable and independent variable, presenting a coefficient of determination of 99%. The statistical significance validated the relation between minimum rainfall intensity and erosion.

• Journal of Korean Society of Steel Construction
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• v.22 no.2
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• pp.197-208
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• 2010

An under-tension system is frequently employed for large-span structures to reduce the deflection and member size. In this study, a microgenetic algorithm was used to find the optimum cross-section of truss structures with an undertension cable under transverse loading. Maximum deflection, allowable stress, and buckling were considered constraints. The proposed approach was verified using a 10-bar truss sample that shows good agreement with the previous results. In the numerical results, minimum-weight design of the under-tension structure was performed for various magnitudes of pretension.