• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.386-394
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• 2021

This study aims to investigate the class satisfaction of the students enrolled in between a primary and secondary teacher's college, and to identify any statistical differences among the class satisfaction factors. In order to answer these questions, a survey of 50 questionnaires were distributed to 54 primary teachers' college students and 50 secondary teacher's college ones, respectively. A survey consisted of 5 categories including class contents, instruction results, class environment, instructional supports and efficiency. To analyze data, the descriptive analysis and independent sample t-test were administerd using Jamovi statistical program. The results revealed that there was no significant difference between two groups in terms of the overall class satisfaction, even though the mean score from the secondary teachers' college students was higher than that of the primary teachers' college students. However, there was a significant difference in the class satisfaction's sub categories: class environment, instructional supports and efficiency.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.90-101
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• 2016

This study was initiated to develop an algorithm for traffic condition adaptive optimal traffic signal control for isolated intersections based on the vehicle trajectory data. The algorithm determines the optimal cycle length, phase lengths, phase sequences using the data collected under V2X communication environment every second. In addition, the algorithm utilizes a traditional feature of the actuated signal control, gap-out, using traditional detector systems to consider the mixture of normal vehicles and vehicles equipped with the V2X communication function. The performance of the algorithm was compared with that of the fixed signal timing plan which was optimized with Synchro under a microscopic traffic simulation-based test bed. As a result, the overall performance, including average delay, average stop delay, the number of stops, and average speed, are improved apparently. In addition, the amount of improvement get bigger as the traffic volume in the intersection as well as the number of vehicles equipped with the V2X communication function increase.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.83-90
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• 2000

The chi-squared test statistic is usually employed for testing independence of two categorical variables in a two-way contingency table. It is well known that, under independence, the test statistic has an asymptotic chi-squared distribution under multinomial or product-multinomial models. For the case where both margins fixed, the sampling model of the contingency table is a multiple hypergeometric distribution and the chi-squared test statistic follows the same limiting distribution. In this paper, we study the difference between the small sample and large sample distributions of the chi-squared test statistic for the case with fixed margins. For a few small sample cases, the exact small sample distribution of the test statistic is directly computed. For a few large sample sizes, the small sample distribution of the statistic is generated via a Monte Carlo algorithm, and then is compared with the large sample distribution via chi-squared probability plots and Kolmogorov-Smirnov tests.

• 대한공업교육학회지
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• v.38 no.2
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• pp.240-266
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• 2013

The purpose of this study is to investigate the self-directed learning readiness of university students' majored in science and engineering as life-long learners, and to analyze the relationship between self-directed learning readiness and learning style. Participants of this study are 142 students majored science and engineering in H university of Chung-nam province to participate in taking self-directed learning readiness tests and Kolb's learning style tests. The results of this study are as follows: First, the average of overall participants' self-directed learning readiness is 3.41, which is possibly regarded as 'an average' according to Guglielmino & Guglielmino (1991)'s interpretation of scores. Second, among four basic scales of participants' learning styles, the highest is found in Active Experiment (AE), the lowest is found in Abstract Conceptualization (AC). In addition, the highest thing of the four learning styles found among the participants is divergers (36.6%) and the lowest is convergers (13.4%). Finally, this study compares the high-level and low-level groups of self-directed learning readiness score with learning style. there is a statistically significant correlation between the score of self-directed learning readiness and CE, AC (p=.01). Therefore, self-directed learning readiness is related to learning style.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.47-57
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• 2015

This study examines whether successful stand-alone firms have more difficulties than the successful firms affiliated to business groups in external financing. The easiness of external financing is measured by investment-cashflow multiple. Controlling the effects on the multiple of the past business performances and the expectation of future business performances, we investigate how the ownership type affects the multiple. The empirical results show that, when cashflows are positive, the stand-alone firms exhibit higher investment-cashflow mupltiples. When cashflows are negative, however, the opposite is true, even though the statistical significance of the result is rather low. These results do not support the general idea that stand-alone firms must have more disadvantage than subsidiary firms in raising funds from outside. If member firms of business groups have no big trouble financing externally, then the above results imply that stand-alone firms do not either identify external financing as a major difficulty in running business. Thus, if the government seeks to formulate the selective policies supporting only the promising start-ups, instead of the general policies benefiting random start-ups, then the start-up financing policy should have a lower priority.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.673-680
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• 2003

In this paper, we study the enhancement of VQ (Vector Quantization) design for text independent speaker recognition. In a concrete way, we present a non-iterative method which makes a vector quantization codebook and this method performs non-iterative learning so that the computational complexity is epochally reduced The proposed Classified Space VQ (CSVQ) design method for text Independent speaker recognition is generalized from Semi-noniterative VQ design method for text dependent speaker recognition. CSVQ contrasts with the existing desiEn method which uses the iterative learninE algorithm for every traininE speaker. The characteristics of a CSVQ design is as follows. First, the proposed method performs the non-iterative learning by using a Classified Space Codebook. Second, a quantization region of each speaker is equivalent for the quantization region of a Classified Space Codebook. And the quantization point of each speaker is the optimal point for the statistical distribution of each speaker in a quantization region of a Classified Space Codebook. Third, Classified Space Codebook (CSC) is constructed through Sample Vector Formation Method (CSVQ1, 2) and Hyper-Lattice Formation Method (CSVQ 3). In the numerical experiment, we use the 12th met-cepstrum feature vectors of 10 speakers and compare it with the existing method, changing the codebook size from 16 to 128 for each Classified Space Codebook. The recognition rate of the proposed method is 100% for CSVQ1, 2. It is equal to the recognition rate of the existing method. Therefore the proposed CSVQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal and CSVQ with CSC can be applied to a general purpose recognition.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.617-626
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• 2009

A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a ${\delta}$-sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the ${\delta}$-sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.1-26
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• 2010

This paper empirically examines whether Korean monetary policy is independent of U.S. monetary policy during the post-crisis period in which capital account is liberalized and floating exchange rate regime is adopted and during the pre-crisis period in which capital mobility is restricted and tightly managed exchange rate regime is adopted. Before capital account liberalization, monetary autonomy can be achieved in view of the trillema, even under tightly managed exchange rate regime, as capital mobility is restricted. On the other hand, for the period after capital account liberalization, monetary autonomy can be also achieved in view of the trillema, as exchange rate stability is given up. Securing monetary autonomy, however, may not be easy under liberalized capital account for a small open economy like Korea. Huge capital movements can generate excessive instability in foreign exchange and asset markets. Strengthened international economic linkages may also be another factor to prevent monetary policy from being independent. Using block-exogenous structural VAR model, the effects of U.S. monetary policy shocks on Korean economy are examined. Empirical results show that Korean monetary policy is not independent of U.S. monetary policy for both periods before and after capital account liberalization. For the period after capital account liberalization, Korea does not seem to have implemented floating exchange rate policy in practice, which may lead Korean monetary policy to be dependent on U.S. monetary policy. For the period after capital account liberalization, portfolio flows respond dramatically to the U.S. monetary policy, which may also keep Korean monetary policy from being independent.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.67-76
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• 2013

In this study we surveyed service satisfaction for the start-up support program and measured the relative importance of the factors that influence service satisfaction. The five service factors(physical facilities, finance and accounting, human resources, marketing, product development) were used to measure service satisfaction. Typically, the relative importance of predictors is assessed by simply comparing their standardized regression coefficients. However, when the predictors are correlated, regression coefficients cannot be used to explain variance shared by two or more predictors. The dominance analysis used by many researchers in recent years to measure the relative importance of predictor variables. In this article, we applied it in satisfaction research for the start-up support program. The results obtained by the dominance analysis are compared with the results obtained by multiple regression analysis. And satisfaction and relative importance of the five factors are analyzed by entrepreneurship motivation. These findings will contribute to the marketing research field relating to service satisfaction. Service satisfaction for the start-up support program can improve based on this study.