• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.60-67
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• 2000

When the eigenvalues of the input covariance matrix of an array system spread by orders of magnitude, conventional adaptive arrays can't remove all the interference signals effectively In this paper, an Applebaum array adopting an adaptive gain controller (AGC) in the feedback loop of the array is proposed When eigenvalue spreaded interferences are incident to an array, a high power interference is removed easily in several iterations while a relative low power interference which is a cause of eigenvalue spread is still remained In the array output After some initial iterations, the proposed array increases the correlation between the low power interference and the array output by amplifying the output signal of the array As a result, the weights vector adapts to the direction of the low power interference as well as that of the high power interference Computer simulation results show that the proposed array gives high output signal to interference plus noise ratio (SINR) and a fast convergence speed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.153-158
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• 2020

In this paper, we studied an algorithm for estimating a desired target by removing noise and interference in a wireless communication environment. When an information signal with a mixture noise and interference receive a receiver, noise and interference signals must be removed to accurately estimate a desired target. In order to divide the received signal region into two spatial, a power spectrum is obtained by analyzing a correlation matrix, covariance, eigen vector, and eigen value. The proposed spectrum is an algorithm that can remove noise and interference, and analyzes the existing algorithm and target estimation performance through simulation. As a result of simulation, the target estimation resolution of existing algorithm is more than 10°, but the resolution of the proposed algorithm is less than 10°. The proposed algorithm has improved the resolution of about 5° than the exiting algorithm. The proposed algorithm proved that the target estimation accuracy and resolution are superior to the existing algorithm.

• Progress in Superconductivity
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• v.4 no.2
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• pp.114-120
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• 2003

We employed a method eliminating a temporally partial principal component (PC) of multichannel-recorded neuromagnetic fields for excluding spatially correlated noises from event-evoked signals. The noises in magnetoencephalography (MEG) are considered to be mainly spontaneous neuromagnetic fields which are spatially correlated. In conventional MEG experiments, the amplitude of the spontaneous neuromagnetic field is much lager than that of the evoked signal and the synchronized characteristics of the correlated rhythmic noise makes it possible for us to extract the correlation noises from the evoked signal by means of the general PC analysis. However, the whole-time PC of the fields still contains a little projection component of the evoked signal and the elimination of the PC results in the distortion of the evoked signal. Especially, the distortion will not be negligible when the amplitude of the evoked signal is relatively large or when the evoked signals have a spatially-asymmetrical distribution which does not cancel out the corresponding elements of the covariance matrix. In the period of prestimulus, there are only the spontaneous fields and we can find the pure noise PC that is not including the evoked signal. Besides that, we propose a method, called the extended temporal decorrelation method (ETDM), to suppress the distortion of the noise PC from remanent evoked signal components. In this study, we applied the Partial Principal component elimination method (PPCE) and ETDM to simulated signals and the auditory evoked signals that had been obtained with our homemade 37-channel magnetometer-based SQUID system. We demonstrate here that PPCE and ETDM reduce the number of epochs required in averaging to about half of that required in conventional averaging.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.289-294
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• 2015

Linear mixed models are commonly used in the clinical pharmaceutical studies to analyze repeated measures such as the crossover study data of bioequivalence studies. In these models, random effects describe the correlation between repeated outcomes and variance-covariance matrix explain within-subject variabilities. Bioequivalence analysis verifies whether a 90% confidence interval for geometric mean ratio of Cmax and AUC between reference drug and test drug is included in the bioequivalence margin [0.8, 1.25] performed using linear mixed models with period, sequence and treatment effects as fixed and sequence nested subject effects as random. A Levofloxacin study is referred to for an example of real data analysis.

• The Korean Journal of Franchise Management
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• v.14 no.2
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• pp.49-60
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• 2023

Purpose: NBS (Natural-based Solutions) characteristics as eco-friendly hotels were divided into eco-friendly indoor and outdoor to structurally verify the relationship between customers' perceived eco-friendly value, psychological well-being, customer satisfaction, and pro-environmental behavioral intention. Research design, data and methodology: This survey conducted responses to customers who had experience using eco-friendly hotels for the past two years. SPSS 22.0 and AMOS 22.0 statistical programs were used for the collected questionnaire data. First, frequency analysis and confirmatory factor analysis (CFA) were verified, and structural correlation between variables was verified by covariance matrix structural equation (CB-SEM). Result: First, NBS was found to have a significant positive (+) effect on perceived eco-friendly value and psychological well-being. Second, psychological well-being was found to have a significant positive (+) effect on customer satisfaction and eco-friendly behavioral intention. Finally, Hypothesis 3 was accepted as perceived eco-value showed a significant positive (+) effect on eco-friendly behavioral intention, but Hypothesis 2 was rejected because it did not have a significant effect on customer satisfaction. Conclusions: theoretical and practical implications for the impact of NBS as an eco-friendly hotel on customers' eco-friendly behavior can be provided, as well as basic evidence for establishing efficient management strategies for hotel companies.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.703-724
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• 2022

Although longitudinal studies mainly produce multivariate longitudinal data, most of existing statistical models analyze univariate longitudinal data and there is a limitation to explain complex correlations properly. Therefore, this paper describes various methods of modeling the covariance matrix to explain the complex correlations. Among them, modified Cholesky decomposition, modified Cholesky block decomposition, and hypersphere decomposition are reviewed. In this paper, we review these methods and analyze Korean children and youth panel (KCYP) data are analyzed using the Bayesian method. The KCYP data are multivariate longitudinal data that have response variables: School adaptation, academic achievement, and dependence on mobile phones. Assuming that the correlation structure and the innovation standard deviation structure are different, several models are compared. For the most suitable model, all explanatory variables are significant for school adaptation, and academic achievement and only household income appears as insignificant variables when cell phone dependence is a response variable.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.157-176
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• 2024

Integrative analysis for better understanding of complex biological systems gains more attention. Observing subjects from various perspectives and conducting integrative analysis of those multiple datasets enables a deeper understanding of the subject. In this paper, we compared two methods that simultaneously consider two datasets gathered from the same objects, canonical correlation analysis (CCA) and co-inertia analysis (CIA). Since CCA cannot handle the case when the data exhibit high-dimensionality, two strategies were considered instead: Utilization of a ridge constant (CCA-ridge) and substitution of covariance matrices of each data to identity matrix and then applying penalized singular value decomposition (CCA-PMD). To illustrate CIA and CCA, both extensions of CCA and CIA were applied to NCI60 cell line data. It is shown that both methods yield biologically meaningful and significant results by identifying important genes that enhance our comprehension of the data. Their results shows some dissimilarities arisen from the different criteria used to measure the relationship between two sets of data in each method. Additionally, CIA exhibits variations dependent on the weight matrices employed.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.361-377
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• 2011

This study has three primary purposes, firstly to identify how leader's personal characters influence to his/her transformational leadership, secondly to find how transformational leadership influences to innovative behavior, finally to explore how organizational cultures moderate between transformational leadership and innovative behavior. The first part of the study, based on literature study on transformational leadership, provides insight into what are antecedents, moderators and dependent variable in transformational leadership. Firstly, leader's personal characters are selected as antecedent variables such as extroversion and self-efficacy. Secondly, innovative behavior is introduced as a dependent variable. Thirdly, two types of organizational culture are considered as moderators between leader's personal character and leadership In this study, a comprehensive research model and hypothesis were empirically tested based on data from three types of questionnaires involving 663 employees in Korean organizations. In order to test the hypotheses, we have used Structural Equations Model (SEM) from AMOS7.0. In this analysis, we have employed raw data as it is instead of correlation matrix or covariance matrix. We have tested hypotheses by examining the significance of each path of the model, and gone through the process of testing the goodness of fit of the model itself. The results of statistical analysis show the following. Firstly, one of leader's personalities, self-efficacy has positive effect on his/her transformational leadership, but extroversion does not have positive effect. Secondly, transformational leadership has positive effect on innovative behavior. Finally, there was not any cultural moderating effects between transformational leadership and innovative behavior.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.81-93
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• 2013

The selection of land for fishing village development project, and the standard used to classify fishing villages has been determined based on the guidelines developed by fishing village cooperatives. The approach fishing village cooperatives follows is likely to classify fishing villages without first reflecting on the overall development environment of the region, such as other industries and workers in the area. It also acts as a barrier for business promotion or evaluation, because the cooperatives do not match the administrative districts, which are the units of administration, and the main policy enforcement agent in regional development. Against this background, this study aimed to identify categories to situate the development direction, as well as the size and distribution of fishing villages based on eup, myeon, and dong administrative units as defined by the Fishing Villages and Fishery Harbors Act. This study was based on the Census of Agriculture, Forestry, and Fisheries of 2010, and analyzed 826 eups, myeon, and dongs with fishery households using the principal component analysis, and 2-Step cluster analysis methods. Therefore, 95% of the variance was explained using the covariance matrix for types of fishing villages, but it was analyzed as one component focusing on the number and ratio of fishery households, and used the cluster-type analysis, which focused on the sizes of fishing villages. The clusters were categorized into three types: (1) the development type based on the number of fishermen in the eups, myeons and dongs was analyzed as village size (682); (2) administrative district size (121); and (3) total eups, myeons and dongs (23), which revealed that the size of most fishing villages was small. We could explain 73% of the variance using the correlation coefficient matrix, which was divided into three types according to the three principal component scores, namely fishery household power, fishery industry power, and fishing village tourism power. Most fishing villages did not have a clear development direction because all business areas within the region were diversified, and 552 regions could be categorized under the harmonious development type, which is in need of balanced development. The fishery industry type typified by industrial strength included 159 regions in need of an approach based on industrialization of fishery product processing. Specialized production areas, which specialized in producing fishery products, were 115 regions with a high percentage of fishermen. The analysis results indicated that various situations in terms of size and development of fishing villages existed. However, because several regions exist in the form of small village units, it was necessary to approach the project in a manner that directed the diversification of regional development projects, such as places for local residents to relax or enjoy tourism experiences within the region, while considering the overall conditions of the relevant eups, myeons, and dongs. Reinforcement of individual support for fishermen based on the Fisheries Act must take precedence over providing support for fishermen through regional development. In addition, it is necessary to approach the development of fishing villages by focusing on industrializing the processing techniques of fishery products. Areas specialized in the production of fishery products are required to consider the facilities for fisheries production, and must make efforts to increase fishery resources, such as releasing fry.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.381-389
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• 2004

Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.