• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.291-308
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• 2024

The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.353-366
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• 2022

Spatial estimation of geoscience data (geo-data) is challenging due to spatial heterogeneity, data scarcity, and high dimensionality. A novel spatial estimation method is needed to consider the characteristics of geo-data. In this study, we proposed the application of Gaussian Mixture Model (GMM) among machine learning algorithms with multivariate data for robust spatial predictions. The performance of the proposed approach was tested through soil chemical concentration data from a former smelting area. The concentrations of As and Pb determined by ex-situ ICP-AES were the primary variables to be interpolated, while the other metal concentrations by ICP-AES and all data determined by in-situ portable X-ray fluorescence (PXRF) were used as auxiliary variables in GMM and ordinary cokriging (OCK). Among the multidimensional auxiliary variables, important variables were selected using a variable selection method based on the random forest. The results of GMM with important multivariate auxiliary data decreased the root mean-squared error (RMSE) down to 0.11 for As and 0.33 for Pb and increased the correlations (r) up to 0.31 for As and 0.46 for Pb compared to those from ordinary kriging and OCK using univariate or bivariate data. The use of GMM improved the performance of spatial interpretation of anthropogenic metals in soil. The multivariate spatial approach can be applied to understand complex and heterogeneous geological and geochemical features.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.57-67
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• 2006

In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.

• Korea Journal of Hospital Management
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• v.7 no.2
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• pp.24-36
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• 2002

The purpose of this paper is to find the factors affecting the number of patients per physician for a day at hospital and compare them with the results of previous studies. We used data of Korean national patients survey that had been carried out by central government and local health centers from October 27th to November 11th in 1999. Descriptive analyses were performed to overview the general characteristics of our study subject. Also, we tried to find the factors affecting the number of patients per physician for a day at hospital through t test and correlation analysis. Factors affecting the number of outpatients per physician for a day at hospital are location, training type, ownership, No. of physicians, No. of beds per physician, No. of physicists per physician, No. of nursing aids per physician and No. of medical technicians per physician. While factors affecting the number of inpatients per physician for a day at hospital are location, ownership, No. of physicians, No. of beds per physician, No. of pharmacists per physician, No. of nurses per physician, No. of nursing aids per physician and No. of administrative auxiliary personnels per physician. The most correlated variable with outpatients per physician for a day at hospital is No. of medical technicians per physician while the most correlated variable with inpatients per physician for a day at hospital is No. of beds per physician. A more detailed investigation is needed for verifying factors affecting the number of patients per physician for a day at hospital and other medical institutions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.297-303
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• 2015

We propose a disturbance observer(DOB) based feedback linearization control to improve position tracking performance in the presence of disturbance. The proposed method consists of a disturbance observer and a feedback linearization controller. The disturbance observer is designed to estimate the load force disturbance in electro-hydraulic systems. An auxiliary state variable is proposed in order to avoid amplification of the measurement noises in the disturbance observer. Using the estimated disturbance enables the Electro-hydraulic servo systems(EHS) dynamics to be changed into feedback linearization from. In order to compensate for the disturbance and to track the desired position, the feedback linearization based controller is proposed. The proposed method has a simple structure which can easily be implemented in practice. As a result, the proposed method improves the position tracking performance in the presence of disturbance. Its performance is validated via simulations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.11
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• pp.849-855
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• 2008

The paper addresses modeling and analysis of the part load performance of a hybrid fuel cell system integrating a polymer electrolyte membrane fuel cell(PEMFC) and a gas turbine(GT). The system is a pressurized one where the working pressure of the PEMFC is higher than the ambient pressure. In addition to the two major components, the system also includes auxiliary parts such as a steam reformer, a humidifier, and afterburner and so on. Based on design analysis, component off-design models are incorporated in the analysis program and part load operation is simulated. The mode for the part load operation of the PEMFC/GT hybrid system is a variable rotational speed operation. The operating characteristics and variations in the system efficiency and component performance parameters at part load are analyzed.

• Survey Research
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• v.5 no.1
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• pp.93-101
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• 2004

In business survey, cut-off sampling is usual, The contribution from cut-off part of the population is at least small in comparison with the remaining population. In this case, part of the target population is excluded from the selection and parameter estimations are only based on Take-all and Take-some stratum. It may be tempting not to use resources on enterprises that contribute little to the overall results of the survey. And this reduces the response burden for these small enterprises. But, the size of cut-off stratum has been increased as a way to manage reduced budgets. This leads to additional bias. In this study, the population have been separated as three stratum, cut -off, take-some, take-all, and we will estimate cut-off part using auxiliary variable.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.6
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• pp.432-440
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• 2010

In this paper, a LC series resonant boost converter using a single switch is proposed. The proposed topology contains additional passive elements in the conventional boost converter and performs Zero Voltage Switching(ZVS) without an additional auxiliary switch when a main switch turned on and off. The switch off time of the proposed system determined by LC series resonance, thus a on-time variable Pulse Frequency Modulation(PFM) method is adapted to control output voltage in the proposed converter. Operational modes of the proposed topology are divided with respected to the current conduction paths and then through the theoretical analysis and experimental results, operational modes and characteristics of the proposed converter are verified.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.124-132
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• 2018

This paper proposes an LLC resonant converter based battery charger which utilizes an adaptive turn ratio scheme to achieve a wide output voltage range and high efficiency. The high frequency transformer of the LLC converter of the proposed strategy has an adaptively changed turn ratio through the auxiliary control circuit. As a result, an optimized converter design with high magnetizing inductance is possible, while minimizing conduction and turn-off losses and providing a regulated voltage gain to properly charge the lithium ion battery. For a step-by-step explanation, operational principle and optimal design considerations of the proposed converter are illustrated in detail. Finally, the effectiveness of the proposed strategy is verified through various experimental results and efficiency analysis based on prototype 300W Li-ion battery charger and battery pack.