• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.1-4
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• 2001

The classification performance of Artificial Neural Network (ANN) and RBF-NN was compared for Landsat TM image. The RBF-NN was validated for three unique landuse types (e.g. Mixed landuse area, Cultivated area, Urban area), different input band combinations and classification class. The bootstrap resampling technique was employed to estimate the confidence intervals and distribution for unit load, The pollutant generation was varied significantly according to the classification accuracy and percentile unit load applied. Especially in urban area, where mixed landuse is dominant, the difference of estimated pollutant load is largely varied.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.82-89
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• 2013

Novelty detection (ND) is an effective technique that can be used to determine whether a future observation is normal or not. In the present study we propose a novelty detection algorithm that can handle a situation where the distributions of target (normal) observations are inhomogeneous. A simulation study and a real case with the TFT-LCD process demonstrated the effectiveness and usefulness of the proposed algorithm.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.339-351
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• 2017

Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.1-16
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• 2024

In the present highway design guidelines suggest that the capacity of one-lane hi-pass lanes is 2,000 veh/h for mainline toll plaza and 1,700 veh/h for interchange toll plaza. However, in a study conducted in early 2010, capacity of the mainline toll plaza was presented with 1,476 veh/h/ln to 1,665 veh/h/ln, and capacity of the interchange toll plaza was presented as 1,443 veh/h/ln. Accordingly, this study examined the feasibility of the capacity of the currently proposed highway one-lane hi-pass lane. Based on the 2021 individual vehicle passing data collected from the one-lane hi-pass gantry, the speed-traffic volume relationship graph and headway were used to calculate and compare capacity. In addition, the bootstrapping technique was introduced to utilize the headway and new processing methods for collected data were reviewed. As a result of the analysis, the one-lane hi-pass capacity could be estimated at 1,700 veh/h/ln for the interchange toll plaza, and at least 1,700 veh/h/ln for the mainline toll plaza. In addition, by using the bootstrap technique when using headway data, it was possible to present an estimated capacity similar to the observed capacity.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.760-770
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• 2016

A 12-bit 750 kS/s Dual-Sampling Successive Approximation Register Analog-to-Digital Converter (SAR ADC) technique with reduced Capacitive DAC (CDAC) is presented in this paper. By adopting the Adaptive Power Control (APC) technique for the two-stage latched type comparator and using bootstrap switch, power consumption can be reduced and overall system efficiency can be optimized. Bootstrapped switches also are used to enhance the sampling linearity at a high input frequency. The proposed SAR ADC reduces the average switching energy compared with conventional SAR ADC by adopting reduced the Most Significant Bit (MSB) cycling step with Dual-Sampling of the analog signal. This technique holds the signal at both comparator input asymmetrically in sample mode. Therefore, the MSB can be calculated without consuming any switching energy. The prototype SAR ADC was implemented in $0.18-{\mu}m$ CMOS technology and occupies $0.728mm^2$. The measurement results show the proposed ADC achieves an Effective Number-of-Bits (ENOB) of 10.73 at a sampling frequency of 750 kS/s and clock frequency of 25 MHz. It consumes only 0.13 mW from a 5.0-V supply and achieves the INL and DNL of +2.78/-2.45 LSB and +0.36/-0.73 LSB respectively, SINAD of 66.35 dB, and a Figures-of-Merit (FoM) of a 102 fJ/conversion-step.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.219-228
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• 2018

Purpose: This study evaluated the feasibility of a near-infrared spectroscopy technique for the rancidity prediction of soybean oil. Methods: A near-infrared spectroscopy technique was used to evaluate the rancidity of soybean oils which were artificially deteriorated. A soybean oil sample was collected, and the acid values were measured using titrimetric analysis. In addition, the transmission spectra of the samples were obtained for whole test periods. The prediction model for the acid value was constructed by using a partial least-squares regression (PLSR) technique and the appropriate spectrum preprocessing methods. Furthermore, optimal wavelength selection methods such as variable importance in projection (VIP) and bootstrap of beta coefficients were applied to select the most appropriate variables from the preprocessed spectra. Results: There were significantly different increases in the acid values from the sixth days onwards during the 14-day test period. In addition, it was observed that the NIR spectra that exhibited intense absorption at 1,195 nm and 1,410 nm could indicate the degradation of soybean oil. The PLSR model developed using the Savitzky-Golay $2^{nd}$ order derivative method for preprocessing exhibited the highest performance in predicting the acid value of soybean oil samples. onclusions: The study helped establish the feasibility of predicting the rancidity of the soybean oil (using its acid value) by means of a NIR spectroscopy together with optimal variable selection methods successfully. The experimental results suggested that the wavelengths of 1,150 nm and 1,450 nm, which were highly correlated with the largest absorption by the second and first overtone of the C-H, O-H stretch vibrational transition, were caused by the deterioration of soybean oil.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.89-96
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• 2015

The mediation methods suggested by Baron and Kenny, Sobel, Aroian and Goodman, have widely used to test the mediating effect. However, as there are many problems in statistical test power, as well as statistical accuracy, a bootstrapping technique has been suggested as an alternative. In this paper, we adopt the phantom variables based on the bootstrapping technique to test the mediating effect in multiple mediator model consisting of three or more mediating variables. In particular, we formulate the multiple mediator model for analyzing the relations among organizational resources, the absorption capacity as mediating variables and technology commercialization capabilities. And using the bootstrapping approach, we analyzed the mediating effect of the absorption capacity by setting of phantom variables and calculated total indirect effect size and the statistical significance. The empirical results are as follows. First, we confirmed that the bootstrapping approach and the phantom variable is the very efficient and systematic mediation method. Second, we recognized that there is a difference in the mediating characteristics of the absorption capacity depending on the resource characteristics of human resources and material resources obviously.

• Progress in Medical Physics
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• v.23 no.4
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• pp.309-316
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• 2012

Multimodal-imaging technique has been rapidly developed for improvement of diagnosis and evaluation of therapeutic effects. In despite of integrated hardware, registration accuracy was decreased due to a discrepancy between multimodal image and insufficiency of count in accordance with different acquisition method of each modality. The purpose of this study was to improve the PET image by event data resampling through analysis of data format, noise and statistical properties of small animal PET list data. Inveon PET listmode data was acquired as static data for 10 min after 60 min of 37 MBq/0.1 ml $^{18}F$-FDG injection via tail vein. Listmode data format was consist of packet containing 48 bit in which divided 8 bit header and 40 bit payload space. Realigned sinogram was generated from resampled event data of original listmode by using adjustment of LOR location, simple event magnification and nonparametric bootstrap. Sinogram was reconstructed for imaging using OSEM 2D algorithm with 16 subset and 4 iterations. Prompt coincidence was 13,940,707 count measured from PET data header and 13,936,687 count measured from analysis of list-event data. In simple event magnification of PET data, maximum was improved from 1.336 to 1.743, but noise was also increased. Resampling efficiency of PET data was assessed from de-noised and improved image by shift operation of payload value of sequential packet. Bootstrap resampling technique provides the PET image which noise and statistical properties was improved. List-event data resampling method would be aid to improve registration accuracy and early diagnosis efficiency.

• Journal of Information Technology Applications and Management
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• v.18 no.4
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• pp.21-40
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• 2011

Emoticons perform an important role as an enhancement to written communication, in areas such as Windows Live Messenger instant messaging, e-mails, mobile Short Message Services (SMS), and others. Emoticons are graphic images used in communications to indicate the feelings of people exchanging messages via mobile technology. In this research, the perceived usefulness of the emoticon in mobile phone text messages is verified with consumers using the five construct model of Huang. A K-means clustering technique for separating three groups based on levels of perceived usefulness of mobile emoticons is used with a structural equation model test using Smart PLS 2.0, and the bootstrap re-sampling procedure. We analyzed relationships among use of emoticons, enjoyment, interaction, information richness, and perceived usefulness. The results show there are relationships among use of emoticons, enjoyment, interaction, perceived usefulness, and information richness, however enjoyment of emoticons did not significantly affect the perceived usefulness of messages with emoticons alone. The results suggest emoticons have different affects on emotion in both mobile, and Messenger contexts. Our study did not consider more detailed media properties, and thus more studies are needed. Our research results contribute to mobile communication activation, provides companies with an understanding of key characteristics of consumers who use emoticons, and provides useful implications for improving management and marketing strategies.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.27-41
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• 2008

A graphical method of checking the adequacy of a generalized linear model is proposed. The graph helps to assess the assumption that the link function of mean can be expressed as a linear combination of explanatory variables in the generalized linear model. For the graph the boosting technique is applied to estimate nonparametrically the relationship between the link function of the mean and the explanatory variables, though any other nonparametric regression methods can be applied. Through simulation studies with normal and binary data, the effectiveness of the graph is demonstrated. And we list some limitations and technical details of the graph.