• Journal of Biosystems Engineering
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• v.33 no.4
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• pp.269-275
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• 2008

This study was conducted to design an impedance sensor that can measure soil water content of soils. Partial least square regression (PLSR) was applied to soil impedance data preprocessed with a smoothing method. An optimal sub-spectrum size and wavelength range were determined by comparing the coefficient of determination ($R^2$) and root mean square error (RMSE) of the PLSR models obtained using soil impedance data. various PLS analysis. Based on the PLSR analysis, it would be concluded that the optimal spectrum measurement range was $32.0{\sim}50.0\;MHz$ with the optimal sub-spectrum size of about 18.5 MHz.

• ETRI Journal
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• v.31 no.2
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• pp.162-172
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• 2009

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.559-570
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• 2017

A partial least squares regression (PLSR) model was developed to map the internal soluble solids content (SSC) of apples using a ground-based hyperspectral scanner that could simultaneously acquire outdoor data and capture images of large quantities of apples. We evaluated the applicability of various preprocessing techniques to construct an optimal prediction model and calculated the optimal band through a variable importance in projection (VIP)score. From the 515 bands of hyperspectral images extracted at wavelengths of 360-1019 nm, 70 reflectance spectra of apples were extracted, and the SSC ($^{\circ}Brix$) was measured using a digital photometer. The optimal prediction model wasselected considering the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP) and coefficient of determination of prediction $r_p^2$. As a result, multiplicative scatter correction (MSC)-based preprocessing methods were better than others. For example, when a combination of MSC and standard normal variate (SNV) was used, RMSECV and RMSEP were the lowest at 0.8551 and 0.8561 and $r_c^2$ and $r_p^2$ were the highest at 0.8533 and 0.6546; wavelength ranges of 360-380, 546-690, 760, 915, 931-939, 942, 953, 971, 978, 981, 988, and 992-1019 nm were most influential for SSC determination. The PLSR model with the spectral value of the corresponding region confirmed that the RMSEP decreased to 0.6841 and $r_p^2$ increased to 0.7795 as compared to the values of the entire wavelength band. In this study, we confirmed the feasibility of using a hyperspectral scanner image obtained from outdoors for the SSC measurement of apples. These results indicate that the application of field data and sensors could possibly expand in the future.

• Clean Technology
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• v.17 no.3
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• pp.215-224
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• 2011

It is an important issue to develop quality assessing system for biofuel for the purpose of accelerating the mass production of biofuel. It is particularly challenging to conduct testing method in the mass production of bioethanol while meeting quality specifications such as ASTM (American Society for Testing & Materials) D4806-10. In order to address this challenge, this paper proposes on-line spectroscopic quality assesment system based on Near Infrared spectrum and Partial Least Squares method in Chemometrics. As a result of testing a number of preprocessing methods and Partial Least Squares, it was found out that Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed system allows us to assess multiple quality components continuously using spectroscopic facilities with the cheap cost. Since the value of R2 is more than 0.99, it is possible to replace the laboratory analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.871-876
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• 2005

In this paper, we propose an improved partial response maximum likelihood (PRML) detection scheme that has an adaptive equalizer and can be applied in the asymmetric optical recording system with high-density. We confirmed that the proposed PRML detector improves detection performance. In addition, we implemented the detector by Verilog HDL. The adaptive equalizer is composed of tap coefficient updating unit using LMS algorithn and FIR filter. FIR filter is implemented by the transposed direct form architecture for high speed operation. Viterbi detector is implemented by the register exchange method.

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.130-140
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• 1998

This paper presents a method to estimate subpixel accuracy motion vectors using a mathermatical model withoug interpolation. the proposed method decides the coefficients of mathematical model, which represents the motion vector which is achieved by full search. And then the proposed method estimates subpixel accuracy motion vector from achieved mathematical model. Step by step mathematical models such as type 1, type 2, type 3, modified bype 2, modified type 3, and Partial Interpolation type 3 are presented. In type 1, quadratic polynomial, which has 9 unknown coefficients and models the 3by 3 pixel plane, is used to get the subpixel accuracy motion vectors by inverse matrix solution. In type 2 and 3, each quadratic polynomial which is simplified from type 1 has 5 and 6 unknown coefficients and is used by least square solution. Modified type 2 and modified type 3 are enhanced models by weighting only 5 pixels out of 9. P.I. type 3 is more accurate method by partial interpolation around subpixel which isachieved by type 3. LThese simulation results show that the more delicate model has the better performance and modified models which are simplified have excellent performance with reduced computational complexity.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.181-193
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• 2020

The midst competition makes a brand all together with its offering products and services is becoming a crucial element for company existence. This requires direct involvement from internal organizational to develop effective strategic branding. According to Asosiasi Penyelenggara Internet Indonesia (APJII), Indonesia's internet penetration is among the highest in Asia. The purpose of this research is to improve the strategic role of brand orientation within Internet Service Provider (ISP) for maximizing return on the company's financial and non-financial benefits by proposing organization change readiness variable. The data collection is taken using an online survey with a non-parametric sampling method and collected 68 qualified respondents for data analysis using SEM-PLS (Structural Equation Modeling with Partial Least Square). The result indicates partial hypotheses on the constructed model between variables brand orientation, brand commitment, and internal brand equity is acceptable. Another finding is stated hypotheses on organization change readiness as moderation is not accepted and means there is no significance to the constructed model. The main conclusion resumes associative human memory can shape up organization change readiness inside internal toward then brand. Relevant cues generate information received in the human brain then will create common associative and becoming social identity on internal brand equity.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.391-399
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• 2020

This study aims to analyze the relationship of e-HRM implementation to employee performance both directly and indirectly through the intervening of the Human Resource service Quality variable, both practically and theoretically. This study uses variance-based structural equation modeling (SEM) techniques with partial least square (PLS) statistical testing tools to test the direct relationship of e-HRM and the performance and relationship moderated by Human Resources service quality tested on 200 civil servants in five offices under the coordination of the Government of the South Sulawesi Province of Indonesia. The data collection model in this study uses an online survey. The data analysis stages through the explanatory concept consist of, first, the interpretation of the distribution of the average frequency of respondents' answers; second, outer-loading; third, determination of the validity and reliability; fourth, the coefficient of determination test and partial test; fifth, the GoF model; sixth, validity test; and seventh, hypothesis testing. This study explores four hypotheses in a comprehensive fashion; the results of this study show that all hypotheses have positive and significant effects both through direct and intervening relationships. Among the three direct relationships, the relationship of e-HRM variables on HR Service Quality is greatest and most dominant.

• International journal of steel structures
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• v.18 no.5
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• pp.1684-1698
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• 2018

Fragility functions are determined for braced steel moment frames (SMFs) with plans such as square-, T-, L-, U-, trapezoidal-, and semicircular-shaped, subjected to blast. The frames are designed for gravity and seismic loads, but not necessarily for the blast loads. The blast load is computed for a wide range of scenarios involving different parameters, viz. charge weight, standoff distance, and blast location relative to plan of the structure followed by nonlinear dynamic analysis of the frames. The members failing in rotation lead to partial collapse due to plastic mechanism formation. The probabilities of partial collapse of the SMFs, with and without bracing system, due to the blast loading are computed to plot fragility curves. The charge weight and standoff distance are taken as Gaussian random input variables. The extent of propagation of the uncertainties in the input parameters onto the response quantities and fragility of the SMFs is assessed by computing Sobol sensitivity indices. The probabilistic analysis is conducted using Monte Carlo simulations. The frames have least failure probability for blasts occurring in front of their corners or convex face. Further, the unbraced frames are observed to have higher fragility as compared to counterpart braced frames for far-off detonations.