• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1484-1494
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• 2017

We present a two-stage inverter with high step-up conversion ratio engaging modified finite-set Model Predictive Control (MPC) for utility-integrated photovoltaic (PV) applications. The anticipated arrangement is fit for low power PV uses, the calculated efficiency at 150 W input power and 19 times boosting ratio was around 94%. The suggested high-gain dc-dc converter based on Cockcroft-Walton multiplier constitutes the first-stage of the offered structure, due to its high step-up ability. It can boost the input voltage up to 20 times. The 3S current-source inverter constitutes the second-stage. The 3S current-source inverter hires three semiconductor switches, in which one is functioning at high-frequency and the others are operating at fundamental-frequency. The high-switching pulses are varied in the procedure of unidirectional sine-wave to engender a current coordinated with the utility-voltage. The unidirectional current is shaped into alternating current by the synchronized push-pull configuration. The MPC process are intended to control the scheme and achieve the subsequent tasks, take out the Maximum Power (MP) from the PV, step-up the PV voltage, and introduces low current with low Total Harmonic Distortion (THD) and with unity power factor with the grid voltage.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.645-650
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• 2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFARF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.31-40
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• 2020

This study investigates whether other comprehensive income (OCI) reported in the statement of comprehensive income (one of the main financial statements after the adoption of K-IFRS) predicts a firm's future performance. Using the quarterly data of Korean listed companies, we examine the association between OCI estimates and future earnings. First of all, we find that OCI is positively associated with earnings in both 1- and 2-quarter ahead, supporting the predictive value of OCI. When we break down OCI into its individual components, our results suggest that the net unrealized gains/losses on available-for-sale (AFS) investment securities are positively associated with future earnings, while the other components (e.g., net unrealized gains/losses on valuation of cash flow hedge derivatives) present insignificant results. In addition, we investigate whether the reliability in OCI estimates enhances the predictive value of OCI to predict future performance. We find that the predictive ability of OCI, in particular the net unrealized gains/losses on available-for-sale (AFS) investment securities, becomes more pronounced when firms are audited by the Big 4 audit firms. Overall, our study suggests that information content embedded in OCI can provide decision-useful information that is helpful for the prediction of future firm performance.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.564-567
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• 1991

In this paper a predictive current control strategy is adopted in the D.C motor drive using dual converter. It is a kind of feedforward control working without overshoot within very short settling time. The difference to the well-known PI current control lies in considering the computer's ability of pre-calcurating the converter's behavior. By simulation it is shown that the predictive current control solve the problems of optimal PI current control, such as overshoot and settling time.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.99-104
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• 1991

An adaptive predictive control method for SISO and MIMO plants is proposed. In this method, future predictions of process output based on a bilinear CARIMA model are used to calculate the control input. Also, a classical recursive adaptation algorithm, equation error method, is used to decrease the uncertainty of the process model. As a result of the application on distillation process, the ability of the set-point tracking and the disturbance rejection is acceptable to apply to the industrial distillation processes.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.225-228
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• 1990

The major difficulty in distillation column control lies in executing the set point tracking and the disturbance rejection, because of continuous changes in model order and dead time. For that, generalized predictive control(GPC) was applied to distillation column control. Recursive least square method was used to adjust the changes of model order and dead time. Quadratic progamming(QP) was used to solve the constraint problems in control action and the rate of control action. As a result of the simulation on the dynamic simulator(SPEEDUP) and the experiment on pilot plant, the ability of the set point tracking and the disturbance rejection was acceptable to apply to the real distillation column.

• Journal of Integrative Natural Science
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• v.4 no.4
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• pp.266-272
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• 2011

Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.

• Physical Therapy Rehabilitation Science
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• v.11 no.4
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• pp.535-545
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• 2022

Objective: This study was conducted to identify predictive factors of physical activity in total hip arthroplasty patients, and to provide basic data for the developing physical activity promotion program for total hip arthroplasty patients. Design: Descriptive correlational research. Methods: Data were collected from August 2017 to May 2018. Surveys were distributed to 60 patients in a G university hospital located at J city, Gyeongsangnam-do. Data were analyzed by frequency, mean, standard deviation, t-test, ANOVA, Pearson's correlation coefficient, multiple regression analysis using SPSS 24 Win program. Results: The variables affecting the 4-week physical activity after discharge were age (β=.07), residence after discharge (β=-.22), cerebrovascular disease (β=-.13), mental and behavioural disease (β=-.11), taking antibiotic (β=-.26), walking ability (β=.41), nutritional status (β=.25), depression (β=.05). The eight variables accounted for 39.4% in the 4-week physical activity (F=4.49 p=.001). The variables affecting the 8-week physical activity after discharge were age (β=.06), waking ability (β=.34), nutritional status (β=.20), exercise self-efficacy (β=.05), depression (β=-.05). The six variables accounted for 28.0% in the 8-week physical activity (F=4.58, p<.001). Conclusions: The walking ability in discharge important to improve the physical activity, there is a need to develop an program to improve walking ability before discharge, in total hip arthroplasty. There is a need to develop a physical activity program to consistently participate in a community.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• Journal of the Korean Chemical Society
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• v.44 no.1
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• pp.68-73
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• 2000

In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.