• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.369-370
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• 2017

In this paper, a model predictive voltage control (MPVC) for the DC-DC buck-boost converters is proposed. It provides a fast seamless bidirectional control method to maintain the DC grid voltage, battery voltage and current within predefined limits. In addition, an inner current control loop is not employed, so that the bandwidth of controller can be higher compared with the PI controller.

• Journal of the Korean Society for information Management
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• v.33 no.4
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• pp.125-157
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• 2016

As the domestic companies which have made inroads into foreign markets have more lawsuits, these companies' demands for responding to E-Discovery are also increasing. E-Discovery, derived from Anglo-American law, is the system to find electronic evidences related to lawsuits among scattered electronic data within limited time, to review them as evidences, and to submit them. It is not difficult to find, select, review, and submit evidences within limited time given the reality that the domestic companies do not manage their records even though lots of electronic records are produced everyday. To reduce items to be reviewed and proceed the process efficiently is one of the most important tasks to win a lawsuit. The Predictive Coding is a computer assisted review instrument used in reviewing process of E-Discovery, which is to help companies review their own electronic data using mechanical learning. Predictive Coding is more efficient than the previous computer assister review tools and has a merit to select electronic data related to lawsuit. Through companies' selection of efficient computer assisted review instrument and continuous records management, it is expected that time and cost for reviewing will be saved. Therefore, in for companies to respond to E-Discovery, it is required to seek the most effective method through introduction of the professional Predictive Coding solution and Business records management with consideration of time and cost.

• Journal of Korean Academy of Nursing
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• v.33 no.2
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• pp.162-169
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• 2003

Purpose: This study was to compare the predictive validity of Norton Scale(1962), Cubbin & Jackson Scale(1991), and Song & Choi Scale(1991). Method: Data were collected three times per week from 48~72hours after admission based on the four pressure sore risk assessment scales and a skin assessment tool for pressure sore on 112 intensive care unit(ICU) patients in a educational hospital Ulsan during Dec, 11, 2000 to Feb, 10, 2001. Four indices of validity and area under the curve(AUC) of receiver operating characteristic(ROC) were calculated. Result: Based on the cut off point presented by the developer, sensitivity, specificity, positive predictive value, negative predictive value were as follows : Norton Scale : 97%, 18%, 35%, 93% respectively; Cubbin & Jackson Scale : 89%, 61%, 51%, 92%, respectively; and Song & Choi Scale : 100%, 18%, 36%, 100% respectively. Area under the curves(AUC) of receiver operating characteristic(ROC) were Norton Scale .737, Cubbin & Jackson Scale .826, Song & Choi Scale .683. Conclusion: The Cubbin & Jackson Scale was found to be the most valid pressure sore risk assessment tool. Further studies on patients with chronic conditions may be helpful to validate this finding.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1398-1408
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• 2018

In order to further improve the steady-state control performance of model predictive torque control (MPTC), a double-vector-based model predictive torque control without a weighting factor is proposed in this paper. The extended voltage vectors synthesized by two basic voltage vectors are used to increase the number of feasible voltage vectors. Therefore, the control precision of the torque and the stator flux along with the steady-state performance can be improved. To avoid testing all of the feasible voltage vectors, the solution of deadbeat torque control is calculated to predict the reference voltage vector. Thus, the candidate voltage vectors, which need to be evaluated by a cost function, can be reduced based on the sector position of the predicted reference voltage vector. Furthermore, a cost function, which only includes a reference voltage tracking error, is designed to eliminate the weighting factor. Moreover, two voltage vectors are applied during one control period, and their durations are calculated based on the principle of reference voltage tracking error minimization. Finally, the proposed method is tested by simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.562-567
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• 2002

Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• Clinics in Shoulder and Elbow
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• v.4 no.1
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• pp.13-16
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• 2001

Object: To determine the sensitivity, specificity, and positive and negative predictive values of an empty can test for diagnosing supraspinatus tendon tear. Methods: We reviewed 146 patients who have shoulder pain with limited active range of motion. We evaluated patients according to empty can test. Sensitivity, specificity, and positive and negative predictive values for supraspinatus test was estimated using arthroscopic evaluation. Results: A hundred and twenty-four of 127 cases with positive empty can test had supraspinatus tendon tear. Of 19 samples with negative empty can test, 15 had no supraspinatus tear. Sensitivity, specificity, and positive and negative predictive values for the empty can test were 97.6%, 83.3%, 97.6%, and 78.9%, respectively. Conclusions: Empty can test was found to have a high sensitivity and good positive predictive value in identifying the tear of rotator cuff tendon. We concluded that empty can test of the shoulder is a reliable diagnostic method which could be used for the diagnosis of rotator cuff tear.

• Journal of Sasang Constitutional Medicine
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• v.32 no.2
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• pp.10-21
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• 2020

Objectives Genome-wide association studies(GWAS) is a useful method to identify genetic associations for various phenotypes. The purpose of this study was to develop predictive models for Sasang constitution types using genetic factors. Methods The genotypes of the 1,999 subjects was performed using Axiom Precision Medicine Research Array (PMRA) by Life Technologies. All participants were prescribed Sasang Constitution-specific herbal remedies for the treatment, and showed improvement of original symptoms as confirmed by Korean medicine doctor. The genotypes were imputed by using the IMPUTE program. Association analysis was conducted using a logistic regression model to discover Single Nucleotide Polymorphism (SNP), adjusting for age, sex, and BMI. Results & Conclusions We developed models to predict Korean medicine constitution types using identified genectic factors and sex, age, BMI using Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN). Each maximum Area Under the Curve (AUC) of Teaeum, Soeum, Soyang is 0.894, 0.868, 0.767, respectively. Each AUC of the models increased by 6~17% more than that of models except for genetic factors. By developing the predictive models, we confirmed usefulness of genetic factors related with types. It demonstrates a mechanism for more accurate prediction through genetic factors related with type.

• Journal of Power Electronics
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• v.15 no.1
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• Smart Structures and Systems
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• v.31 no.1
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• pp.69-78
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• 2023

The purpose of this paper is to develop a scalable grey predictive controller with unavoidable random delays. Grey prediction is proposed to solve problems caused by incorrect parameter selection and to eliminate the effects of dynamic coupling between degrees of freedom (DOFs) in nonlinear systems. To address the stability problem, this study develops an improved gray-predictive adaptive fuzzy controller, which can not only solve the implementation problem by determining the stability of the system, but also apply the Linear Matrix Inequality (LMI) law to calculate Fuzzy change parameters. Fuzzy logic controllers manipulate robotic systems to improve their control performance. The stability is proved using Lyapunov stability theorem. In this article, the authors compare different controllers and the proposed predictive controller can significantly reduce the vibration of offshore platforms while keeping the required control force within an ideal small range. This paper presents a robust fuzzy control design that uses a model-based approach to overcome the effects of modeling errors. To guarantee the asymptotic stability of large nonlinear systems with multiple lags, the stability criterion is derived from the direct Lyapunov method. Based on this criterion and a distributed control system, a set of model-based fuzzy controllers is synthesized to stabilize large-scale nonlinear systems with multiple delays.