• MALSORI
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• no.60
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• pp.13-28
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• 2006

This study focused on comparing the following acoustic changes according to age and sex in adulthood: Fo, Jitter, Shimmer, and NHR. One hundred twenty Korean adults were divided into three age groups (20's, 50's, and 70's) and two sex groups (male and female). The subjects of this study performed three tasks: (1) sustained three vowels; (2) read on paragraph of 'Taking a Walk' (3) explained a picture. The data was analyzed using the MDVP of Multi-Speech. In the parameter of Fo, sex and age were influential factors. In the parameters of Jitter, Shimmer and NHR, the effect of sex and age was different in all three parameters. When the groups organized by sex were analyzed by age, the 20's group showed a statistical difference in all four parameters (Fo, Jitter, Shimmer, and NKR), when compared to the other two age ranges of 50's and 70's. We need to consider our standard parameter for the normal voice in the Korean elderly because the 50's and 70's age normal groups in our study are out of the current range of normal in MDVP.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.59-67
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• 2019

Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.137-143
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• 2019

As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.19-23
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• 2000

In this paper, we deal with the problem of designing guaranteed cost state feedback controller for the generalized time-varying delay systems with delayed state and control input. The generalized time delay system problems solved on the basis of LMI(linear matrix inequality) technique considering time-varying delays. The sufficient condition for the existence of controller and guaranteed cost state feedback controller design methods are presented. Also, using some changes of variables and Schur complements, the obtained sufficient condition can be reformulated as LMI forms in terms of transformed variables. Therefore, all solutions of LMIs, guaranteed cost controller gain, and guaranteed cost are obtained at the same time. The proposed controller design method can be extended into the problem of robust guaranteed cost controller design method for parameter uncertain systems with time-varying delays easily.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1371-1376
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• 2003

In the thermal power plant, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the 2-DOF PID Controller on the DCS for steam temperature control using immune based multiobjective approach. The stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Therefore tuning technique of multiobjective based on immune network algorithms in this paper can be used effectively in tuning 2-DOF PID controllers.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.514-518
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• 2003

In this paper, we investigate three dimensional optimal evasive maneuver patterns for air-to-surface attack missiles against proportionally navigated anti-air defense missiles. Interception error of the defense missile can be generated by evasive maneuver of the attack missile during the time of flight for which the defense missile intercepts the attack missile. Time varying weighted sum of the inverse of these interception errors forms a performance index to be minimized. Direct parameter optimization technique using CFSQP is adopted to get the attack missile's optimal evasive maneuver patterns according to parameter changes of both the attack missile and the defense missile such as maneuver limit and time constant of autopilot approximated by the 1st order lag system. The overall shape of resultant optimal evasive maneuver to enhance the survivability of air-to-surface missiles against proportionally navigated anti-air missiles is a kind of deformed barrel roll.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.325-335
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to to changes in the noise factors that represent the source of variation. In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was suggested by Welch et. al. (1990) and studied by others. In these studies, only single response variable was considered. We propose how to simultaneously optimize multiple responses when we use the combined array approach.

• Journal of ILASS-Korea
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• v.1 no.2
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• pp.57-65
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• 1996

Breakup models are evaluated using the experimental drop trajectory ill this study. The experimental conditions corespond to Weber # 56, 260, 463. Computations are carried out using a modified KIVA-II program with 2 different breakup submodel(TAB and Wave breakup model) and dynamic drag model which the drag coefficient changes dynamically with distortion parameter. Results show that computation with wave breakup model represents the experimental drop trajectory better than that with TAB submodel. And result with wave breakup model shows similar breakup pattern to experimental breakup process. It is thought that in wave breakup model the small drops are shed from the parent drop throughout parcel lifetime such thai this modelling represents the real breakup process well.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.17-26
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• 2005

In this paper we propose three nonparametric tests such as Wilcoxon test, Median test and Van der Waerden test, based on linear rank statistics for detecting edges in images. The methods used herein are based on detecting changes in gray-levels obtained using an edge-height parameter between two sub-regions in a 5$\times$5 window We compare and analysis the performance of three statistical edge detectors in terms of qualitative measures with the edge maps and objective, quantitative measures.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.1
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• pp.169-175
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• 2006

This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.