• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.5
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• pp.321-327
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• 2016

This paper presents the application of airfoil impeller for enhancement of aerodynamic performance of a high speed centrifugal fan. Three airfoil impellers are proposed, considering the maximum thickness and the location of maximum thickness of the airfoil. C4 airfoil thickness distribution is applied to the three airfoil impellers. The impellers are evaluated using CFD (computational fluid dynamics) and suction power test. From the results, it is confirmed that flow separations on the pressure side of the impeller blades and the pressure side of diffuser blades are reduced when airfoil blade is applied to the impellers. It is also confirmed that with the centrifugal fan having airfoil impellers, there is an increase in fan efficiency by approximately 3% and reduction in specific sound level by approximately 1.3 dB(A).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.3
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• pp.83-89
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• 2000

In hydraulic control system turbine and gear motor type flowmeters are widely used to measure the flow rate under steady flow conditions. With the recent growth of interest in the measurement of instantaneous values of unsteady flow rate the test of the transient response of these flowmeters are in some significance. however an unsteady flow rate mea-surment and its calibration method with a fast response and a high accuracy have not beendeveloped. In this research particularly the dynamic characteristics of turbine and gear motor type flowmeters are investigated experimentally and simple mathematical models are proposed. The measured flow rate waveforms are compared with those by remote instan-taneous flow rate measurement method(RIFM) which has been developed by author and used for calibration As the result of frequency response test gain and phase between the measured flow rate waveforms by turbine type flowmeter and those estimated by RIFM are in good agreement up to 70Hz For the gear motor type flowmeter th simulated results by a math-ematical model proposed here agree well with the experiment nearly up to 100Hz. Also it if sound that the pressure drop across the flowmeter is increased in proportion to the frequency of the flow rate variation in a high frequency region of more than 100Hz. It can be explained that the dealy of gear motor type flowmeter in high frequency regionis mainly attributed to a first order delay consisting of the inertia of gears and internal leakage of the gear motor.

• The Journal of the Acoustical Society of Korea
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• v.30 no.7
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• pp.402-407
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• 2011

The necessary and sufficient condition for causality of a physical system can be expressed as Kramers-Kr$\ddot{o}$nig (K-K) relation. K-K relation for acoustic wave is a Hilbert transforms pair between dispersion equations of phase speed and attenuation. In this study, we quantitatively compare the acoustic measurements in water-saturated glass beads for the frequency ranges from 400 kHz to 1.1 MHz with the predictions of differential form of K-K relation obtained by Waters et al. For media with attenuation obeying an arbitrary frequency power law, acoustic measurements show good agreements with the predictions of Kramers-Kr$\ddot{o}$nig relation.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.227-234
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• 2020

In this paper, we propose wav-U-Net to improve speech enhancement in heavy noisy environments, and it has implemented three principal techniques. First, as input data, we use 128 modified Mel-scale filter banks which can reduce computational burden instead of 512 frequency bins. Mel-scale aims to mimic the non-linear human ear perception of sound by being more discriminative at lower frequencies and less discriminative at higher frequencies. Therefore, Mel-scale is the suitable feature considering both performance and computing power because our proposed network focuses on speech signals. Second, we add a simple ResNet as pre-processing that helps our proposed network make estimated speech signals clear and suppress high-frequency noises. Finally, the proposed U-Net model shows significant performance regardless of the kinds of noise. Especially, despite using a single channel, we confirmed that it can well deal with non-stationary noises whose frequency properties are dynamically changed, and it is possible to estimate speech signals from noisy speech signals even in extremely noisy environments where noises are much lauder than speech (less than SNR 0dB). The performance on our proposed wav-U-Net was improved by about 200% on SDR and 460% on NSDR compared to the conventional Jansson's wav-U-Net. Also, it was confirmed that the processing time of out wav-U-Net with 128 modified Mel-scale filter banks was about 2.7 times faster than the common wav-U-Net with 512 frequency bins as input values.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.16 no.1
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• pp.28-32
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• 2005

Background and Objectives : The most important two factors of the voice production are the respiratory function which is the power source of voice and the glottic closure that transform the air flow into sound signals. The purpose of this study was to investigate the differences between trained singers and untrained controls under varying intensity at a constant vocal pitch by simulataneous using the airway interruption method and electroglottography(EGG). Materials and Methods : Under two different intensity condition at a constant vocal pitch(/G/), 20(Male 10, Female 10) trained singers were studied. Mean flow rate(MFR), subglottic pressure(Psub) and intensity were measured with aerodynamic test using the Phonatory function analyzer. Closed quotients(CQ), jitter and shimmer were also investigated by electroglottography using Lx speech studio. These data were compared with that of normal controls. Results : MFR and Psub were increased on high intensity condition in all subject groups but there was no statistically significance. Statistically significant increasing of CQ. were observed in male trained singers on high intensity condition (untrained male : 51.31${\pm}$3.70%, trained male :55.52${\pm}$6.07%, p=.039). Shimmer percent, one of the phonatory stability parameters, was also decreased statistically in all subject groups(p<.001). Conclusion : The trained singers' phonation was more efficient than untrained singers. The result means that the trained singers can increase the loudness with little changing of mean flow rate, subglottic pressure but more increasing of glottic closed quotients.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.16 no.1
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• pp.10-14
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• 2005

Background and Objectives : Vowels are characterized on the basis of formant patterns. The first formant(F1) is determined by high-low placement of the tongue, and the second formant (F2) by front-back placement of the tongue. The fundamental frequency(F0) of a soprano often exceed the normal frequency of the first formant. And the vocal intensity is boosted when F0 is high and a harmonic coincides with a formant. This is called a formant tuning. Experienced singers thus learned how to tune their formants over a resonable range by lowering the tongue to maximize their vocal intensity. So, the current study aimed to identify the formant tuning in one experienced soprano by comparing the first formants of vowel [i] in three different voice production : speech, ascending scale, and vocalize. Materials and Method : All voices recordings of vowel [i] in speech, ascending scale (from F4 note to A4 note), and vocalize(:Ridente la calam") were made with digital audio tape-corder in a sound treated room. And the captured data were analyzed by the long term average(LTA) power spectrum using the FFT algorithm of the Computerized Speech Lab(CSL, Kay elementrics, Model, 4300B). Results : Although the first formant of vowel [i] in speech was 238Hz, those of ascending scale [i] were 377Hz, 405Hz, 453Hz respectively in F4(349z), G4(392Hz), A4(440Hz) note, and 722Hz, 820Hz, 918Hz respectively in F5 (698Hz), G5(784Hz), A5(880Hz) note. In vocalize, first formants of [i] were 380Hz, 398Hz, 453Hz respectively in F4, G4, A4 note, and 720Hz, 821Hz, 890Hz respectively in F5, G5, A5 note. Conclusion : These results showed that the first formant of ascending scale and vocalize sustained higher frequency than fundamental frequency in high pitch. This finding implicates that the formant tuning of vowel [i] in ascending scale was also noted in vocalize.

• Journal of Drive and Control
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• v.13 no.3
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• pp.24-31
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• 2016

The performance characteristics of a dynamic control system are evaluated according to the transient and steady-state responses. The transient performance is the controllability of the output for the tracking of the reference or the ability to reduce or reject the effects of unwanted disturbances; alternatively, the steady-state performance is represented by the magnitude of the control error at the steady state. As the effects of the two performances on each other are reciprocal, a controller design that shows a zero steady-state error for the ramp input is uncommon because of the challenge regarding the achievement of an acceptable transient response. This paper proposes a PI+double-integral controller for the elimination of the steady-state error for the ramp input while a sound transient performance is maintained. The control-gain design procedure is described by the second-order response for the step input and the response of the error dynamics for the ramp input. The PI+double-integral controller is designed for the first-order transfer function that is derived from a system identification with the open-loop experiment data of the dc-motor. The simple structure of the proposed controller enables the adoption of a low-end microcontroller for the implementation of a real-time control. The experiment results show that the control performance is as effective as that of the simulation analysis for the operating point of linear system; furthermore, the PI+double-integral controller can be conveniently applied to the control system, which is desirable for the improvement of the steady-state error.

• Journal of Drive and Control
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• v.14 no.2
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• pp.16-22
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• 2017

This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system's complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.