• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.13 no.1
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• pp.52-58
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• 2002

The pitch range of the human voice is variable, extending from chest register to falsetto. Although numerous studies have investigated after laryngeal mechanism description of registers, systematic and objective studies were lack. The purpose of this study was to analyze and compare head register with chest register of singers acoustically. Fifteen healthy tenor major students were selected. Fifteen healthy untrained adults were the control group for this study. Long term average(LTA) power spectrum using the Fast Fourier transform(FFT) algorithm and Linear predictive coding (LPC) filter response were made during /a/ sustained in both head(G4, 392Hz) md chest registers (C3, 131Hz). Statistical analysis was performed using Mann-Whitney test. In the LTA power spectrum, head register of singer has increased level(energy gain) in the frequency band of 2.2-3.4kHz(p<0.01), and 7.5-8.4kHz(p<0.01, p<0.05). Chest register of singer has increased level in the frequency band of 2.2-3.1kHz(p<0.01), 7.8-8.4kHz(p<0.05) and around 9.6kHz(p<0.01). LTA power spectrum reveals a peak of acoustic energy around 2500Hz known as the singer's formant and another peak of acoustic energy around 8000Hz in singer's voice.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1840-1846
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• 2005

In this paper, does by purpose DC servo motor speed controller design about PID coefficient tuning techniques that use genetic algerian. DC servo motor is used in application field of a peat many control machine or robot etc. and in this field, selection of controller parameters requires user's expert knowledge. Therefore, general amount of work engineers must continuously iteration tuning in controller parameters by trial and error. With this, when must tuning parameter coefficient about change of dynamic system or disturbance, can improve the efficiency according to following that is more precised and parameter coefficient value that is optimized by using genetic algorithm. In this paper, from dynamic character modeling get in analyze dynamic character of DC motor desist controller drive control possible that is fast response character md improved speed precision using a Genetic Algorithms.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.2
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• pp.124-129
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• 2005

This paper presents an advanced method for an initial pole position estimation of a Permanent Magnet Linear Synchronous Motor(PMLSM) that has an accurate incremental encoder for servo applications but does not have Hall sensors as a magnetic pole sensor. By appropriately using the secant method as a numerical method the proposed algorithm finds either of two zero force positions and then the correct d-axis by applying a q-axis test current. It only requires the tuned current controller and the relative position information md so it can be simply applicable to a rotary PMSM. The experimental results show the validity of the proposed method, which has an excellent performance with respect to an accurate pole position estimation under the minimal moving distance(average of about 85㎛) during the estimation process.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1009-1017
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• 2011

A Ballistic Missile(BM) is a missile that follows a sub-orbital ballistic flightpath with the objective of delivering one or more wardheads to a predetermined target and An Anti-Ballistic Missile(ABM) is a missile designed to destroy a ballistic missile before reaching its target. The main objective of this study is to assess the requirement of ABM by considering both flight characteristic of the SCUD-B/C, Nodong missiles and intercept performance of ABM in the Lower tier Ballistic Missile Defense(BMD). The Ballistic Missile's flight characteristics, such as trajectory, velocity etc., are estimated by simulation using the physical motion equations. The requirement of ABM is calculated by evaluating whether the BMD forces can defend those when the ballistic missiles attack prime facilities.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.3
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• pp.258-266
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• 2007

When the magnetic levitation system(MAGLEV) initially rise, The MAGLEV has a weak point that is very large variation of the electric current. In this paper, The author applied the multi-loop-control to stably control the magnetic levitation system(MAGLEV). The gains of the control algorithm were selected based on pole locations formulated from a prototype Bessel transfer function model. The design incorporate tradeoffs in DC-to-DC converter hard-ware para-meters and pole locations. In order to confirm the superiority of the proposed pole selection md controller, MATLAB simulation and experiment results are presented.

• Wind and Structures
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• v.29 no.1
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• pp.65-75
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• 2019

A heated square cylinder (with height $A^*$) is kept parallel to the cold wall at a fixed gap height $0.5A^*$ from the wall. Another adiabatic rectangular cylinder (of same height $A^*$ and width $0.5A^*$) is placed upstream in an inline tandem arrangement. The spacing between the two cylinders is fixed at $3.0A^*$. The inlet flow is taken as Couette-Poiseuille flow based non-linear velocity profile. The conventional fluid (also known as base fluid) is chosen as water (W) whereas the nanoparticle material is selected as $Al_2O_3$. Numerical simulations are performed by using SIMPLE algorithm based Finite Volume approach with staggered grid arrangement. The dependencies of hydrodynamic and heat transfer characteristics of the cylinder on non-dimensional parameters governing the nanofluids and the fluid flow are explored here. A critical discussion is made on the mechanism of improvement/reduction (due to the presence of the upstream cylinder) of heat transfer and drag coefficient, in comparison to those of an isolated cylinder. It is observed that the heat transfer increases with the increase in the non-linearity in the incident velocity profile at the inlet. For the present range studied, particle concentration has a negligible effect on heat transfer.

• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.174-184
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• 2019

In this study, we present a new scheme for smart education utilizing the concept of a blockchain for question sharing. A two-phase encryption technique for encrypting question papers (QSPs) is proposed. In the first phase, QSPs are encrypted using a timestamp, and in the second phase, previously encrypted QSPs are encrypted again using a timestamp, salt hash, and hash from the previous QSPs. These encrypted QSPs are stored in a blockchain along with a smart contract that helps the user to unlock the selected QSP. An algorithm is also proposed for selecting a QSP for the exam that randomly picks a QSP. Moreover, a timestamp-based lock is imposed on the scheme so that no one can decrypt the QSP before the allowed time. Security analysis is conducted to demonstrate the feasibility of the proposed scheme against different attacks. Finally, the effectiveness of the proposed scheme is demonstrated through implementation, and the superiority of the proposed scheme over existing schemes is proven through a comparative study based on different features.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.1-10
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• 2021

Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject's facial skin. The proposed method is applied in two regions of the subject's face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.165-175
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• 2015

Energy storage system has been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply. This paper presents a model predictive algorithm to control a bidirectional AC-DC converter, which is used in an energy storage system for power transferring between the three-phase AC voltage supply and energy storage devices. This model predictive control (MPC) algorithm utilizes the discrete behavior of the converter and predicts the future variables of the system by defining cost functions for all possible switching states. Subsequently, the switching state that corresponds to the minimum cost function is selected for the next sampling period for firing the switches of the AC-DC converter. The proposed model predictive control scheme of the AC-DC converter allows bidirectional power flow with instantaneous mode change capability and fast dynamic response. The performance of the MPC controlled bidirectional AC-DC converter is simulated with MATLAB/Simulink(R) and further verified with 3.0kW experimental prototypes. Both the simulation and experimental results show that, the AC-DC converter is operated with unity power factor, acceptable THD (3.3% during rectifier mode and 3.5% during inverter mode) level of AC current and very low DC voltage ripple. Moreover, an efficiency comparison is performed between the proposed MPC and conventional VOC-based PWM controller of the bidirectional AC-DC converter which ensures the effectiveness of MPC controller.