• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.5
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• pp.179-184
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• 2006

In a power system, an out-of-step condition causes a variety of risk such as serious damage to system elements, tripping of loads and generators, mal-operation of relays, etc. Therefore, it is very important to detect the out-of- step condition and take a proper measure. This paper presents a study on implementation of out-of-step detection algorithm using VHDL(Very high speed Hardware Description Language). The structure of out-of-step detection algorithm is analyzed for development of out-of-step detection relay on the FPGA(Field Programmable Gate Array). The out-of-step algorithm is separated to 4 parts: DFT IP, complex power calculation IP, out-of-step detection IP, control unit. Each parts are developed and simulated by using VHDL.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.64-69
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• 2013

In this paper, a high-speed CMOS Image Sensor (CIS) based on a 10-bit two-step single-slope A/D converter is proposed. The A/D converter is composed of both a 5-bit coarse ADC and a 6-bit fine ADC, and the conversion speed is 10 times faster than that of the single-slope A/D converter. In order to have a small noise characteristics, further, a Digital Correlated Double Sampling(D-CDS) is also discussed. The proposed A/D converter has been fabricated with 0.13um 1-poly 4-metal CIS process, and it has a QVGA($320{\times}240$) resolution. The fabricated chip size is $5mm{\times}3mm$, and the power consumption is about 35mW at 3.3V supply voltage. The measured conversion speed is 10us, and the frame rate is 220 frames/s.

• Korean Journal of Applied Biomechanics
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• v.26 no.4
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• pp.333-341
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• 2016

Objective: The purpose of this study was to assess the consistency of the gliding and push-off motion for single leg skating from the first to fourteenth steps. We hypothesized that: 1) there would be no difference in stroke trajectory, step rate, and cycle rate between the left and right steps of gliding; and 2) there would be a difference in the resultant velocity of toe push-off and the horizontal velocity of the center of mass after six step push-offs. Method: The study included five male 500-m speed skaters (mean height, $1.80{\pm}0.02m$; mean weight, $76.8{\pm}3.96kg$; record, $35.83{\pm}0.30sec$; 100-m record, <9.97 sec). Data were collected from the first to fourteenth steps (40 m) and recorded using five digital JVC GR-HD1KR video cameras (Victor Co., Japan) operating at a sampling frequency of 60 fields/sec and shutter speed of 1/500 sec. For each film frame, the joint positions were digitized using the KWON3D motion analyzer. Position data were filtered with low-pass Butterworth $4^{th}$ order at the cut-off frequency of 7.4 Hz. Results: The right toe of the skating trajectories at $2^{nd}$, $5^{th}$, and $7^{th}$ strokes differed from those of the left toe. The angles of the right and left knee demonstrated unbalanced patterns from the flexion and extension legs. The step and cycle rates of the right and left leg differed from the start until 20 m. The resultant velocities of the toe at the push-off phase and of the body mass center diverged before the six push-offs. Conclusion: This study's findings indicate that the toe of skating trajectory on left and right sliding after push-off should maintain a symmetrical trajectory. The resultant velocity of toe push-off and horizontal velocity from the center of body need to be separated after about six step push-offs.

• Phonetics and Speech Sciences
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• v.13 no.4
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• pp.47-53
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• 2021

Autoregressive Text-to-Speech (TTS) models suffer from inference instability and slow inference speed. Inference instability occurs when a poorly predicted sample at time step t affects all the subsequent predictions. Slow inference speed arises from a model structure that forces the predicted samples from time steps 1 to t-1 to predict the sample at time step t. In this study, an end-to-end non-autoregressive fast text-to-speech model is suggested as a solution to these problems. The results of this study show that this model's Mean Opinion Score (MOS) is close to that of Tacotron 2 - WaveNet, while this model's inference speed and stability are higher than those of Tacotron 2 - WaveNet. Further, this study aims to offer insight into the improvement of non-autoregressive models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.1006-1009
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• 2000

In this study, a multi-step optimization technique combined with a simple genetic algorithm is introduced in order to minimize the static compliance, the dynamic compliance, and the weight of a high speed machining center simultaneously. Dimensional thicknesses of the eight structural members on the static force loop are adopted as design variables. The first optimization step is a static design optimization, in which the static compliance and the weight are minimized under some dimensional and safety constraints. The second step is a dynamic design optimization, where the dynamic compliance and the weight are minimized under the same constraints. After optimization, the weight of the moving body only was reduced to 57.75% and the weight of the whole machining center was reduced to 46.2% of the initial design respectively. Both static and dynamic compliances of the optimum design are also in the feasible range even though they were slightly increased than before.

• Journal of computational fluids engineering
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• v.1 no.1
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• pp.26-34
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• 1996

The performance of the SIMPLE, SIMPLE-C and PISO algorithms for the treatment of the pressure-velocity coupling in fluid flow problems were examined by comparing the computational effort required to obtain the same level of the convergence. Example problems are circular duct and 90-degree bent square-duct. For circular duct case, laminar and turbulent flow were computed. For 90-degree bent square-duct case, laminar flow was simulated by the time-marching method as well as the iterative method. The convergence speed of the other two algorithms are not always superior to SIMPLE algorithm. SIMPLE algorithm is faster than SIMPLE-C algorithm in the simple laminar flow calculations. The application of the PISO algorithm in three dimensional general coordinates is not so effective as in two-dimensional ones. Since computational time of PISO algorithm is increased at each time step(or iterative step) in three dimension, the total convergence speed is not decreased. But PISO algorithm is stable for large time step by using time marching method,.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.229-231
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• 1994

In recent years, as the industry has been highly developed and precised, its driving and control system have been changed, what is more, revolutionized. The requirements of these change are more accuracy, more high efficiency, more miniaturized size and more servo functions. Step motor has been adopted for driving servo systems, because of easier controllability, open-loop control, high position accuracy at low speed. In this paper, we deal with developing step motor system, and describe the procedure that contains design, analysis. testing characteristics.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.32-38
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• 2000

One of the most popular algorithm in adaptive signal processing is the least mean square(LMS) algorithm. The majority of these papers examine the LMS algorithm with a constant step size. The choice of the step size reflects a tradeoff between misadjustment and the speed of adaptation. Subsequent works have discussed the issue of optimization of the step size or methods of varying the step size to improve performance. However there is as yet no detailed analysis of a variable step size algorithm that is capable of giving both the adaptation speed and the convergence. In this paper we propose a new variable step size algorithm where the step size adjustment is controlled by the gradient of error square. The proposed algorithm is performed in the Walsh-Hadamard domain in real-valued orthogonal transform because of fast convergence. The simulation results using the new algorithm for noise canceller system is described. They are compared to the results obtained by other algorithms. It is shown that the proposed algorithm produces good results compared with conventional algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1732-1735
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• 2003

In this paper, a DSP-based test apparatus for Control Rod Drive Mechanism (CRDM) that is used in nuclear power plants is described. Using this apparatus, we can test the mechanical and electrical characteristics of CRDM and obtain some information about how to improve the CRDM further and how to design a power controller to actuate the CRDM. Since firing angles can be directly applied to the gate-drive circuits of thyristors in the power controller by using this apparatus, the maximum and minimum values of firing angles within available limits are easily measured. Also step-current inputs help us investigate each coil's response characteristics. Therefore, we can easily find the range of control gains which enables a stable CRDM operation in insertion and withdrawal actions at high speed, mid speed, and low speed. Since this apparatus has a test mode in which an insertion or withdrawal action is divided into several phases so that the current command for each phase is given step by step, we may judge whether the CRDM works as expected or not. We also describe a fault detection capability of the test apparatus for the power controller by using discrete Fourier transform.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.97-105
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• 2022

Human casualties from fires are increasing worldwide. The majority of human deaths occur during the evacuation process, as occupants panic and are unaware of the location of the fire and evacuation routes. Using an Internet of Things (IoT) sensor and reinforcement learning, we propose a method to find the safest evacuation route by considering the fire location, flame speed, occupant position, and walking conditions. The first step is detecting the fire with IoT-based devices. The second step is identifying the occupant's position via a beacon connected to the occupant's mobile phone. In the third step, the collected information, flame speed, and walking conditions are input into the reinforcement learning model to derive the optimal evacuation route. This study makes it possible to provide the safest evacuation route for individual occupants in real time. This study is expected to reduce human casualties caused by fires.