• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1181-1184
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• 2007

The new self-priming addressing driving scheme was proposed to improve an address discharge time lag. It utilizes the priming effect maintaining the priming ramp discharge during an address period and the address discharge time lag is significantly improved. In this study, the basic characteristics of the priming ramp discharge are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.113-117
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• 1989

Generally, stabilization system is surely needed for the compensation of the ship motion. In this paper, the study investigated stabilizer design for the large driving system. We make a performance analysis for the stabilization scheme through the computer simulation.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.5
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• pp.450-454
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• 2003

This paper proposes a new driving scheme for single-phase SRM. The driving scheme is very simple and inexpensive. By use of this scheme, simple power devices based on low switching losses enable to high efficiency SRM drive. Starting, One of the main problem in single-phase SRM is overcame by a new starting algorithm with one hall sensor and a parting magnet. The proposed single phase SRM has a high efficiency and robust drive characteristics compared to that of a universal motor.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.449-451
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• 2002

We reported the algorithm of driving scheme that enhances moving picture property by improving gray-to-gray response time. Here, we report result of simulation for estimation of driving voltage to reduce response time, and experimental result. We investigated optimization of algorithm so that minimum size of LUT can support to reducing the gray-to-gray response time within 1 frame period, and with single algorithm it is possible to apply the algorithm to various kinds of LC material. So in our system there is no external EEPROM.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.802-805
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• 2007

A hardware architecture is presented of a wavelet based multiple line addressing driving scheme for passive matrix displays using the FPGA (Field Programmable Gate Arrays), which will be integrated in the scalable video coding $architecture^{[1]}$. The incoming compressed video data stream will then directly be transformed to the required column voltages by the hardware architecture without the need of employing the video decompression.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1053-1059
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• 2007

This paper presents a target sate estimator(TSE) with low pass filter for improving the gun driving command. The ballistic computer uses target information such as predicted range, velocity, acceleration of a target to generate the gun command. We adopt the finite impulse response(FIR) filter as our TSE to shorten calculation time for the driving command and due to its inherent stability property. We also introduce a post-processing filter to reduce the high frequency components in the output signal of a TSE which may cause instability of gun driving. The first order low pass filter has been designed based on $H{\infty}$ criteria considering the noise characteristics. To show the validity of the present scheme, simulation results are given for the overall gun driving system including aircraft target information.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.55.2-55.2
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• 2017

We study the effect of driving scheme on the density-magnetic field correlation. We numerically investigate how the correlation time of driving affects the correlation between density and magnetic field. We performed MHD turbulence simulation using two different driving schemes - a finite-correlated driving and a delta-correlated driving. In the former, the forcing vectors change continuously with a correlation time comparable to the large-eddy turnover time. In the latter, the direction and amplitude of driving changes in a very short time scale.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.128-135
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• 2005

This paper presents a scheme for experimentally analyzing bounce, roll and pitch frequencies of major systems of a large truck using a multi-axial road simulator. The excitation input (amplitude and frequency range) fur a frequency response test with the multi-axial road simulator is selected in order that bounce, roll and pitch modes are not coupled each other, the excitation amplitude can be reproduced in a specified excitation frequency range, and tires do not lose contact with posters. Three accelerometers, one gyroscope and four displacement meters are used in the frequency response test using the multi-axial road simulator. The reliability of the presented bounce mode frequency response test scheme is validated by comparing the result from a test using the multi-axial road simulator with the result from a road driving test. The road driving test is performed with velocities of 20km/h and 30km/h, and in an unladen state. The vertical accelerations at the cab and the front axle are measured in the road driving test. The roll and pitch mode frequency response tests are also performed with the presented frequency response test scheme. Roll and pitch frequencies of major systems of a large truck that are hard to acquire from a road driving test are analyzed as well as bounce frequency.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.849-854
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• 2007

This paper describes design and tuning of a full-range Adaptive Cruise Control (ACC) with collision avoidance. The control scheme is designed to control the vehicle so that it would feel natural to the human driver and passengers during normal safe driving situations and to avoid rear-end collision in vehicle following situations. In this study, driving situations are determined using a non-dimensional warning index and time-to-collision (TTC). A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC System. An ECU-Brake Hardware-in-the-loop Simulation (HiLS) was developed and used for an evaluation of ACC System. The ECU-Brake HiLS results for alternative driving situation are compared to manual driving data measured on actual traffic way. The ACC/CA control logic implemented in an ECU was tested using the ECU-Brake HiLS in a real vehicle environment.