• 전기학회논문지
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• 제62권1호
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• pp.83-89
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• 2013

In order to reduce the power consumption in international standard IEC62087, the luminance efficiency should be improved at the low discharge load rather than at the high discharge load. Thus, this paper analysed the characteristics of the discharge at the panels with ITO Gap of $65{\mu}m$, $80{\mu}m$, and $100{\mu}m$ in 50-inch PDP with FHD resolution. It was well known that the long gap panel improves the luminance and the luminous efficiency. However, it is very difficult to drive the panel due to high driving voltage. When the normal driving method was applied at the panel with ITO gap of $100{\mu}m$, the phenomenon of the double peak was generated in the sustain period. We confirmed that main factor of the double peak is the self-erasing discharge. When the CLHS driving method was applied at the panel with ITO gap of $100{\mu}m$, the self-erasing discharge was improved in the sustain period. Also, the $V_S$ and $V_A$ minimum voltage of the CLHS driving method decreased about 9V and 12V compared with those of the normal driving method. Moreover, when the CLHS driving method was applied to the panel with ITO gap of $100{\mu}m$, the luminance and the luminous efficiency increased compared with those of the normal driving method. The luminance and the luminous efficiency greatly increased at the low discharge load. The less discharge load, the higher increase rate of the luminance and the luminous efficiency. Especially, the luminous efficiency at ITO gap of $100{\mu}m$ increased about 26.3% at the discharge load of 4% compared with that at ITO gap of $65{\mu}m$.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2004년도 Asia Display / IMID 04
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• pp.251-254
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• 2004

We developed a novel Fame interpolation method to interpolate a frame between two successive original frames. Using this method, we are able to apply a double-rate driving method instead of an impulse driving method where a black Fame is inserted between two successive original Fames. The double-rate driving method enables improvement to the motion blur of LCDs caused by the characteristics of human vision without reducing the luminosity of the whole screen. Here, we report on the initial model of our frame interpolation method.

• 한국자동차공학회논문집
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• 제9권5호
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• pp.115-121
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• 2001

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.

• 대한인간공학회지
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• 제29권5호
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• pp.735-739
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• 2010

Driving workload is increasing according to developing new in-vehicle devices and introducing driving information systems. In this research using a driving simulator, EFRP (Eye Fixation Related Potential) was measured for evaluating driving attention and distraction while tasking cognitive workload, n-back tasks. The result of EFRP was compared with driver behaviors. Results suggest that EFRP is able to use for a method of evaluating driving workload, however, the analysis of driver behavior is difficult to find driving attention and distraction in the case of free flow of traffic situation.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.470-473
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• 2009

We have developed a novel driving method, Six times Rate Driving(SRD) for the purpose of making cost competitive TFT-LCD. By applying SRD method to an a-Si TFT-LCD, the driving rate was increased six times as it was named but the number of data lines and so its D-Ics were reduced to one sixth of the conventional one which resulted in the cost saving of that much. We also newly designed the gate driver in order to avoid any expansion of the bezel width caused by applying SRD. Our newly developed driving technology, SRD was successfully applied to 7.0-inch WSVGA (1024 ${\times}$ 600) TFT-LCD which can be driven with only one data D-IC and here introduced.

• 한국정밀공학회지
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• 제13권7호
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• pp.115-121
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• 1996

Multi-axes driving system is more suitable for FMS(Flexible Manufacturing System) compared with a conventional single-azis driving system. It has some merits such as flexibility in operation, improvement of net working rate, maintenance free because of no gear train, etc. However, studies on position synchronous control for high precision in the multi-axes driving system are not enough. In this paper, a new method of position synchronous control is suggested in order to apply to the multi- axes driving system. The proposed method is structured very simply using speed and position controller based on PID control law. Especially, the position controller is designed to keep position error to minimize by controlling either speed of two motors. The effectiveness of the proposed method is successfully confirmed through several experiments.

• 한국산학기술학회논문지
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• 제9권1호
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• pp.35-40
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• 2008

본 논문에서 대전입자형 디스플레이 패널의 기본적인 구동방식 및 각각의 셀의 선택적 구동방식에 관하여 기술하였다. 패널을 제작하기 위해 $500{\mu}m{\times}500{\mu}m$의 셀면적을 가지고 있는 마스크패턴을 설계하였으며 기본적인 구동조건을 바탕으로 셀갭의 변화에 따른 구동전압의 변화를 관찰하였다. 수동메트릭스 방식으로 구동되는 패널의 각각의 셀을 선택적으로 구동하기 위해 선택된 셀과 선택되지 않은 셀의 전위차 상관관계를 확립하여 패널의 선택적인 구동을 수행하였으며 구동이 완료된 패널의 crosstalk현상을 관찰하였다. 또한 추가적인 전압을 인가하지 않아도 마지막 이미지가 오랜 시간 동안 유지되는 패널의 메모리 효과를 확인하였다.

• 대한임베디드공학회논문지
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• 제15권3호
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• pp.119-127
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• 2020

The detection and recognition of abnormal driving becomes crucial for achieving safety in Intelligent Transportation Systems (ITS). This paper presents a feature extraction method based on spectral data to train a neural network model for driving behavior recognition. The proposed method uses a two stage signal processing approach to derive time-saving and efficient feature vectors. For the first stage, the feature vector set is obtained by calculating variances from each frequency bin containing the power spectrum data. The feature set is further reduced in the second stage where an intersection method is used to select more significant features that are finally applied for training a neural network model. A stream of live signals are fed to the trained model which recognizes the abnormal driving behaviors. The driving behaviors considered in this study are weaving, sudden braking and normal driving. The effectiveness of the proposed method is demonstrated by comparing with existing methods, which are Particle Swarm Optimization (PSO) and Convolution Neural Network (CNN). The experiments show that the proposed approach achieves satisfactory results with less computational complexity.

• 한국정보기술학회 영문논문지
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• 제8권2호
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• pp.139-145
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• 2018

Improvement of the speed of the gantry among equipment that mounts a chip using SMT can improve productivity. In order to improve the performance of the gantry, there are studies such as a method of increasing the speed of adsorption, the speed of the gantry by reducing the weight, and a method of facilitating the use of the gantry. But all of these are ways of improving equipment. In this paper, we propose a method to improve the speed of gantry mounting microchip. The method is to shorten the driving time of the gantry. To do this, calculate the driving time using the existing method. And we calculate the travel time using the method presented in this paper. As a result, the time calculated by the proposed method is reduced by 14%.

• ETRI Journal
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• 제43권4호
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.