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A Study on the Gamut Mapping Method of the Wide Gamut Display Device (광 색역 디스플레이 장치의 색역 사상에 관한 연구)

  • Um Jinsub;Shin Yoonchol;Kim Moonchol
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.2 s.302
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    • pp.69-80
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    • 2005
  • In these days, the technology development of the imaging/optic industry and the digital broadcasting replace the classic CRT with the new display devices that is getting slimmer and larger. Especially, when the general TV signal is applied directly to the wide gamut display using LED or laser, which can display higher chromatic colors that can't be reproduced on CRT, the color distortion occurs and it causes serious problems. Thus, in this paper the gamut mapping is studied, which gets rids of the color distortion and utilizes the wider color gamut than that of the CRT sufficiently. In the gamut mapping the general mapping concept is the increasement of the chroma on the same hue plane but it causes the over chromatic enhancement. So, the vector mapping, which increases the lightness md the chroma at the same time, is proposed to prevent the side effect. In the vector mapping the chromaticity is maintained constantly, hence the image can be seen more natural than that of the chroma mapping. By using the gamut fitting, it is compensated that the tone disappearance or the contour effect that is arose from the geometric properties of the input and the output color gamut. These gamut mapping and gamut fitting can prevent the color distortion and reproduce the natural image on the wide gamut displays.

Experimental Study of the Effect of Shortening of Life of Tapered Roller Bearings when Subjected to Excessive Axial Pre-Load (과다 예압을 받는 테이퍼롤러 베어링의 수명단축효과에 대한 실험적 연구)

  • Park, Jong-Won;Kim, Hyoung-Eui;Kim, Jong-Ock;Sim, Yang-Jin;Jung, Won-Wook
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.9
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    • pp.1161-1166
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    • 2010
  • Tapered roller bearings are core components of rotating machine parts and are simultaneously subjected to axial and radial loads. Life-shortening effect was particularly evident in the case of tapered roller bearings used in the input and output shafts of transmission; this shortening of life was a result of excessive axial pre-load, which is common in the transmission assembly line. In this study, we derived an equation for evaluating the life of tapered roller bearings subjected to excessive pre-load by using accelerated life test data. The DOE(Design Of Experiment) method and FEA(Finite Element Analysis) was used for determining the condition for performing an accelerated life test. This equation for evaluating the service life of the bearings was derived by analyzing the Weibull distribution of the test results. Using the derived equation the life evaluated was 6-7 times longer than that evaluated by the conventional L10 bearing-life equation. The results of this study will be helpful in predicting the life of tapered roller bearings subjected to excessive pre-load and in designing reliable rotating machines.

Durability Evaluation on the Air-Braking Release Failure Proof Valve of Cargo Train (화물열차 공기제동 완해불량 방지 밸브의 내구성 평가)

  • Lee, Jun-Ku;Kim, Chul-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.9
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    • pp.32-38
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    • 2020
  • Cargo train braking uses the pressure changes in the air braking pipe to operate the braking tightening and releasing service repeatedly. Air-braking release failure means partial braking caused by a failure of the variable load valve after the driver handling the brake release. This phenomenon causes wheel flaws while driving a wagon, resulting in wheel breakage or train derailment. This study developed the air-braking release failure proof valve considering the technical requirements of the railway operation corporations. In addition, a durability test of the valve was carried out using a braking performance simulator, and its operating performance was evaluated from the pneumatic history under cyclic braking conditions. The warranty life of this valve was assessed by performing 160,000 cycles of testing of 12 prototypes in accordance with the zero-failure test method, considering the number of braking cycles while driving the wagon. During the durability test, the pneumatic input time, output time, and release velocity were almost constant. The warranty life of this valve was 59,860 times the 95% confidence level, which means that it can be operated without trouble for four years when the valve is installed in the bogie of the wagon.

Genetic Programming based Manufacutring Big Data Analytics (유전 프로그래밍을 활용한 제조 빅데이터 분석 방법 연구)

  • Oh, Sanghoun;Ahn, Chang Wook
    • Smart Media Journal
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    • v.9 no.3
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    • pp.31-40
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    • 2020
  • Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

Application of neural network for airship take-off and landing mode by buoyancy control (기낭 부력 제어에 의한 비행선 이착륙의 인공신경망 적용)

  • Chang, Yong-Jin;Woo, Gui-Ae;Kim, Jong-Kwon;Lee, Dae-Woo;Cho, Kyeum-Rae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.2
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    • pp.84-91
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    • 2005
  • For long time, the takeoff and landing control of airship was worked by human handling. With the development of the autonomous control system, the exact controls during the takeoff and landing were required and lots of methods and algorithms were suggested. This paper presents the result of airship take-off and landing by buoyancy control using air ballonet volume change and performance control of pitch angle for stable flight within the desired altitude. For the complexity of airship's dynamics, firstly, simple PID controller was applied. Due to the various atmospheric conditions, this controller didn't give satisfactory results. Therefore, new control method was designed to reduce rapidly the error between designed trajectory and actual trajectory by learning algorithm using an artificial neural network. Generally, ANN has various weaknesses such as large training time, selection of neuron and hidden layer numbers required to deal with complex problem. To overcome these drawbacks, in this paper, the RBFN (radial basis function network) controller developed. The weight value of RBFN is acquired by learning which to reduce the error between desired input output through and airship dynamics to impress the disturbance. As a result of simulation, the controller using the RBFN is superior to PID controller which maximum error is 15M.

Modeling of a PEM Fuel Cell Stack using Partial Least Squares and Artificial Neural Networks (부분최소자승법과 인공신경망을 이용한 고분자전해질 연료전지 스택의 모델링)

  • Han, In-Su;Shin, Hyun Khil
    • Korean Chemical Engineering Research
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    • v.53 no.2
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    • pp.236-242
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    • 2015
  • We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

Spatial Multiplexing Using Open-Loop Precoding in Maritime Communication Environment with Channel Correlation and LOS (채널 상관 및 직접파가 존재하는 해상 통신 환경에서 개루프 프리코딩 기반의 공간다중화 전송 기법)

  • Jang, Jungyup;Lee, Seong Ro;Kim, Dong Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.7
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    • pp.1397-1404
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    • 2015
  • Recently, high data rate transmission is required in maritime communication. In this paper, we consider multiple input multiple output (MIMO) spatial multiplexing (SM). However, the performance of SM is severly degraded due to spatial channel correlation and line-of-sight (LOS) component. In the maritime communication, the MIMO channel correlation and LOS are critical due to the lack of scatteres around the transmitter and/or the receiver. When the feedback of channel information is available, precoding can enhance the error performance by exploiting the channel information. However, it is difficult to derive closed-form solution considering both the correlation and LOS. In this paper, we present open-loop precoding-based spatial multiplexing transmission method by showing that the effect of performance for the correlation and LOS. It is shown that the open-loop precoding can mitigate the performance degradation due to the LOS as well as the correlation. Consequently, we expect that the proposed open-loop precoding can be adopted to the maritime communication system.

A Research about Time Domain Estimation Method for Greenhouse Environmental Factors based on Artificial Intelligence (인공지능 기반 온실 환경인자의 시간영역 추정)

  • Lee, JungKyu;Oh, JongWoo;Cho, YongJin;Lee, Donghoon
    • Journal of Bio-Environment Control
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    • v.29 no.3
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    • pp.277-284
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    • 2020
  • To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO2 is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO2. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO2. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.

Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks (II) Development of Groundwater Flow Model (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구(II) -산사면에서의 지하수위 예측 모델의 개발-)

  • Lee, In-Mo;Park, Gyeong-Ho;Im, Chung-Mo
    • Geotechnical Engineering
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    • v.8 no.2
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    • pp.5-20
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    • 1992
  • The physical-based and lumped-parameter hydrologic groundwater flow model for predicting the rainfall-triggered rise of groundwater levels in hillside slopes is developed in this paper to assess the risk of landslides. The developed model consists of a vertical infiltration model for unsaturated zone linked to a linear storage reservoir model(LSRM) for saturated zone. The groundwater flow model has uncertain constants like soil depttL slope angle, saturated permeability, and potential evapotranspiration and four free model parameters like a, b, c, and K. The free model parameters could be estimated from known input-output records. The BARD algorithm is uses as the parameter estimation technique which is based on a linearization of the proposed model by Gauss -Newton method and Taylor series expansion. The application to examine the capacity of prediction shows that the developed model has a potential of use in forecast systems of predicting landslides and that the optimal estimate of potential 'a' in infiltration model is the most important in the global optimum analysis because small variation of it results in the large change of the objective function, the sum of squares of deviations of the observed and computed groundwater levels. 본 논문에서는 가파른 산사면에서 산사태의 발생을 예측하기 위한 수문학적 인 지하수 흐름 모델을 개발하였다. 이 모델은 물리적인 개념에 기본하였으며, Lumped-parameter를 이용하였다. 개발된 지하수 흐름 모델은 두 모델을 조합하여 구성되어 있으며, 비포화대 흐름을 위해서는 수정된 abcd 모델을, 포화대 흐름에 대해서는 시간 지체 효과를 고려할 수 있는 선형 저수지 모델을 이용하였다. 지하수 흐름 모델은 토층의 두께, 산사면의 경사각, 포화투수계수, 잠재 증발산 량과 같은 불확실한 상수들과 a, b, c, 그리고 K와 같은 자유모델변수들을 가진다. 자유모델변수들은 유입-유출 자료들로부터 평가할 수 있으며, 이를 위해서 본 논문에서는 Gauss-Newton 방법을 이용한 Bard 알고리즘을 사용하였다. 서울 구로구 시흥동 산사태 발생 지역의 산사면에 대하여 개발된 모델을 적용하여 예제 해석을 수행함으로써, 지하수 흐름 모델이 산사태 발생 예측을 위하여 이용할 수 있음을 입증하였다. 또한, 매개변수분석 연구를 통하여, 변수 a값은 작은 변화에 대하여 목적함수값에 큰 변화를 일으키므로 a의 값에 대한 최적값을 구하는 것이 가장 중요한 요소라는 결론을 얻었다.

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FPGA Implementation of Real-time 2-D Wavelet Image Compressor (실시간 2차원 웨이블릿 영상압축기의 FPGA 구현)

  • 서영호;김왕현;김종현;김동욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.683-694
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    • 2002
  • In this paper, a digital image compression codec using 2D DWT(Discrete Wavelet Transform) is designed using the FPGA technology for real time operation The implemented image compression codec using wavelet decomposition consists of a wavelet kernel part for wavelet filtering process, a quantizer/huffman coder for quantization and huffman encoding of wavelet coefficients, a memory controller for interface with external memories, a input interface to process image pixels from A/D converter, a output interface for reconstructing huffman codes, which has irregular bit size, into 32-bit data having regular size data, a memory-kernel buffer to arrage data for real time process, a PCI interface part, and some modules for setting timing between each modules. Since the memory mapping method which converts read process of column-direction into read process of the row-direction is used, the read process in the vertical-direction wavelet decomposition is very efficiently processed. Global operation of wavelet codec is synchronized with the field signal of A/D converter. The global hardware process pipeline operation as the unit of field and each field and each field operation is classified as decomposition levels of wavelet transform. The implemented hardware used FPGA hardware resource of 11119(45%) LAB and 28352(9%) ESB in FPGA device of APEX20KC EP20k600CB652-7 and mapped into one FPGA without additional external logic. Also it can process 33 frames(66 fields) per second, so real-time image compression is possible.