• Title/Summary/Keyword: robust performance.

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Evaluation of the Degrees of Genetic Connectedness Among Duroc Breed Herds (국내 두록종 농장간 유전적 연결성 추정)

  • Cho, Chungil;Choi, Jaekwan;Park, Byoungho;Kim, Sidong;Kwon, Ohsub;Choi, Youlim;Choy, Yunho
    • Journal of Animal Science and Technology
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    • v.54 no.5
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    • pp.337-340
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    • 2012
  • The genetic connectedness between herds is an essential requirement to make robust across-herd estimation of the breeding values of the animals. In this study, genetic connectedness between herds was evaluated by a connectedness rating method. A total of 24,971 records of days to 90 kg (D90KG) of the pigs on performance testing programs collected from six herds (labeled from 'A' to 'F') of Duroc breed along with pedigree information comprising 456,697 families were used. Results showed that a total of eight boars were used for semen exchange programs among participant farms. Herds 'A' through 'E' were found strongly connected among them. But 'F' herd was genetically connected strongly only with 'A' herd. The highest average connectedness rating was 91.7% between 'A' herd and 'C' herd. The lowest average connectedness rating was 65.1% between 'D' and 'F'. The concept of a single genetic group comprising six Duroc herds studied is meaningful due to high connectedness rates among them. Therefore, with this high genetic ties between participant Duroc farms, the more accurate genetic evaluation would be possible.

Design of a Neural Network PI Controller for F/M of Heavy Water Reactor Actuator Pressure (신경회로망과 PI제어기를 이용한 중수로 핵연료 교체 로봇의 구동압력 제어)

  • Lim, Dae-Yeong;Lee, Chang-Goo;Kim, Young-Baik;Kim, Young-Chul;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.3
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    • pp.1255-1262
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    • 2012
  • Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.

Content based Video Segmentation Algorithm using Comparison of Pattern Similarity (장면의 유사도 패턴 비교를 이용한 내용기반 동영상 분할 알고리즘)

  • Won, In-Su;Cho, Ju-Hee;Na, Sang-Il;Jin, Ju-Kyong;Jeong, Jae-Hyup;Jeong, Dong-Seok
    • Journal of Korea Multimedia Society
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    • v.14 no.10
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    • pp.1252-1261
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    • 2011
  • In this paper, we propose the comparison method of pattern similarity for video segmentation algorithm. The shot boundary type is categorized as 2 types, abrupt change and gradual change. The representative examples of gradual change are dissolve, fade-in, fade-out or wipe transition. The proposed method consider the problem to detect shot boundary as 2-class problem. We concentrated if the shot boundary event happens or not. It is essential to define similarity between frames for shot boundary detection. We proposed 2 similarity measures, within similarity and between similarity. The within similarity is defined by feature comparison between frames belong to same shot. The between similarity is defined by feature comparison between frames belong to different scene. Finally we calculated the statistical patterns comparison between the within similarity and between similarity. Because this measure is robust to flash light or object movement, our proposed algorithm make contribution towards reducing false positive rate. We employed color histogram and mean of sub-block on frame image as frame feature. We performed the experimental evaluation with video dataset including set of TREC-2001 and TREC-2002. The proposed algorithm shows the performance, 91.84% recall and 86.43% precision in experimental circumstance.

Bayesian parameter estimation of Clark unit hydrograph using multiple rainfall-runoff data (다중 강우유출자료를 이용한 Clark 단위도의 Bayesian 매개변수 추정)

  • Kim, Jin-Young;Kwon, Duk-Soon;Bae, Deg-Hyo;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.53 no.5
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    • pp.383-393
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    • 2020
  • The main objective of this study is to provide a robust model for estimating parameters of the Clark unit hydrograph (UH) using the observed rainfall-runoff data in the Soyangang dam basin. In general, HEC-1 and HEC-HMS models, developed by the Hydrologic Engineering Center, have been widely used to optimize the parameters in Korea. However, these models are heavily reliant on the objective function and sample size during the optimization process. Moreover, the optimization process is carried out on the basis of single rainfall-runoff data, and the process is repeated for other events. Their averaged values over different parameter sets are usually used for practical purposes, leading to difficulties in the accurate simulation of discharge. In this sense, this paper proposed a hierarchical Bayesian model for estimating parameters of the Clark UH model. The proposed model clearly showed better performance in terms of Bayesian inference criterion (BIC). Furthermore, the result of this study reveals that the proposed model can also be applied to different hydrologic fields such as dam design and design flood estimation, including parameter estimation for the probable maximum flood (PMF).

Design of Sliding Mode Fuzzy Controller for Vibration Reduction of Large Structures (대형구조물의 진동 감소를 위한 슬라이딩 모드 퍼지 제어기의 설계)

  • 윤정방;김상범
    • Journal of the Earthquake Engineering Society of Korea
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    • v.3 no.3
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    • pp.63-74
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    • 1999
  • A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

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Wavelet-Based Digital Watermarking Using Level-Adaptive Thresholding (레벨 적응적 이치화를 이용한 웨이블릿 기반의 디지털 워터마킹)

  • Kim, Jong-Ryul;Mun, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.1
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    • pp.1-10
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    • 2000
  • In this paper, a new digital watermarking algorithm using wavelet transform is proposed. Wavelet transform is widely used for image processing, because of its multiresolution characteristic which conforms to the principles of the human visual system(HVS). It is also very efficient for localizing images in the spatial and frequency domain. Since wavelet coefficients can be characterized by the gaussian distribution, the proposed algorithm uses a gaussian distributed random vector as the watermark in order to achieve invisibility and robustness. After the original image is transformed using DWT(Discrete Wavelet Transform), the coefficients of all subbands including LL subband are utilized to equally embed the watermark to the whole image. To select perceptually significant coefficients for each subband, we use level-adaptive thresholding. The watermark is embedded to the selected coeffocoents, using different scale factors according to the wavelet characteristics. In the process of watermark detection, the similarity between the original watermark and the extracted watermark is calculated by using vector projection method. We analyze the performance of the proposed algorithm, compared with other transform-domain watermarking methods. The experimental results tested on various images show that the proposed watermark is less visible to human eyes and more robust to image compressions, image processings, geometric transformations and various noises, than the existing methods.

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An Empirical Study of the Trading Rules on the basis of Market Anomalies and Technical Analysis (시장이상현상과 기술적 분석을 이용한 거래전략에 관한 연구)

  • Ohk, Ki-Yool;Lee, Min-Kyu
    • Management & Information Systems Review
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    • v.37 no.1
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    • pp.41-53
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    • 2018
  • This study validates the trading rules based market anomalies and technical analysis in the Korean stock market. For the analysis, we built decile portfolios on the basis of corporate characteristics factors that clearly demonstrate specific patterns of stock returns including the firm size, book-to-market equity, and accruals. This portfolio was used to develop a portfolio based on the moving average trading strategy which was used for popular technical analysis tools, and then that was evaluated using the Sharpe ratio. We also created a zero-cost portfolio to identify the profitability and success rate of the moving average trading strategy. We lastly sought to ensure a more robust evaluation by calculating the Sortino ratio of the portfolio based on the moving average trading strategy with various lags. Key findings from this validation are as follows. First, a smaller firm size, a higher book-to-market equity, and lower accruals led to larger average returns. Second, the risk-adjusted performance of the moving average trading strategy was the highest in terms of the firm size, followed by book-to-market equity and accruals. Third, the returns of the zero-cost portfolios all had a positive value, with its overall success rate hovering over 68.8%, demonstrating the successfulness of the moving average trading strategy. Fourth, various evaluations revealed the economic usefulness of our trading strategy that used market anomalies and technical analysis.

IoT Open-Source and AI based Automatic Door Lock Access Control Solution

  • Yoon, Sung Hoon;Lee, Kil Soo;Cha, Jae Sang;Mariappan, Vinayagam;Young, Ko Eun;Woo, Deok Gun;Kim, Jeong Uk
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.8-14
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    • 2020
  • Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

A License Plate Recognition System Robust to Vehicle Location and Viewing Angle (영상 내 차량의 위치 및 촬영 각도에 강인한 차량 번호판 인식 시스템)

  • Hong, Sungeun;Hwang, Sungsoo;Kim, Seongdae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.12
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    • pp.113-123
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    • 2012
  • Recently, various attempts have been made to apply Intelligent Transportation System under various environments and conditions. Consequently, an accurate license plate recognition regardless of vehicle location and viewing angle is required. In this paper, we propose a novel license plate recognition system which exploits a) the format of license plates to remove false candidates of license plates and to extract characters in license plates and b) the characteristics of Hangul for accurate character recognition. In order to eliminate false candidates of license plates, the proposed method first aligns the candidates of license plates horizontally, and compares the position and the shape of objects in each candidate with the prior information of license plates provided by Korean Ministry of Construction & Transportation. The prior information such as aspect ratio, background color, projection image is also used to extract characters in license plates accurately applying an improved local binarization considering luminance variation of license plates. In case of recognizing Hangul in license plates, they are initially grouped according to their shape similarity. Then a super-class method, a hierarchical analysis based on key feature points is applied to recognize Hangul accurately. The proposed method was verified with high recognition rate regardless of background image, which eventually proves that the proposed LPR system has high performance regardless of the vehicle location or viewing angle.

New Methods for Estimation of Time Delay and Time-Frequency Delay in Impulsive NOise Environment Using FNOM and MD Criterion (임펄스 잡음 환경 하에서 FNOM와 MD를 이용한 새로운 시지연 및 시간-주파수 지연 복합 추정 방법)

  • Lee, Jin;Jung, Jung-Kyun;Lee, Young-Seok;Kim, Sung-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.5
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    • pp.96-104
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    • 1997
  • In this paper, we proposed new methods for estimation of time delay and time-frequency delay in impulsive noise environment. The proposed methods are developed using the theory of ${\alpha}-stable$ distribution, including the fractional negative order moment(FNOM) and minimum dispersion(MD), which are formulated for the time delay estimation and the fractional negative order ambiguity function and complex minimum dispersion, which are difined for the joint estimation of time delay and frequency delay. Through simulation work, its performance was compared with various other algorithms. As a result, while the conventional approaches based on second-order statistics are only verified in Gaussian noise environent ($S{\alpha}S$ noise with ${\alpha}$=2) and also the recently proposed robust methods by Nikias[7] are verified only in limited impulse noise ($S{\alpha}S$ noise with the range of $1<{\alpha}{\le}2$), the methods proposed are able to estimate the time delay in Gaussian and any impulsive noise environments($S{\alpha}S$ noise with the range of $0<{\alpha}{\le}2$).

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