• 한국정밀공학회지
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• 제30권10호
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• pp.1079-1086
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• 2013

Optimal mount position of a front pillar trim considering heat resistant characteristics can be determined by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network (ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently.

• 디지털산업정보학회논문지
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• 제10권4호
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• pp.151-160
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• 2014

In this paper, a comparison of superpixel characteristics based on SLIC(simple linear iterative clustering) for several color feature spaces is presented. Computer vision applications have come to rely increasingly on superpixels in recent years. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. A superpixel is consist of pixels with similar features such as luminance, color, textures etc. Thus superpixels are more efficient than pixels in case of large scale image processing. Generally superpixel characteristics are described by uniformity, boundary precision and recall, compactness. However previous methods only generate superpixels a special color space but lack researches on superpixel characteristics. Therefore we present superpixel characteristics based on SLIC as known popular. In this paper, Lab, Luv, LCH, HSV, YIQ and RGB color feature spaces are used. Uniformity, compactness, boundary precision and recall are measured for comparing characteristics of superpixel. For computer simulation, Berkeley image database(BSD300) is used and Lab color space is superior to the others by the experimental results.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 추계학술대회 논문집
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• pp.187-192
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• 2001

In this paper, a practical method to generate task strategies applicable to charmfulness and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result form various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal through iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the assembly task can be performed successfully.

• 한국정밀공학회지
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• 제18권3호
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• pp.131-142
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• 2001

다양한 산업체에서 반복적인 특정업무를 수행하는 경우가 흔히 발생한다. 반복되는 오차의 경험치를 근거로 주어진 작업을 추진하는 과정에서 이들 업무의 정밀도제고를 추구함으로써 갖는 성능개선은 사업장의 품질관리와 직결된다. 학습제어의 본래 적용동기는 생산조립라인에 투입되어 반복적인 일을 수행하는 산업로봇의 정밀도 제고이다. 본 논문에서 분산이산시형시스템에서 출발하였으며, 이를 산업용로봇에 적용하기 위하여 수학적으로 모델링한 모의실험을 통하여 알고리즘의 안정성과 반복오차를 줄여가는 과정을 보여 주었다. 입출력정보가 상호간섭 하는 산업용로봇과 같은 복합구조물에서도 모든 시스템(링크)의 정밀도를 만족함을 보여 줌으로써 복합구조물에서 선형반복학습제어의 안정성을 증명하였다.

• 한국정밀공학회지
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• 제10권3호
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• pp.175-181
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• 1993

In this paper, a practical method to generate task strategies applicable to chamferless and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result from various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal trrough iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the chamferless assembly can be performed successfully.

• 대한의용생체공학회:의공학회지
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• 제26권3호
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• pp.133-138
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• 2005

This paper presents a new method for measuring ocular torsion using the optical flow. Images of the iris were cropped and transformed into rectangular images that were orientation invariant. Feature points of the iris region were selected from a reference and a target image, and the shift of each feature was calculated using the iterative Lucas-Kanade method. The feature points were selected according to the strength of the corners on the iris image. The accuracy of the algorithm was tested using printed eye images. In these images, torsion was measured with $0.15^{\circ}$ precision. The proposed method shows robustness even with the gaze directional changes and pupillary reflex environment of real-time processing.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.1486-1489
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• 2009

Micro wall is fabricated using iterative screen printing that it is able to fabricate the pattern as low cost, simple process, formation of pattern at large area on the various substrates. In the process of micro wall fabrication using screen printing, the printing result with pressure change in process and improvement of surface roughness using hydrophillic plasma treatment are included. Height of micro wall increase linearly and precision of iteration is very high. Error rate of printed pattern width is very high, but change rate of width is under 10 %. Fabricated micro pattern have minimum width $48.75{\mu}m$ and maximum height $75.45{\mu}m$ with aspect ratio 1.55.

• 전자공학회논문지S
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• 제35S권9호
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• pp.35-42
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• 1998

CNC 가공에 있어서 가공정밀도와 생산성을 동시에 향상시킬 수 있는 기술의 개발이 필수적이다. 이러한 고정밀 고속가공을 위하여 이 논문에서는 신경망을 이용한 이송속도 신경망 적응제어 기법을 제안한다. 이 제어기는 신경망을 이용한 모사기와 이 신경망의 인버젼 알고리듬을 통한 반복학습 제어기로 구성된다. 신경망 모사기는 CNC 시스템의 비선형성과 불확실성으로 인한 이송속도와 윤곽오차 사이의 비선형 특성을 모사하고, 신경망 인버젼 방법과 목적 함수의 정의를 통해 반복학습 제어기법으로 허용 오차 내에서 최적의 이송속도를 실시간으로 구해 냄으로써 가공 성능을 향상시킨다.제안한 방법은 원, 코너, 인볼루트 윤곽 가공의 모의 실험을 통하여 성공적으로 평가되었다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권1호
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• pp.95-100
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• 2016

Background: Survival time of lymphoma patients can be estimated with the help of microarray technology. In this study, with the use of iterative Bayesian Model Averaging (BMA) method, survival time of Mantle Cell Lymphoma patients (MCL) was estimated and in reference to the findings, patients were divided into two high-risk and low-risk groups. Materials and Methods: In this study, gene expression data of MCL patients were used in order to select a subset of genes for survival analysis with microarray data, using the iterative BMA method. To evaluate the performance of the method, patients were divided into high-risk and low-risk based on their scores. Performance prediction was investigated using the log-rank test. The bioconductor package "iterativeBMAsurv" was applied with R statistical software for classification and survival analysis. Results: In this study, 25 genes associated with survival for MCL patients were identified across 132 selected models. The maximum likelihood estimate coefficients of the selected genes and the posterior probabilities of the selected models were obtained from training data. Using this method, patients could be separated into high-risk and low-risk groups with high significance (p<0.001). Conclusions: The iterative BMA algorithm has high precision and ability for survival analysis. This method is capable of identifying a few predictive variables associated with survival, among many variables in a set of microarray data. Therefore, it can be used as a low-cost diagnostic tool in clinical research.

• Korean Journal of Radiology
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• 제22권6호
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.