• 대한의용생체공학회:의공학회지
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• 제29권5호
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• pp.392-399
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• 2008

Thin-film transistor (TFT) arrays for an x-ray detector require quite different design concept from that of the conventional active-matrix liquid crystal devices (AM-LCDs). In this paper anew design of TFT array which uses only SiNx for passivation layer is described to meet the detector performance and the product availability simultaneously. For the purpose of optimizing the design parameters of the TFT array, a Spice simulation was performed. As a result, some parameters, such as the TFT width, the data line capacitance, and the storage capacitance, were able to be fixed. The other parameters were decided within a permissible range of the TFT process especially the photolithography process and the wet etch process. Then we adapted the TFT array which had been produced by the proposed design to our prototype model (FDXD-1417 and evaluated it clinically by comparing with a commercial model (EPEX, Hologic, Beford, USA). The results say that our prototype model is slightly better than EPEX system in chest PA images. So we can prove the technical usefulness and the commercial values of the proposed TFT design.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.512-519
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• 2003

본 논문에서는 계층적 클러스터링과 GMM을 순차적으로 이용하여 최적의 파라미터를 추정하고 이를 뉴로-퍼지 모델의 초기 파리미터로 사용하여 모델의 성능 개선을 제안한다. 반복적인 시도 중 가장 좋은 파라미터를 선택하는 기존의 알고리즘 과 달리 계층적 클러스터링은 데이터들 간의 유클리디언 거리를 이용하여 클러스터를 생성하므로 반복적인 시도가 불필요하다. 또한 클러스터링 방법에 의해 퍼지 모델링을 행하므로 클러스터와 동일한 갯수의 적은 규칙을 갖는다. 제안된 방법의 유용함을 비선형 데이터인 Box-Jenkins의 가스로 예측 문제와 Sugeno의 비선형 시스템에 적용하여 이전의 연구보다 적은 규칙으로도 성능이 개선되는 것을 보였다.

• 산업경영시스템학회지
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• 제34권3호
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• pp.1-7
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• 2011

The stocker system is another name of automated storage and retrieval system (AS/RS) and being popularly used as main material handling tools in Liquid Crystal Display (LCD) and semiconductor fabrication facilities. Recently the use of the stocker system has been extended to transportation from conventional storage and retrieval in LCD fabrication facilities. Toolsets are connected in the ground level of the stocker system and 4~6 stories of the shelves are placed in the upper or lower ground level. As a consequence of the more sophisticated design, move requests imposed on the system greatly increased. For solving this problem, the industry adopted the dual-robot stocker system that two robots are moving along the same guide line in the stocker system. This research develops a closed-form solution to estimate a delivery rate of the dual robot stocker system under given design and operation parameters. Using this stochastic model, industry practitioners could analyze performance levels under given various design parameters, and ultimately the model helps optimizing the design parameters.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1759-1768
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• 2018

The energy density, power density and ohm resistance of battery change significantly as results of battery aging, which lead to decrease in the accuracy of the equivalent model. A parameter identification method of the equivale6nt circuit model with 3 R-C branches based on the test database of battery life cycle is proposed in this paper. This database is built on the basis of experiments such as updating of available capacity, charging and discharging tests at different rates and relaxation characteristics tests. It can realize regular update and calibration of key parameters like SOH, so as to ensure the reliability of parameters identified. Taking SOH, SOC and T as independent variables, lookup table method is adopted to set initial value for the parameter matrix. Meanwhile, in order to ensure the validity of the model, the least square method based on variable forgetting factor is adopted for optimizing to complete the identification of equivalent model parameters. By comparing the simulation data with measured data for charging and discharging experiments of Li-ion battery, the effectiveness of the full life cycle database and the model are verified.

• Journal of Power Electronics
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• 제19권5호
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• pp.1087-1098
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• 2019

In this paper, a detuning factor (DeFac) method is proposed to design the key parameters for optimizing the transfer power and efficiency of an Inductively Coupled Power Transfer (ICPT) system with primary-secondary side compensation. Depending on the robustness of the system, the DeFac method can guarantee the stability of the transfer power and efficiency of an ICPT system within a certain range of resistive-capacitive or resistive-inductive loads. A MATLAB-Simulink model of a ICPT system was built to assess the system's main evaluation criteria, namely its maximum power ratio (PR) and efficiency, in terms of different approaches. In addition, a magnetic field simulation model was built using Ansoft to specify the leakage flux and current density. Simulation results show that both the maximum PR and efficiency of the ICPT system can reach almost 70% despite the severe detuning imposed by the DeFac method. The system also exhibited low levels of leakage flux and a high current density. Experimental results confirmed the validity and feasibility of an ICPT system using DeFac-designed parameters.

• Geomechanics and Engineering
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• 제17권6호
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• pp.515-525
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• 2019

The calculation of active earth pressure behind retaining wall is a typical three-dimensional (3D) problem with spatial effects. With the help of limit analysis, this paper firstly deduces the internal energy dissipation power equations and various external forces power equations of the 3D retaining wall under the nonlinear strength condition, such as to establish the work-energy balance equation. The pseudo-static method is used to consider the effect of earthquake on active earth pressure in horizontal state. The failure mode is a 3D curvilinear cone failure mechanism. For the different width of the retaining wall, the plane strain block is inserted in the symmetric plane. By optimizing all parameters, the maximum value of active earth pressure is calculated. In order to verify the validity of the new expressions obtained by the paper, the solutions are compared with previously published solutions. Agreement shows that the new expressions are effective. The results of different parameters are given in the forms of figures to analysis the influence caused by nonlinear strength parameters.

• Smart Structures and Systems
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• 제30권1호
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• Advances in materials Research
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• 제13권1호
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• Journal of Biosystems Engineering
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• 제37권4호
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• 대한전자공학회논문지TC
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• 제43권4호
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• pp.58-66
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• 2006

본 논문에서는 설계자가 원하는 주파수 특성을 갖는 FSS(Frequency Selective Surface)를 자동으로 설계해주는 시스템을 개발하고 실제 적용한 예를 기술한다. 설계 시스템은 전자파 산란 해석이론, 실제 제작한 FSS들의 특성을 측정하여 구축된 DB, 그리고 유전 알고리즘을 이용해서 설계자가 기대하는 특성을 가진 FSS의 설계 요소들을 제시한다. 설계 시스템은 첫 단계로 설계자가 요구한 특성과 가장 유사한 특성을 갖는 FSS 파라미터들을 DB로부터 구하고, 두 번째 단계로 이 파라미터들로부터 초기 개체들을 구성하여 유전학적 진화를 통해 설계자가 요구한 특성을 갖는 FSS 설계 파라미터가 출력되도록 개발되었다. 유전 알고리즘 내에서 사용되는 FSS 해석이론은 실제 제작된 FSS 샘플을 혼 안테나를 사용하여 실제로 측정한 데이터와 비교 분석하여 그 타당성을 검증하였다. 아울러 FSS를 제작하는 과정도 간단히 소개하였다.