• 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.

• 대한기계학회논문집A
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• 제32권8호
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• pp.678-684
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• 2008

A general treatment is to restore abfraction lesions with dental filler materials to reduce stress concentration. A material should be selected from various dental products based on long term experiences of dentist or personal preference concerning filler methods. A quantitative criterion is necessary to make an evaluation of the results as dentists decide treatment methods and dental materials relying on their clinical experiences. The purpose of this study is to find an optimal restoration method and material for noncarious cervical lesions using the finite element method. An objective function was defined to minimize the sum of tension or compression stress. Trial-and-error and approximation were used to find an optimal restoration method. An optimal solution was to fill TetricFlow inside the lesion and Z100 in the remaining region. The most desirable thickness ratio of the two filler materials was 0.125 with trial-and-error and it was similar to the results of approximation, 0.121 and 0.132.

• 드라이브 ㆍ 컨트롤
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• 제15권4호
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• pp.74-80
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• 2018

A damper is a hydraulic device designed to absorb or eliminate shock impulses which is acting on the sprung mass of vehicle. It converting the kinetic energy of the shock into another form of energy, typically heat. In a vehicle, a damper reduce vibration of car, leading to improved ride comfort and running stability. Therefore, a damper is one of the most important components in a vehicle suspension system. Conventionally, the design process of vehicle suspensions has been based on trial and error approaches, where designers iteratively change the values of the design variables and reanalyze the system until acceptable design criteria are achieved. Therefore, the ability to tune a damper properly without trial and error is of great interest in suspension system design to reduce time and effort. For this reason, a many previous researches have been done on modeling and simulation of the damper. In this paper, we have conducted optimal design process to find optimal design parameters of damping force which minimize a acceleration of sprung mass for a given suspension system using genetic algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.288-291
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• 1999

The PID (Proportional-Integral-Derivative) controller is widely used in the industries for more than fifty years with the well known Ziegler-Nichols tuning method and others varieties. However, most of the PID controller being used in the real practice still require trial and error adjustment for each process after the tuning method is done, which is consuming of time and needs the operator experiences to obtain the best results for the controller parameter. In order to reduce the inconvenience in the controller tuning, this paper presents a design of an automatic PID controller parameter analyzer being used as a support instrument in the industrial process control. This analyzer is designed based on the tuning formula of Dahlin to synthesize the PID controller parameter. Using this analyzer, the time to be spent in the trial and error procedures and its complexity can be neglected. Experimental results using PID controller parameter synthesized from this analyzer to the liquid level control plant model and the fluid flow control plant model show that the responses of the controlled systems can be efficiently controlled without any difficulty in mathemathical computation.

• Korean Journal of Radiology
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• 제24권7호
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• pp.698-714
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• 2023

In recent years, artificial intelligence, especially object detection-based deep learning in computer vision, has made significant advancements, driven by the development of computing power and the widespread use of graphic processor units. Object detection-based deep learning techniques have been applied in various fields, including the medical imaging domain, where remarkable achievements have been reported in disease detection. However, the application of deep learning does not always guarantee satisfactory performance, and researchers have been employing trial-and-error to identify the factors contributing to performance degradation and enhance their models. Moreover, due to the black-box problem, the intermediate processes of a deep learning network cannot be comprehended by humans; as a result, identifying problems in a deep learning model that exhibits poor performance can be challenging. This article highlights potential issues that may cause performance degradation at each deep learning step in the medical imaging domain and discusses factors that must be considered to improve the performance of deep learning models. Researchers who wish to begin deep learning research can reduce the required amount of trial-and-error by understanding the issues discussed in this study.

• 한국정보통신학회논문지
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• 제16권3호
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• pp.432-439
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• 2012

본 논문에서 이륜 역진자 로봇의 밸런싱에 사용되고 있는 기존 PD 제어기를 대신하여 신경회로망 학습을 통해 향상된 PD 제어기를 이륜 역진자형 이동로봇에 적용하여 실험하고 성능을 검증하였다. 먼저 제어실험에 사용할 이륜 역진자 로봇시스템을 구축하고 나서 기존의 PD 제어기를 사용하여 사용자 몸무게에 따라 시행착오적으로 이득값을 구해 로봇을 밸런싱시켰다. 그리고 시행착오적으로 구한 이득 값을 신경회로망 학습을 통해 일반화시켜 몸무게에 따라 일반화된 PD 이득 값을 가지는 제어기를 구현하였다. 이렇게 구현된 제어기가 기존의 PD 제어기보다 안정적 제어 측면에서 더 유리함을 실험적으로 확인할 수 있었다.

• 소성∙가공
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• 제24권2호
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• pp.121-129
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• 2015

A net-shape forming of small and complex-shaped metal parts by metal injection molding (MIM) has economic advantages in mass production, especially for STS 316L valve fitting. STS 316L offers excellent corrosion resistance, but it has poor machinability, which is a limitation in using it for a cost-effective production where both forging and machining are employed. Simulation and experimental analysis were performed to develop a MIM STS 316L 90° elbow fitting minimizing trial and error. A Taguchi method was used to determine which input parameter was the most sensitive to possible defects (e.g. sink mark depth) during the injection molding. The final prototype was successfully built. The results indicate that the simulation tool can be used during the design process to minimize trial and error, but the final adjustment of parameters based on field experience is essential.

• 한국음향학회지
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• 제42권3호
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• pp.169-180
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• 2023

수중음향통신의 성능은 다중경로 전달과 도플러 확산에 크게 영향을 받는다. 본 논문은 다중경로 전달 환경에서 강인한 기존의 Sweep Spread Carrier(SSC) 기법을 변형하여, 새로운 통신기법인 Triangle Spread Carrier(TSC) 기법을 제안한다. 제안한 TSC 기법은 상승-처프와 하강-처프 신호가 반복되는 반송파를 갖는 형태이며, 각각의 상관함수 특성을 활용하여 수신 신호의 도플러 천이 주파수를 추정하고 보정한다. 제안된 TSC 기법의 성능을 입증하기 위하여 수중 채널 시뮬레이터를 이용한 모의실험과 동해에서 수행된 해상실험을 결과를 제시한다. 해상실험 결과 추정된 도플러 천이 주파수만을 이용하여 복조하였을 때 비부호화 된 비트 오류율은 최대 0.194였지만, 제안한 방법을 적용하였을 때 비부화화된 비트 오류율이 0.001로 감소하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.255-258
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• 2003

It is hard to centrol the wheeled mobile robot because of uncertainty of modeling, non-holonomic constraint and so on. To solve the problems, we design the controller of wheeled mobile robot based on fuzzy-neural network algorithm. In this paper, we should research the problem of classical controller for path-tracking algorithm and design of Fuzzy-Neural Network algorithm controller. Classical controller acquired different control value according to change of initial position and direction. In this control value having very difficult and having acquired a lot of trial and error Fuzzy is implemented to adaptive adjust control value by error and change of error and neural network is implemented to adaptive adjust the control gain during the optimization. The computer simulation shows that the proposed fuzzy-neural network controller is effective.

• 한국안광학회지
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• 제15권3호
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• pp.281-286
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• 2010

목적: 시험렌즈와 포롭터에서의 측정된 교정굴절력 변화를 비교하기 위하여 실시하였다. 방법: 시험렌즈와 포롭터를 사용했을 때의 교정굴절력을 비교하고, 굴절검사기기(시험렌즈와 포롭터)에 따른 구면렌즈교정굴절력, 원주렌즈 교정굴절력의 통계학적 유의성과 상관성, 난시안에서 난시량과의 굴절검사기기와의 상관성과 통계학적 유의성을 분석하였다. 결과: 단순근시안의 교정굴절력을 시험렌즈와 포롭터를 이용하여 측정한 결과 평균교정굴절력이 시험렌즈는 S-2.74D, 포롭터는 S-2.65D로, 포롭터로 측정했을 때의 교정굴절력이 약 0.09D 낮게 측정되었고, 난시량은 시험렌즈는 C-0.81D, 포롭터는 C-0.77D로, 포롭터를 이용하였을 때 약 0.04D 정도 낮게 측정되었다. 굴절검사기기(시험렌즈와 포롭터)와 교정굴절력과의 상관성 분석 결과, 굴절검사기기와 구면렌즈 교정굴절력은 r=0.996으로 높은 상관성이 있었고, 통계학적으로도 유의한 차이가 있었으며(p<0.01), 원주렌즈 교정굴절력도 r=0.986으로 높은 상관성이 있었고, 통계학적으로도 유의한 차이가 있었다(p<0.01). 결론: 고도비정시안(단순굴절이상과 고도 난시안)의 굴절검사는 시험렌즈보다는 포롭터를 이용하는 것이 바람직하고, 시험렌즈를 이용할 경우 처방 시 정점간거리나 렌즈사이의 간격에 주의가 요구 된다.