• 산업기술연구
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• 제28권A호
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• pp.155-161
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• 2008

Muscle force prediction in forward dynamic analysis of human motion depends many muscle parameters associated with muscle actuation. This research studies the effects of various parameters of Hill type muscle model using the simple hand raising motion. Motion analysis is carried out using motion capture system, and each muscle force is recorded for comparison with muscle model generated muscle force. Using Hill type muscle model, muscle force for generating the same hand rasing motion was setup adjusting 5 activation parameters. The test showed the importance of activation parameters on the accurate generation of muscle force.

• 한국식품영양과학회지
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• 제26권6호
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• pp.1135-1139
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• 1997

Major factors inhibiting nonenzymatic browning in stored ginger paste were investigated using aqueous model systems with temperature, water activity, pH and sulfur compounds. Browning index and total gingerols were measured during storage. The rate of nonenzymatic browning reactions showed a strong depencence on temperature and pH and a negligible influence on water activity. It was also reduced by the addition of 0.04% N-actyl-L-cysteine(NAcCys), effectively. Activation energies for aqueous ginger model systems with and without 0.04% NAcCys were 29.0 and 25.8kcal/mole, respectively.

• 대한기계학회논문집B
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• 제39권3호
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• pp.215-221
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• 2015

삼두박근 반사는 인체 상지에서 발생하는 대표적인 신장반사이며 경추의 이상 등을 판단하는데 중요한 역할을 수행한다. 본 연구에서는 이를 생체역학적으로 해석하기 위하여 새롭게 정의된 신장반사 해석 모델을 이용하여 해석적으로 상완 이두박근과 삼두박근의 근활성도 및 상완의 운동 정보를 예측하였다. 해석을 통해 예측된 운동 정보와 실험 결과가 같도록 하는 근활성도를 구하고, 이를 근전도 실험 결과와 비교하여 해석 모델과 방법의 타당성을 검증하였다. 제안된 모델과 실험을 통해 얻은 관절의 각도들의 최소자승오차는 0.056 으로 기존의 모델을 사용하여 얻은 오차의 절반 수준이다. 이것은 제안된 모델이 실제 현상과 잘 부합한다는 것을 나타낸다.

• 대한기계학회논문집A
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• 제24권4호
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• pp.907-915
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• 2000

The movement of teeth and initial stress associated with the treatment of orthodontics have been successfully studied using the finite element method. To reduce the effort in preprocessing of finite element analysis, we developed two types of three-dimensional finite element models based on the standard teeth model. Individual malocclusions were incorporated in the finite element The movement of teeth and initial stress associated with the treatment of orthodontics have been successfully studied using the finite element method. To reduce the effort in preprocessing of finite element analysis, we developed two types of three-dimensional finite element models based on the standard teeth model. Individual malocclusions were incorporated in the finite element models by considering the measuring factors such as angulation, crown inclination, rotation and translations. The finite element analysis for the wire activation with a T-loop arch wire was carried out. Mechanical behavior on the movement and the initial stress for the malocclusion finite element model was shown to agree with the objectives of the actual treatment. Finite element models and procedures of analysis developed in this study would be suitably utilized for the design of initial shape of the wire and determination of activation displacements.

• 한국항공우주학회지
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• 제31권4호
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• pp.26-34
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• 2003

본 논문에서는 이동최소자승 근사법 등의 무요소 근사법을 이용하여 유한요소모델 절점의 연결성과 무관하게 유한요소 절점을 자유로이 활성화시킬 수 있는 절점활성화 기법을 제안하고, 제안된 방법의 타당성을 고찰하기 위해 일관성 조건, 수치해의 유계성 등에 대한 이론적 고찰을 수행한다. 제안된 절점활성화 기법을 이용하면 많은 수의 유한요소 절점 중 관심이 있는 일부 절점만을 선택, 활성화시켜 이들만을 미지수로 이용하여 문제를 해석할 수 있기 때문에 설계 및 재해석을 효율적으로 수행할 수 있다.

• 농업과학연구
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• 제50권3호
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• pp.357-364
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• 2023

In this study, we propose a ripe tomato bunch localization method based on convolutional neural networks, to be applied in robotic harvesting systems. Tomato images were obtained from a smart greenhouse at the Rural Development Administration (RDA). The sample images for training were extracted based on tomato maturity and resized to 128 × 128 pixels for use in the classification model. The model was constructed based on four-layer convolutional neural networks, and the classes were determined based on stage of maturity, using a Softmax classifier. The localization of the ripe tomato bunch region was indicated on a class activation map. The class activation map could show the approximate location of the tomato bunch but tends to present a local part or a large part of the ripe tomato bunch region, which could lead to poor performance. Therefore, we suggest a recursive method to improve the performance of the model. The classification results indicated that the accuracy, precision, recall, and F1-score were 0.98, 0.87, 0.98, and 0.92, respectively. The localization performance was 0.52, estimated by the Intersection over Union (IoU), and through input recursion, the IoU was improved by 13%. Based on the results, the proposed localization of the ripe tomato bunch area can be incorporated in robotic harvesting systems to establish the optimal harvesting paths.

• 한국건축시공학회지
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• 제2권4호
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• pp.177-182
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• 2002

The purpose of this study is to develope the strength prediction model by Maturity Method. A maturity function is a mathematical expression to account for the combined effects of time and temperature on the strength development of a cementious mixture. The method of equivalent ages is to use Arrhenius equation which indicates the influence of curing temperature on the initial hydration ratio of cement. For the experimental factors of this study, we selected the concrete mixing of W/C ratio 45, 50, 55 and 60% and curing temperature 5, 10, 20 and $30^{\circ}C$. And we compare and evaluate with logistic model that is existing strength prediction model, because we have to verify adaption possibility of new strength prediction model which is proposed by maturity method. As the results, it is found that investigation of the activation energy that are used to calculate equivalent age is necessary, and new strength prediction model was proved to be more accurate in the strength prediction than logistic model in the early age. Moreover, the use of new model was more reasonable because it has low SSE and high decisive factor.

• Elastomers and Composites
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• 제39권4호
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• pp.281-285
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• 2004

이 연구는 열분석법을 이용하여 간단하게 자유 라디칼 중합의 활성화 에너지를 결정하는 방법을 부틸 아크릴레이트을 모델로 하여 구했다. 활성화 에너지는 Kissinger, Osawa 및 half-width법인 다수의 주사 속도법 (multiple scanning-rate method)을 이용하여 $1^{\circ}C/min,\;2^{\circ}C/min,\;5^{\circ}C/min$, 그리고 $10^{\circ}C/min$로 측정하였으며 단수 주사 속도법인 Barret 법을 이용하여 구하였다. 열분석법에 의해 구해진 중합반응의 활성화 에너지는 개시반응, 성장반응 및 종결반응의 각각의 활성화 에너지에서 계산된 전체 중합반응에서의 활성화 에너지와 가깝게 접근하였다.

• International journal of advanced smart convergence
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• 제6권4호
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• pp.73-79
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• 2017

The Convolutional Neural Network (CNN) has shown an excellent performance in computer vision task. Applications of CNN include image classification, object detection in images, autonomous driving, etc. This paper will evaluate the performance of CNN model with ReLU and SELU as activation function. The evaluation will be performed on four different choices of hyperparameter which are initialization method, network configuration, optimization technique, and regularization. We did experiment on each choice of hyperparameter and show how it influences the network convergence and test accuracy. In this experiment, we also discover performance improvement when using SELU as activation function over ReLU.

• Korean Chemical Engineering Research
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• 제51권4호
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• pp.493-499
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• 2013

저급탄의 가스화에서 얻은 비산재를 활용하기 위한 목적으로 비산재의 열분해와 비산재 촤의 $CO_2$ 가스화반응에 대한 실험을 비등온의 승온 조건(10, 20, $30^{\circ}C$/min)에서 TGA를 이용하여 수행하였다. 비산재의 열분해 속도는 1차의 열분해 모델(Kissinger법)에 의해 해석하였지만, 비산재에 포함된 휘발분의 함량이 낮아 모델의 신뢰도는 낮게 평가되었다. 비산재 촤의 $CO_2$ 가스화반응에 대한 실험결과는 미반응핵 모델, 균일반응 모델 및 랜덤 기공 모델 등으로 해석하여 석탄 촤의 $CO_2$ 가스화반응 결과와 비교하였다. 저탄소가 함유된 비산재 촤(LG탄)는 200.8 kJ/mol의 활성화 에너지로 균일반응 모델의 의해 잘 모사되었으며, 고탄소가 함유된 비산재 촤(KPU탄)의 경우에는 198.3 kJ/mol의 활성화 에너지로 석탄 촤의 $CO_2$ 가스화 특성과 유사하게 랜덤 기공 모델의 의해 잘 모사되었다. 결과로서, 두 비산재 촤의 $CO_2$ 가스화반응에 대한 활성화 에너지는 큰 차이를 나타내지는 않았지만, 고정탄소의 함량에 따라 적용할 수 있는 모델이 다르다는 것을 확인할 수 있었다.