• Journal of Industrial Technology
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• v.28 no.A
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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.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.6
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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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.3
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• pp.215-221
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• 2015

The elbow reflex, a principal reflex in the upper extremity, plays an important role in the diagnosis of cervical spine syndromes. In this study, the muscle activations of brachial biceps and triceps, and the kinematics of upper extremities were predicted using an activation model for the stretch reflex. The muscle activations that equated the simulation results estimated by the analysis model with the experimental results were obtained first, and the activations obtained from the simulations were compared with the electromyography signals obtained from the experiments, for model validation. The root mean squares error of the joint angles (obtained from experiments and simulation using the suggested model) was 0.056, a value that is half of that obtained using the previous model. This demonstrates that the suggested model corresponded well with the actual reflex.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.4
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• pp.26-34
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• 2003

In this paper, a novel technique is proposed to arbitrarily activate the nodal points in finite element model through the meshless approximation methods such as MLS(moving least squares method), and theoretical investigations are carried out including the consistency and boundeness of numerical solution to prove the validity of the proposed method. By using the proposed node activation technique, one can activate and handle only the concerned nodes as unknown variables among the large number of nodal points in the finite element model. Therefore, the proposed technique has a great potential in design and reanalysis procedure.

• Korean Journal of Agricultural Science
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• v.50 no.3
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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.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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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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• v.39 no.4
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• pp.281-285
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• 2004

In this paper, the simple way to evaluate the value of the activation energy for the overall rate of free radical polymerization by using DSC thermograms was studied using free radical polymerization or butylacrylate as a model. Activation ehergies were determined at heating rates of 1, 2, 5, and $10^{\circ}C/min$ by applying the multiple scanning-rate methods of Kissinger, Osawa, and half-width methods as well as the single rate method of Barrett. The value of the overall activation energy measured was closely matched with the values calculated from individual data. This work also demonstrated that the use of the isoconversional method was a simple and effective way to estimate the activation energy for the overall free radical polymerization.

• International journal of advanced smart convergence
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• v.6 no.4
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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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• v.51 no.4
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• pp.493-499
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• 2013

For the purpose of utilizing fly ash from gasification of low rank coal, we performed the series of experiments such as pyrolysis and char-$CO_2$ gasification on fly ash by using the thermogravimetric analyzer (TGA) at non-isothermal heating conditions (10, 20 and $30^{\circ}C/min$). Pyrolysis rate has been analyzed by Kissinger method as a first order, the reliability of the model was lower because of the low content of volatile matter contained in the fly ash. The experimental results for the fly ash char-$CO_2$ gasification were analyzed by the shrinking core model, homogeneous model and random pore model and then were compared with them for the coal char-$CO_2$ gasification. The fly ash char (LG coal) with low-carbon has been successfully simulated by the homogeneous model as an activation energy of 200.8 kJ/mol. In particular, the fly ash char of KPU coal with high-carbon has been successfully described by the random pore model with the activation energy of 198.3 kJ/mol and was similar to the behavior for the $CO_2$ gasification of the coal char. As a result, the activation energy for the $CO_2$ gasification of two fly ash chars don't show a large difference, but we can confirm that the models for their $CO_2$ gasification depend on the amount of fixed carbon.