• Structural Engineering and Mechanics
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• v.69 no.6
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• pp.637-649
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• 2019

In the current research paper, a quasi-3D beam theory is developed for free vibration analysis of functionally graded microbeams. The volume fractions of metal and ceramic are assumed to be distributed through a beam thickness by three functions, power function, symmetric power function and sigmoid law distribution. The modified coupled stress theory is used to incorporate size dependency of micobeam. The equation of motion is derived by using Hamilton's principle, however, Navier type solution method is used to obtain frequencies. Numerical results show the effects of the function distribution, power index and material scale parameter on fundamental frequencies of microbeams. This model provides designers with guidance to select the proper distributions and functions.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.627-637
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• 2023

As the population and income levels rise, meat consumption steadily increases annually. However, the number of farms and farmers producing meat decrease during the same period, reducing meat sufficiency. Information and Communications Technology (ICT) has begun to be applied to reduce labor and production costs of livestock farms and improve productivity. This technology can be used for rapid pregnancy diagnosis of sows; the location and size of the gestation sacs of sows are directly related to the productivity of the farm. In this study, a system proposes to determine the number of gestation sacs of sows from ultrasound images. The system used the YOLOv7-E6E model, changing the activation function from sigmoid-weighted linear unit (SiLU) to a multi-activation function (SiLU + Mish). Also, the upsampling method was modified from nearest to bicubic to improve performance. The model trained with the original model using the original data achieved mean average precision of 86.3%. When the proposed multi-activation function, upsampling, and AutoAugment were applied, the performance improved by 0.3%, 0.9%, and 0.9%, respectively. When all three proposed methods were simultaneously applied, a significant performance improvement of 3.5% to 89.8% was achieved.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.856-867
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• 1990

In this paper, the convergence and the learning accuracy of the back-propagation (BP) method in neural network are investigated by 1) analyzing the reason for decelerating the convergence of BP method and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative and 2) proposing the modified logistic activation function by defining, the convergence factor based on the analysis. Learning on the output patterns of binary as well as analog forms are tested by the proposed method. In binary output patter, the test results show that the convergence is accelerated and the learning accuracy is improved, and the weights and thresholds are converged so that the stability of neural network can be enhanced. In analog output patter, the results show that with extensive initial transient phenomena the learning error is decreased according to the convergence factor, subsequently the learning accuracy is enhanced.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.157-171
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• 2010

To effectively maintain manufacturing collaboration, the development of effective performance measurements for the collaboration is required. Most existing key performance indicators however were developed to measure the performances of internal activities or outsourcing of a company. For that reason, it is necessary to devise new key performance indicators that the partners participating in the collaboration can arrange and compromise with each other to reflect their common goals. In this paper, we propose collaborative Key Performance Indicators(cKPIs), which is used to measure the collaboration work of multiple manufacturing partners on the basis of the Supply Chain Operations Reference(SCOR) model. Also, a modified Sigmoid function is devised as a desirability function to reflect the characteristics of Service Level Agreement(SLA) between two partners. The proposed indicators and the desirability functions can be utilized to perform and maintain the successful collaboration by providing a way to the quantitative measurement.

• Proceedings of the KIEE Conference
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• summer
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• pp.578-580
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• 2004

Substation facilities have become large and complex in the electric power systems. Development of condition monitoring and diagnosis techniques have been very important to improve the security of substation transformers. This paper presents a method to analyze the cause and the degree of aging of power transformers by Self organizing map(SOM). Dissolved gas data were non-linearly transformed by sigmoid function to make determination of SOM close to that of human. Potential of a failure and the degree of aging of a normal transformer are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.40-45
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• 2005

Substation facilities have become extremely large and complex parts of electric power systems. The development of condition monitoring and diagnosis techniques has been a very significant factor in the improvement of substation transformer security. This paper presents a method to analyze the cause, the degree, and the aging process power transformers by the Self Organizing Map (SOM) method. Dissolved gas data were non-linearly transformed by the sigmoid function in SOM that works much the same way as the human decision making process. The potential for failure and the degree of aging of normal transformers are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.242-244
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• 1992

Conventionally in the industrial control, PlD controller has been used because of its robustness, and nonlinear characteristic of a system under control. Although the PlD controller produce suitable parameter of the each system and also variable of PlD controller should be changed according to environment, disturbance, load. In this paper, the convergence and learning accuracy of the back-propagation(BP) method in neural network are investigated by analyzing the reason for decelerating the convergence of BP method. and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative. The modified logistic activation function it proposed by defining the convergence factor based on the analysis and applied to the position and speed control of a DC-servo motor. This paper revealed for experimental, a neural network and a PD controller combined off-line system using developed the position and speed characteristics of a DC-servo motor.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.103-116
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• 2021

Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

• Progress in Medical Physics
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• v.19 no.3
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• pp.150-156
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• 2008

An applied technique of contrast enhancement for X-ray image is proposed which is based on combined enhancement of scaling and wavelet coefficients in discrete wavelet transform space. Conventional contrast enhancement methods such as contrast limited adaptive histogram equalization (CLAHE), multi-scale image contrast amplification (MUSICA) and gamma correction were applied on scaling coefficients to enhance the contrast of an original. In order to enhance the detail as well as reduce the blurring caused by up scaling of contrast modified scale coefficients from lower resolution, the sigmoid manipulation function was used to manipulate wavelet coefficients. The contrast detail mammography (CDMAM) phantom was imaged and processed to measure the image line profile of results and contrast to noise ratio (CNR) comparatively. The proposed technique produced better results than direct application of various contrast enhancement methods on image itself. The proposed method can enhance contrast, and also suppress the amplification of noise components in a single process. It could be useful for various applications in medical, industrial and graphical images where contrast and detail are of importance.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.175-189
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• 1999

The purpose of this study was to established the characteristic radiographic features in salivary gland diseases by means of sialography and scintigraphy. Sialograms and scintigrams with diseases of salivary gland were examined. In this group were 5 salivary stones, 14 sialadenitis, 17 Sjogren's syndromes and 8 benign tumors. The obtained results were as follows; 1. In the configuration of the shape of main duct, those revealed that modified curvilinear and curvilinear types were predominant in Sjogren's syndromes but reverse sigmoid and angular types were in sialolithiasis and sialadenitis combined with sialodochitis. 2. In the configuration of the course of main duct, those revealed that smooth types were predominant in sialadenitis and irregular types were predominant in Sjogren's syndromes and benign tumors and irregular types were seen in all salivary stones and sialadenitis combined with sialodochitis, 3. In the type of intraglandular pattern, those revealed that destructive changes of salivary duct system and parenchyma were severe in sialadenitis and salivary stones and predominantly severe in Sjogren's syndromes. 4. The function of salivary gland was decreased severely in Sjogren's syndrome. and also decrease in salivary stone and sialadenitis. In benign tumor, the uptake of radioisotope was not seen in lesion and the function of salivary gland decreased in its remaining normal parenchyma.