• Journal of the Korean Society of Tobacco Science
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• v.3 no.1
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• pp.66-74
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• 1981

This study was conducted to investigate the interaction between chemical compositions and agronomic characteristics of perique tobacco leaf. At the topping stage, the thickness of leaf was positively correlated with total sugar($\textrm{0.975}^{**}$), reducing sugar($\textrm{0.975}^{**}$), alkaloid($\textrm{0.518}^{*}$) and petroleum ether extract($\textrm{0.801}^{**}$) contents. The length of upper leaf was negatively correlated with its chemical contents. Total sugar contents of the harvested leaf showed a sigmoid pattern of distribution along the leaf stalk positions.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.281-287
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• 1999

In this paper, a design method based on evolutionary programming for feedforward neural networks which have a single hidden layer is presented. By using an evolutionary programming, the network parameters such as the network structure, weight, slope of sigmoid functions and bias of nodes can be acquired simultaneously. To check the effectiveness of the suggested method, two numerical examples are examined. The performance of the identified network is demonstrated.

• Tunnel and Underground Space
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• v.6 no.4
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• pp.316-325
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• 1996

A new accelerated neural network adopting modified sigmoid function was developed and applied to estimate engineering properties of rock from insufficient geological data. Developed network was tested on the well-known XOR and character recognition problems to verify the validity of the algorithms. Both learning speed and recognition rate were improved. Test learn on the Lee and Sterling's problems showed that learning time was reduced from tens of hours to a few minutes, while the output pattern was almost the same as other studies. Application to the various case studies showed exact coincidence with original data or measured results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.44-50
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• 1993

In this paper, we will present an array processor for implementation of digital neural networks. Back-propagation model can be formulated as a consecutive matrix-vector multiplication problem with some prespecified thresholding operation. This operation procedure is suited for the design of an array processor, because it can be recursively and repeatedly executed. Systolic array circuit architecture with Residue Number System is suggested to realize the efficient arithmetic circuit for matrix-vector multiplication and compute sigmoid function. The proposed design method would expect to adopt for the application field of neural networks, because it can be realized to currently developed VLSI technology.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.5-8
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• 2000

Voltage mode chaotic neuron has been designed in integrated circuit and fabricated by using 0.8$\mu\textrm{m}$ single poly CMOS technology. The fabricated CMOS chaotic neuron consist of chaotic signal generator and sigmoid output function. This paper presents an analysis of the chaotic behavior in the voltage mode CMOS chaotic neuron. From empirical equations of the chaotic neuron, the dynamical responses such as time series, bifurcation, and average firing rate are calculated. And, results of experiments in the single chaotic neuron and chaotic neural networks by two neurons are shown and compared with the simulated results.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.24 no.2
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• pp.217-225
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• 1994

저자는 측두하악장애 환자의 파노라마 방사선사진 상에서 이 장애와 관련된 변화를 조사하여 측두하악관절 장애의 진단과 치료에 도움을 주고자 하였다. 측두하악장애 환자의 364관절과 정상인 160관절부위를 대상으로 antegonial notch의 깊이, 과두돌기와 하악골상행지의 후방변위정도, 과두돌기, coronoid process 와 sigmoid notch의 길이를 측정하였다. 결과를 보면, 측두하악장애에 이환 된 경우 정상인에 비하여 통계적으로 유의하게 짧은 과두돌기와 하악지, 과두돌기에 비하여 상대적으로 긴 coronoid process, 그리고 깊은 antegonial notch와 오목한 하악골 상행지의 후연을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.586-588
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• 2001

최근에는 순환 신경망의 생성모델이 비교사 학습에 관련하여 활발히 연구되고 있다. 이러한 형태의 신경망은 형태 추출이나 인식에 효과적으로 사용될 수 있는 반면 반복 loop를 사용하므로 대단히 많은 계산이 필요하다. 본 논문에서는 Oh와 Seung에 의해 제안된 상향전파(Up-propagation) network이라는 순환 신경망을 FPGA를 이용해서 구현하였다. 단층 신경망은 9개의 상층 neuron과 256개의 하층 neuron으로 구성되 있으며 4만 게이트의 FPGA 하나로 효과적으로 구현할 수 있다. pipeline된 곱셈기로 게산 속도를 향상시켰고 sigmoid 전달 함수는 유한 정밀도의 2차 다항식으로 근사될 수 있다. 구현된 하드웨어는 hand-written 숫자 영상인 USPS data를 재생하는데 사용되었으며 좋은 결과를 얻었다.

• Journal of Embryo Transfer
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• v.24 no.4
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• pp.293-295
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• 2009

Two postmortem male and female reticulated giraffes were examined. The adult male giraffe showed sigmoid flexure of penis similar to most ungulates. Epididymis was well-developed and divided with head, body and tail parts. On the tip of penis, there was a urethral process. At the necropsy of a 20-month-old and nulliparous giraffe, ovaries, oviducts, two uterine horns with a septum and a cervix were distinctively shown. Understanding reproductive organs of giraffes would be beneficial to succeed in artificial breeding on this species especially in the difficult situation of importing hoofed animals.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.47.1-47
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• 2001

The drilling process has a great importance for the production technology due to its widerspread use in the manufacturing industry. In order to enhance a maximum production rate and prevent the drill from the damage, it is important to monitor and control the drilling system. Thrust force and cutting torque are the main output variables in the design of drilling control systems. In this paper, an alternative estimation method of thrust force by using flexible neural networks is proposed. Flexible neural network uses the sigmoid activation function with adjustable parameter in order to enhance the approximation accuracy ...

• Journal of Applied and Pure Mathematics
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• v.4 no.5_6
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• pp.269-286
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• 2022

In this article we exhibit univariate and multivariate quantitative approximation by Kantorovich-Choquet type quasi-interpolation neural network operators with respect to supremum norm. This is done with rates using the first univariate and multivariate moduli of continuity. We approximate continuous and bounded functions on ℝ^N , N ∈ ℕ. When they are also uniformly continuous we have pointwise and uniform convergences. Our activation functions are induced by the arctangent, algebraic, Gudermannian and generalized symmetrical sigmoid functions.