• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2035-2042
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• 1997

We consider the design of soft decision functions for each stage of multistage detection for coherent demodulation in an asynchronous code-division multiple-access(CDMA) system. In particular, the sigmoid function, which is shown to be optimal under the mean square error(MSE) criterion, andmultilevel quantizers that best approximate the sigmoid function are derived. At each stage of multistage detection, the parameters of these decision functions are adjusted depending on estimated input statistics. Computer simulation results demonstrate that multistage detectors employing these soft decision functions perform considerably better than those with hard decision.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.177-186
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• 2005

This paper introduces nonlinear estimators with reduced complexity, and proposes the Bussgang blind equalization algorithm employing the nonlinear estimators. The proposed algorithm utilized the facts that the Bayesian estimator is well approximated to the sigmoid estimator in initial stage of equalization with closed eye and is well approximated to the threshold estimator under open eye condition. The proposed method adopts selectively one of the two nonlinear estimators, i.e., the sigmoid estimator and the threshold estimator, according to channel distortion level at each iteration. As a result, by using the sigmoid estimator with reduced constellation, the proposed scheme, as it is applied to blind equalization of high-order QAM signals, simplifies the computational complexity extremely, and enhances the blind convergence capability and steady-state performance.

• Steel and Composite Structures
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• v.30 no.6
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• pp.603-615
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• 2019

In the present work, free vibration of beams made of imperfect functionally graded materials (FGMs) including porosities is investigated. Because of faults during process of manufacture, micro voids or porosities may arise in the FGMs, and this situation causes imperfection in the structure. Therefore, material properties of the beams are assumed to vary continuously through the thickness direction according to the volume fraction of constituents described with the modified rule of mixture including porosity volume fraction which covers two types of porosity distribution over the cross section, i.e., even and uneven distributions. The governing equations of power law FGM (P-FGM) and sigmoid law FGM (S-FGM) beams are derived within the frame works of classical beam theory (CBT) and first order shear deformation beam theory (FSDBT). The resulting equations are solved using separation of variables technique and assuming FG beams are simply supported at both ends. To validate the results numerous comparisons are carried out with available results of open literature. The effects of types of volume fraction function, beam theory and porosity volume fraction, as well as the variations of volume fraction index, span to depth ratio and porosity volume fraction, on the first three non-dimensional frequencies are examined in detail.

• Advances in nano research
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• v.12 no.5
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• pp.441-455
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• 2022

This study explores the linear and nonlinear solutions of sigmoid functionally graded material (S-FGM) nanoplate with porous effects. A size-dependent numerical solution is established using the strain gradient theory and isogeometric finite element formulation. The nonlinear nonlocal strain gradient is developed based on the Reissner-Mindlin plate theory and the Von-Karman strain assumption. The sigmoid function is utilized to modify the classical functionally graded material to ensure the constituent volume distribution. Two different patterns of porosity distribution are investigated, viz. pattern A and pattern B, in which the porosities are symmetric and asymmetric varied across the plate's thickness, respectively. The nonlinear finite element governing equations are established for bending analysis of S-FGM nanoplates, and the Newton-Raphson iteration technique is derived from the nonlinear responses. The isogeometric finite element method is the most suitable numerical method because it can satisfy a higher-order derivative requirement of the nonlocal strain gradient theory. Several numerical results are presented to investigate the influences of porosity distributions, power indexes, aspect ratios, nonlocal and strain gradient parameters on the porous S-FGM nanoplate's linear and nonlinear bending responses.

• Annals of Coloproctology
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• v.34 no.6
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• pp.292-298
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• 2018

Purpose: This study compared the perioperative clinical outcomes of reduced-port laparoscopic surgery (RPLS) with those of conventional multiport laparoscopic surgery (MPLS) for patients with sigmoid colon cancer and investigated the safety and feasibility of RPLS performed by 1 surgeon and 1 camera operator. Methods: From the beginning of 2010 until the end of 2014, 605 patients underwent a colectomy for sigmoid colon cancer. We compared the characteristics, postoperative outcomes, and pathologic results for the patients who underwent RPLS and for the patients who underwent MPLS. We also compared the clinical outcomes of single-incision laparoscopic surgery (SILS) and 3-port laparoscopic surgery. Results: Of the 115 patients in the RPLS group, 59 underwent SILS and 56 underwent 3-port laparoscopic surgery. The MPLS group included 490 patients. The RPLS group had shorter operating time ($137.4{\pm}43.2minutes$ vs. $155.5{\pm}47.9minutes$, P < 0.001) and shorter incision length ($5.3{\pm}2.2cm$ vs. $7.8{\pm}1.2cm$, P < 0.001) than the MPLS group. In analyses of SILS and 3-port laparoscopic surgery, the SILS group showed younger age, longer operating time, and shorter incision length than the 3-port surgery group and exhibited a more advanced T stage, more lymphatic invasion, and larger tumor size. Conclusion: RPLS performed by 1 surgeon and 1 camera operator appears to be a feasible and safe surgical option for the treatment of patients with sigmoid colon cancer, showing comparable clinical outcomes with shorter operation time and shorter incision length than MPLS. SILS can be applied to patients with favorable tumor characteristics.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.56-59
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• 2017

CNN(Convolutional Neural Network)을 이용하여 발화 주제 다중 분류 task를 multi-labeling 방법과, cluster 방법을 이용하여 수행하고, 각 방법론에 MSE(Mean Square Error), softmax cross-entropy, sigmoid cross-entropy를 적용하여 성능을 평가하였다. Network는 음절 단위로 tokenize하고, 품사정보를 각 token의 추가한 sequence와, Naver DB를 통하여 얻은 named entity 정보를 입력으로 사용한다. 실험결과 cluster 방법으로 문제를 변형하고, sigmoid를 output layer의 activation function으로 사용하고 cross entropy cost function을 이용하여 network를 학습시켰을 때 F1 0.9873으로 가장 좋은 성능을 보였다.

• Tuberculosis and Respiratory Diseases
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• v.72 no.3
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• pp.318-322
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• 2012

Sarcoidosis is an inflammatory disease involving multiple-organs with an unknown cause. The new onset of sarcoidosis associated with therapeutic agents has been observed in 3 clinical settings; tumor necrosis factor antagonists in autoimmune rheumatologic diseases, interferon alpha with or without ribavirin in patients with chronic hepatitis C or melanoma, and antineoplastic agent-associated sarcoidosis in patients with hematologic malignancies. Here, we report a female patient who developed sarcoidosis after capecitabine treatment as an adjuvant chemotherapy for sigmoid colon cancer. To our knowledge, this is the first report of a capecitabine-induced sarcoidosis.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.115-122
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• 1994

The problems in back-propagation(BP) generally are learning speed and misclassification due to lacal minimum. In this paper, to solve these problems, the classical modified methods of BP are reviewed and an extension of the BP to compensate the sigmoide-prime function around the extremity where the actual output of a unit is close to zero or one is proposed. The proposed method is not onlu faster than the conventional methods in learning speed but has an advantage of setting variables easily because it shows good classification results over the vast and uncharted space about the variations of learning rate, etc.. And it is simple for hardware implementation.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.27-38
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• 1999

This paper proposes a high speed digital neuron processor which uses the residue number system, making the high speed operation possible without carry propagation,. Consisting of the MAC(Multiplier and with Accumulator) operation unit, quotient operation unit and sigmoid function operation unit, the neuron processor is designed through 0.8$\mu$m CMOS fabrication. The result shows that the new implemented neuron processor can run at the speed of 19.2 nSec and the size can be reduced to 1/2 compared to the neuron processor implemented by the real number operation unit.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.405-407
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• 2009

SVM(Support Vector Machine) is a classification method which is recently watched in mechanical learning system. Vapnik, Osuna, Platt etc. had suggested methodology in order to solve needed QP(Quadratic Programming) to realize SVM so that have extended application field. SVM find hyperplane which classify into 2 class by converting from input space converter vector to characteristic space vector using Kernel Function. This is very systematic and theoretical more than neural network which is experiential study method. Although SVM has superior generalization characteristic, it depends on Kernel Function. There are three category in the Kernel Function as Polynomial Kernel, RBF(Radial Basis Function) Kernel, Sigmoid Kernel. This paper has analyzed performance of SVM against kernel using virtual data.