• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.171-185
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• 2006

A sophisticated reliability analysis method is proposed to evaluate the reliability of real nonlinear complicated dynamic structural systems excited by short duration dynamic loadings like earthquake motions by intelligently integrating the response surface method, the finite element method, the first-order reliability method, and the iterative linear interpolation scheme. The method explicitly considers all major sources of nonlinearity and uncertainty in the load and resistance-related random variables. The unique feature of the technique is that the seismic loading is applied in the time domain, providing an alternative to the classical random vibration approach. The four-parameter Richard model is used to represent the flexibility of connections of real steel frames. Uncertainties in the Richard parameters are also incorporated in the algorithm. The laterally flexible steel frame is then reinforced with reinforced concrete shear walls. The stiffness degradation of shear walls after cracking is also considered. The applicability of the method to estimate the reliability of real structures is demonstrated by considering three examples; a laterally flexible steel frame with fully restrained connections, the same steel frame with partially restrained connections with different rigidities, and a steel frame reinforced with concrete shear walls.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1175-1183
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• 2001

In this paper, we use hyper chaos circuit which is made through the phase differences which is generated during the process of weak-coupling of CNN between two and more chaos attractors. Notwithstanding the complexity of the hyper chaos, we could do the synchronization and according to it, Secure communication through this method coo]d be accomplished. On this research, we configurated 2-double scroll and 3-double scroll circuit ,not using Chua circuit, but SC-CNN(State-Controlled CNN) which is more flexible to configure the system.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.45-48
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• 2002

무선 이동통신환경에서는 시간에 따라 네트워크에 의한 데이터 손실, 일관성 없는 패킷의 도착 간격 등과 같은 문제와 전송 속도의 저하가 발생함으로써 일정한 수준의 QoS 를 제공하기 어렵다. 이러한 문제점에 대처하기 위하여 다중 비트율 코딩, 트랜스코딩 등과 같은 기술이 제안되었다. 그러나 이러한 방식들은 서버의 과도한 연산량 요구나 저장 공간 낭비라는 단점을 가지고 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 다중 비트율 코딩 방식과 스케일러블 코딩 방식을 결합하여 네트워크 QoS 변화에 유연하게 적응될 수 있는 방식을 제시한다. 기존의 심플 혹은 메인 프로파일이 네트워크의 상태가 일정하다는 것을 전제로 하는 반면, 스케일러블 프로파일은 기본 데이터와 부가 데이터를 분리하여 하나의 파일로 관리되므로 서버의 연산량을 줄이고, 저장 공간도 절약한다. 또한 같은 스트림에 대해서도 단말기의 능력에 따라서 부가 데이터를 복호화 할지를 결정할 수 있어 여러 사용자에게 같은 스트림 데이터를 전송할 수 있는 장점이 있다.

• Journal of Adhesion and Interface
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• v.22 no.1
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• pp.8-15
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• 2021

In this study, a polyol was prepared using Jeffamine D-400 as a propylene glycol-based diamine to impart flexibility to the urethane-modified epoxy, and a urethane-modified epoxy was synthesized using the polyol. Urethane-modified epoxy synthesized with existing Bisphenol A diglycidyl ether (BADGE) epoxy, a curing agent, and a curing accelerator are mixed to prepare an epoxy adhesive, and shear strength is measured by measuring adhesion strength. As a result, shear strength and shear elongation tended to increase. These results are due to the high crosslinking density. It is believed that it can be applied to structural adhesives that are restricted in use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.93-98
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• 2017

The fixing behaviors of raw silk yarns treated with melamine and formaldehyde at a molar ratio of 1:3 for trimethylolmelamine were investigated. Sericin was fixed during the fixing process, but a part of sericin I was removed simultaneously by hot water. The weight losses by fixing and the degumming losses by degumming greatly decreased with increasing concentrations of melamine and formaldehyde. The silk yarns fixed with 0.011 M melamine and 0.033M formaldehyde were significantly degummed due to the insufficient fixation of sericin and the alkaline hydrolysis of sericin by sodium carbonate during the degumming process. On the other hand, the silk yarns fixed with 0.055M melamine and 0.165M formaldehyde were degummed slightly (the degumming losses of 3-8%) due to the strong fixation of sericin, which might result from the many cross-linkages between the sericin I molecules, which were formed by trimethylolmelamine. Those fixed with the fixing solution containing 15% owf softener showed the lowest weight and degumming losses because under the condition of 15% owf softener, the cation of the softener can effectively form ionic bonds with the negatively charged side chain of aspartic acid in sericin. In addition, van der Waals' forces may be also formed between the hydrophobic tail of the softener and the hydrophobic region of sericin, which may help inhibit the removal of sericin I.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.269-269
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• 2020

수자원은 유역 내에서 제한적인 범위 내에서 무한하게 순환한다. 이러한 물의 순환의 특성을 지속적으로 파악하는 것은 지속적인 수자원 확보, 자연 환경에 대한 변화를 유연하게 대처할 수 있는 가장 중요한 연구 중 하나이다. 유역 내에 물의 유입은 대표적으로 강우량이 있고 유출로는 하천 및 지하수의 유출량과, 증발산량이 있다. 유입의 형태와 지면의 상태에 의해 다양한 유출 특성이 나타나기 때문에 지면 내에서의 물의 이동 특성을 분석하는 것은 필수적이다. 본 연구에서는 토양수분량을 지속적으로 측정하여 토양내의 물의 저류량을 실증적으로 추정하였으며 초기 토양수분량과 토양 저류량의 관계를 분석하였다. 또한 유역내의 얼마만큼의 강우량이 토양 내에서 저류하고 유출 발생에 기여하는지에 대해 분석하고자 하였다. 이를 위해 토양수분량과 강우량이 안정적으로 측정되고 있는 2018, 2019년 설마천 유역에 적용하였다. 특히 선정된 설마천 유역은 증발산량과 유역 하단부에 유량 관측소가 존재하여 물수지 분석에 유리한 조건을 가지고 있어 유역 내에 물 흐름에 정량적으로 비교 및 파악할 수 있는 지역이다. 사양토 성질을 가진 설마천 유역은 20%때의 습윤 구간에서 중력에 의한 직접유출이 발생하며 이때를 기준으로 초기토양수분과 선행토양수분량의 조건에 따라 토양내의 저류량의 거동의 경향성이 뚜렷하게 나타났다. 향후 본 연구를 통해 각 유역의 토양 성질에 따른 토양 저류량을 파악하고 그에 따라 유출량 자료를 결합한다면 수자원 재해에 대한 예보 및 피해 저감 방안을 마련할 수 있을 것이라 판단된다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.185-192
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• 2006

This experiment was conducted to assess genetic diversity of waxy corn inbred lines and to identify SSR markers related to major characteristics affected kernel quality for improving waxy corn $F_1$ hybrid with good quality. Diversity of 64 waxy com inbred lines was evaluated using 30 microsatellite markers. The 30 microsatellite markers representing 30 loci in the maize genome detected polymorphisms among the 64 inbred lines and revealed 225 alleles with a mean of 7.5 alleles per primer. The polymorphism Information content (PIC) value ranged from 0.14 to 0.87, with an average of 0.69. Based on Nei's genetic distances, the 64 inbred lines were classified into 9 groups by the cluster analysis. The group I included 26 inbred lines (41%), other groups included 3 to 9 inbred lines. One-way analysis of variance was conducted to identify significant relationship between individual markers and major characteristics that affect kernel quality. The analysis showed that umc1019 was related to amylopectin and crude protein content, me 1020 to amylopectin content and peak viscosity, and bnlg1537 to 100-kernel weight, kernel length, and kernel width.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.155-159
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• 2004

Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.