• Wind and Structures
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• 제19권6호
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• pp.623-647
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• 2014

In this paper, a probability distribution which is consistent with the observed phenomenon at the roof corner and, also on other portions of the roof, of a low-rise building is proposed. The model is consistent with the choice of probability density function suggested by the statistical thermodynamics of open systems and turbulence modelling in fluid mechanics. After presenting the justification based on physical phenomenon and based on statistical arguments, the fit of alpha-stable distribution for prediction of extreme negative wind pressure coefficients is explored. The predictions are compared with those actually observed during wind tunnel experiments (using wind tunnel experimental data obtained from the aerodynamic database of Tokyo Polytechnic University), and those predicted by using Gumbel minimum and Hermite polynomial model. The predictions are also compared with those estimated using a recently proposed non-parametric model in regions where stability criterion (in skewness-kurtosis space) is satisfied. From the comparisons, it is noted that the proposed model can be used to estimate the extreme peak negative wind pressure coefficients. The model has an advantage that it is consistent with the physical processes proposed in the literature for explaining large fluctuations at the roof corners.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2173-2174
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• 2006

심음은 심장이 수축, 확장 시에 심장의 움직임과 혈류의 흐름에 의해 발생하는 음향이다. 심음은 여러 신호원으로 이루어져 있고, 매우 복잡하고 비고정적인 신호이다. 심장의 질환에 따라 심음의 소리는 다르게 나타난다. 심음을 구분하여 심장 질환의 유무를 판단하는 가장 기초적인 기준이 될 수 있다. 본 연구에서는 Support Vector Machine 기법을 이용하여 심음을 통한 심장 질환 판별 검출 알고리즘을 제안하였다. Support Vector Machine은 신경망의 한 종류이며 이진분류에서 좋은 성능을 보인다. 또한 Polynomial Radial Basis Function, Multi-Layer Perceptron Classifiers를 위한 대안적인 학습방법으로 사용된다. 이러한 특성을 사용하여 심음의 데이터들을 일정한 기준에 의하여 (+)데이터와 (-)데이터로 분리한 후, 각 데이터들을 학습시켜 최적의 데이터를 만든다. 이후 각 데이터들은 점층적인 추가 학습을 시킴으로써 적은 양의 학습 데이터만으로도 높은 분류 성능을 표현할 수 있다. 이 연구에서 제안된 SVM을 실제 심음 데이터에 적용한 실험에서 심장 질환의 유무 판별에 우수한 성능을 보임을 확인할 수 있을 것으로 판단된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.120-122
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• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• 한국지진공학회논문집
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• 제22권4호
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• pp.245-251
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• 2018

In this paper, we address some issues in existing seismic hazard closed-form equations and present a novel seismic hazard equation form to overcome these issues. The presented equation form is based on higher-order polynomials, which can well describe the seismic hazard information with relatively high non-linearity. The accuracy of the proposed form is illustrated not only in the seismic hazard data itself but also in estimating the annual probability of failure (APF) of the structural systems. For this purpose, the information on seismic hazard is used in representative areas of the United States (West : Los Angeles, Central : Memphis and Kansas, East : Charleston). Examples regarding the APF estimation are the analyses of existing platform structure and nuclear power plant problems. As a result of the numerical example analyses, it is confirmed that the higher-order-polynomial-based hazard form presented in this paper could predict the APF values of the two example structure systems as well as the given seismic hazard data relatively accurately compared with the existing closed-form hazard equations. Therefore, in the future, it is expected that we can derive a new improved APF function by combining the proposed hazard formula with the existing fragility equation.

• 한국전산구조공학회논문집
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• 제23권2호
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• pp.165-173
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• 2010

본 논문에서는 비동질 탄성무한공간에 대한 비례경계유한요소법의 동적강도행렬을 해석적으로 유도하였다. 해석영역의 비동질성은 비동질파라메터를 지수로 하는 멱함수로 고려하였다. 동적강도행렬은 진동수영역에서 다항식으로 점근전개한 후, 방사조건을 만족시키도록 하여 각 다항식의 계수를 구하는 과정을 통하여 유도되었다. 얻어진 동적강도행렬의 타당성을 검증하기 위해 정확해가 알려져 있는 대표적인 문제에 대하여 비동질파라메터의 값을 변화시키면서 수치해석을 수행하였다. 그 결과 유도된 동적강도행렬이 비동질공간에 대한 특성을 적절하게 반영하는 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.2292-2309
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• 2017

Ciphertext policy attribute-based encryption (CP-ABE) is a useful cryptographic technology for guaranteeing data confidentiality but also fine-grained access control. Typically, CP-ABE can be divided into two classes: small universe with polynomial attribute space and large universe with unbounded attribute space. Since the learning with errors over rings (R-LWE) assumption has characteristics of simple algebraic structure and simple calculations, based on R-LWE, we propose a small universe CP-ABE scheme to improve the efficiency of the scheme proposed by Zhang et al. (AsiaCCS 2012). On this basis, to achieve unbounded attribute space and improve the expression of attribute, we propose a large universe CP-ABE scheme with the help of a full-rank differences function. In this scheme, all polynomials in the R-LWE can be used as values of an attribute, and these values do not need to be enumerated at the setup phase. Different trapdoors are used to generate secret keys in the key generation and the security proof. Both proposed schemes are selectively secure in the standard model under R-LWE. Comparison with other schemes demonstrates that our schemes are simpler and more efficient. R-LWE can obtain greater efficiency, and unbounded attribute space means more flexibility, so our research is suitable in practices.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.52-58
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• 2005

We have developed a Group Method of Data Handling (GMDH) type algorithm for designing multi-layered neural networks. The algorithm is general enough that it will accept any number of inputs and any sized training set. Each neuron of the resulting network is a function of two of the inputs to the layer. The equation for each of the neurons is a quadratic polynomial. Several forms of the equation are tested for each neuron to make sure that only the best equation of two inputs is kept. All possible combinations of two inputs to each layer are also tested. By carefully testing each resulting neuron, we have developed an algorithm to keep only the best neurons at each level. The algorithm's goal is to create as accurate a network as possible while minimizing the size of the network. Software was developed to train and simulate networks using our algorithm. Several applications were modeled using our software, and the result was that our algorithm succeeded in developing small, accurate, multi-layer networks.

• 전기학회논문지
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• 제64권9호
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• pp.1347-1355
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• 2015

In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition performance. Honda/UCSD database consists of 20 people, with 5 poses per person for a total of 500 face images. Extracted image consists of 5 poses using Multiple-Space PCA and each pose is performed by using (2D)²PCA for performing pose classification. Linear polynomial function is used as connection weight of RBFNNs Pattern Classifier and parameter coefficient is set by using Particle Swarm Optimization for model optimization. Proposed (2D)²PCA-based face pose classification performs recognition performance with PCA, (2D)²PCA and RBFNNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2686-2708
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• 2020

This paper investigates the energy efficiency of energy harvesting (EH) bidirectional cooperative sensor networks, in which the considered system model enables the uplink information transmission from the sensor (SN) to access point (AP) and the energy supply for the amplify-and-forward (AF) relay and SN using power-splitting (PS) or time-switching (TS) protocol. Considering the minimum EH activation constraint and quality of service (QoS) requirement, energy efficiency is maximized by jointly optimizing the resource division ratio and transmission power. To cope with the non-convexity of the optimizations, we propose the low complexity iterative algorithm based on fractional programming and alternative search method (FAS). The key idea of the proposed algorithm first transforms the objective function into the parameterized polynomial subtractive form. Then we decompose the optimization into two convex sub-problems, which can be solved by conventional convex programming. Simulation results validate that the proposed schemes have better output performance and the iterative algorithm has a fast convergence rate.

• 충청수학회지
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• 제29권1호
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• pp.73-82
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• 2016

The utility of exponential generating functions is that they are relevant for combinatorial problems involving sets and subsets. Sequences of polynomials play a fundamental role in applied mathematics, such sequences can be described using the exponential generating functions. The actuarial polynomials ${\alpha}^{({\beta})}_n(x)$, n = 0, 1, 2, ${\cdots}$, which was suggested by Toscano, have the following exponential generating function: $${\limits\sum^{\infty}_{n=0}}{\frac{{\alpha}^{({\beta})}_n(x)}{n!}}t^n={\exp}({\beta}t+x(1-e^t))$$. A linear functional on polynomial space can be identified with a formal power series. The set of formal power series is usually given the structure of an algebra under formal addition and multiplication. This algebra structure, the additive part of which agree with the vector space structure on the space of linear functionals, which is transferred from the space of the linear functionals. The algebra so obtained is called the umbral algebra, and the umbral calculus is the study of this algebra. In this paper, we investigate some umbral representations in the actuarial polynomials.