• 대한전자공학회논문지TC
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• 제39권1호
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• pp.42-48
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• 2002

본 논문에서는 직접확산 코드분할 다중접속 시스템의 PN 코드 동기획득에서 다중 임계치를 사용하는 결정방식에 대해서 설명하기로 한다. 본 논문에서 제안하는 다중 임계치 결정방식을 이중적분 직렬동기획득 알고리듬에 적용하고, 평균 동기획득 시간 측면에서 분석한다. 분석을 위해, 제안된 방식의 수학적 모델을 제시하고, IMT-2000 채널모델에서 시뮬레이션을 수행한다. 수식적인 분석 결과는 제안된 방식이 한 쌍의 임계치를 사용하는 기존 방식에 비해 평균 동기획득 시간에서 약 0.2초 내지 0.5초 정도의 성능향상을 가져오는 것을 보여준다. 이것은 다중 임계치가 하나의 임계치를 사용함으로써 발생했던 탐색 성능 저하를 보상할 수 있기 때문이라고 볼 수 있다.

• 지능정보연구
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• 제9권2호
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• pp.51-63
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. There are several treatments to deal with the incomplete data problem such as case deletion and single imputation. Those approaches are simple and easy to implement but they may provide biased results. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.614-619
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• 2005

The object of this study was to presented regression equations for obtaining simply and quickly values of water quality items, BOD, COD, T-N, and T-P. Regression equations obtained to analyze relationships for water quality items to land use types in agricultural reservoir watersheds. In order to derive regression equations, a multiple linear regression analysis was used in this studying reservoirs. In this regression analysis, a independent values used land used types and dependent values used BOD, COD, T-N, T-P values in water quality items. The results showed that numbers of regression equation ranging above 0.90 in a multiple correlation coefficient (MCC) was not found, ranging from 0.70 to 0.90 in the MCC was 6, ranging from 0.40 to 0.70 in the MCC was 20, and ranging from 0.20 to 0.40 in the MCC was 4. The results of this study can be used as a basic information for evaluating simply and quickly water quality for proposing and designing steps in water quality policy.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2859-2870
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• 2022

Because nuclear power plants (NPPs) are safety-critical infrastructure, it is essential to increase their safety and minimize risk. To reduce human error and support decision-making by operators, several artificial-intelligence-based diagnosis methods have been proposed. However, because of the nature of data-driven methods, conventional artificial intelligence requires large amount of measurement values to train and achieve enough diagnosis resolution. We propose a graph neural network (GNN) based accident diagnosis algorithm to achieve high diagnosis resolution with limited measurements. The proposed algorithm is trained with both the knowledge about physical correlation between components and measurement values. To validate the proposed methodology has a sufficiently high diagnostic resolution with limited measurement values, the diagnosis of multiple accidents was performed with limited measurement values and also, the performance was compared with convolution neural network (CNN). In case of the experiment that requires low diagnostic resolution, both CNN and GNN showed good results. However, for the tests that requires high diagnostic resolution, GNN greatly outperformed the CNN.

• 대한수학회보
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• 제54권2호
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• pp.593-605
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• 2017

In this paper, we consider some normality criteria concerning multiple values. Let $\mathcal{F}$ be a family of meromorphic functions defined in a domain D. Let k be a positive integer and ${\psi}(z){\not\equiv}0$, ${\infty}$ be a meromorphic function in D. If, for each $f{\in}\mathcal{F}$ and $z{\in}D$, (1) $f(z){\neq}0$, and all of whose poles are multiple; (2) all zeros of $f^{(k)}(z)-{\psi}(z)$ have multiplicities at least k + 3 in D; (3) all poles of ${\psi}(z)$ have multiplicities at most k in D, then $\mathcal{F}$ is normal in D.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.1051-1059
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• 2014

In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.925-936
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• 2009

자료의 독립성 가청 하에서 EM 알고리즘에 의한 경측치 대체 (imputation of missing values) 기법은 잘 알려져 있다. 그러나 공간자료를 다루는 응용문제에서는 독립성 가정이 확장된 마코프 랜덤 필드 (Markov random field; MRF) 하에서 다루어져야 할 것이다. 이에 본 논문에서는 마코프 랜덤 필드 모형 궁에서 다변량 자료 중에 다중의 결측치의 대체를 위한 EM 알고리즘을 제공한다. 이 기법은 몇 가지 현실척 가정하에서 결국 혼합모형에 의한 대체 기법 임을 보인다. 그리고 제공된 기법으로 3-변량으로 구성된 색조영상(color image)의 결측화소값 대체문제에 적용하여 그 유용성과 문제점을 밝히며, 문제정의 개선방안에 대해 논의한다.

• Structural Engineering and Mechanics
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• 제53권3호
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• pp.537-573
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• 2015

Multiple-step beams carrying intermediate lumped masses with/without rotary inertias are widely used in engineering applications, but in the literature for free vibration analysis of such structural systems; Bernoulli-Euler Beam Theory (BEBT) without axial force effect is used. The literature regarding the free vibration analysis of Bernoulli-Euler single-span beams carrying a number of spring-mass systems, Bernoulli-Euler multiple-step and multi-span beams carrying multiple spring-mass systems and multiple point masses are plenty, but that of Timoshenko multiple-step beams carrying intermediate lumped masses and/or rotary inertias with axial force effect is fewer. The purpose of this paper is to utilize Numerical Assembly Technique (NAT) and Differential Transform Method (DTM) to determine the exact natural frequencies and mode shapes of the axial-loaded Timoshenko multiple-step beam carrying a number of intermediate lumped masses and/or rotary inertias. The model allows analyzing the influence of the shear and axial force effects, intermediate lumped masses and rotary inertias on the free vibration analysis of the multiple-step beams by using Timoshenko Beam Theory (TBT). At first, the coefficient matrices for the intermediate lumped mass with rotary inertia, the step change in cross-section, left-end support and right-end support of the multiple-step Timoshenko beam are derived from the analytical solution. After the derivation of the coefficient matrices, NAT is used to establish the overall coefficient matrix for the whole vibrating system. Finally, equating the overall coefficient matrix to zero one determines the natural frequencies of the vibrating system and substituting the corresponding values of integration constants into the related eigenfunctions one determines the associated mode shapes. After the analytical solution, an efficient and easy mathematical technique called DTM is used to solve the differential equations of the motion. The calculated natural frequencies of Timoshenko multiple-step beam carrying intermediate lumped masses and/or rotary inertias for the different values of axial force are given in tables. The first five mode shapes are presented in graphs. The effects of axial force, intermediate lumped masses and rotary inertias on the free vibration analysis of Timoshenko multiple-step beam are investigated.

• East Asian mathematical journal
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• 제18권2호
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• pp.219-224
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• 2002

Recently the theory of the multiple Gamma functions, which were studied by Barnes and others a century ago, has been revived in the study of determinants of Laplacians. Here we are aiming at evaluating the values of the multiple Gamma functions ${\Gamma}_n(\frac{1}{2})$ in terms of the Hurwitz or Riemann Zeta functions.