• International journal of advanced smart convergence
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• 제7권1호
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• pp.15-23
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• 2018

Spectrum allocation is a key operation in cognitive radio networks (CRNs), where secondary users (SUs) are usually selfish - to achieve itself utility maximization. In view of this context, much prior lit literature proposed spectrum allocation base on non-cooperative game models. However, the most of them proposed non-cooperative game models based on complete information of CRNs. In practical, primary users (PUs) in a dynamic wireless environment with noise uncertainty, shadowing, and fading is difficult to attain a complete information about them. In this paper, we propose a non-cooperative game joint hidden markov model scheme for spectrum allocation in CRNs. Firstly, we propose a new hidden markov model for SUs to predict the sensing results of competitors. Then, we introduce the proposed hidden markov model into the non-cooperative game. That is, it predicts the sensing results of competitors before the non-cooperative game. The simulation results show that the proposed scheme improves the energy efficiency of networks and utilization of SUs.

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.273-293
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• 2019

We consider the problem of model selection in multiple linear regression with outliers and non-normal error distributions. In this article, the robust model selection criterion is proposed based on the robust estimation method with the least absolute deviation (LAD). The proposed criterion is shown to be consistent. We suggest proposed criterion based algorithms that are suitable for a large number of predictors in the model. These algorithms select only relevant predictor variables with probability one for large sample sizes. An exhaustive simulation study shows that the criterion performs well. However, the proposed criterion is applied to a real data set to examine its applicability. The simulation results show the proficiency of algorithms in the presence of outliers, non-normal distribution, and multicollinearity.

• International journal of advanced smart convergence
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• 제7권4호
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• pp.57-65
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• 2018

Artificial neural network is inspired by the biological neural network. For simplicity, in computer science, it is represented as a set of layers. Many research has been made in evaluating the number of neurons in the hidden layer but still, none was accurate. Several methods are used until now which do not provide the exact formula for calculating the number of thehidden layer as well as the number of neurons in each hidden layer. In this paper model selection approach was presented. Proposed model is based on geographical analysis of decision boundary. Proposed model selection method is useful when we know the distribution of the training data set. To evaluate the performance of the proposed method we compare it to the traditional architecture on IRIS classification problem. According to the experimental result on Iris data proposed method is turned out to be a powerful one.

• KEPCO Journal on Electric Power and Energy
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• 제6권4호
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• pp.473-480
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• 2020

In this paper, we proposed a high frequency equivalent circuit considering parasitic impedance components for differential noise analysis on the input stage during DC-DC buck converter switching operation. Based on the proposed equivalent circuit model, we presented a method to measure parasitic impedance parameters included in DC bus plate, IGBT, and PCB track using the gain phase method of a network analyzer. In order to verify the validity of this model, a DC-DC prototype consisting of a buck converter, a signal analyzer, and a LISN device, and then resonance frequency was measured in the frequency range between 150 kHz and 30 MHz. The validity of the parasitic impedance measurement method and the proposed equivalent model is verified by deriving that the measured resonance frequency and the resonance frequency of the proposed high frequency equivalent model are the same.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.772-779
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• 2006

The new model proposed in this paper is the hidden Markov mesh model or the 2D HMM with the causality of top-down and left-right direction. With the addition of the causality constraint, two algorithms for the evaluation of a model and the maximum likelihood estimation of model parameters have been developed theoretically which are based on the forward-backward algorithm. It is a more natural extension of the 1D HMM than other 2D models. The proposed method will provide a useful way of modeling highly variable image patterns such as offline cursive characters.

• 경영과학
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• 제28권1호
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• pp.11-24
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• 2011

In this paper, we develop a new conceptual framework for finding new business opportunities in the cloud computing environment. We propose a service model framework for cloud computing business. In the service concept of the proposed business model, we categorize customer needs and service offering value, while we analyze customer behavior for developing revenue model. In addition, we analyze cloud computing market drivers for finding an evolution path of the proposed business model. Finally, we develop cloud computing business strategies for Korean IT service industry.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.106-111
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• 1994

We proposed a new variable sampling rate model which expresses the phenomena with both rapid and slow components. A method for determining the variable sampling rate and the older of the time series model was explained. The proposed variable sampling rate model was evaluated based oil an information criterion(AIC). Tile variable sampling rate model brought smaller an information criterion than one of a constant sampling rate model of conventional type, and was proved to be effective as a prediction model of the system with both rapid and slow components.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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• pp.99-101
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• 2003

Unsaturated hydraulic conductivity models have been widely used for the numerical modeling of water flow and contaminant transport in soils. In this study, a simple hydraulic conductivity model is developed by using information of particle-size distribution from the lognormal distribution model and its results are compared with those from the Kosugi-Mualem (KM) model. The accuracy of the proposed model is verified for observed data chosen from the international UNSODA database. Results showed that the proposed model produces adequate predictions of hydraulic conductivities. Performance of this model is generally better than the KM function.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.2-2
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• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• 대한토목학회논문집
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• 제13권4호
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• pp.131-140
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• 1993

기존의 Mualem의 Model III-1에서 공기가 공극으로 진입할 때 이에 대한 공극들의 방해효과를 설명하는 가중치(加重値) $P_a({\theta})$가 무차원 공극반경과 선형적 관계를 가진다는 가정을 바탕으로 하여 모형의 검정을 위하여 한 개의 주곡선이 필요한 새로운 모형을 개발하였다. 개발된 모형은 모형의 검정을 위하여 기존에 제시된 바 있는 한 개의 주곡선이 필요한 모형들보다 실측치를 잘 모의하며, 한쌍의 주곡선이 필요한 영역모형중에서 이력현상을 모형화하는 목적에 가장 부합한 Model III-1과의 비교에서 개발된 모형은 거의 같은 정확성을 가지면서 실측자료를 재현하고 있음을 알 수 있었다. 또한 개발된 모형은 비포화 흐름을 해석할 때 효율적으로 적용될 수 있음을 알 수 있었다.