• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.352-355
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• 1998

A musculotendon model is investigated to show muscle fatigue under the repeated functional electrical stimulation (FES). The normalized Hill-type model can predict the decline in muscle force. It consists of nonlinear activation and contraction dynamics including physiological concepts of muscle fatigue. A muscle fatigue as a function of the intracellular acidification, pHi is inserted into contraction dynamics to estimate the force decline. The computer simulation shows that muscle force declines in stimulation time and the change in the estimate of the optimal fiber length has an effect only on muscle time constant not on the steady-state tetanic force.

• 전력전자학회논문지
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• 제25권4호
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• pp.303-310
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• 2020

Estimating the accurate internal state of lithium ion batteries to increase their safety and efficiency is crucial. Various algorithms are used to estimate the internal state of a lithium ion battery, such as the extended Kalman filter and sliding mode observer. A state-space model is essential in using algorithms to estimate the internal state of a battery. Two principal methods are used to express the state-space model, namely, continuous time and discrete time. In this work, the extended Kalman filter is employed to estimate the internal state of a battery. Moreover, this work presents and analyzes the estimation performance of algorithms consisting of a continuous time state-space model and a discrete time state-space model through static and dynamic profiles.

• 국토계획
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• 제53권6호
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• pp.117-130
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• 2018

Heavy snow is a natural disaster that causes serious economic damage. Since snowfall has been increasing recently, there is a need for measures against heavy snowfall. In order to make a policy decision on heavy snowfall, it is necessary to estimate the precise amount of damage by heavy snowfall. The direct damage of the heavy snow is severe, however the indirect damage caused by the road congestion and the urban dysfunction is also serious. Therefore, it is necessary to estimate indirect damage of snowfall. The purpose of this study is to estimate the effects on the regional economy from the limitation in traffic logistics caused by heavy snow using the transport demand model and inoperability input-output Model. The result shows that the amount of production loss caused by the heavy snow is KRW 2,460 billion per year and if the period of snowfall removal is shortened by one day or two days, it could be reduced to KRW 1,219 or 2,787 billion in production loss.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.215-224
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• 2021

The purpose of this study is to estimate the factors that affect college students' drinking needs and spending. An analysis model to estimate the determinants affecting drinking needs was applied with a truncated Poisson model and a truncated negative binomial model. Tests to select more appropriate models of the two types were made using the comparison of log-likelihood function and the over-dispersion test. The analysis result was interpreted by applying the truncated negative binomial model as the truncated Poisson model showed over-dispersion. We also applied the Tobit model to analyze the determinantsthat affect college students' expenditure on drinking. According to the analysis, gender, grade, allowance and parental occupation were the factors influencing statistics, and gender, type of household income, and student religion were the factors influencing expenditure.

• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1061-1065
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• 2002

Sensors need to be implanted to obtain necessary information for LVAS (Left Ventricular Assist System) operations. Size of the sensors can prevent them from being implanted in a patient and reliabilities of the sensors are questionable for a long term use. In this wort we utilize a developed pump model to estimate flow and pressure difference across the pump without implanted sensors and present a method to obtain the physiological variables as aorta pressure and left ventricle pressure from the pump model and pulsatility of flow estimate or pressure difference estimate. These estimated variables can be used for LVAS control as an index or indices.

• 조명전기설비학회논문지
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• 제29권7호
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• pp.80-86
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• 2015

As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is needed to estimate power outputs of wind generation resources. As a result, geographic information such as latitude and longitude plays a key role to estimate power outputs of spatially distributed wind farms. In this paper, we introduce spatial correlation analysis to estimate the power outputs produced by wind farms that are geographically distributed. We present spatial correlation analysis of empirical power output data for the JEJU Island and ERCOT ISO (Texas) wind farms and propose the Correlation Decay Distance (CoDecDist) model based on geographic correlation analysis to enhance the estimation of wind power outputs.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.381-394
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• 2005

In order to estimate the damage of orchards due' to natural disasters such as typhoon, severe rain, freezing or frost, it is necessary to estimate the number of fruit bearing before and after the damage. To estimate the fruit bearing after the damages are easily done by delegations, but it cost too high to survey every insured farm household and calculate the fruit bearing before the damage. In this article, we suggest to use a random coefficient model to predict the numbers of fruit bearing in the orchards before the damage based on the tree age and the area information.

• Journal of applied mathematics & informatics
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• 제39권5_6호
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• pp.805-811
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• 2021

Currently, batteries use commonly as energy sources for mobile electric devices. Due to the high density of energy, the energy storage state of a battery is very important information. To know the battery's energy storage state, it is necessary to find out the open state voltage of the battery. The open state voltage calculates with a mathematical model, but the computation of the real time state is complicated and requires many calculations. Therefore, the state observer designs to estimate in real time the battery open-circuit voltage as disturbance including model error. Using the estimated open voltage and applying it to the state estimation algorithm, we can estimate the charge. In this study, we first estimate the open-circuit voltage and design an estimation algorithm for estimating the state of battery charge. This includes errors in the system model and has a robust characteristic to noise. It is possible to increase the precision of the charge state estimation.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• Asia Marketing Journal
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• 제21권3호
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• pp.47-64
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• 2019

We analyze and study competition in differentiated product market using public data source. Understanding competitive market structure is critical for firms to assess how their products compete against other firms in a given market. In this paper, we estimate consumer demand, extend clout and vulnerability framework, and study competition among multi-product manufacturers in differentiated product market. For our empirical analysis, we adopt choice-based aggregate demand model and estimate consumer demand while accounting for unobserved product characteristics. Once we estimate consumer demand, we compute full price elasticity matrix and investigate intra- and inter- manufacturer substitutions among consumers. This research offers a framework for marketers to analyze and understand market structures, leading them to informed decisions.