• 한국정보통신학회논문지
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• 제13권4호
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• pp.727-736
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• 2009

본 논문에서는 모바일 벡터 그래픽 가속기용 역코사인 연산 회로를 설계하였다. 모바일 그래픽스 응용은 기존 데스크 톱 컴퓨터에 비해 면적, 연산 시간, 전력 소모와 정밀도 측면에서 제약이 크다. 설계한 역코사인 함수 회로는 연산시간과 정밀도 조건을 만족하기 위해 IEEE 표준 부동 소수점 데이터 형식을 사용하며, 계수 테이블을 사용하는 2차 다항식 근사 기법을 채택하였으며, 하드웨어 공유 기법을 통해 면적을 감소시켰다. 역코사인 회로는 약 15,280개의 게이트로 구성되며, $0.35{\mu}m$ CMOS 공정 조건에서 약 125 Mhz의 동작 주파수를 가진다. 7개의 클록 사이클에 역코사인 함수를 구현하므로, 설계된 회로는 약 17.85 MOPS의 연산 성능을 갖고 있어서 OpenVG 프로세서에 적용이 가능하다. 또한 융통성 있는 구조 특성으로 설계된 회로는 ROM 내용의 교체와 속규모의 하드웨어 변경을 통해 지수함수, 삼각함수, 로그 함수와 같은 다른 초월함수에 적용이 가능하다.

• Journal of Ecology and Environment
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• 제33권2호
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• pp.165-173
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• 2010

Soil respiration ($R_S$) is a critical component of the annual carbon balance of forests, but few studies thus far have attempted to evaluate empirical regression models in $R_S$. The principal objectives of this study were to evaluate the relationship between $R_S$ rates and soil temperature (ST) and soil water content (SWC) in soil from a cool-temperate deciduous broad-leaved forest, and to evaluate empirical regression models for the prediction of $R_S$ using ST and SWC. We have been measuring $R_S$, using an open-flow gas-exchange system with an infrared gas analyzer during the snowfree season from 1999 to 2001 at the Takayama Forest, Japan. To evaluate the empirical regression models used for the prediction of $R_S$, we compared a simple exponential regression (flux = $ae^{bt}$Eq. [1]) and two polynomial multiple-regression models (flux = $ae^{bt}{\times}({\theta}{\nu}-c){\times}(d-{\theta}{\nu})^f:$ Eq. [2] and flux = $ae^{bt}{\times}(1-(1-({\theta}{\nu}/c))^2)$: Eq. [3]) that included two variables (ST: t and SWC: ${\theta}{\nu}$) and that utilized hourly data for $R_S$. In general, daily mean $R_S$ rates were positively well-correlated with ST, but no significant correlations were observed with any significant frequency between the ST and $R_S$ rates on periods of a day based on the hourly $R_S$ data. Eq. (2) has many more site-specific parameters than Eq. (3) and resulted in some significant underestimation. The empirical regression, Eq. (3) was best explained by temporal variations, as it provided a more unbiased fit to the data compared to Eq. (2). The Eq. (3) (ST $\times$ SWC function) also increased the predictive ability as compared to Eq. (1) (only ST exponential function), increasing the $R^2$ from 0.71 to 0.78.

• 응용통계연구
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• 제16권1호
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• pp.87-100
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• 2003

서로 연관관계에 있는 실제의 통계자료들은 동태적, 확률적 동시발생적으로 유발되며, 이로 인해 한 자료의 변동이 다른 자료에 미치는 영향은 같은 기간 뿐 아니라 시차를 두고 여러 기간에 걸쳐 지속되며 조정되어 간다. 그러나 일반적인 선형, 비선형 통계모형을 사용하여 현실동향을 분석하는 경우 자료의 이러한 특성에서 오는 시차관계를 통상 무시함으로써 변수 사이의 관계는 같은 기간 내에 결정되어야 하는 제약이 가해지게 된다. 그 결과 시간이 흐름에 따라 이들의 관계가 변화하는 과정이나 한 변수의 변동이 다른 변수에 미치는 장기적 영향도 추정할 수 없을 뿐 아니라 현실여건의 변동이나 전개과정을 설명하는 데도 큰 결함을 갖게 된다. 시차관계가 존재하는 변수에 실제 여건에 합당한 시차구조가 설정되면 현실이 정확히 반영되고, 모형에 내재된 변수들의 장단기 변동상황과 동태적 적응과정이 파악됨과 동시에 다양한 분석이 가능해지므로 모형의 활용도는 높아지게 된다.

• 한국인터넷방송통신학회논문지
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• 제15권6호
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• pp.257-266
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• 2015

비 볼록 발전비용함수에 대한 최적화 문제는 다항시간으로 해를 구하는 알고리즘이 알려져 있지 않아 전기분야에서는 부득이 2차 함수만을 사용하고 있다. 본 논문은 비 볼록 발전비용함수의 경제급전 최적화 문제에 대한 밸브지점 최적화 알고리즘을 제안하였다. 제안된 알고리즘은 초기 치로 최대 발전량 $P_i{\leftarrow}P_i^{max}$로 설정하고, 평균 발전단가가 $_{max}\bar{c}_i$인 발전기 i의 발전량을 밸브지점 $P_{ik}$로 감소시키는 방법을 적용하였다. 제안된 알고리즘을 13과 40-발전기 데이터에 적용한 결과 기존의 휴리스틱 알고리즘보다 좋은 성능을 보였다. 따라서 비 볼록 발전비용함수의 경제급전문제 최적 해는 각 발전기의 밸브지점 발전량으로 수렴함을 보였다.

• 한국시뮬레이션학회논문지
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• 제25권1호
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• pp.1-9
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• 2016

본 연구는 공대공 미사일 조종날개의 공력 및 구조를 동시에 고려한 구동력 최소화에 대한 최적화를 수행하였다. 본 연구에서는 조종날개의 공력 및 구조적 특성을 동시에 고려하기 위하여 공력-구조 연계 시뮬레이션을 사용하였으며 공력 및 구조 시뮬레이션에 각각의 전용 소프트웨어를 사용하고자 비정상-약결합 방식 연계기법을 적용하였다. 전역 최적화에는 많은 반복 계산이 필요하므로 빠른 계산을 위하여 수학적 모델링을 이용하였으며 이를 위하여 면 중앙 합성 실험계획법으로 실험점을 선정하였다. 선정된 실험점 및 그에 대한 공력-구조 연계 시뮬레이션 결과를 토대로 2차 다항식 반응면을 생성하였으며 생성된 수학적 모델링을 이용, 유전자 알고리즘 기반 전역최적 설계를 수행하였다. 최적화 목적함수는 마하 0.7 및 마하 2.0 사이의 압력 중심점 이동거리 최소화로 설정하였으며 최적화 결과 압력 중심점 이동거리가 7.5% 감소된 최적형상을 도출하였다.

• 한국지구과학회지
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• 제34권5호
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• pp.393-401
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• 2013

Spherical harmonics power spectrum of the geopotential field of Gaussian-bell type on the sphere was investigated using integral formula that is associated with Legendre polynomials. The geopotential field of Gaussian-bell type is defined as a function of sine of angular distance from the bell's center in order to guarantee the continuity on the global domain. Since the integral-formula associated with the Legendre polynomials was represented with infinite series of polynomial, an estimation method was developed to make the procedure computationally efficient while preserving the accuracy. The spherical harmonics power spectrum was shown to vary significantly depending on the scale parameter of the Gaussian bell. Due to the accurate procedure of the new method, the power (degree variance) spanning over orders that were far higher than machine roundoff was well explored. When the scale parameter (or width) of the Gaussian bell is large, the spectrum drops sharply with the total wavenumber. On the other hand, in case of small scale parameter the spectrum tends to be flat, showing very slow decaying with the total wavenumber. The accuracy of the new method was compared with theoretical values for various scale parameters. The new method was found advantageous over discrete numerical methods, such as Gaussian quadrature and Fourier method, in that it can produce the power spectrum with accuracy and computational efficiency for all range of total wavenumber. The results of present study help to determine the allowable maximum scale parameter of the geopotential field when a Gaussian-bell type is adopted as a localized function.

• 전기학회논문지
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• 제63권5호
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• pp.676-682
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• 2014

In this paper, precipitation echo(PRE) and non-precipitaion echo(N-PRE)(including ground echo and clear echo) through weather radar data are identified with the aid of neuro-fuzzy algorithm. The accuracy of the radar information is lowered because meteorological radar data is mixed with the PRE and N-PRE. So this problem is resolved by using RBFNN and judgement module. Structure expression of weather radar data are analyzed in order to classify PRE and N-PRE. Input variables such as Standard deviation of reflectivity(SDZ), Vertical gradient of reflectivity(VGZ), Spin change(SPN), Frequency(FR), cumulation reflectivity during 1 hour(1hDZ), and cumulation reflectivity during 2 hour(2hDZ) are made by using weather radar data and then each characteristic of input variable is analyzed. Input data is built up from the selected input variables among these input variables, which have a critical effect on the classification between PRE and N-PRE. Echo judgment module is developed to do echo classification between PRE and N-PRE by using testing dataset. Polynomial-based radial basis function neural networks(RBFNNs) are used as neuro-fuzzy algorithm, and the proposed neuro-fuzzy echo pattern classifier is designed by combining RBFNN with echo judgement module. Finally, the results of the proposed classifier are compared with both CZ and DZ, as well as QC data, and analyzed from the view point of output performance.

• 전기학회논문지
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• 제66권2호
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• pp.416-424
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• 2017

In this study, we propose a design of digits recognition system based on RBFNNs through a comparative study of pre-processing algorithms in order to recognize digits in handwritten. Histogram of Oriented Gradient(HOG) is used to get the features of digits in the proposed digits recognition system. In the pre-processing part, a dimensional reduction is executed by using Principal Component Analysis(PCA) and (2D)2PCA which are widely adopted methods in order to minimize a loss of the information during the reduction process of feature space. Also, The architecture of radial basis function neural networks consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, the connection weights are used as the extended type of polynomial expression such as constant, linear, quadratic and modified quadratic. By using MNIST handwritten digit benchmarking database, experimental results show the effectiveness and efficiency of proposed digit recognition system when compared with other studies.

• Food Science and Biotechnology
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• 제17권6호
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• pp.1316-1321
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• 2008

This study was conducted to develop a model to describe the effect of antimicrobials [potassium sorbate (PS), potassium lactate (PL), and combined PL and sodium diacetate (SDA, PLSDA)] on the growth parameters of Listeria monocytogenes such as specific growth rate (SGR) and lag phase periods (LT) in air-dried raw sausages as a function of storage temperature (4, 10, 16, and $25^{\circ}C$). Results showed that the SGR of L monocytogenes was dependent on the storage temperature and level of antimicrobials used. The most effective treatment was the 4% PLSDA, followed by the 2% PLSDA and 4% PL and 0.2% PS exhibited the least antimicrobial effect. Increased growth rates were observed with increasing storage temperatures from 4 to $25^{\circ}C$. The growth data were fitted with a Gompertz equation to determine the SGR and LT of the L. monocytogenes. Six polynomial models were developed for the SGR and LT to evaluate the effect of PS (0.1, 0.2%) and PL (2,4%) alone and PLSDA (2, 4%) on the growth kinetics of L. monocytogenes from 4 to $25^{\circ}C$.

• 한국기계가공학회지
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• 제20권5호
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• pp.85-95
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• 2021

Structure design sensitivity was evaluated using the orthogonal array experimental method for passive-type deck support frame (DSF) developed for float-over installation of the offshore plant. Moreover, approximation characteristics were also reviewed based on various meta-models. The minimum weight design of the DSF is significantly important for securing both maneuvering performance and buoyancy of a ship equipped with the DSF and guaranteeing structural design safety. The performance strength of the passive type DSF was evaluated through structure analysis based on the finite element method. The thickness of main structure members was applied to design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experimental method and analysis of variance. The optimum design case was also identified from the orthogonal array experiment results. Various meta-models, such as Chebyshev orthogonal polynomial, Kriging, response surface method, and radial basis function-based neural network, were generated from the orthogonal array experiment results. The results of the orthogonal array experiment were validated using the meta-modeling results. It was found that the radial basis function-based neural network among the meta-models could approximate the design space of the passive type DSF with the highest accuracy.