• Journal of the Korean Physical Society
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• 제73권11호
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• pp.1774-1786
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• 2018

Phenotypic variation among clones (individuals with identical genes, i.e. isogenic individuals) has been recognized both theoretically and experimentally. We investigate the effects of phenotypic variation on evolutionary dynamics of a population. In a population, the individuals are assumed to be haploid with two genotypes : one genotype shows phenotypic variation and the other does not. We use an individual-based Moran model in which the individuals reproduce according to their fitness values and die at random. The evolutionary dynamics of an individual-based model is formulated in terms of a master equation and is approximated as the Fokker-Planck equation (FPE) and the coupled non-linear stochastic differential equations (SDEs) with multiplicative noise. We first analyze the deterministic part of the SDEs to obtain the fixed points and determine the stability of each fixed point. We find that there is a discrete phase transition in the population distribution when the probability of reproducing the fitter individual is equal to the critical value determined by the stability of the fixed points. Next, we take demographic stochasticity into account and analyze the FPE by eliminating the fast variable to reduce the coupled two-variable FPE to the single-variable FPE. We derive a quasi-stationary distribution of the reduced FPE and predict the fixation probabilities and the mean fixation times to absorbing states. We also carry out numerical simulations in the form of the Gillespie algorithm and find that the results of simulations are consistent with the analytic predictions.

• 스마트미디어저널
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• 제4권4호
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• pp.111-119
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• 2015

다양한 HMD(Head Mounted Display)의 등장으로 입체영상 제작은 VR(Virtual Reality)기술을 접목 가능하게 되었고 체감형, 몰입형 영상콘텐츠 제작의 활성화에 기여하고 있다. VR기반 영상콘텐츠는 애니메이션과 게임으로 시작하여 실사영상에 이르기까지 엔터테인먼트산업 전반으로 활용성을 넓혀가고 있으며 동시에 VR 영상콘텐츠 제작을 위한 솔루션 개발도 탄력을 받고 있다. 그러나 기존의 제작 솔루션 중 고정된 양안카메라 기반촬영은 사용자의 양안시차가 고정된다는 한계점을 가지고 있다. 이것은 제작자가 연출하고자 하는 표현을 제한할 뿐만 아니라 사용자입장에서의 시야조건이 고려되지 않아 입체감과 공간감을 충분히 느끼지 못할 수 있다. 본 논문은 실사 VR 영상콘텐츠 제작에서 발생하는 컨버전스 포인트(Convergence Point) 조절의 한계를 입체영상 제작의 후반작업 기술을 통하여 해결하고자 한다. 입체영상 후반작업에서 컨버전스 포인트 조절에 대한 유효성을 양안시차의 시각화를 통하여 분석하고 게임엔진에 적용하여 컨버전스 포인트가 사용자 임의로 조절 가능하도록 구현한다.

• Animal Bioscience
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• 제35권5호
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• 에너지공학
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• 제23권3호
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• pp.66-71
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• 2014

Oil is obviously vital for economic growth and industry development. This paper attempts to explore whether or not there is a inverted-U relationship between oil consumption and economic growth. To this end, we employ a panel data analysis with fixed effect or random effect models using the set of data from 61 countries for the year 1990-2008. In conclusion, a statistically significant inverted-U relationship between per capita consumption of oil and per capita GDP is found. However, the level of per capita GDP at the peak point of per capita oil consumption is estimated to be 65,072 in 2005 international constant dollars, which is much larger than economic scales of sampled countries. Thus, as per capita GDP grows, per capita oil consumption is predicted to increase until eventually reaching the peak.

• 대한안전경영과학회지
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• 제15권1호
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• pp.141-150
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• 2013

In this paper, the learnability of haptic icons was tested as a way of conveying turn-by-turn directions to users involved in navigation interactions with commercial smartphones. To do this, six most distinctive haptic icons were identified from those having different duration of each pulse, interval between pulses, and rhythm. Associations between the selected haptic icons and 3 pairs of navigation directions were analyzed using data gathered from 30 subjects by 7 point Likert scale. The haptic icons were then assigned to proper directions based on the results from that stereotype analysis. The results showed that the commercial smartphone with one linear motor at a fixed location is not capable of making hapticons to have clear directional stereotypes. The hapticons with poor stereotypes has no advantage in learnability compared to those of random assignment.

• 한국컴퓨터정보학회논문지
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• 제23권10호
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• pp.23-31
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• 2018

Recently, there have been many studies on machine learning. Among them, studies on reinforcement learning are actively worked. In this study, we propose a controller to control bicycle using DDPG (Deep Deterministic Policy Gradient) algorithm which is the latest deep reinforcement learning method. In this paper, we redefine the compensation function of bicycle dynamics and neural network to learn agents. When using the proposed method for data learning and control, it is possible to perform the function of not allowing the bicycle to fall over and reach the further given destination unlike the existing method. For the performance evaluation, we have experimented that the proposed algorithm works in various environments such as fixed speed, random, target point, and not determined. Finally, as a result, it is confirmed that the proposed algorithm shows better performance than the conventional neural network algorithms NAF and PPO.

• BMB Reports
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• 제54권10호
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• pp.489-496
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• 2021

Chromatin has highly organized structures in the nucleus, and these higher-order structures are proposed to regulate gene activities and cellular processes. Sequencing-based techniques, such as Hi-C, and fluorescent in situ hybridization (FISH) have revealed a spatial segregation of active and inactive compartments of chromatin, as well as the non-random positioning of chromosomes in the nucleus, respectively. However, regardless of their efficiency in capturing target genomic sites, these techniques are limited to fixed cells. Since chromatin has dynamic structures, live cell imaging techniques are highlighted for their ability to detect conformational changes in chromatin at a specific time point, or to track various arrangements of chromatin through long-term imaging. Given that the imaging approaches to study live cells are dramatically advanced, we recapitulate methods that are widely used to visualize the dynamics of higher-order chromatin structures.

• ETRI Journal
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• 제45권1호
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• 정보처리학회논문지B
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• 제10B권4호
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• pp.397-402
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• 2003

본 연구에서는 뉴우턴법의 고정점 알고리즘에 적응 조정이 가능한 학습 파라미터를 이용한 효율적인 신경망 기반 독립성분분석기법을 제안하였다. 이는 엔트로피 최적화 함수의 1차 미분을 이용하는 뉴우턴법의 고정점 알고리즘에서 학습율과 모멘트를 역혼합행렬의 경신 상태에 따나 적응조정되도록 함으로써 분리속도와 분리성능을 개선시키기 위함이다 제안된 기법을 256$\times$256 픽셀의 8개 지문과 512$\times$512 픽셀의 10개 영상으로부터 임의의 혼합행렬에 따라 발생되는 지문과 영상의 분리에 적용한 결과, 기존의 고정점 알고리즘에 의한 결과보다 우수한 분리성능과 빠른 분리속도가 있음을 확인하였다. 특히 제안된 알고리즘은 문제의 규모가 클수록 분리성능과 분리속도의 개선 정도가 큼을 확인하였다.

• 정보처리학회논문지B
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• 제9B권5호
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• pp.643-652
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• 2002

본 연구에서는 신경망 기반 독립성분분석의 분리성능을 개선하기 위해 할선법과 모멘트의 조합형 고정점 알고리즘을 제안하였다. 할선법은 독립성분 상호간의 정보를 최소화하는 목적함수의 근을 근사적으로 구함으로써 계산과정을 단순화하여 좀 더 개선된 분리성능을 얻기 위함이고, 모멘트는 계산과정에서 발생하는 발진을 억제하여 보다 빠른 분리속도를 얻기 위함이다. 이렇게 하면 할선법이 가지는 근사성에 따른 우수성과 과거의 속성을 반영하여 발진을 억제하는 모멘트의 우수성을 동시에 살릴 수 있다. 제안된 알고리즘을 $256\times{256}$ 픽셀의 8개 지문과 $512\times{512}$ 픽셀의 10개 영상으로부터 임의의 혼합행렬에 따라 생성된 복합지문과 복합영상을 각각 대상으로 시뮬레이션 한 결과, 뉴우턴법에 기초한 기존의 알고리즘과 할선법만에 기초한 알고리즘보다 각각 우수한 분리률과 빠른 분리속도가 있음을 확인하였다. 또한 할선법의 이용은 뉴우턴법을 이용한 고정점 알고리즘보다 초기값에도 덜 의존하며, 문제의 규모가 커짐에 따른 비현실적인 분리시간도 해결할 수 있음을 확인하였다.