• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Proceedings of the KAIS Fall Conference
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• 2011.05b
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• pp.757-760
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• 2011

본 논문의 주목적은 확률변수의 내삽을 이용하여 Mg-Al-Zn합금에 적합한 확률론적 피로균열전파모델을 평가하여 제시하는 것이다. 모델을 평가하기 위하여 최대하중조건을 변화시키면서 피로균열전파실험을 수행하였으며, 실험을 통해 통계적 피로데이터를 확보하였다. 균열성장의 불확실성을 묘사하기 위하여 실험적 피로균열전파모델에 확률변수를 도입한 확률론적 피로균열전파모델을 제안하였으며, 각 모델의 파라미터는 최우추정법으로 추정하였다. 제안된 모델의 적합성을 평가하기 위하여 균열성장에 따른 확률변수의 내삽데이터를 이용하였으며, 평가한 결과 Mg-Al-Zn합금에 적합한 모델은 '확률론적 Paris-Erdogan모델'과 '확률론적 Walker모델'임을 규명하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1386-1392
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• 2006

This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to WWW of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modelling in informatics.

• KSBB Journal
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• v.21 no.4
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• pp.231-235
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• 2006

This study is a numerical representative modeling analysis for the application of the process that unravels networks between cells in genetics to web of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modeling in informatics

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.4
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• pp.379-386
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• 2012

The primary aim of this paper was to evaluate several probabilistic fatigue crack propagation models using the residual of a random variable, and to present the model fit for probabilistic fatigue behavior in Mg-Al-Zn alloys. The proposed probabilistic models are the probabilistic Paris-Erdogan model, probabilistic Walker model, probabilistic Forman model, and probabilistic modified Forman models. These models were prepared by applying a random variable to the empirical fatigue crack propagation models with these names. The best models for describing fatigue crack propagation behavior in Mg-Al-Zn alloys were generally the probabilistic Paris-Erdogan and probabilistic Walker models. The probabilistic Forman model was a good model only for a specimen with a thickness of 9.45 mm.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.89-91
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• 2000

멀티미디어 응용이 점점 널리 사용되면서 멀티미디어 응용에 적합한 태스크 모델의 연구가 진행되었으나, 기존의 태스크 모델은 멀티미디어 응용의 특성을 충분히 반영하지 못하였다. 본 논문에서는 멀티미디어 응용의 자원 사용량의 패턴에 기반한 확률적 멀티프레임 태스크 모델(PMF)을 제시하고, PMF를 멀티미디어 응용의 스케줄링에 적용하여 CPU 자원을 효율적으로 이용하면서 멀티미디어 응용에게 통계적 QoS를 제공할 수 있는 방안을 제시한다. 또한, 다양한 스케줄링 기법을 채용한 모의실험을 통해 제시한 태스크 모델이 자원을 최대한 활용 하면서 응용에게 QoS를 보장할 수 있음을 보인다.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.523-530
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• 2007

This paper proposes a new stochastic optimization algorithm for hidden Markov models (HMMs) used as a recognizer of automatic lipreading. The proposed method combines a global stochastic optimization method, the simulated annealing technique, and the local optimization method, which produces fast convergence and good solution quality. We mathematically show that the proposed algorithm converges to the global optimum. Experimental results show that training HMMs by the method yields better lipreading performance compared to the conventional training methods based on local optimization.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.649-656
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• 2011

This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to Network of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extend them to genetic representation data in the method of network modelling in informatics.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.301-303
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• 2001

최근 DNA 칩 또는 마이크로어레이 기술의 발전으로 인해 한 세포 내의 수천 개의 유전자의 발현 정도를 동시에 측정할 수 있게 되었다. 이러한 마이크로어레이 데이터를 분석해서 암의 경과나 세포의 주기적 변화 등에 영향을 미치는 유전자들을 알아낼 수 있다. 본 논문에서는 베이지안망을 이용해서 마이크로어레이 데이터를 분석, 백혈병의 경과를 예측한다. 베이지안망은 다수의 변수들간의 확률적 관계를 표현하는 그래프 모델로 각 유전자들간의 확률적 관계를 표현하는 그래프 모델로 각 유전자들간의 확률적 관계를 사람이 알아보기 쉬운 형태로 학습할 수 있다는 장점이 있다. 마이크로어레이 데이터에 대해서 학습된 베이지안망은 백혈병 경과 예측에 대해서 기존의 방법보다 뛰어난 성능을 보였다.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.217-226
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• 2001

In this paper, for continuous media access operations performed by Clustered Continuous Media Storage Server (CCMSS) system, we present the analytical model based on the open queueing network, which considers simultaneously two critical delay factors, the disk I/O and the internal network, in the CCMSS system. And we derive by using the analytical model the stochastic model for the total service delay time in the system. Next, we propose the integrated stochastic admission control model for the CCMSS system, which estimate the maximum number of admittable service requests at the allowable service failure rate by using the derived stochastic model and apply the derived number of requests in the admission control operation. For the performance evaluation of the proposed model, we evaluated the deadline miss rates by means of the previous stochastic model considering only the disk I/O and the propose stochastic model considering the disk I/O and the internal network, and compared the values with the results obtained from the simulation under the real cluster-based distributed media server environment. The evaluation showed that the proposed admission control policy reflects more precisely the delay factors in the CCMSS system.