• The Mathematical Education
• /
• v.20 no.1
• /
• pp.51-72
• /
• 1981

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.228-229
• /
• 2008

This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

• IEIE Transactions on Smart Processing and Computing
• /
• v.2 no.2
• /
• pp.67-76
• /
• 2013

Under an imperfect channel estimation, a Device-to-Device (D2D) communication framework based on MIMO relay technology is presented. The model consists of a D2D pair equipped with M antennas and a relay equipped with N antennas as well as a cellular user equipped with M antennas. The outage probability under different relaying protocols (i.e. AF and DF protocol) with and without considering a direct link was derived. The actual and theoretical outage probability of the five links under different antenna numbers was emulated. The number of user antennas and channel estimation error was analyzed carefully to determine their impact on the outage probability of a system. The simulation verified the theory analyses and the results showed that MIMO relaying improves the D2D communication system performance.

• The KSFM Journal of Fluid Machinery
• /
• v.16 no.2
• /
• pp.42-47
• /
• 2013

Ship stability prediction is very complex in reality. In this paper, risk based approach is applied to predict the probability of a certified ship, which is effected by the forces of sea especially the wave loading. Safety assessment and risk analysis process are also applied for the probabilistic prediction of ship stability. The survival probability of ships encountering with different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.

• Ocean Systems Engineering
• /
• v.1 no.3
• /
• pp.249-261
• /
• 2011

The stochastic nonlinear dynamic behavior and probability density function of ship rolling are studied using the nonlinear dynamical systems approach and probability theory. The probability density function of the rolling response is evaluated through solving the Fokker Planck Equation using the path integral method based on a Gauss-Legendre interpolation scheme. The time-dependent probability of ship rolling restricted to within the safe domain is provided and capsizing is investigated from the probability point of view. The random differential equation of ships' rolling motion is established considering the nonlinear damping, nonlinear restoring moment, white noise and colored noise wave excitation.

• The Mathematical Education
• /
• v.25 no.1
• /
• pp.1-8
• /
• 1986

It is a common saying that markov-chain is a special case of probability course. That is to say, It means an unchangeable markov-chain process of the transition-probability of discontinuous time. There are two kinds of ways to show transition probability parade matrix theory. The first is the way by arrangement of a rightangled tetragon. The second part is a vertical measurement and direction sing by transition-circle. In this essay, I try to find out existence of procession for transition-probability applied markov-chain. And it is possible for me to know not only, what it is basic on a study of chain but also being applied to abnormal problems following a flow change and statistic facts expecting to use as a model of air expansion in physics.

• ETRI Journal
• /
• v.36 no.4
• /
• pp.609-616
• /
• 2014

Even though many computational methods (recursive formulae) for blocking probabilities in finite-capacity M/D/1 queues have already been produced, these are forms of transforms or are limited to single-node queues. Using a distinctly different approach from the usual queueing theory, this study introduces explicit (transform-free) formulae for a blocking probability, a stationary probability, and mean sojourn time under either production or communication blocking policy. Additionally, the smallest buffer capacity subject to a given blocking probability can be determined numerically from these formulae. With proper selection of the overall offered load ${\rho}$, the approach described herein can be applicable to more general queues from a computational point of view if the explicit expressions of random vector $D_n$ are available.

• Journal of the military operations research society of Korea
• /
• v.25 no.1
• /
• pp.55-74
• /
• 1999

In this study, a nonsymmetric model of directional probability variation (dpv), which is fundamental and conforms well to various moving situations of attacking tanks, is obtained based on the Whittaker's theory. It is shown that it produces the same expression of the probability density function as the Whittaker's under the special moving condition of an attacking tank. Using the derived dpvs, the probability densities for the various cases of some examples are calculated numerically to verify the derived formulas, and compared with other existing symmetrical distributions widely used to grasp characteristics of them. As a result, it is noted that the plots of the probability density function for various cases selected exhibit very different and useful behavioral features. Applying the results with respect to the every tank in the computer simulation of engagement between two tank forces, it is expected that more reasonable shot distributions can be given comparing with other existing symmetrical ones. The derived dpvs may be utilized to decide shot distribution of other weapon systems through small modification.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.40 no.1
• /
• pp.39-49
• /
• 2003

Watermark detection has a crucial role in copyright protection of and authentication for multimedia and has classically been tackled by means of correlation-based algorithms. Nevertheless, when watermark embedding does not obey an additive rule, correlation-based detection is not the optimum choice. So a new detection algorithm is proposed which is optimum for non-additive watermark embedding. By relying on statistical decision theory, the proposed method is derived according to the Bayes decision theory, Neyman-Pearson criterion, and distribution of wavelet coefficients, thus permitting to minimize the missed detection probability subject to a given false detection probability. The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation- based method.

• Journal of Information Processing Systems
• /
• v.11 no.3
• /
• pp.421-437
• /
• 2015

This paper aims to present a supervised classification algorithm based on data fusion for the segmentation of the textured images. The feature extraction method we used is based on discrete wavelet transform (DWT). In the segmentation stage, the estimated feature vector of each pixel is sent to the support vector machine (SVM) classifier for initial labeling. To obtain a more accurate segmentation result, two strategies based on information fusion were used. We first integrated decision-level fusion strategies by combining decisions made by the SVM classifier within a sliding window. In the second strategy, the fuzzy set theory and rules based on probability theory were used to combine the scores obtained by SVM over a sliding window. Finally, the performance of the proposed segmentation algorithm was demonstrated on a variety of synthetic and real images and showed that the proposed data fusion method improved the classification accuracy compared to applying a SVM classifier. The results revealed that the overall accuracies of SVM classification of textured images is 88%, while our fusion methodology obtained an accuracy of up to 96%, depending on the size of the data base.