• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.1
• /
• pp.28-35
• /
• 2002

In cavity flow, the rectangular step generates so strong sound that many researchers have investigated method to suppress the nois during interaction between vortical flow and rectangular forward step. In this study the flow noise from the vortex motion in two-dimentional low Mach number flow past a forward step with various chamfering angle is calculated numerically. Inviscid incompressible discrete vortex model and matched asymptotic expansion(MAE) theory are applied to obtain the inner flow field and the outer noise field. Both source acoustic pressure and sound intensity are obtained with various chamfering height, chamfering angle and initial vortex position. The pressure amplitude is most suppressed when the chamfering angle is between $15^{\circ}C$ and $30^{\circC}$ at the chamfering length of 30% of the step height.

• Journal of the Institute of Convergence Signal Processing
• /
• v.20 no.2
• /
• pp.78-83
• /
• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Journal of the Korea Society for Simulation
• /
• v.23 no.2
• /
• pp.1-6
• /
• 2014

CPS (cyber-physical systems) which consists of connected and diverse embedded systems and physical systems are a new paradigm. Traditional systems were usually considered to be passive and dumb parts in physical systems, but with CPS, we have to take into account what are being moved or changed in the physical systems. So, as increasing the complexity of CPS, potential errors in the systems also increase. In this paper, for enhancing the reliability of CPS, we exploit an executable-model-based design methodology and propose a distributed simulation method to verify the design of CPS. For the design of the systems including discrete and continuous factors, we apply DEV&DESS formalism and simulate models in distributed simulation environments through DDS middleware. We also illustrate the applications of CPS with our modeling tool.

• KIISE Transactions on Computing Practices
• /
• v.21 no.1
• /
• pp.94-99
• /
• 2015

With the recent machine learning paradigm of using nonparametric Bayesian statistics and statistical inference based on random sampling, the Dirichlet distribution finds many uses in a variety of graphical models. It is a multivariate generalization of the gamma distribution and is defined on a continuous (K-1)-simplex. This paper presents a sampling method for a Dirichlet distribution for the problem of dividing an integer X into a sequence of K integers which sum to X. The target samples in our problem are all positive integer vectors when multiplied by a given X. They must be sampled from the correspondingly gridded simplex. In this paper we develop a Markov Chain Monte Carlo (MCMC) proposal distribution for the neighborhood grid points on the simplex and then present the complete algorithm based on the Metropolis-Hastings algorithm. The proposed algorithm can be used for the Markov model, HMM, and Semi-Markov model for accurate state-duration modeling. It can also be used for the Gamma-Dirichlet HMM to model q the global-local duration distributions.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.2
• /
• pp.125-132
• /
• 2010

The authors have investigated the acoustic field analysis using the Constrained Interpolation Profile(CIP) Method recently proposed by Yabe. This study has examined the calculation accuracy of the three-dimensional(3-D) acoustic field analysis using the type C CIP method. In this paper we show phase error of type C CIP method and the dependence on the wave-propagation direction in the type C CIP acoustic field analysis, and then demonstrate that it gives less-diffusive results than conventional analysis. Moreover, in comparison between type C-1 CIP, type C-2 CIP, type M CIP and FDTD, reports the memory requirements and calculation time of each method.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.3
• /
• pp.639-648
• /
• 1997

As the areas of computer application are expanded, the real-time applicition enviroments that must process as many transactions as possible within their deadlines have been increased recently. Conventional disk based databaes system is not appropriate in real-time transaction processing due to delying time for disk I/O processing. When the system is overloaede, the performance of transaction scheduling technique using earliest deadline first deteriorates rapidly because it can assign the highest priority ot a transaction that has already missed or is about to miss tis deadline. Therfore, the performance of suggested transaction secheduling technique is made to improved by propos-ing the doule locking mechanism based on priority. Finally, in order to evaluate the performance of the proposed priority-based double locking techniques under single proessor and main memory database system environments, the simulation model was developed using the SLAM II language.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.7
• /
• pp.1734-1745
• /
• 1996

In this paper, a modified fixed-delay tree search with decision feedback(FDTS/DF) for compensation of non-linear distortion in digital magnetic recording channels is discussed. Since the nonlinear distortion, which becomes significant as recording density increases, is generally well modeled by the discrete Volterra series, the proposed equlizer is composed of a nolinear feedforward filter, a linear feedback filter, and a nonlinear distorton table, the values of which are determined by considering the effect of nonlinear distortion due to future data as well as the previous and current one. At the decision stage of FDTS, a path minimizing the branch metric is chosen by using the previously detected values, current predicted value, and future predicted value. We compare the performance of the linear FDTS/DF, the previous nonlinear FDTS/DF, and the proposed nonlinear FDTS/DF by computer simulation, and confirm that the proposed one chieves the best performance at high-density recording.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.30 no.6
• /
• pp.515-522
• /
• 2017

In this paper, an isogeometric analysis for multipatch problem is investigated, in which two or more geometries are connected at the interface in a conforming or non-conforming conditions. To express higher continuity at the patch interface, two approaches such as Nitsche based method and master-slave method are formulated for the linear elasticity problem and discretized using the isogeometric approach using NURBS basis functions. A short comparison between two approaches in formulations reveals the pros and cons of them with the applicability in the isogeometric multipatch problem. In addition, a NURBS based stress recovery is adopted to express a better stress continuity through the post-processing. Numerical examples indicate the effectiveness of Nitsche method in the non-conforming patch, following the exact solution well. For the stress concentration problem with the conforming patch, introduced two methodologies show comparative results, meanwhile the NURBS based stress recovery presents an improved smooth stress contour in the whole domain including the patch interface.

• Journal of Digital Contents Society
• /
• v.19 no.1
• /
• pp.35-41
• /
• 2018

The Q-learning algorithm based on reinforcement learning is useful for learning the goal for one behavior at a time, using a combination of discrete states and actions. In order to learn multiple actions, applying a behavior-based architecture and using an appropriate behavior adjustment method can make a robot perform fast and reliable actions. Q-learning is a popular reinforcement learning method, and is used much for robot learning for its characteristics which are simple, convergent and little affected by the training environment (off-policy). In this paper, Q-learning algorithm is applied to a lamp robot to learn multiple behaviors (human recognition, desk object recognition). As the learning rate of Q-learning may affect the performance of the robot at the learning stage of multiple behaviors, we present the optimal multiple behaviors learning model by changing learning rate.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.7
• /
• pp.190-200
• /
• 2014

The video-based system of the broadcasters and the video-related institutions have shifted from analogical to digital in worldwide. This migration process can generate a defect, digital dropout, in the quality of the contents. Moreover, there are limited researches focused on these kind of defects and those related have limitations. For that reason, we are proposing a new method for feature extraction emphasizing in the peculiar block pattern of digital dropout based on discrete cosine transform (DCT). For classification of error block, we utilize support vector machine (SVM) which can manage feature vectors efficiently. Further, the proposed method overcome the limitation of the previous one using continuity of frame by frame. It is using only the information of a single frame and works better even in the presence of fast moving objects, without the necessity of specific model or parameter estimation. Therefore, this approach is capable of detecting digital dropout only with minimal complexity.