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

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.29-34
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• 2019

If it takes much time to calculate the fitness of the solution in genetic algorithms, it is essential to create a metamodel. Much research has been completed to improve the performance of metamodels. In this study, we tried to get a better performance of metamotel using discrete Walsh transform in discrete domain. We transforms the basis of the solution and creates a metamodel using the transformed solution. We experimented with NK-landscape, a representative function of the pseudo-boolean function, and provided empirical evidence on the performance of the proposed model. When we performed the genetic algorithm using the proposed model, we confirmed that the genetic algorithm found a better solution. In particular, our metamodel showed better performance than that using the radial basis function network that modified the similarity function for the discrete domain.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.127-136
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• 2009

Modeling and Simulation, especially in mobile ad hoc network(MANET), are the most effective way to analyze performance or optimize system parameters without establishing real network environment. Focusing mainly on overall network behaviors in MANET concerns dynamics of network transport operations, which can efficiently be characterized with event based system states rather than execution details of protocols. We thus consider the network as a discrete event system to analyze dynamics of network transport performance. Zeigler's set-theoretic DEVS(Discrete Event Systems Specification) formalism can support specification of a discrete event system in hierarchical, modular manner. The DEVSim++ simulation environment can not only provide a rigorous modeling methodology based on the DEVS formalism but also support modelers to develop discrete event models using the hierarchical composition methodology in object-orientation. This environment however hardly supports to specify connection paths of network nodes, which are continuously altered due to mobility of nodes. This paper proposes a DEVS-based modeling and simulation methodology of enabling node mobility, and develops DEVS models for the mobile ad hoc network. We also simulate developed models with the DEVSim++ engine to verify the proposal.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

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

• Journal of the Korean Society for Precision Engineering
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• v.20 no.1
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• pp.229-239
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• 2003

The design process of machine tools is regarded as a sequential, discrete, and inefficient works as it requires various kinds of design tools and many working hours. This paper describes an integrated design system embedding a design methodology that can support efficiently and systematically the conceptual structural design of machine tools. The system is a knowledge-based design system and has four machine-tool-specific functional modules including configuration design, configuration analysis, structure design, and structural analysis support module. Through the configuration design and analysis module, a machine configuration appropriate for design requirements is selected, and then the arrangement of ribs fer each structural part is decided in the structure design module. Also, the structural analysis support module is used to evaluate design result by utilizing structural analysis software, ANSYS. The system is applied to design of a tapping machine, and shows that the machine structure can be designed fast and conveniently by processing each design step interactively.

• ETRI Journal
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• v.20 no.3
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• pp.251-271
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• 1998

It is well known that if usage parameter control/network parameter control (UPC/NPC) functions are used together with a cell loss priority control scheme in ATM networks, the measurement phasing problem can occur. This makes it difficult for a network provider to define and commit the cell loss ratio as a QoS parameter. To solve the problem, we propose a new UPC/NPC algorithm. By using the proposed UPC/NPC algorithm, we can define the cell loss ratios for CLP = 0 and CLP = 0+1 cell streams without the measurement phasing problem under any conditions. We analyzed the performance of the proposed UPC/NPC algorithm. Using a discrete time model for the UPC/NPC architecture with a discrete-time semi-Markov process (DSMP) input model, we obtained the cell discarding probabilities of CLP = 0 and CLP = 0+1 cells streams and showed that more CLP = 0 cells are accepted compared to what was proposed in ITU-T.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.39-43
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• 2004

A research shows that a new category of software, Collaborative Product Commerce (CPC), is now emerging, allowing discrete manufacturers to once again distinguish themselves on their products and innovations. CPC permits discrete manufacturers to significantly improve the core processes around the management functions associated with the complete product life cycle that are the basis of their existence. As a way to develop computing tools of CPC to support a design process of product, a web-based design supporting system was constructed in the paper. The system consists of C-Product system and Net Meeting Communication system to improve communications between designers and persons for verification of design. The product data files of C-Product system were designed by Pro/Engineer and converted to 3D Viewer format for being used in the web browser. Also, Net Meeting Communication system and Database were developed using ASP and Microsoft SQL 2000 Server to share diverse files that can be utilized to design on the web in real time.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.113-123
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• 2014

Electrophysiological recordings are considered a reliable method of assessing a person's alertness. Sleep medicine is asked to offer objective methods to measure daytime alertness, tiredness and sleepiness. As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in recognition of alertness level. In this paper, EEG signals have been analyzed using wavelet transform as well as discrete wavelet transform and classification using statistical classifiers such as euclidean and mahalanobis distance classifiers and a promising method SVM (Support Vector Machine). As a result of simulation, the average values of accuracies for the Linear Discriminant Analysis (LDA)-Quadratic, k-Nearest Neighbors (k-NN)-Euclidean, and Linear SVM were 48%, 34.2%, and 86%, respectively. The experimental results show that SVM classification method offer the better performance for reliable classification of the EEG signal in comparison with the other classification methods.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.15-30
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• 2001

Hybrid simulation may employ different types of simulation based on which models in different system types are developed. The simulation requires simulation time synchronization and data exchange between such simulators, which is called simulators interoperation. This paper develops such interoperable simulation environments for modeling and simulation of hybrid systems whose components consist of continuous and discrete event systems. The environments, one for centerized and the other for distribute, support interoperation between a discrete event simulator of DEVSim++ and a continuous simulator of MATLAB. The centerized environment, HDEVSim++, is developed by extending the sxisting DEVSim++ environment; the distributed environment, HDEVSimHLA, is developed using the HLA/RTl library. Verification of both environments is made and performance comparison between the two using a simple example is presented. .