• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.3
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• pp.9-18
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• 1983

In many geological investigation, a data sequence may be created which consisted of a succession of mutually exclusive state. However, now our interest lie in the nature of transition from one state to another, rather than in the position of states in the sequence. In this paper, authors studied for the deformation of HAEUNDAE beach by transition matrices and empirical eigenfunction method. In this paper, 5-yr. set of profile data from HAEUNDAE beach measured at several monthly or yearly intervals are analyzed by using the transition matrices and empirical eigen-function. Results of this study indicate that the transition matrices and empirical eigenfunctions are useful in the analysis of beach profile data and provide objective insight in the nature of profile configuration.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.79-84
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• 1996

In this paper, adaptive correlator model using backpropagation neural network based on complex multilayer perceptron is presented for suppressing interference of narrow-band of direct sequence spread spectrum receiver in CDMA mobile communication systems. Recursive least square backpropagation algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise ratio and transmission power ratio, computer simulation results show that bit error ratio of adaptive correlator uswing backpropagation neural network improved than that of adaptive transversal filter of direct sequence spread spectrum considering of co-channel and narrow-band interference. Bit error ratio of adaptive correlator using backpropagation neural network is reduced about $10^{-1}$ than that of adaptive transversal filter where interference versus signal ratio is 5 dB.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.245-254
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• 2004

This paper deals with the problem of estimating structure and motion from long continuous image sequences, applying the Expectation Maximization algorithm based on extended Kalman smoother to impose the time-continuity of the motion parameters. By repeatedly estimating the state transition matrix of the dynamic equation and the parameters of noise processes in the dynamic and measurement equations, this optimization gives the maximum likelihood estimates of the motion and structure parameters. Practically, this research is essential for dealing with a long video-rate image sequence with partially unknown system equation and noise. The algorithm is implemented and tested for a real image sequence.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.333-342
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• 2022

Cellular Automata (CA) is a discrete and abstract computational model that is being applied in various fields. Applicable as an excellent pseudo-random sequence generator, CA has recently developed into a basic element of cryptographic systems. Several studies on CA-based stream ciphers have been conducted and it has been observed that the encryption strength increases when the radius of a CA's neighbor is increased when appropriate CA rules are used. In this paper, among CAs that can be applied as a one-dimensional pseudo-random number sequence generator (PRNG), one-dimensional 5-neighbor CAs are classified according to the connection state of their neighbors, and the ignition relationship of the characteristic polynomial is obtained. Also this paper propose a synthesis algorithm for an asymmetric 1-D linear 5-neighbor MLCA in which the radius of the neighbor is increased by 2 using the one-dimensional 3-neighbor 90/150 CA state transition matrix.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.299-310
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• 1998

Actually mixed assembly line is mixed with open and close type workstation. This workstation is called hybridworkstation. The propose of this paper is to determine the sequencing of model that minimize line length for actual(hybridworkstation) mixed model assembly line. we developed three mathematical formulation of the problem to minimize the overall length of a line with hybrid station. Mathematical formulation classified model by operato schedule. Mixed model assembly line is combination program and NP-hard program. Thus computation time is often a critical factor in choosing a method of determining the sequence. This study suggests a tabu search technique which can provide a near optimal solution in real time and use the hill climbing heuristic method for selecting initial solution. Modified tabu search method is compared with MIP(Mixed Integer Program). Numerical results are reported to demonstrate the efficiency of the method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1933-1939
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• 1990

In this paper, we proposed an algorithm which used backtracking method to get time information, and it be modelled DMS (Dynamic Multisection) by feature vectors and time information whic are represented to similiar feature in word patterns spoken during continuous time domain, for Korean Speech recognition by independent speaker using DMS. Each state of model is represented time sequence, and have time information and feature vector. Typical feature vector is determined as the feature vector of each state to minimize the distance between word patterns. DDD Area names are selected as recognition wcabulary and 12th LPC cepstrum coefficients are used as the feature parameter. State of model is made 8 multisection and is used 0.2 as weight for time information. Through the experiment result, recognition rate by DMS model is 94.8%, and it is shown that this is better than recognition rate (89.3%) by MSVQ(Multisection Vector Quantization) method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.452-460
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• 2001

Most of researches of tolerance optimization have used a simple sum of tolerance-cost functions with several constraint equations as an optimization model. However, if there is a machining sequence with more than one processes to complete a part, and machining failure, i.e., out-of-tolerance occurs at one of the intermediate processes, the tolerance-cost of this process should be added by the machining cost of all the previous processes already completed on the part. In this study, an accumulated scrap cost model(ASCM) is proposed considering the scrapped machining cost, and applied to a simple assembly example. The result of tolerance optimization using ASCM is compared with that of using a traditional optimization model to confirm its effectiveness.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.147-149
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• 2006

We designed an intelligent intrusion detection scheme that works based on target system's operational states and doesn't depend on humans' analysis. As a prior work, we presents a scheme to describe computer system's operational states. For this, Hidden Markov Model is used. As input to modeling, huge amount of system audit trail including data on events occurred in target system connected to network and target system's resource usage monitoring data is used. We can predict system's future state based on current events' sequence using developed model and determine whether it would be in daniel or not.

• International Commerce and Information Review
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• v.10 no.4
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• pp.81-96
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• 2008

uEFL is an open source solution to integrate general business/learning activities and processes. uEFL is originally developed to adopt LD (Learning Design) specification, which represents learning as various combination of learning activities with learning conditions and outcomes. Learning activities are described with participant's role, learning environment, and contextual sequence. This viewpoint resembles BPM (Business Process Modeling). uEFL can convert LD to BPM description. uEFL engine can run converted LD activity with other business activities. This paper presents 4 templates and 2 sample models for uEFL. The templates and models will show how learning activities can be integrated with business activities efficiently.

• Journal of Biomedical Engineering Research
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• v.11 no.1
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• pp.157-162
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• 1990

In this study, a peripheral auditory model is used as a frequency feature extractor and a recurrent network which has recurrent links on input nodes is constructed in order to show the reliability of the recurrent network as a recognizer by executing recognition tests for 4 Korean place names and syllables. In the case of using the general learning rule, it is found that the weights are diverged for a long sequence because of the characteristics of the node function in the hidden and output layers. So, a refined weight compensation method is proposed and, using this method, it is possible to improve the system operation and to use long data. The recognition results are considerably good, even if time worping and endpoint detection are omitted and learning patterns and test patterns are made of average length of data. The recurrent network used in this study reflects well time information of temporal speech signal.