• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.634-640
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• 2000

This paper proposes a new extended decision directed-decision estimated phase recovery algorithm based on maximum likelihood parameter estimation for OQPSK. In this scheme, comparing conventional one, the data dependent noise of phase recovery loop is reduced by inserting filter with 2 taps to in-phase and quadrature-phase channel respectively before phase detector. The proposed scheme is compared to conventionalscheme and OQPSK in aspect to BER(Bit Error Rate) and phase error according to the roll-off factor of baseband filter, the output back-offs of nonlinear satellite channel, and loop bandwidth.

• Smart Structures and Systems
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• v.26 no.4
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2347-2352
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• 2012

In this paper, a new alternating equalizer and its differential adjustment algorithm are proposed. The proposed alternating equalizer achieves equalization effectively using an algorithm performing symbol decisions based on soft/hard decision. In addition, it is possible to improve the initial blind convergence speed and steady-state error performance simultaneously by adjusting the equalizer differentially according to the relative reliability of the symbol decisions by soft/hard decision devices. The simulation results on 16/64-QAM constellations under multipath propagation channel and additive noise conditions confirmed to support usefulness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1111-1117
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• 2003

The maximum Doppler frequency, or equivalently, the mobile speed is very useful information to optimize the performance of many wireless communication systems. However, the performance of a maximum Doppler frequency estimator is limited since it requires an estimate of the signal-to-noise ratio (SNR) of the channel environment. In this paper, the improved method for the maximum Doppler frequency estimations based on the decision feedback Doppler adaptive band-limit (DF-DABL) method is proposed. To reduce the effect of additive noise, the proposed algorithm uses a novel Doppler adaptive band-limit (DABL) technique. The distortion due to the additive noise is drastically removed by the proposed DF-DABL method. Especially, the DF-DABL method does not need any other channel information such as SNR.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.1-6
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• 2023

In this paper, we present a new method for classifying malicious URLs to reduce cases of learning difficulties due to unfamiliar and difficult terms related to information protection. This study plans to extract only visually distinguishable features within the URL structure and compare them through map learning algorithms, and to compare the contribution values of the best map learning algorithm methods to extract features that have the most impact on classifying malicious URLs. As research data, Kaggle used data that classified 7,046 malicious URLs and 7.046 normal URLs. As a result of the study, among the three supervised learning algorithms used (Decision Tree, Support Vector Machine, and Logistic Regression), the Decision Tree algorithm showed the best performance with 83% accuracy, 83.1% F1-score and 83.6% Recall values. It was confirmed that the contribution value of https is the highest among whether to use https, sub domain, and prefix and suffix, which can be visually distinguished through the feature contribution of Decision Tree. Although it has been difficult to learn unfamiliar and difficult terms so far, this study will be able to provide an intuitive judgment method without explanation of the terms and prove its usefulness in the field of malicious URL detection.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.177-180
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• 2000

An algorithm for modeling of yeast fermentation process using genetic-fuzzy algorithm is presented in this work. The algorithm involves developing the fuzzy modeling of the process and model update capability against the system change. The membership functions of state variables and specific rates and the decision table were generated using genetic algorithm. This algorithm could replace the complex mathematical model to simple fuzzy model and cope with the change of process characteristics well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.94-101
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• 2005

This paper presents a data-mining aided heuristic algorithm development. The developed algorithm includes three steps. The steps are a uniform selection, development of feature functions and clustering, and a decision tree making. The developed algorithm is employed in designing an optimal multi-station fixture layout. The objective is to minimize the sensitivity function subject to geometric constraints. Its benefit is presented by a comparison with currently available optimization methods.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.493-493
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• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.76-80
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• 1992

We consider the tapped-delay line (TDL) equalizer with the few calculation quantity and the simplity, the decision feedback equalizer (DFE) with the good property for interference, and lattice equalizer(LE) with high insensitivity to roundoff noise in mobile communication fading channel. The used adaptive algorithm is the LMS algorithm and RLS algorithm. In this paper, we have evaluated the performance of the TDL equalizer, the decision feedback equalizer, and lattice-structured equalizer, for the digital signal corrupted by the impulsive noise and the white gaussian noise under the fading channel environment. From the results of error performance analysis, it is confirmed that lattice-structured equalizer has better performance than DFE equalizer and TDL equalizer.