• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.21-25
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• 2006

As the mobile computing technologies rapidly develops, the mobile phones are evolving into smart phones capable of higher performance. However, it is inevitable that the mobile phones have limited input/output functions in order to maintain the current portability. Because of the limited input and output, the mobile user interfaces currently adopt the inefficient structures based on sequential search and selection. In this paper, an intelligent and adaptive user interface techniques are proposed in order to surmount the current inefficiency of the static interface and to maximize the user convenience. The proposed techniques, based on the users' previous tasks, automatically generate an intelligent and adaptive user interface in order to make users efficiently utilize the mobile services.

• Journal of IKEEE
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• v.11 no.1 s.20
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• pp.1-14
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• 2007

In this paper, a design of an integral augmented nonlinear optimal variable structure system(INOVSS) is presented for the prescribed output control of uncertain MIMO systems under persistent disturbances. This algorithm basically concerns removing the problems of the reaching phase and combining with the nonlinear optimal control theory. By means of an integral nonlinear sliding surface, the reaching phase is completely removed. The ideal sliding dynamics of the integral nonlinear sliding surface is obtained in the form of the nonlinear state equation and is designed by using the nonlinear optimal control theory, which means the design of the integral nonlinear sliding surface and equivalent control input. The homogeneous $2{\upsilon}(\kappa)$ form is defined in order to easily select the $2{\upsilon}$ or even $(\kappa)-form$ higher order nonlinear terms in the suggested sliding surface. The corresponding nonlinear control input is designed in order to generate the sliding mode on the predetermined transformed new surface by means of diagonalization method. As a result, the whole sliding output from a given initial state to origin is completely guaranteed against persistent disturbances. The prediction/predetermination of output is enable. Moreover, the better performance by the nonlinear sliding surface than that of the linear sliding surface can be obtained. Through an illustrative example, the usefulness of the algorithm is shown.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.7
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• pp.500-508
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• 2000

Basic design for single-phase active power filter, which aims at railway application provided with PWM-controlled converters, is comprehensively studied and its performance is presented in this paper. Active power filters are used to compensate railway signaling and public telecommunication interference due to the high-order harmonic currents generated in railway traction locomotives. A type of hybrid digital filter which is composed of low pass filter and high pass filter is proposed so that the desired harmonic reference current with accurate magnitude and phase shift can be extracted from catenary line current. A design criteria to determine input inductor L and output capacitor C is also described, considering voltage, current, PWM pattern, and switching frequency of the main converters. Finally, computer simulation and DSP-based experiments resulted from laboratory test are presented.

• Journal of Environmental Health Sciences
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• v.31 no.2 s.83
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• pp.152-159
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• 2005

Laboratory scale experiments were conducted to study the applicability, and to compare the performance of two types of sequencing batch reactor (SBR)systems, a conventional SBR and sequencing batch biofilm reactor (SBBR) on the biological nitrogen and phosphorus removal. The nitrification rate in SaR was higher than that in SBBR both in high influent TOC concentration. The denitrification was completed at the first non-aeration period in SBR, however, the additional non-aeration period should be installed or the first aeration period should be extended more in order to complete the nitrogen removal in SBBR. The time at the first aeration period was more needed as about 4-5 h in order to uptake all the released $PO_4^{3-}\;-P$ at the first non-aeration period. SBBR needed more operation time, especially the first aeration time, than SBR at the high influent TOC concentration in order to complete nitrogen and phosphorus removal.

• Korean Journal of Optics and Photonics
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• v.4 no.3
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• pp.252-259
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• 1993

A holosymmetric four-mirror system with unit magnification is designed for use in the micro-lithography using a deep ultraviolet wavelength of $0.248 {\mu}m$(KrF excimer laser line). In the holosymmetric system all orders of coma and distortion are zero. By applying this principle to the 4-spherical mirror system, we have obtained only one exact solution for the unit magnification holosymmetric four-spherical mirror system with all zero third order aberrations. For correction of the residual higher order aberrations of the system, aspherization is introduced keeping the holosymmetric properties. We have obtained near diffraction-limited performance for the wavelength of 0.248 pm within N.A. of 0.33 and image field diameter of 7.6 mm.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.11-23
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• 2007

Applications involving moving objects require index structures to handle frequent updates of objects' locations efficiently. Several methods to index the current, the past and the future positions of moving objects have been proposed for the applications. Most of them are based on R-tree like index structures. Some researches have made efforts to improve update performance of R-trees that are actually focused on query performance. Even though the update performance is improved by researchers' efforts, the overhead and immaturity of concurrency control algorithms of R-trees makes us hesitate to choose them for moving objects. In this paper, we propose an update efficient indexing method that can be applicable for indexing the past, the current and the future locations. The proposed index is based on B+-Trees and Hilbert curve. We present an advanced Hilbert curve that adjusts automatically the order of Hilbert curve in subregions according to the data distribution and the number of data objects. Through empirical studies, we show that our strategy achieves higher response time and throughput.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.297-303
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• 1998

The sinus distal to the prosthetic heart valve influences the valve closure behavior and velocity field near the valve, therefore affects the hydrodynamic performance of the prosthetic heart valve. In order to study the effects of valve distal geometry on the hydrodynamic performance of the prosthetic valves, mechanical bileaflet valve(SJMV), monoleaflet polymer valve(MLPV) and trileaflet polymer valve(FTPV) are inserted in the test sections which have the straight and the sinus shape distal to the valve. Leakage volumes and systolic mean pressure drops are measured in the pulsatile mock circulation flow loop. Leakage volumes are slightly less and systolic mean pressure drops are higher in the sinus test section comparing to those in the straight test section, but the differences are statistically insignificant. Flow waveforms are analyzed in order to predict the valve closure behavior. The distal sinus does not affect the closure of the MLPV, but early valve closure of SJMV is observed in the sinus test section. This effect is more significant in FTPV, and the reverse flow peak of FTPV is reduced in the sinus test section. Therefore the sinus distal to the valve can reduce the reverse flow jet caused by sudden valve closure.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.255-262
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• 2020

In modern passive sonar systems, a towed array sensor is used to minimize the effects of own ship noise and to get a higher SNR. The thin and long towed array sensor can be guided in a non-linear form according to the maneuvering of tow-ship. If this change of the array shape is not considered, the performance of beamformer may deteriorate. In order to properly beamform the elements in the array, an accurate estimate of the array shape is required. Various techniques exist for estimating the shape of the linear array. In the case of a method using a heading sensor, the estimation performance may be degraded due to the effect of heading sensor noise. As means of removing this potential error, weighted polynomial fitting technique for estimating array shape is developed here. In order to evaluate the performance of proposed method, we conducted computer simulation. From the experiments, it was confirmed that the proposed method is more robust to noise than the conventional method.

• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.