• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.10
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• pp.1161-1168
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• 2010

The FHSS(Frequency Hopping Spread Spectrum), in which a transmitter changes its carrier frequency according to a certain hopping pattern, is widely used in the military communication system, since it is highly resistant to deliberate Jamming. However, the difference of BER performance of satellite communication system which using the different modulation scheme and Jamming model was not studied. Thus, in this paper, we consider PBNJ(Partial-Band Noise Jamming) and WPBJ(Worst case Partial-Band noise Jamming) as Jamming models, and evaluate BER(Bit Error Rate) performances of NC-MFSK(Non-Coherent M-ary Frequency-Shift Keying), SDPSK(Symmetric Differential Phase-Shift Keying), and GMSK(Gaussian filtered Minimum-Shift Keying) modulation schemes. Based on the results, we suggest the best transmission method for each condition.

• Journal of radiological science and technology
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• v.41 no.5
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• pp.391-396
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• 2018

The purpose of this study was to compare and analyze the patient dose according to the distance between the X-ray tube focus and the image receptor, and to propose a new method for quantitatively evaluating the image quality. Using this quantitative evaluation method, the optimal distance for increasing x-ray image quality with low radiation dose was estimated between source and image receptor in Rib series radiography. Phantom images were obtained by changing the distance between focus and image receptor (100 cm and 180 cm). The patient radiation dose was estimated using entrance surface dose and dose area product. In order to evaluate image quality objectively, a non - reference image evaluation method was employed with paper and salt noise and Gaussian filter. As a result of this study, when the SID was changed from 100 cm to 180 cm, the entrance surface dose decreased by 4 ~ 5 times and the dose area product decreased by 3 times. In addition, there is no significant difference in image quality between of SID 180 cm and SID 100 cm. In conclusion, it was demonstrated that performing the rib series radiography at SID 180 cm is an optimal method to reduce the exposure dose and improve the image quality.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.3
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• pp.144-151
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• 2012

Chronic gastritis is the disease that is occuring in one in every 10 persons in Korea. In western medicine, endoscopy is needed to diagnose chronic gastritis, but it causes patients a pain and budget of expense. According to the TEM (Traditional Eastern Medicine), on the other hand, the 'Guan' position of the right wrist is related to a stomach. Thus we can diagnosis chronic gastritis by analyzing of pulse signal. However, pulse signal diagnosis is depended on oriental doctor's knowledge and experience. In this study, a systematic approach is proposed to analyze the computerized pulse signal. The pulse signals are firstly pre-processed, Gaussian model is adopted to fit the pulse signal, and then some related parameters are extracted from the model. Consequently, disease-sensitive parameters are selected by T-test and statistical difference. Finally, the selected parameters are entered into a Fuzzy C-Means (FCM) algorithm for classification. Classification results show that healthy persons and chronic gastritis patients are 95% and 87%, respectively.

• Water for future
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• v.28 no.4
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• pp.125-136
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• 1995

ELM, a characteristic line based method, was applied to advection-dispersion equation, and the results obtained were compared with those of Eulerian schemes(Stone-Brian and QUICKEST). The calculation methods consisted of Lagrangian interpolation scheme and cubic spline interpolation scheme for the advection calculation, and the Crank-Nicholson scheme for the dispersion calculation. The results of numerical methods were as follows: (1) for Gaussian hill: ELM, using Lagrangian interpolation scheme, gave the most accurate computational result, ELM, using cubic spline interpolation scheme, and QUICKEST scheme gave numerical damping for Peclet number 50. Stone-Brian scheme gave phase shift introduced in the numerical solution for Peclet number 10 and 50. (2) for advanced front: All schemes gave accurate computational results for Peclet number 1 and 4. ELM, Lagrangian interpolation scheme, and Stone,Brian scheme gave dissipation error and ELM, using cubic spline interpolation scheme, and QUICKEST scheme gave numerical oscillation for Peclet number 50.

• Bulletin of the Korean Chemical Society
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• v.31 no.5
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• pp.1247-1251
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• 2010

We propose an improved solvent contact model to estimate the solvation free energies of amino acids from individual atomic contributions. The modification of the solvation model involves the optimization of three kinds of parameters in the solvation free energy function: atomic fragmental volume, maximum atomic occupancy, and atomic solvation parameters. All of these atomic parameters for 17 atom types are developed by the operation of a standard genetic algorithm in such a way to minimize the difference between experimental and calculated solvation free energies. The present solvation model is able to predict the experimental solvation free energies of amino acids with the squared correlation coefficients of 0.94 and 0.93 for the parameterization with Gaussian and screened Coulomb potential as the envelope functions, respectively. This result indicates that the improved solvent contact model with the newly developed atomic parameters would be a useful tool for the estimation of the molecular solvation free energy of a protein in aqueous solution.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.563-582
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• 2021

This paper deals with developing a general class of accelerated sequential procedures and obtaining the associated second-order approximations for the expected sample size and 'regret' (difference between the risks of the proposed accelerated sequential procedure and the optimum fixed sample size procedure) function. We establish that the estimation problems based on various lifetime distributions can be tackled with the help of the proposed class of accelerated sequential procedures. Extensive simulation analysis is presented in support of the accuracy of our proposed methodology using the Pareto distribution and a real data set on carbon fibers is also analyzed to demonstrate the practical utility. We also provide the brief details of some other inferential problems which can be seen as the applications of the proposed class of accelerated sequential procedures.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1133-1145
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• 2015

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.928-940
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• 2017

State-of-the-art speaker recognition systems may work better for the English language. However, if the same system is used for recognizing those who speak different languages, the systems may yield a poor performance. In this work, the decisions of a Gaussian mixture model-universal background model (GMM-UBM) and a learning vector quantization (LVQ) are combined to improve the recognition performance of a multilingual speaker identification system. The difference between these classifiers is in their modeling techniques. The former one is based on probabilistic approach and the latter one is based on the fine-tuning of neurons. Since the approaches are different, each modeling technique identifies different sets of speakers for the same database set. Therefore, the decisions of the classifiers may be used to improve the performance. In this study, multitaper mel-frequency cepstral coefficients (MFCCs) are used as the features and the monolingual and cross-lingual speaker identification studies are conducted using NIST-2003 and our own database. The experimental results show that the combined system improves the performance by nearly 10% compared with that of the individual classifier.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.38-43
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• 1996

Windowing routines have as their purpose the reduction of the sidelobes of a spectral output of the FFT or DFT routines. Windowing routines accomplish this by forcing the beginning and end of any sequence to approach each other in value. Since they must work with any sequence they force the beginning and ending samples near zero. To make up for this reduction in power, windowing routines give extra weight to the values near the middle of the sequence. The difference between windows is the way in which they transition from the low weights near the edges to the higher weights neqr the middle of the sequence. Signal-to-noise ratio(SNR) can be determined by the ratio of the output noisy signal variance to the input noisy signal variance of a window. Standard deviation of noise is reduced by windowing. Thus, the windowing operation improved the SNR of the noisy signal. This paper shows a performance estimation of windowing on a single tone with added Gaussian noise and uniform noise.