• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.20-26
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• 2000

In speaker verification system the HMM(hidden Markov model) parameter updating using small amount of data and the priori threshold decision are crucial factor for dealing with long-term variability in people voices. In the paper we present the speaker model updating technique which can be adaptable to the session-to-intra speaker variability and the priori threshold determining technique. The proposed technique decreases verification error rates which the session-to-session intra-speaker variability can bring by adapting new speech data to speaker model parameter through Baum Welch re-estimation. And in this study the proposed priori threshold determining technique is decided by a hybrid score measurement which combines the world model based technique and the cohen model based technique together. The results show that the proposed technique can lead a better performance and the difference of performance is small between the posteriori threshold decision based approach and the proposed priori threshold decision based approach.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.18-23
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• 2008

In this paper, we propose the input image selection-method to improve the reconstructed high-resolution (HR) image quality. To obtain ideal super-resolution (SR) reconstruction image, all input images are well-registered. However, the registration is not ideal in practice. Due to this reason, the selection of input images with low registration error (RE) is more important than the number of input images in order to obtain good quality of a HR image. The suitability of a candidate input image can be determined by using statistical and restricted registration properties. Therefore, we propose the proper candidate input Low Resolution(LR) image selection-method as a pre-processing for the SR reconstruction in automatic manner. In video sequences, all input images in specified region are allowed to use SR reconstruction as low-resolution input image and/or the reference image. The candidacy of an input LR image is decided by the threshold value and this threshold is calculated by using the maximum motion compensation error (MMCE) of the reference image. If the motion compensation error (MCE) of LR input image is in the range of 0 < MCE < MMCE then this LR input image is selected for SR reconstruction, else then LR input image are neglected. The optimal reference LR (ORLR) image is decided by comparing the number of the selected LR input (SLRI) images with each reference LR input (RLRI) image. Finally, we generate a HR image by using optimal reference LR image and selected LR images and by using the Hardie's interpolation method. This proposed algorithm is expected to improve the quality of SR without any user intervention.

• Journal of Environmental Health Sciences
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• v.41 no.5
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• pp.299-304
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• 2015

Objectives: A people-counting system measures real-time occupancy through motion detection. Accurate people-counting can be used to calculate suitable ventilation demands. This study determined the optimum motion threshold for a people-counting system. Methods: In a closed room with two occupants moving constantly, different thresholds were tested for the accuracy of a people-counting system. The experiments were conducted at 150, 300, 450 and 600 lux. These levels of brightness included the illumination levels of most public indoor areas. The experiments were repeated with three types of clothing coloration. Results: Overall, a threshold of 16 provided the lowest mean error percentage for the people-counting system. Brightness and clothing color did not have a significant impact on the results. Conclusion: A people-counting system could be used with threshold of 16 for most indoor environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.767-783
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• 2013

This paper aims at designing a selective demodulation scheme based on Log-likelihood Ratio threshold (SDLT) instead of the conventional adaptive demodulation (ADM) scheme, by using rateless codes. The major difference is that the Log-likelihood ratio (LLR) threshold is identified as a key factor to control the demodulation rate, while the ADM uses decision region set (DRS) to adjust the bit rate. In the 16-QAM SDLT scheme, we deduce the decision regions over an additive white Gaussian channel, corresponding to the variation of LLR threshold and channel states. We also derived the equations to calculate demodulation rate and bit error rate (BER), which could be proven by simulation results. We present an adaptation strategy for SDLT, and compare it with ADM and adaptive modulation (AM). The simulation results show that our scheme not only significantly outperforms the ADM in terms of BER, but also achieves a performance as good as the AM scheme. Moreover, the proposed scheme can support much more rate patterns over a wide range of channel states.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.8
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• pp.17-22
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• 2007

In this paper, we propose a threshold estimation algorithm for a noncoherent IR-UWB receiver using 1-bit sampler. The proposed method reduces the hardware complexity by using the information of binary data resulted from 1-bit sampler instead of measuring the energy level of a received signal. Besides, mathematical modeling shows that the performances are similar to those of theoretically optimal threshold in terms of bit error rate. Computer simulations based on the IEEE 802.15.4a channel model also demonstrate the superiority of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.467-472
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• 2008

In this paper, we analyzed the error rate Performance of convolution coded 16 QAM signal with Optimum Threshold Detection with selective combining diversity in Rician Fading Environments. The performance of 16-QAM signal with CTD (conventional threshold detection) which employs convolution coding technique was analyzed and the performance improvement of convolution coded 16-QAM signal with OTD (optimum threshold detection) which is varied according to fading parameter "K" and AWGN in Rician Fading channel was simulated. As a result of analysis, it was shown the effect of performance improvement to overcome the environment of mobile radio data communication channel.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.152-158
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• 2006

The objective of this work is to develop the knee joint model for representing various pendulum motions and quantifying the spasticity. Knee joint model included the extension and flexion muscles. The joint moment consists of both the active moment from the stretch reflex and the passive moment from the viscoelastic joint properties. The stretch reflex was modeled as nonlinear feedback of muscle length and the muscle lengthening velocity, which is Physiologically-feasible. Moreover, we modeled the spastic reflex as having dynamic threshold to account far the various pendulum trajectories of spastic patients. We determined the model parameters of three patients who showed different pendulum trajectories through minimization of error between experimental and simulated trajectories. The simulated joint trajectories closely matched with the experimental ones, which show the proposed model can predict pendulum motions of patients with different spastic severities. The predicted muscle force from spastic reflex appeared more frequently in the severe spastic patient, which indicates the dynamic threshold relaxes slowly in this patient as is manifested by the variation coefficient of dynamic threshold. The proposed method provides prediction of muscle force and intuitive and objective evaluation of spasticity and it is expected to be useful in quantitative assessment of spasticity.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.347-356
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• 2022

This article is concerned with asymmetric volatility models for financial time series. A generalization of standard single-threshold volatility model is discussed via multiple-threshold in which we specialize to twothreshold case for ease of presentation. An empirical illustration is made by analyzing S&P500 data from NYSE (New York Stock Exchange). For comparison measures between competing models, parametric bootstrap method is used to generate forecast distributions from which summary statistics of CP (Coverage Probability) and PE (Prediction Error) are obtained. It is demonstrated that our suggestion is useful in the field of asymmetric volatility analysis.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.119-122
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• 2010

Cognitive Radioo(CR)기술은 주파수 자원을 효율적으로 이용하기 위해 Joseph Mitora가 개념을 적립한 것으로 유비쿼터스 시대의 부족한 주파수 자원을 극복 할 수 있는 기술로 각광받고 있다. 이와 같은 무선인지 기술(CR)을 도입하기 위한 핵심적인 요소는 부사용자(Secondary User)가 주사용자(Primary User)의 통신을 방해하지 않도록 주파수 점유 여부를 정확하게 판단하는 Spectrum Sensing기술이다. 이 스펙트럼 센싱 기술에 두 가지 종류의 에러가 발생하는데 하나는 미검출 오류(miss error)이고 또 하나는 오경보 오류(false alarm error)이다. 따라서 본 논문은 이 두 가지를 합친 검출 오류(detection error)를 최소화 하기위해 협력 스펙트럼 센싱(Cooperative spectrum sensing)에서 몇 명 이상의 부사용자가 주사용자가 사용중이라 검출하였을 때 최종 결정이 주사용자가 사용한다고 결론 짓는 것이 최적인지를 수학적으로 분석하고 그 최적의 K값을 사용하여 전체 시스템의 성능을 향상 시키는 방법을 제시 한다.