• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.902-910
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• 2016

Recently, the volume of mobile data traffic increases exponentially due to the emergence of various mobile services. In order to resolve the problem of mobile traffic increase, various new technologies have been devised. Especially, two-way relay communication in which two nodes can transfer data simultaneously through relay node, has gained lots of interests due to its capability to improve spectral efficiency. In this paper, we analyze the SM-PNC which combines Physical-layer Network Coding (PNC) and Spatial Modulation (SM) under two-way relay communication environment. Log-Likelihood Ratio (LLR) is considered and both separate decoding and direct decoding have been taken into account in performance analysis. Through performance evaluation, we have found that the bit error rate of the proposed scheme is improved compared to that of the conventional PNC scheme, especially when SNR is high and the number of antennas is large.

• Korean Journal of Social Welfare Studies
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• v.40 no.2
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• pp.5-32
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• 2009

The purpose of this study is analyze the pattern and factors affecting the shelter exit and the patterns of homeless women in Korea. For this study, survey data were collected from 139 sheltered homeless women in Seoul in May of 2007. And respondent's exit time and exit pattern from the shelter were investigated through administration data of shelter in December of 2008. Life table analysis, Cox-proportional hazard analysis and competing risk survival analysis were employed in order to analyze data. The major findings were as follows. First, life table analysis shows that the exit ratio of homeless women started to fall sharply in 24 months from entry into shelter. Second, subjective health status, ratio of the homeless in social network and shelter entry with children affected the likelihood of shelter exit of homeless women. Third, age, subjective health status, depression and shelter entry with children affected the likelihood of positive exit. And ratio of the homeless in social network affected the likelihood of negative exit. Based on these findings, this study implied the introduction of case management service concerning individual shelter exit plan and policy for residential stability of homeless women.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.727-735
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• 2008

Consider a clinical trial in which the main end-point is survival. Suppose after the start of the study an intermediate event occurs which may be influenced by a covariate(or treatment). In many clinical studies the occurrence of an intermediate event may change the survival distribution. This investigation develops two-stage model which, in the first stage, models the effect of covariate on the intermediate event and models the relationship between survival time and covariate as well as the intermediate event. In this paper, the two-stage model is presented in order to model intermediate event and a test based on this model is also provided. A numerical simulations are carried out to evaluate its overall significance level.

• Speech Sciences
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• v.10 no.2
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• pp.35-43
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• 2003

General speaker verification systems improve their recognition performances by normalizing log likelihood ratio, using a speaker model and its background speaker model that are required to be verified. So these systems rely heavily on the availability of much speaker independent databases for background speaker model design. This constraint, however, may be a burden in practical and portable devices such as palm-top computers or wireless handsets which place a premium on computations and memory. In this paper, new approach for the GMM-based background model design used in portable speaker verification system is presented when the enrollment data is available. This approach is to modify three parameters of GMM speaker model such as mixture weights, means and covariances along with reduced mixture order. According to the experiment on a 20 speaker population from YOHO database, we found that this method had a promise of effective use in a portable speaker verification system.

• ETRI Journal
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• v.37 no.4
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• pp.736-742
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• 2015

A serial concatenated decoding algorithm with dynamic threshold is proposed for low-density parity-check codes with short and medium code lengths. The proposed approach uses a dynamic threshold to select a decoding result from belief propagation decoding and order statistic decoding, which improves the performance of the decoder at a negligible cost. Simulation results show that, under a high SNR region, the proposed concatenated decoder performs better than a serial concatenated decoder without threshold with an Eb/N0 gain of above 0.1 dB.

• ETRI Journal
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• v.42 no.1
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• pp.17-25
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• 2020

Multiple-input multiple-output systems can achieve a full sum rate (SR) via full duplex (FD). However, its performance is degraded by self-interference (SI) that occurs between the transmitter and receiver at the same node and thus is constrained by error floors. Conversely, half duplex (HD) can avoid the SI albeit at lower spectral efficiency, and the slope of its error curve is determined by the diversity order. In this study, a link selection scheme based on switching between FD and HD is examined as a simple method to improve the bit error rate (BER) performance of FD systems. In the proposed link selection algorithm, either FD or HD is selected based on the received minimum distance and signal-to-interference plus noise ratio. Simulation results indicate that the proposed hybrid FD/HD switching system offers significant BER performance improvement when compared with that of the conventional FD and FD based on only the received minimum distance under the same fixed SR. Under relatively sufficient SI cancellation, it is demonstrated to outperform the HD with a diversity advantage in low and medium signal-to-noise ratio region.

• Health Policy and Management
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• v.18 no.2
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• pp.19-38
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• 2008

Financial ratios are key indicators of an organization's financial and business conditions. Among various financial indicators, profitability, financial structure, financial activity and liquidity ratios are frequently used and analyzed. Using the structural equation modeling(SEM) technique, this study examines the structural causal relationships among key financial indicators. Data for this study are taken from complete financial statements from 142 hospitals that passed the standardization audit undertaken by the Korean Hospital Association from 1998 to 2001 for the purpose of accrediting teaching hospitals. In order to improve comparability, ratio values are standardized using the Blom's normal distribution. The final model of the SEM has four latent constructs: financial activity(total asset turnover, fixed asset turnover), liquidity(current ratio, quick ratio, collection period), financial structure(total debt to equity, long-term debt to equity, fixed assets to fund balance), and profitability(return on assets, normal profit to total assets, operating margin to gross revenue, normal profit to gross revenue). While examining several model fit indices(Chi-square (df) = 178.661 (40), likelihood ratio=4.467, RMR=.11, GFI=.849, RMSEA=.157), the final SEM we employed shows a relatively good fit. After examining the path coefficient of the constructs, the financial structure of the hospital affects the hospital's profitability in a statistically significant way. A hospital which utilizes its liabilities, more specifically fixed liabilities, and makes a stable investment decision for fixed assets was found to have a higher profitability than other hospitals. Then, the standard path coefficients were examined to directly compare the influence of variables. It was found that there were no statistically significant path coefficients among constructs. When it comes to variables, however, statistically significant relationships were found. between. financial activity and. fixed. asset turnover, and between profitability and normal profit to gross revenue. These results show that the observed variables of fixed asset turnover and normal profit to gross revenue can be used as indicators representing financial activity and profitability.

• ETRI Journal
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• v.45 no.6
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• pp.952-962
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• 2023

In this study, a space-time transmission scheme is proposed to tackle the limitations of channel estimation with orthogonal pilot information in colocated multiple-input multiple-output systems with several transmitting and receiving antennas. Channel information is obtained using orthogonal pilots. Channel estimation introduces pilot heads required to estimate a channel. This leads to bandwidth insufficiency. As a result, trade-offs exist between the number of pilots required to estimate a channel versus spectral efficiency. The detection of data symbols is performed using the maximum likelihood decoding method as it provides a consistent approach to parameter estimation problems. The moment-generating function of the instantaneous signal-to-noise ratio is used to drive an approximate expression of the symbol error rate for the proposed scheme. Furthermore, the order of diversity is less by one than the number of receiver antennas used in the proposed scheme. The effect of the length of a pilot sequence on the proposed scheme's performance is also investigated.

• The Journal of the Acoustical Society of Korea
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• v.11 no.2
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• pp.73-84
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• 1992

This paper studies noise subtraction methods and distance measures for speech recognition in a noisy environment, and investigates noise robustness of the distance measures applied to the problem of isolated word recognition in white Gaussian and colored noise (vehicle noise) environments. Noise subtraction methods which can be used as a pre-processor for the speech recognition system, such as the spectral subtraction method, autocorrelation subtraction method, adaptive noise cancellation and acoustic beamforming are studied, and distance measures such and Log Likelihood Ratio ($d_{LLR}$), cepstral distance measure ($d_{CEP}$), weighted cepstral distance measure ($d_{WCEP}$), spectral slope distance measure ($d_{RPS}$) and cepstral projection distance measure ($d_{CP},\;d_{BCP},\;d_{WCP},\;d_{BWCP}$) are also investigated. Testing of the distance measures for speaker-dependent isolated word recognition in a noisy environment indicate that $d_{RPS}\;and\;d_{WCEP}$ which weigh higher order cepstral coefficients more heavily give considerable performance improvement over $d_{CEP}and\;d_{LLR}$. In addition, when no pre-emphasis is performed, the recognizer can maintain higher performance under high noise conditions.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.