• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.398-400
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• 2014

In this letter, we propose a cross-layer technique jointly considering modulation coding schemes (MCSs) of medium access control (MAC) layer, source significance information (SSI) and error concealment unit of application (APP) layer, and channel quality information (CQI) of physical (PHY) layer. We demonstrate the improved video quality by the proposed technique when H.264 videos are streamed over Rayleigh fading wireless channels.

• Economic and Environmental Geology
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• v.41 no.2
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• pp.219-223
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• 2008

Many cross-over errors due to position errors, meter errors, observation errors, sea conditions and so on occur when marine geophysical data collected by own and other agencies are merged, and these errors can create artificial anomalies which cause an improper interpretation. Many methods have been introduced to reduce cross-over errors. However, most methods are designed to compare each point or segment data to find cross-over points, and require a long processing time. Therefore, FORTRAN program (FastXcorr) is presented to fast determine cross-over points using an overlap-sector, and to adjust cross-over errors using a weighted linear interpolation algorithm.

• Journal of Communications and Networks
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• v.7 no.1
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• pp.45-53
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• 2005

In this paper, we present a cross-layer analysis of wireless TCP systems over correlated channels. The effects of error correlation on the behavior of link retransmission strategy and the end-to-end throughput of TCP layer are investigated. Based on the cross-layer analysis, an efficient refinement of link layer protocol is proposed by consciously utilizing the information of channel correlations, which leads to the performance improvement of wireless TCP systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3061-3080
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• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.146-154
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• 1995

By using simple Taylor expansion, we derive an easy bias-correction rule for the apparent prodiction error of the predictor defined by the general M-estimators with respect to an arbitrary measure of prediction error. Our method has a considerable computational advantage over the previous methods based on the resampling thchnique such as Cross-validaton and Boothtrap. Connections with AIC, Cross-Validation and Boothtrap are discussed too.

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.229-234
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• 2006

Cross-over errors (XOEs) may mislead scientists when interpreting marine geophysical data. Such risk can be reduced by correcting the data proportionally between two cross-over points (XOPs). C program is presented to determine XOPs using a quick rejection test and a straddle test, and to adjust XOEs using a weighted linear interpolation algorithm.

• ETRI Journal
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• v.17 no.1
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• pp.11-22
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• 1995

This paper proposes a modified error function to improve the error back-propagation (EBP) algorithm for multi-Layer perceptrons (MLPs) which suffers from slow learning speed. It can also suppress over-specialization for training patterns that occurs in an algorithm based on a cross-entropy cost function which markedly reduces learning time. In the similar way as the cross-entropy function, our new function accelerates the learning speed of the EBP algorithm by allowing the output node of the MLP to generate a strong error signal when the output node is far from the desired value. Moreover, it prevents the overspecialization of learning for training patterns by letting the output node, whose value is close to the desired value, generate a weak error signal. In a simulation study to classify handwritten digits in the CEDAR [1] database, the proposed method attained 100% correct classification for the training patterns after only 50 sweeps of learning, while the original EBP attained only 98.8% after 500 sweeps. Also, our method shows mean-squared error of 0.627 for the test patterns, which is superior to the error 0.667 in the cross-entropy method. These results demonstrate that our new method excels others in learning speed as well as in generalization.

• Transactions of Materials Processing
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• v.23 no.6
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• pp.369-375
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• 2014

Flexible roll forming allows profiles to have variable cross-sections. However, the profile may have some shape errors, such as, warping which is a major defect. The shape error is induced by geometrical deviations in both the concave zone and the convex zone. In the current study, flexible roll forming was modeled with FE simulations to analyze the shape error and the longitudinal strain distribution along the flange section over the profile. A distribution of analytically calculated longitudinal strains was used to develop relationships between the shape error and the longitudinal strain distribution as a function of the defined shape parameters for the profile. The FE simulations showed that the shape error is primarily affected by the deviations between the distribution of analytically calculated longitudinal strain and the longitudinal strain distribution of the profile. The results show that the shape error can be controlled by designing the shape parameters to control the geometrical deviations at the flange section in the transition zones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2266-2284
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• 2012

Recent studies have indicated that a significant improvement in wireless video throughput can be achieved by Cross Layer Design with Side-information (CLDS) protocols. In this paper, we derive the operational rate of a CLDS protocol operating over a realistic wireless channel. Then, a Rate-Distortion (R-D) empirical model for above-capacity Scalable Video Coding (SVC) is deduced to estimate the loss of video quality incurred under inaccurate rate estimation scenarios. Finally, we develop a novel Unequal Error Protection (UEP) scheme which leverages the characteristics of LDPC codes to reduce the distortion of video quality in case of typically-observed burst wireless errors. The efficacy of the proposed rate adaptation architecture over conventional protocols is demonstrated by realistic video simulations using actual IEEE 802.11b wireless traces.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.529-540
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• 2015

A cross-over design is frequently used in clinical trials (especially in bioequivalence tests with a parametric method) for the comparison of two treatments. Missing values frequently take place in cross-over designs in the second period. Usually, subjects that have missing values are removed and analyzed. However, it can be unsuitable in clinical trials with a small sample size. In this paper, we compare single imputation methods in a $2{\times}2$ cross-over design when missing values exist in the second period. Additionally, parametric and nonparametric methods are compared after applying single imputation methods. A Monte-Carlo simulation study compares type I error and the power of methods.