• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.21-27
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• 2019

Selection of feature pattern gathered from the observation of the RNA sequencing data (RNA-seq) are not all equally informative for identification of differential expressions: some of them may be noisy, correlated or irrelevant because of redundancy in Big-Data sets. Variable selection of feature pattern aims at differential expressed gene set that is significantly relevant for a special task. This issues are complex and important in many domains, for example. In terms of a computational research field of machine learning, selection of feature pattern has been studied such as Random Forest, K-Nearest and Support Vector Machine (SVM). One of most the well-known machine learning algorithms is SVM, which is classical as well as original. The one of a member of SVM-criterion is Support Vector Machine-Recursive Feature Elimination (SVM-RFE), which have been utilized in our research work. We propose a novel algorithm of the SVM-RFE with Q-learning in reinforcement learning for better variable selection of feature pattern. By comparing our proposed algorithm with the well-known SVM-RFE combining Welch' T in published data, our result can show that the criterion from weight vector of SVM-RFE enhanced by Q-learning has been improved by an off-policy by a more exploratory scheme of Q-learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1403-1417
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• 2019

With the rapid growth of multimedia data, research on cross-media feature learning has significance in many applications, such as multimedia search and recommendation. Existing methods are sensitive to noise and edge information in multimedia data. In this paper, we propose a semi-supervised method for cross-media feature learning by means of $L_{2,q}$ norm to improve the performance of cross-media retrieval, which is more robust and efficient than the previous ones. In our method, noise and edge information have less effect on the results of cross-media retrieval and the dynamic patch information of multimedia data is employed to increase the accuracy of cross-media retrieval. Our method can reduce the interference of noise and edge information and achieve fast convergence. Extensive experiments on the XMedia dataset illustrate that our method has better performance than the state-of-the-art methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.295-296
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• 2010

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.1-7
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• 2006

In this paper, adaptive Facial Emotional Recognition system based on Gabor Wavelet Neural Network, considering six feature Points in face image to extract specific features of facial expression, is proposed. Levenberg-Marquardt-based training methodology is used to formulate initial network, including feature extraction stage. Therefore, heuristics in determining feature extraction process can be excluded. Moreover, to make an adaptive network for new user, Q-learning which has enhanced reward function and unsupervised fuzzy neural network model are used. Q-learning enables the system to ge optimal Gabor filters' sets which are capable of obtaining separable features, and Fuzzy Neural Network enables it to adapt to the user's change. Therefore, proposed system has a good on-line adaptation capability, meaning that it can trace the change of user's face continuously.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.745-746
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• 2009

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.7-13
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• 2022

Radio frequency fingerprinting refers to a methodology that extracts hardware-specific characteristics of a transmitter that are unintentionally embedded in a transmitted waveform. In this paper, we put forward a fingerprinting feature and deep learning structure that can identify the same type of Digital Mobile Radio(DMR) by inputting the in-phase(I) and quadrature(Q). We proposes using the magnitude in polar coordinates of I/Q as RF fingerprinting feature and a modified ResNet-1D structure that can identify them. Experimental results show that our proposed modified ResNet-1D structure can achieve recognition accuracy of 99.5% on 20 DMR.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.143-144
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• 2005

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.192-200
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• 2015

Several algorithms have been developed to classify arrhythmia which rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to classify the pattern by analyzing personalized ECG signal and extracting minimal feature. Thus, QRS pattern Analysis of personalized ECG Signal by Q, R, S peak variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and extract eight feature by amplitude and phase variability. Also, we classified nine pattern in realtime through peak and morphology variability. PVC, PAC, Normal, LBBB, RBBB, Paced beat arrhythmia is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 93.72% in QRS pattern detection classification.

• Clinical and Experimental Pediatrics
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• v.59 no.sup1
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• pp.19-24
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• 2016

Constitutional interstitial deletions of the long arm of chromosome 5 (5q) are quite rare, and the corresponding phenotype is not yet clearly delineated. Severe mental retardation has been described in most patients who present 5q deletions. Specifically, the interstitial deletion of chromosome 5q33.3q35.1, an extremely rare chromosomal aberration, is characterized by mental retardation, developmental delay, and facial dysmorphism. Although the severity of mental retardation varies across cases, it is the most common feature described in patients who present the 5q33.3q35.1 deletion. Here, we report a case of a de novo deletion of 5q33.3q35.1, 46,XY,del(5)(q33.3q35.1) in an 11-year-old boy with mental retardation; to the best of our knowledge this is the first case in Korea to be reported. He was diagnosed with severe mental retardation, developmental delay, facial dysmorphisms, dental anomalies, and epilepsy. Chromosomal microarray analysis using the comparative genomic hybridization array method revealed a 16-Mb-long deletion of 5q33. 3q35.1(156,409,412-172,584,708)x1. Understanding this deletion may help draw a rough phenotypic map of 5q and correlate the phenotypes with specific chromosomal regions. The 5q33.3q35.1 deletion is a rare condition; however, accurate diagnosis of the associated mental retardation is important to ensure proper genetic counseling and to guide patients as part of long-term management.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.427-430
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• 2005

A multi-code biorthogonal code keying (MBCK) system consists of multiple waveform coding blocks, and the sum of output codewords is transmitted. Drawback of MBCK is that it requires amplifier with high linearity because its output symbol is multi-level. MBCK with constant amplitude precoding block (CA-MBCK) has been proposed, which guarantees sum of orthogonal codes to have constant amplitude. The precoding block in CA-MBCK is a redundant waveform coder whose input bits are generated by processing the information bits. Redundant bits of constant amplitude coded CA-MBCK are not only used to make constant amplitude signal but also used to improve the BER performance at the receiver. In this paper, we proposed a transmission scheme which combines CA-MBCK with $Q^2PSK$ modulation to improve bandwidth efficiency of CA-MBCK and also uses chip interleaving to maintain a constant amplitude feature of CA-MBCK. bandwidth efficiency of a proposed transmission scheme is increased fourfold. And the BER performance of the scheme is same as that of CA-MBCK.