• Journal of KIISE
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• v.43 no.6
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• pp.686-691
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• 2016

In this paper, we introduced the adaptive spectral co-clustering, a spectral clustering for multiview data, especially data with more than three views. In the adaptive spectral co-clustering, the performance is improved by sharing information from diverse views. For the efficiency in information sharing, a co-training approach is adopted. In the co-training step, a set of parameters are estimated to make all views in data maximally independent, and then, information is shared with respect to estimated parameters. This co-training step increases the efficiency of information sharing comparing with ordinary feature concatenation and co-training methods that assume the independence among views. The adaptive spectral co-clustering was evaluated with synthetic dataset and multi lingual document dataset. The experimental results indicated the efficiency of the adaptive spectral co-clustering with the performances in every iterations and similarity matrix generated with information sharing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1253-1262
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• 2004

The Data Over Cable System Interface Specification (DOCSIS) protocol enables the delivery of Internet Protocol(IP) traffic over Cable TV networks with significantly higher data rates. In this paper, we assessed the performance of the DOCSIS protocol using the OPNET. The simulation can be used to predict the upstream system throughput, mean access delay and channel utilization on varying packet size and transmission stream and wid/without concatenation, and it has shown that maximum system throughput is 4.6 Mbps for channel capacity of 5.12 Mbps and packet size of 1500 bytes. The mean access delay varies depending on the offered load, and it is assumed that the offered load does not exceed the capacity of the channel. Excess offered load causes service starvation according to the assigned priority.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.285-292
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• 2002

One of the problems that should be solved in Text-To-Speech (TTS) is discontinuities at unit-joining points. To cope with this problem, a smoothing method using a low-pass filter is employed in this paper, In the proposed soothing method, a filter coefficient that controls the amount of smoothing is determined according to contort information to be synthesized. This method efficiently reduces both discontinuities at unit-joining points and artifacts caused by undesired smoothing. The amount of smoothing is determined with discontinuities around unit-joins points in the current synthesized speech and discontinuities predicted from context. The discontinuity predictor is implemented by CART that has context feature variables. To evaluate the performance of the proposed method, a corpus-based concatenative TTS was used as a baseline system. More than 6075 of listeners realized that the quality of the synthesized speech through the proposed smoothing is superior to that of non-smoothing synthesized speech in both naturalness and intelligibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.10-23
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• 1994

To transmit information efficiently and securely in On-line transmission, data compression, secrecy and authentication are required. In this paper, we propose LZWH4 which creates two compression strings with applying Hnageul to LZW. design HDES1 by extending S-box (S1-S16) which satsfies SAC and correlation coefficient as a partial countermeasure of Differential Cryptanalysis and implement LZWHDES1 which concatenates efficiently these for digital signature in On-line transmission. Also HDES1 is more in U.D.(Unicity Distance) than DES and HDES. We show that the proposed LZWHDES1 reduces processing times than LZWHDES which LZW is directly concatnated to DES and LZWHDES which LZWH1 is directly concatenated to HDES. LZWHDES1 can be used to digital signature system as conventional key cryptosystem.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.547-557
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• 2015

The security of all cryptographic algorithms and protocols is based on the confidentiality of secret keys. Key management mechanism is an indispensable part of the cryptographic system and this deals with the generation, exchange, storage, use, and replacement of keys. Within the key management mechanism there are key derivation functions (KDFs) which derive one or more keys from a master key. NIST specifies three families of PRF-based KDFs in SP 800-108. In this paper, we examine the difference of security models between the KDFs and the encryption modes of operations. Moreover we focus on the provable security of PRF-based KDFs according to input types of counters, and show that the counter and feedback modes of KDFs using XOR of counters are insecure, while these modes using concatenation of counters are secure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.18-25
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• 2002

In this paper, the performance of three types of serial concatenated convolutional codes (SCCC) in AWGN (additive white Gaussian noise) channel is compared and analyzed. As results of simulations, it can be observed that Type I shows the best error performance at lower signal-to-noise ratio (SNR) region. However, Type III shows the best error performance at higher SNR region. It can be also observed the error floor that the performance cannot be improved even though increasing of the number of iterations and SNR at Type I. However, the performance of Type II and Type III are still improved over the five iterations at higher SNR without error floor. And BER performance of three types can be closed to upper bound of three types with increase of SNR. It can be also observed that the upper bound of Type III shows the best performance among the three types due to the greatest free distance.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.407-414
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• 2002

In this paper, we present a method that automatically generates concatenate morpheme based language models to improve the performance of Korean large vocabulary continuous speech recognition. The focus was brought into improvement against recognition errors of monosyllable morphemes that occupy 54% of the training text corpus and more frequently mis-recognized. Knowledge-based method using POS patterns has disadvantages such as the difficulty in making rules and producing many low frequency concatenate morphemes. Proposed method automatically selects morpheme-pairs from training text data based on measures such as frequency, mutual information, and unigram log likelihood. Experiment was performed using 7M-morpheme text corpus and 20K-morpheme lexicon. The frequency measure with constraint on the number of morphemes used for concatenation produces the best result of reducing monosyllables from 54% to 30%, bigram perplexity from 117.9 to 97.3. and MER from 21.3% to 17.6%.

• Journal of radiological science and technology
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• v.43 no.4
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• pp.251-257
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• 2020

This study was purpose to quantitative evaluation of edge method of modulation transfer function(MTF) and physical image characteristics of by obtain the optimal edge image by using magnetic resonance imaging(MRI). The MRI equipment was used (MAGNETOM Vida 3.0T MRI, Siemense healthcare system, Germany) and the head/neck matrix shim MR coil were 20 channels(elements) receive coil. The MTF results of showed the best value of 0.294 based on the T2 Nyquist frequency of 1.0 mm^-1. The MTF results of showed that the T1 image is 0.160, the T1 CE image is 0.250, T1 Conca2 image is 0.043, and the T1 CE (Concatenation) Conca2 image is 0.190. The T2 image highest quantitatively value for MTF. The physical image characteristics of this study were to that can be used efficiently of the MRI and to present the quantitative evaluation method and physical image characteristics of 3.0T MRI.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.930-933
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• 2011

This paper addresses an adaptive postprocessing method applied in the spatial domain for block-based discrete cosine transform (BDCT) coded images. The proposed algorithm is designed by a serial concatenation of a 1D simple smoothing filter and a 2D directional filter. The 1D smoothing filter is applied according to the block type, which is determined by an adaptive threshold. It depends on local statistical properties, and updates block types appropriately by a simple rule, which affects the performance of deblocking processes. In addition, the 2D directional filter is introduced to suppress the ringing effects at the sharp edges and the block discontinuities while preserving true edges and textural information. Comprehensive experiments indicate that the proposed algorithm outperforms many deblocking methods in the literature, in terms of PSNR and subjective visual quality evaluated by GBIM.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1113-1121
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• 2019

In this paper, we propose the face anti-spoofing method based on combination of luminance and chrominance with convolutional neural networks. The proposed method extracts luminance and chrominance features independently from live and fake faces by using stacked convolutional neural networks and auxiliary networks. Unlike previous methods, an attention module has been adopted to adaptively combine extracted features instead of simply concatenating them. In addition, we propose a new loss function, called the contrast loss, to learn the classifier more efficiently. Specifically, the contrast loss improves the discriminative power of the features by maximizing the distance of the inter-class features while minimizing that of the intra-class features. Experimental results demonstrate that our method achieves the significant improvement for face anti-spoofing compared to existing methods.