• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.245-252
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• 2008

We present a classification algorithm based on ant colony system(ACS) for classifying digital images. The ACS has been recently emerged as a useful tool for the pattern recognition, image extraction, and edge detection. The classification algorithm of digital images is very important in the application areas of digital image coding, image analysis, and image recognition because it significantly influences the quality of images. The conventional procedures usually classify digital images with the fixed value for the associated parameters and it requires postprocessing. However, the proposed algorithm utilizing randomness of ants yields the stable and enhanced images even for processing the rapidly changing images. It is also expected that, due to this stability and flexibility of the present procedure, the digital images are stably classified for processing images with various noises and error signals arising from processing of the drastically fast moving images could be automatically compensated and minimized.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.359-369
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• 2021

In underwater communications, to compensate performance degradation induced from rapidly changing channel transfer characteristic, multi-band communication method which allocate the same data to different frequency bands is used. However, the multi-band configuration may have worse performance than the single-band one because performance degradation in a particular band affects the output from the entire bands. This problem can be solved through a receiving end that analyzes error rates of each band, sets threshold values and allocates lower weights to inferior bands. Therefore, this paper proposed a weighting algorithm based on estimated Bit Error Rate (BER) which analyzes reliability of received data based on the performance difference between demodulated and decoded data. Employing turbo codes with coding rate of 1/3, we evaluate the performance of the proposed weighted multi-band transmission model in real underwater environments based on optimal simulation parameters. Through the sea trial experiment, we confirmed error performance was improved by applying the proposed weighting algorithm.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.47-57
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• 2021

Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.206-210
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• 2024

Industrial facilities that use modern IT technologies require the ensured reliability and security of information in automated enterprise management. Concurrently, so as to ensure a high quality of communication, it is necessary to expand the bandwidth of communication channels, which are limited by the physical parameters of the radio frequency spectrum. In order to overcome this contradiction, we propose the application of technology fundamental to ultra-wideband signals, in which the ratio between the bandwidth and its central part is greater than "one". For this reason, the information signal is emitted without a carrier frequency - simultaneously within the entire frequency band - provided that the signal level is lower than the noise level. For the transmission of information content, the method of positional-time coding is used, in which each information bit is encoded by hundreds of ultrashort pulses that arrive within a certain sequence. Mathematical models of signals and values observed in wireless communication systems with autocorrelation reception of modulated ultra-wideband signals are furthermore recommended. These assist in identifying features of the dependence of the error probability on the normalized signal-to-noise ratio and the signal base. Comparative analysis has shown that the best noise immunity of the systems considered in this paper is the communication system, which uses the time separation of the reference and information signals. During the first half of the bit interval, the switch closes the output of the transmitter directly to the generator of the ultra-wideband signal - forming a reference signal. In the middle of the bit interval, the switch alternates the output to one of two possible positions depending on the encoding signal - "zero" or "one", forming the information part of the ultra-wideband signal. It should also be noted that systems with autocorrelation reception and separate transmission of reference and information signals, provide a high level of structural signal secrecy. Furthermore, they provide the reliable transmission of digital information, especially in interference conditions.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.310-339
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• 2015

In this paper, the possibility of a terrestrial fixed 4K UHD (Ultra High Definition) and mobile HD (High Definition) convergence broadcasting service through a single channel employing the FEF (Future Extension Frame) multiplexing technique in DVB (Digital Video Broadcasting)-T2 (Second Generation Terrestrial) systems is examined. The performance of such a service is also investigated. FEF multiplexing technology can be used to adjust the FFT (fast Fourier transform) and CP (cyclic prefix) size for each layer, whereas M-PLP (Multiple-Physical Layer Pipe) multiplexing technology in DVB-T2 systems cannot. The convergence broadcasting service scenario, which can provide fixed 4K UHD and mobile HD broadcasting through a single terrestrial channel, is described, and transmission requirements of the SHVC (Scalable High Efficiency Video Coding) technique are predicted. A convergence broadcasting transmission system structure is described by employing FEF and transmission technologies in DVB-T2 systems. Optimized transmission parameters are drawn to transmit 4K UHD and HD convergence broadcasting by employing a convergence broadcasting transmission structure, and the reception performance of the optimized transmission parameters under AWGN (additive white Gaussian noise), static Brazil-D, and time-varying TU (Typical Urban)-6 channels is examined using computer simulations to find the TOV (threshold of visibility). From the results, for the 6 and 8 MHz bandwidths, reliable reception of both fixed 4K UHD and mobile HD layer data can be achieved under a static fixed and very fast fading multipath channel.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.235-242
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• 2008

To improve video quality and coding efficiency, H.264/AVC adopted an adaptive rate control. But this method has a problem as it cannot predict an accurate quantization parameter(QP) for the first frame. The first QP is decided among four constant values by using encoder input parameters. It does not consider encoding bits, results in significant fluctuation of the image quality and decreases the average quality of the whole coded sequence. In this paper, we propose a new algorithm for the first frame QP decision in the H.264/AVC encoder. The QP is decided by the existing algorithm and the first frame is encoded. According to the encoded bits, the new initial QP is decided. We can predict optimal value because there is a linear relationship between encoded bits and the new initial QP. Next, we re-encode the first frame using the new initial QP. Experimental results show that the proposed algorithm not only achieves better quality than the state of the art algorithm, but also adopts a rate control forthe sequence that was impossible with the existing algorithm. By reducing fluctuation, subjective quality also improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.795-804
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• 1999

The increasing number of users of mobile communication systems and the corresponding need for increased system capacity require the use of a modulation scheme which is both power and spectrally efficient. In this paper, we numerically calculate the BER performance of DS/CDMA-BPSK system in different fading channel (Rayleigh, Rician, Shadow Rician). Also, we calculate BER performance and the channel capacity of DS/CDMA-BPSK system which is constant or nearly constant envelopes in 3-state fading channel model. The Shadow Rician fading model described in this paper apply the parameters of the Canadian Mobile Satellite (MSAT). And we assume that the 3-state fading channel model is consist of Rayleigh fading state, Rician fading state, and shadow Rician fading state. This model can be used as a basis for the simulation of the land mobile satellite channel. The dynamic 3-state fading channel model is considered corresponding to different environments and the transitions between these environments. From the numerically calculate results, the DS/CDMA-BPSK system with MUI-20, PG-511 can not achieve the BER performance ($P_b\leq10^{-5}$). And the channel capacity did not meet the system requirement. Also, we know that the BER performance is depend m the occupancy probability of radio channel and the degree of shadow. From the results, we how that during shadowed time intervals it is necessary to use some form of error control coding and receiver diversity in order to support reliable data communication.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.522-526
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• 2007

Since newly emerged disease, the Severe Acute Respiratory Syndrome (SARS), spread from Asia to North America and Europe rapidly in 2003, many researchers have tried to determine where the virus came from. In the phylogenetic point of view, SARS virus has been known to be one of the genus Coronavirus, but, the overall conservation of SARS virus sequence was not highly similar to that of known coronaviruses. The natural reservoirs of SARS-CoV are not clearly determined, yet. In the present study, the genomic sequences of SARS-CoV were analyzed by bioinformatics techniques such as multiple sequence alignment and phylogenetic analysis methods as well multivariate statistical analysis. All the calculating processes, including calculations of the relative synonymous codon usage (RSCU) and other genomic parameters using 30,305 coding sequences from the two genera, Coronavirus, and Lentivirus, and one family, Orthomyxoviridae, were performed on SMP cluster in KISTI, Supercomputing Center. As a result, SARS_CoV showed very similar RSCU patterns with feline coronavirus on the both axes of the correspondence analysis, and this result showed more agreeable results with serological results for SARS_CoV than that of phylogenetic result itself. In addition, SARS_CoV, human immunodeficiency virus, and influenza A virus commonly showed the very low RSCU differences among each synonymous codon group, and this low RSCU bias might provide some advantages for them to be transmitted from other species into human beings more successfully. Large-scale genomic analysis using bioinformatics techniques may be useful in genetic epidemiology field effectively.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.23-35
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• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.69-78
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• 2017

Shannon of the 5G smartphone and Fourier of the signal processing meet in the sampling theorem (2 times the highest frequency 1). In this paper, the initial Shannon Theorem finds the Shannon capacity at the point-to-point, but the 5G shows on the Relay channel that the technology has evolved into Multi Point MIMO. Fourier transforms are signal processing with fixed parameters. We analyzed the performance by proposing a 2N-1 multivariate Fourier-Jacket transform in the multimedia age. In this study, the authors tackle this signal processing complexity issue by proposing a Jacket-based fast method for reducing the precoding/decoding complexity in terms of time computation. Jacket transforms have shown to find applications in signal processing and coding theory. Jacket transforms are defined to be $n{\times}n$ matrices $A=(a_{jk})$ over a field F with the property $AA^{\dot{+}}=nl_n$, where $A^{\dot{+}}$ is the transpose matrix of the element-wise inverse of A, that is, $A^{\dot{+}}=(a^{-1}_{kj})$, which generalise Hadamard transforms and centre weighted Hadamard transforms. In particular, exploiting the Jacket transform properties, the authors propose a new eigenvalue decomposition (EVD) method with application in precoding and decoding of distributive multi-input multi-output channels in relay-based DF cooperative wireless networks in which the transmission is based on using single-symbol decodable space-time block codes. The authors show that the proposed Jacket-based method of EVD has significant reduction in its computational time as compared to the conventional-based EVD method. Performance in terms of computational time reduction is evaluated quantitatively through mathematical analysis and numerical results.