• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.44-55
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• 1993

In this paper, we proposed a new optical method for the efficient recognition of Korean characters. There are six filters in the proposed method which employed the concepts of amplitude-modulated phase-only filter(AMPOF) and spatial frequency modulation(SFM). Here, amplitude modulation is used to achieve improved correlation discrimination and SFM is to reduce the number of filters. We also used a simplified synthetic discriminant function(SDF) for distortion invariance of input image. In order to recognize the partial rotation invariant Korean characters, the proposed distortion invariant minimum average correlation energy (MACE) filter is synthesized SFM, partial rotation invariant filter (PRIF), AMPOF and MACE for partial rotation invariance in the frequency domain. The advantage of the proposed filters is to supress the sidelobes of cross correlation peak away from the autocorrelation peak and to produce sharp correlation peaks. We performed simulation and optical experiment for some of Korea characters using the proposed method. The results show that the proposed method has more improved discriminant ability and reduced processing time than the conventional methods.

• Molecules and Cells
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• v.38 no.10
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• pp.836-842
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• 2015

G protein-coupled receptors (GPCRs) constitute the largest and the most physiologically important membrane protein family that recognizes a variety of environmental stimuli, and are drug targets in the treatment of numerous diseases. Recent progress on GPCR structural studies shed light on molecular mechanisms of GPCR ligand recognition, activation and allosteric modulation, as well as structural basis of GPCR dimerization. In this review, we will discuss the structural features of GPCRs and structural insights of different aspects of GPCR biological functions.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.10-18
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• 2019

Since the introduction of CRT(Cathode Ray Tube) in the 1950s, display technologies have been developed continuously. Flat panel displays such as PDP(Plasma Display Panel) and LCD(Liquid Crystal Display) were commercialized in the late 1990s, and OLED(Organic Light Emitting Diodes) and Micro-LED(Micro-Light Emitting Diodes) are now being developed and are becoming widespread. In the future, we expect to develop ultra-realistic, flexible, embedded sensor displays. Ultra-realistic display can be applied to AR/VR(Augmented Reality/Virtual Reality) devices and spatial light modulators for holography. The sensor-embedded display can be applied to robots; electronic skin; and security devices, including iris recognition sensors, fingerprint recognition sensors, and tactile sensors. AR/VR technology must be developed to meet technical requirements such as viewing angle, resolution, and refresh rate. Holography requires optical modulation technology that can significantly improve resolution, viewing angle, and modulation method to enable wide-view and high-quality hologram stereoscopic images. For electronic skin, stable mass production technology, large-area arrays, and system integration technologies should be developed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1464-1471
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• 1999

This paper introduces complex-valued competitive learning neural network for spatio-temporal pattern recognition. There have been quite a few neural networks for spatio-temporal pattern recognition. Among them, recurrent neural network, TDNN, and avalanche model are acknowledged as standard neural network paradigms for spatio-temporal pattern recognition. Recurrent neural network has complicated learning rules and does not guarantee convergence to global minima. TDNN requires too many neurons, and can not be regarded to deal with spatio-temporal pattern basically. Grossberg's avalanche model is not able to distinguish long patterns, and has to be indicated which layer is to be used in learning. In order to remedy drawbacks of the above networks, unsupervised competitive learning using complex umber is proposed. Suggested neural network also features simultaneous recognition, time-shift invariant recognition, stable categorizing, and learning rate modulation. The network is evaluated by computer simulation with randomly generated patterns.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2009-2019
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• 2013

In this paper, we propose an automatic modulation recognition algorithm based on cyclic moment and new modified cumulant for analog and digital modulation signals. It is noteworthy that each modulated signal has different cycle frequency characteristics according to its order of cyclic moment. By means of this characteristics as classification features, various modulated signals can be efficiently classified. Also, to identify modulated signals having the same cycle frequency characteristics, we take advantage of the additional classification factors such as variations of envelope and phase as well as modified cumulant. The proposed algorithm was evaluated by considering the number of symbols, SNR, and frequency offset. In the simulation condition where the number of gathered symbols was about 819, and SNR and frequency offset were above 10dB and below 25%, respectively, the average accuracy of the proposed algorithm was more than 95%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.658-672
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• 2021

Since the signal with strong power need be demodulated first for successive interference cancellation (SIC) receiver in non-orthogonal multiple access (NOMA) systems, the base station (BS) need inform the near user terminal (UT), which has allocated higher power, of the far UT's modulation mode. To avoid unnecessary signaling overhead of control channel, a blind detection algorithm of NOMA signal modulation mode is designed in this paper. Taking the joint constellation density diagrams of NOMA signal as the detection features, the deep residual network is built for classification, so as to detect the modulation mode of NOMA signal. In view of the fact that the joint constellation diagrams are easily polluted by high intensity noise and lose their real distribution pattern, the wavelet denoising method is adopted to improve the quality of constellations. The simulation results represent that the proposed algorithm can achieve satisfactory detection accuracy in NOMA systems. In addition, the factors affecting the recognition performance are also verified and analyzed.

• ETRI Journal
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• v.43 no.6
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• pp.991-1003
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• 2021

Automatic modulation classification is essential in radar emitter identification. We propose a cascade classifier by combining a support vector machine (SVM) and convolutional neural network (CNN), considering that noise might be taken as radar signals. First, the SVM distinguishes noise signals by the main ridge slice feature of signals. Second, the complex envelope features of the predicted radar signals are extracted and placed into a designed CNN, where a modulation classification task is performed. Simulation results show that the SVM-CNN can effectively distinguish radar signals from noise. The overall probability of successful recognition (PSR) of modulation is 98.52% at 20 dB and 82.27% at -2 dB with low computation costs. Furthermore, we found that the accuracy of intermediate frequency estimation significantly affects the PSR. This study shows the possibility of training a classifier using complex envelope features. What the proposed CNN has learned can be interpreted as an equivalent matched filter consisting of a series of small filters that can provide different responses determined by envelope features.

• International Journal of Oral Biology
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• v.34 no.2
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• pp.49-52
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• 2009

Perception of sweet compounds is important for animals to detect external carbohydrate source of calories and plays a crucial role in feeding behavior of animals. Recent progress in molecular genetic studies provides evidence for a candidate receptor (heterodimers with taste receptor type 1 member 2 and 3: T1R2/T1R3), and major downstream transduction molecules required for sweet taste signaling. Several studies demonstrated that the sweet taste signal can be modulated by a satiety hormone, leptin, through its receptors expressed in a subset of sweet-sensitive taste cells. Increase of internal energy storage in the adipose tissue leads to increase in the plasma leptin level which can reduce activities of sweet-sensitive cells. In human, thus, diurnal variation of plasma leptin level parallels variation of taste recognition thresholds for sweet compounds. This leptin modulation of sweet taste sensitivity may influence individuals' preference, ingestive behavior, and absorption of nutrients, thereby plays important roles in regulation of energy homeostasis.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.491-494
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• 2000

A scheme is proposed for measuring similarities between the binary pulse signals in the pulse-code modulation using the Integra-Normalizer. The Integra-Normalizer provides a better interpretation of the relationship between the pulse signals by removing redundant codes, which maps all possible observed signals to one of the codes to be received with relative similarities between each pair of compared signals. The proposed method provides better error tolerance than L2 metric, such as Hamming distance, since the distances between pulse signals are measured not useful for the time-delay detection in the pulse-code modulation.

• MALSORI
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• no.51
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• pp.1-16
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• 2004

The aim of this paper is to analyze vowels in voice imitation and disguised voice, and to find the invariable phonetic features of the speaker. In this paper we examined the formants of monophthongs /a, u, i, o, {$\omega},{\;}{\varepsilon},{\;}{\Lambda}$/. The results of the present are as follows : $\circled1$ Speakers change their vocal tract features. $\circled2$ Vowels /a, ${\varepsilon}$, i/ appear to be proper for speaker recognition since they show invariable acoustic feature during voice modulation. $\circled3$ F1 does not change easily compared to higher formants. $\circled4$ F3-F2 appears to be constituent for a speaker identification in vowel /a/ and /$\varepsilon$/, and F4-F2 in vowel /i/. $\circled5$ Resulting of F-ratio, differences of each formants were more useful than individual formant of a vowel to speaker recognition.