• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.69-76
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• 2015

In this paper, we propose and analyze a M-ary transmission scheme in time hopping ultra-wide band(UWB) system using mutually orthogonal modified Hermite polynomial(MHP) pulses. The proposed M-ary transmission scheme employs the orthogonal property between different ordered pulses and N data bits make the M-ary signals by linear combination of M MHP pluses. The theoretical analysis and simulation results show that the proposed system has better performance and higher data rate than conventional M-ary UWB system. We derive the general form of correlation function for MHP pulses and analyze bit error rate(BER) performance over additive white Gaussian noise(AWGN) with the presence of timing jitter. We show that the proposed system has the improved BER performance and robustness to timing jitter and low power spectrum density compared with conventional M-ary UWB system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1833-1839
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• 2014

In this paper, a systematic demapping algorithm for three-dimensional (3-D) lattice signal constellations is presented. The algorithm consists of decision of an octant, computation of a distance from the origin, and determination of the coordinates of a symbol. Since the algorithm can be extended systematically, it is applicable to the larger lattice constellations. To verify the algorithm, 3-D signal transmission systems with field programmable gate array (FPGA) and $Matlab^{(R)}$ are implemented. And they are exploited to carry out computer simulation. As a result, both hardware and software based systems produce almost the same symbol error rates (SERs) in an additive white Gaussian noise (AWGN) environment. In addition, the hardware based system implemented with an FPGA generates waveforms of 3-D signals and recovers the original binary sequences perfectly. Those results confirm that the algorithm and the implemented 3-D transmission system operate correctly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.279-286
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• 2015

EMD is a fully data-driven signal processing method without using any predetermined basis function and requiring any user parameters setting. However EMD experiences a problem of mode mixing which interferes with decomposing the signal into similar oscillations within a mode. To overcome the problem, EEMD method was introduced. The algorithm performs the EMD method over an ensemble of the signal added independent identically distributed white noise of the same standard deviation. Even so EEMD created problems when the decomposition is complete. The ensemble of different signal with added noise may produce different number of modes and the reconstructed signal includes residual noise. This paper propose an modified EEMD method to overcome mode mixing of EMD, to provide an exact reconstruction of the original signal, and to separate modes with lower cost than EEMD's. The experimental results show that the proposed method provides a better separation of the modes with less number of sifting iterations, costs 20.87% for a complete decomposition of the signal and demonstrates superior performance in the signal reconstruction, compared with EEMD.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.227-232
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• 2006

In this paper, a Kalman filter application for GDSS(Group Digital Surveillance System) developed to protect an aquaculture farms is discussed GDSS is composed by a WIWAS(Watching, Identification, Warning, and Action System) and a FDS(Fishery Detection System) that will monitor incoming and outgoing vessels in the aquaculture farms. In the FDS, a tracking function to track vessels without F-AIS(Fishery Automatic Identification System) is needed and the Kalman filter is applied to track vessels around the aquaculture farms. Some simulation results for the multi-objects with white noise is presented and the adaptation possibility for tracking system is discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1433-1443
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• 2004

The power line modem proposed in this paper transmits the remote control signal using CSK(Code Shift Keying) and DS/SS method. The CSK technique provides the increased capacity of transmission and robustness towards noise. Besides, the DS/SS technique provides protection against narrow-band Gaussian interference and multi-path interference. The modem supports full-duplex communication using FDD(Frequency Division Duplex) and the modem structure for forward link is same with that for reverse link. To switch each sub-controlled unit smoothly, 4/$\pi$-DQPSK is adopted for noncoherent demodulation. The PN code for spreading spectrum seues to divide each group which consists of sub-controlled units and Walsh code is used for the M-ary CSK technique. Each block is designed and verified with TMS320C5402 DSP. We show the superiority of the proposed method by analyzing numerically the system performance for the factors of the DS/SS and CSK method ullder additive white Gaussian noise and PBI.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.23-29
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• 2020

The National Institute of Agricultural Sciences of the Rural Developement Administration (NAS, RDA) is conducting various studies on various crops, such as monitoring the cultivation environment and analyzing harvested seeds for high-throughput phenotyping. In this paper, we propose a deep learning-based rice seed segmentation method to analyze the seeds of various crops owned by the NAS. Using Mask-RCNN deep learning model, we perform the rice seed segmentation from manually taken images under specific environment (constant lighting, white background) for analyzing the seed characteristics. For this purpose, we perform the parameter tuning process of the Mask-RCNN model. By the proposed method, the results of the test on seed object detection showed that the accuracy was 82% for rice stem image and 97% for rice grain image, respectively. As a future study, we are planning to researches of more reliable seeds extraction from cluttered seed images by a deep learning-based approach and selection of high-throughput phenotype through precise data analysis such as length, width, and thickness from the detected seed objects.

• Journal of Fashion Business
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• v.6 no.3
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• pp.41-51
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• 2002

The author of the paper investigated the changes of hairstyle along the developments in hairdressing industry in the 20th century. The development process of hairdressing industry was divided into four periods of introduction, origination, growth, and establishment. The corresponding changes of hairstyle were analyzed and the findings are as follows. 1. Hairstyle could be classified into such typical ones as traditional style, cut, bob, wave, permanent wave, up style, and hair coloring. 2. Fashion leaders affected the changes of hairstyle. 3. Whenever hairdressing appliances were introduced, new hairstyle was practiced as follows with the use of the appliances. (1) Introduction Period - Traditional Style : Chignon, pigtail ribbon $\rightarrow$ Variations were designed in hair length or split due to the limited availability of appliances. - Up Style : Pompadour, thick and up hair, encircling hair $\rightarrow$ Padding was used for sweep-up. (2) Origination Period - Bob Style : Women's first bob style. - Wave style : Wave with bob, close-cropped hair, up style $\rightarrow$ Iron, set, permanent devices were used. (3) Development Period - Wave Style : Wind wave, easily manageable wave $\rightarrow$ Blow dry, body permanent were used. (4) Establishment Period - Straight Style : Use of straight permanent. - Thick Wave Style : Development of various kinds of rod. - Hair Coloring : Advent of diverse fashion hair coloring, apart from the coloring of white hair, with the introduction of color TV. - Bob Style : Romantic bob style $^{\circ}\hat{E}$ Use of clippers and thinning scissors. Thus, the changes of hairstyle according to the development in hairdressing industry had close relationship with the improvement in hairdressing appliances.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.81-86
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• 2014

In this paper, we present an effective sound classification system for recognizing the real-time context of a smartphone user. Our system avoids unnecessary consumption of limited computational resource by filtering both silence and white noise out of input sound data in the pre-processing step. It also improves the classification performance on low energy-level sounds by amplifying them as pre-processing. Moreover, for efficient learning and application of HMM classification models, our system executes the dimension reduction and discretization on the feature vectors through k-means clustering. We collected a large amount of 8 different type sound data from daily life in a university research building and then conducted experiments using them. Through these experiments, our system showed high classification performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.811-816
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• 2019

This paper first proposes a technique to separate clean speech signals and mixed noise signals by using an independent vector analysis algorithm of frequency band for 4 channel speech source signals with a noise. An improved output speech signal from the proposed independent vector analysis algorithm is obtained by using the cross-correlation between the signal outputs from the frequency domain delay-sum beamforming and the output signals separated from the proposed independent vector analysis algorithm. In the experiments, the proposed algorithm improves the maximum SNRs of 10.90dB and the segmental SNRs of 10.02dB compared with the frequency domain delay-sum beamforming algorithm for the input mixed noise speeches with 0dB and -5dB SNRs including white noise, respectively. Therefore, it can be seen from this experiment and consideration that the speech quality of this proposed algorithm is improved compared to the frequency domain delay-sum beamforming algorithm.