• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

• Atmosphere
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• v.32 no.2
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• pp.163-178
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• 2022

This study aims to evaluate the accuracy of retrieved horizontal winds with different quality control methods from three Doppler lidars deployed over the complex terrain during the PyeongChang 2018 Olympic and Paralympic games. To retrieve the accurate wind profile, this study also proposes two quality control methods to distinguish between meteorological signals and noises in the Doppler velocity field, which can be broadly applied to different Doppler lidars. We evaluated the accuracy of retrieved winds with the wind measurements from the nearby or collocated rawinsondes. The retrieved wind speed and direction show a good agreement with rawinsonde with a correlation coefficient larger than 0.9. This study minimized the sampling error in the wind evaluation and estimation, and found that the accuracy of retrieved winds can reach ~0.6 m s^-1 and 3° in the quasi-homogeneous wind condition. We expect that the retrieved horizontal winds can be used in the high-resolution analysis of the horizontal winds and provide an accurate wind profile for model evaluation or data assimilation purposes.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.365-378
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• 2022

Complete blood cell count(CBC) is a technique that counts leukocytes for each type of blood cell being analyzed. The principle is that laser is incident to ex vivo flowing leukocytes in a microcapillary tube and scattered light occurs by laser and leukocytes. By collecting the scattered light, we can count the types of cells because different cells generate different light-scattering patterns. However, the technique has an intrinsic limitation, scattering pattern is shown in a wide range region in the resulting, which makes it difficult to accurate analyze and use fluorescent dyes. To overcome this limitation, a new design of CBC with a dual laser, which irradiates with orthogonal angles for collecting quad-scattering information was proposed. Before development, the scattering difference depending on wavelength must be investigated to only catch up to the scattered signal by angles. Some studies, which focused on simple particles, have been conducted to theoretically and experimentally investigate different scatterings by wavelength. In this study, we propose an optical system for measuring scattered light and investigate a complex particle. As a result, the green laser made strong scattering signals in both the forward and side direction: 10% and 30%, respectively.

• Smart Structures and Systems
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• v.29 no.1
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• pp.117-127
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• 2022

Data anomalies seriously threaten the reliability of the bridge structural health monitoring system and may trigger system misjudgment. To overcome the above problem, an efficient and accurate data anomaly detection method is desiderated. Traditional anomaly detection methods extract various abnormal features as the key indicators to identify data anomalies. Then set thresholds artificially for various features to identify specific anomalies, which is the artificial experience method. However, limited by the poor generalization ability among sensors, this method often leads to high labor costs. Another approach to anomaly detection is a data-driven approach based on machine learning methods. Among these, the bidirectional long-short memory neural network (BiLSTM), as an effective classification method, excels at finding complex relationships in multivariate time series data. However, training unprocessed original signals often leads to low computation efficiency and poor convergence, for lacking appropriate feature selection. Therefore, this article combines the advantages of the two methods by proposing a deep learning method with manual experience statistical features fed into it. Experimental comparative studies illustrate that the BiLSTM model with appropriate feature input has an accuracy rate of over 87-94%. Meanwhile, this paper provides basic principles of data cleaning and discusses the typical features of various anomalies. Furthermore, the optimization strategies of the feature space selection based on artificial experience are also highlighted.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.73-80
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• 2009

G protein-coupled receptors(GPCRs) family is a cell membrane protein, and plays an important role in a signaling mechanism which transmits external signals through cell membranes into cells. But, GPCRs each are known to have various complex control mechanisms and very unique signaling mechanisms. Structural features, and family and subfamily of GPCRs are well known by function. and accordingly, the most fundamental work in studies identifying the previous GPCRs is to classify the GPCRs with given protein sequences. Studies for classifying previously identified GPCRs more easily with mathematical models have been mainly going on. In this paper Considering that functions of proteins are determined by their stereoscopic structures, the present paper proposes a method to compare secondary structures of two GPCRs having different amino acid sequences, and then detect an unknown GPCRs assumed to have a same function in databases of previously identified GPCRs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.235-236
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• 2021

As a result of analyzing the fire accident of the Jecheon complex that occurred at the end of 2017, there have been many casualties due to delays in checking the location information of isolated people. In order to prevent such an accident, various research has been conducted to estimate the location of requesters by means of detecting wireless communication information of mobile phones existing at disaster sites. The main concept is to detect an RF signal of a mobile phone at fire sites and, based on this, precisely estimate the location of the mobile phone on the LOS/NLOS. However, it is difficult to get visibility at fire sites due to smoke and the fire. Therefore, apart from estimating the location of requesters, a research is also needed to determine the direction of entry within fire sites. In this paper, we propose a method to determine a direction of entry to provide effective rescue activities using wireless communication information of mobile phones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.275-276
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• 2021

In the event of a fire in a complex, the identification of isolated people's location information is delayed, resulting in many casualties. In order to prevent such an accident, research on estimating the location of the requesters by detecting the wireless signal of the mobile phone at fire sites is in progress. The main concept is to use a wireless signal scanner to detect the wireless signal of a mobile phones at fire sites, and then position the mobile phone based on this. However, it is difficult to secure visibility at the fire site due to the smoke, and there is a difficulty in rescuing requesters in need compared with general disaster sites. Therefore, it will be one of the important issues to be solved to determine the minimum number of rescuers to be deployed according to the number and condition of the requesters. In this study, we propose a method to calculate the number of rescuers put to fire sites by using the radio signal generated from mobile phones and the information generated from the inertial sensor of the mobile phones.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.3
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• pp.39-52
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• 1999

In this paper we propose a new watermarking technique for copyright protection of images. The proposed technique is based on a spatial masking method with a spatial scale parameter. In general it becomes more robust against various attacks but with some degradations on the image quality as the amplitude of the watermark increases. On the other hand it becomes perceptually more invisible but more vulnerable to various attacks as the amplitude of the watermark decreases. Thus it is quite complex to decide the compromise between the robustness of watermark and its visibility. We note that watermarking using the spread spectrum is not robust enought. That is there may be some areas in the image that are tolerable to strong watermark signals. However large smooth areas may not be strong enough. Thus in order to enhance the invisibility of watermarked image for those areas the spatial masking characteristics of the HVS(Human Visual System) should be exploited. That is for texture regions the magnitude of the watermark can be large whereas for those smooth regions the magnitude of the watermark can be small. As a result the proposed watermarking algorithm is intend to satisfy both the robustness of watermark and the quality of the image. The experimental results show that the proposed algorithm is robust to image deformations(such as compression adding noise image scaling clipping and collusion attack).

• Analytical Science and Technology
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• v.7 no.2
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• pp.213-224
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• 1994

Several isotopomers of cyclooctanone were prepared by selective deuterium substitution. Intrinsic isotope effects on $^{13}C$ NMR chemical shifts of these isotopomers were investigated systematically at low temperature. These istope effects were discussed in relation to the preferred boat-chair conformation of cyclooctanone. Deuterium isotope effects on NMR chemical shifts have been known for a long time. Especially in a conformationally mobile molecule, isotope perturbation could affect NMR signals through a combination of isotope effects on equilibria and intrinsic effects. The distinction between intrinsic and nonintrinsic effects is quite difficult at ambient temperature due to involvement of both equilibrium and intrinsic isotope effects. However if equilibria between possible conformers of cyclooctanone are slowed down enough on the NMR time scale by lowering temperature, it should be possible to measure intrinsic isotope shifts from the separated signals at low temperature. $^{13}C$ NMR has been successfully utilized in the study on molecular conformation in solution when one deals with stable conformers or molecules were rapid interconversion occurs at ambient temperature. The study of dynamic processes in general requires analysis of spectra at several temperature. Anet et al. did $^1H$ NMR study of cyclooctanone at low temperature to freeze out a stable conformation, but were not able initially to deduce which conformation was stable because of the complexity of alkyl region in the $^1H$ NMR spectrum. They also reported the $^1H$ and $^{13}C$ NMR spectra of the $C_9-C_{16}$ cycloalkanones with changing temperature from $-80^{\circ}C$ to $-170^{\circ}C$, but they did not report a variable temperature $^{13}C$ NMR study of cyclooctanone. For the analysis of the intrinsic isotope effect with relation to cylooctanone conformation, $^{13}C$ NMR spectra are obtained in the present work at low temperatures (up to $-150^{\circ}C$) in order to find the chemical shifts at the temperature at which the dynamic process can be "frozen-out" on the NMR time scale and cyclooctanone can be observed as a stable conformation. Both the ring inversion and pseudorotational processes must be "frozen-out" in order to see separate resonances for all eight carbons in cyclooctanone. In contrast to $^1H$ spectra, slowing down just the ring inversion process has no apparent effects on the $^{13}C$ spectra because exchange of environments within the pairs of methylene carbons can still occur by the pseudorotational process. Several isotopomers of cyclooctanone were prepared by selective deuterium substitution (fig. 1) : complete deuterium labeling at C-2 and C-8 positions gave cyclooctanone-2, 2, 8, $8-D_4$ : complete labeling at C-2 and C-7 positions afforded the 2, 2, 7, $7-D_4$ isotopomer : di-deuteration at C-3 gave the 3, $3-D_2$ isotopomer : mono-deuteration provided cyclooctanone-2-D, 4-D and 5-D isotopomers : and partial deuteration on the C-2 and C-8 position, with a chiral and difunctional case catalyst, gave the trans-2, $8-D_2$ isotopomer. These isotopomer were investigated systematically in relation with cyclooctanone conformation and intrinsic isotope effects on $^{13}C$ NMR chemical shifts at low temperature. The determination of the intrinsic effects could help in the analysis of the more complex effects at higher temperature. For quantitative analysis of intrinsic isotope effects, the $^{13}C$ NMR spectrum has been obtained for a mixture of the labeled and unlabeled compounds because the signal separations are very small.