• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.140-142
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• 2013

Cognitive radio (CR) has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing control is identified as one of the most crucial issues of cognitive radio networks. Out-of-band sensing to find an available channels to sense. Sensing is also required in case of spectrum hand-off. Sensing process needs to be done very fast in order to enhance the quality of service (QoS) of the CR nodes, and transmission not to be cut for longer time. During the sensing, the PU(primary user) detection probability condition should be satisfied. We adopt a channel prediction method to find target channels. Proposed prediction method combines chaotic global method and chaotic local method for channel idle probability prediction. Global method focus on channel history information length and order number of prediction model. Local method focus on local prediction trend. Through making simulation, Proposed method can find an available channel with very high probability, total sensing time is minimized, detection probability of PU's are satisfied.

• Journal of Life Science
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• v.23 no.9
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• pp.1170-1176
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• 2013

Essential oils have been used to treat psychophysiological disorders, but their effects on human electroencephalographic (EEG) activity have not been thoroughly investigated. We evaluated the effects of essential oil of Zizyphus jujuba seeds, a Korean folk medicine known as San-Jo-In, on human EEG activity. For this purpose, essential oil was extracted from San-Jo-In by the supercritical carbon dioxide extraction method. The effect of its inhalation on EEG activity was evaluated by measuring the EEG power spectrum (25 indices) in 20 healthy participants. The results of the EEG power spectrum indicated that the values of the theta wave decreased significantly (p<0.05) in the left (from 17.277 to $13.854{\mu}V$) and right parietal (from 15.324 to $13.020{\mu}V$) regions compared to the other regions. During the inhalation of San-Jo-In oil, the EEG spectrum values of fast alpha, relative gamma, and spectral edge frequency increased 50% compared to those before inhalation. The values of the fast alpha wave increased significantly (p<0.05) in the left prefrontal (from 0.063 to $0.085{\mu}V$), right prefrontal (from 0.064 to $0.085{\mu}V$), and left frontal (from 0.073 to $0.100{\mu}V$) regions following inhalation of the San-Jo-In essential oil. The changes in the EEG activities following inhalation of San-Jo-In suggest that the oil can improve psychological well-being by increasing attention and relaxation.

• Journal of Radiation Protection and Research
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• v.1 no.1
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• pp.1-9
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• 1976

A suggestion has been made for neutron dosimetric techniques using activation and threshold detectors in criticality accidents. Neutron dosimetrical parameters, namely, the fission spectrum-averaged cross-sections of some threshold reactions and fluence-to-dose conversion factors have been calculated by the use of an electronic computer. It appears that detectors having comparatively high threshold energy give more fine information on spectral deformation in criticality accidents, while detectors with low threshold energy are of usefulness for measuring fast neutron fluence regardless of fissioning types. Unexpectedly it is found that the fission spectrum-averaged cross sections of the $^{32}S(n,\;p)^{32}P$ reaction is not sensitive to analytical forms of fission neutron spectrum: the modified Cran-berg and Maxwellian forms. In addition, the fluence-to-dose conversion factors seem to be insensitive to both spectral functions and fissioning types.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.1-8
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• 2016

As demand for paper cups markedly increases, this has brought about a requirement to develop fast paper cup forming machines. However, the fast manufacturing speed of these machines causes faults to occur more frequently in the final product. To reduce the possibility of producing faulty products, it is necessary to develop technologies to monitor the manufacturing process and diagnose the machine status. In this research, we selected the main driving axis of the forming machine for fault diagnosis. We searched the states of rotational elements related to the driving axis and suggested a fault diagnostic system based on spectrum analysis consisting of a real-time data acquisition device, accelerometers, and a diagnosis algorithm. To evaluate the developed fault diagnostic system, we performed experiments using a test station which resembles the actual paper cup forming machine. As a result, we were able to confirm that the proposed system was sufficiently feasible to diagnose any abnormalities in the operation of the paper cup forming machine.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.1
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• pp.15-23
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• 2003

This paper proposes a fast direction of arrival (DOA) estimation algorithm that can rapidly estimate incidence angles of incoming signals using a pseudo covariance matrix. The conventional subspace DOA estimation methods such as MUSIC (multiple signal classification) algorithms need many sample signals to acquire covariance matrix of input signals. Thus, it is difficult to estimate the DOAs of signals because they cannot perform DOA estimation during receiving sample signals. Also if the D0As of signals are changing rapidly, conventional algorithms cannot estimate incidence angles of signals exactly. The proposed algorithm obtains bearing response and directional spectrum after acquiring pseudo covariance matrix of each snapshot. The incidence angles can be exactly estimated by using the bearing response and directional spectrum. The proposed DOA estimation algorithm uses only concurrent snapshot so as to obtain covariance matrix. Compared to conventional DOA estimation methods. The proposed algorithm has an advantage that can estimate DOA of signal rapidly.

• Analytical Science and Technology
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• v.35 no.2
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• pp.69-81
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• 2022

The method of measuring and classifying the energy category of neutrons directly using raw data acquired through a CZT detector is not satisfactory, in terms of accuracy and efficiency, because of its poor energy resolution and low measurement efficiency. Moreover, this method of measuring and analyzing the characteristics of low-energy or low-activity gamma-ray sources might be not accurate and efficient in the case of neutrons because of various factors, such as the noise of the CZT detector itself and the influence of environmental radiation. We have therefore developed an efficient method of analyzing radiation characteristics using a neutron and gamma-ray analysis algorithm for the rapid and clear identification of the type, energy, and radioactivity of gamma-ray sources as well as the detection and classification of the energy category (fast or thermal neutrons) of neutron sources, employing raw data acquired through a CZT detector. The neutron analysis algorithm is based on the fact that in the energy-spectrum channel of 558.6 keV emitted in the nuclear reaction ¹¹³Cd + ¹n → ¹¹⁴Cd + in the CZT detector, there is a notable difference in detection information between a CZT detector without a PE modulator and a CZT detector with a PE modulator, but there is no significant difference between the two detectors in other energy-spectrum channels. In addition, the gamma-ray analysis algorithm uses the difference in the detection information of the CZT detector between the unique characteristic energy-spectrum channel of a gamma-ray source and other channels. This efficient method of analyzing radiation characteristics is expected to be useful for the rapid radiation detection and accurate information collection on radiation sources, which are required to minimize radiation damage and manage accidents in national disaster situations, such as large-scale radioactivity leak accidents at nuclear power plants or nuclear material handling facilities.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2452-2459
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• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1175-1182
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• 2021

The receiver of each radio telescope of KVN, has a sampler that converts astronomical radio signal to digital data. The ability of this sampler (the bandwidth, sampling frequency, and sampling bits) is improved by sqrt(n), if the bandwidth is increased by n times, and the number of observable objects increases exponentially in the case of continum spectrum radio sources. As the bandwidth increases, there are the more spectrum lines that can be simultaneously monitored in the radio source. This will greatly expand the research area in astronomical radio observation. For this reason, we are trying to independently develop the technology of the fast digital sampler. Therefore, based on the research experience and technology accumulated so far, An ability of sampling up to 3.5 GHz, that can vary the sampling frequency and can observe in a wider band, was designed and made for proto-type. In this study, we introduce the development details and test results for new sampling system.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.512-522
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• 2014

This paper proposes fast millimeter-wave (mm-wave) beam training protocols with receive beamforming. Both IEEE standards and the academic literature have generally considered beam training protocols involving exhaustive search over all possible beam directions for both the beamforming initiator and responder. However, this operation requires a long time (and thus overhead) when the beamwidth is quite narrow such as for mm-wave beams ($1^{\circ}$ in the worst case). To alleviate this problem, we propose two types of adaptive beam training protocols for fixed and adaptive modulation, respectively, which take into account the unique propagation characteristics of millimeter waves. For fixed modulation, the proposed protocol allows for interactive beam training, stopping the search when a local maximum of the power angular spectrum is found that is sufficient to support the chosen modulation/coding scheme. We furthermore suggest approaches to prioritize certain directions determined from the propagation geometry, long-term statistics, etc. For adaptive modulation, the proposed protocol uses iterative multi-level beam training concepts for fast link configuration that provide an exhaustive search with significantly lower complexity. Our simulation results verify that the proposed protocol performs better than traditional exhaustive search in terms of the link configuration speed for mobile wireless service applications.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.1100-1108
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• 2017

A thermal-hydraulic system code is an essential tool for the design and safety analysis of a nuclear power plant, and its accuracy quantification is very important for the code assessment and applications. The fast Fourier transform-based method (FFTBM) by signal mirroring (FFTBM-SM) has been used to quantify the accuracy of a system code by using a comparison of the experimental data and the calculated results. The method is an improved version of the FFTBM, and it is known that the FFTBM-SM judges the code accuracy in a more consistent and unbiased way. However, in some applications, unrealistic results have been obtained. In this study, it was found that accuracy quantification by FFTBM-SM is dependent on the frequency spectrum of the fast Fourier transform of experimental and error signals. The primary objective of this study is to reduce the frequency dependency of FFTBM-SM evaluation. For this, it was proposed to reduce the cut off frequency, which was introduced to cut off spurious contributions, in FFTBM-SM. A method to determine an appropriate cut off frequency was also proposed. The FFTBM-SM with the modified cut off frequency showed a significant improvement of the accuracy quantification.