• The Journal of the Acoustical Society of Korea
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• v.30 no.7
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• pp.396-401
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• 2011

In this paper, we propose a novel voice activity detection (VAD) algorithm to effectively distinguish speech from nonspeech in various noisy environments. The presented VAD utilizes the power spectral deviation (PSD) based on Teager energy (TE) instead of the conventional PSD scheme to improve the performance of decision for speech segments. In addition, the speech absence probability (SAP) is derived in each frequency subband to modify the PSD for further VAD. Performances of the proposed VAD algorithm are evaluated by objective test under various environments and better results compared with the conventional methods are obtained.

• Journal of the Korean Vacuum Society
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• v.10 no.1
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• pp.67-71
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• 2001

Optical investigation on Zn-doped InGaN grown by MOCVD was performed by using the photoluminescence. Two different spectra related to Zn-acceptor-like centers occurred at room temperature, with broad emissions peaking at 2.81, and 2.60 eV, Specially, emissions interacted with phonon were observed at 2.81 eV where phonon energy was 92.5 meV From temperature dependent blue-band emissions of InGaN, we observe that the intensity in high energy region was quickly decreased more than that in low energy region with increased temperature, and the peak position at 2.81 eV was blue shift of about 18 meV, The blue-band emmissions would be originated from the transition related to the localized Zn complex centers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1105-1116
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• 2008

Cognitive radio is one of the most effective techniques to improve the spectrum utilization efficiency. To implement the cognitive radio, spectrum sensing is considered as the key functionality because only counting on it, can the secondary users identify the spectrum holes and utilize them efficiently without causing interference to primary users. Generally, there are several spectrum sensing methods; the most common and simplest method is energy detection. However, the conventional energy detection has some disadvantages, which are caused by noise, especially, uncertain noise power leads to degradation of energy detector. In this paper, to solve this problem, we proposed sliding window-based energy detection method which can devide the frequency band of primary signal and noise using sliding window to estimate the power of primary user without the noise effect and achieve the better performance. It can calculate the energy of primary user only and can detect the primary signal. The simulation result shows that our proposed method outperforms conventional one.

• Journal of KIISE
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• v.43 no.12
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• pp.1412-1419
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• 2016

In cognitive radio sensor networks (CRSNs), secondary users (SUs) can occupy licensed bands opportunistically without causing interferences to primary users (PUs). SUs perform spectrum sensing to detect the presence of PUs. Sensing time is a critical parameter for spectrum sensing that can yield a tradeoff between sensing performance and secondary throughput. In this study, we investigate new approaches for spectrum sensing by exploring the tradeoff from a) spectrum sensing for PU detection (SSPD) and b) spectrum sensing for secondary throughput (SSST). In the proposed scheme, the first sensing result of the current frame determines the dynamic performance of the second spectrum sensing. Energy constraint in CRSNs leads to maximized network energy efficiency via optimization of sensing time. Simulation results show that the proposed scheme of SSPD and SSST improves network performance in terms of energy efficiency and secondary throughput, respectively.

• Journal of Radiation Protection and Research
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• v.34 no.4
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• pp.170-175
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• 2009

For the emergency radiation monitoring using gamma spectrometry, we should sufficiently survey the background spectra as environmental samples with systematic nuclide identification method. In this study, we obtained the gamma ray energy spectrum using a HPGe gamma spectrometry system from an air sample. And we identified nuclide of the gamma ray energy peaks in the spectrum using two methods -1) Half life calculation and 2) survey for cascade coincidence summing peaks using nuclear data. As the results, we produced the nuclide identification results for the air sample.

• Journal of Radiation Protection and Research
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• v.22 no.2
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• pp.127-133
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• 1997

In this study an EGS4 simulation code was used to calculate real energy spectrum from measured ${\gamma}$-ray energy spectrum obtained using 2-dimensional radiation monitoring system. As a result, the $39{\times}39$ response matrix was calculated the energy range of 0.1 to 2 MeV which energy interval of 50 keV The real energy spectrum for Co-60 radioisotope was calculated using inverse of response matrix. It was confirmed that the calculated response matrix was useful to the analysis of the measured energy spectrum for the radiation monitoring system.

• Nuclear Engineering and Technology
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• v.15 no.4
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• pp.280-285
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• 1983

Effects of fission neutron spectra in the reactor calculations have been analysed through applications of several cases of spectra in the criticality calculations of fast critical assemblies. They were the application of Maxwellian or Watt-Cranberg type formulae, of region dependent spectrum, of composition dependent spectrum, of fission transfer matrix, and the effects due to the selection of nuclear temperature in Maxwellian formula.

• Journal of radiological science and technology
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• v.38 no.3
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• pp.187-197
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• 2015

This study analysed the effectiveness of aluminium(Al) filter in the added compound filtration for the removal of characteristic radiation by energy spectrum and image evaluation. 0.1, 0.2, 0.3 mm copper with and without 1 mm Al were evaluated. The energy spectrum was measured using the GATE and evaluated separately by each energy. Image quality was evaluated by PSNR, MAE, MSE, CNR, SNR and qualitative analysis was performed by seven items for resolution and contrast from chest x-ray criteria of National Cancer Screening and Cardiovascular evaluation table. In the analysis of the quality of the energy per photon spectrum with the exception of a low energy region, without Al were superior in all area. PSNR MAE, MSE, CNR, SNR and qualitative analysis were the same or slightly better. PSNR was over 30 dB and all significant and the p>0.05 in the T-test of qualitative analysis. The energy spectrum and image quality have little difference between before and after use of Al filter. Therefore, it is effective to use the Al filter for the radiation dose management with the compensation capability of DR system.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.289-295
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• 2018

Most diagnostic devices in the medical field use X-ray sources, which emit energy spectra. In radiological diagnosis, the quantitative and qualitative analyses of X-rays are essential for maintaining the image quality and minimizing the radiation dose to patients. This work aims to obtain the X-ray energy spectra used in diagnostic imaging by Monte Carlo simulation. Various X-ray spectra are simulated using a Monte Carlo simulation tool. These spectra are then compared to the reference data obtained with a tungsten anode spectral model using the interpolating polynomial (TASMIP) code. The X-ray tube voltages used are 50, 60, 80, 100, and 110 kV, respectively. CdTe and a-Se detector are used as the detectors for obtaining the X-ray spectra. Simulation results demonstrate that the various X-ray spectra are well matched with the reference data. Based on the simulation results, an appropriate X-ray spectrum, in accordance with the tube voltage, can be selected when generating an image for diagnostic imaging. The dose to be delivered to the patient can be predicted prior to examination in the diagnostic field.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.1-6
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• 2012

In the paper, an information divergence called Kullback-Leiber divergence, which measures the average of the logarithmic difference between two probability density functions, is utilized to derive a novel method for spectrum sensing in cognitive radio systems. In the proposed sensing method, we test whether the observed samples are drawn from the noise distribution by using Kullback-Leiber divergence. It is shown by numerical results that under the same conditions, the proposed Kullback-Leiber divergence-based spectrum sensing always outperforms the energy detection based spectrum sensing significantly, especially in low SNR regime and in fading circumstance.