• Title/Summary/Keyword: 신호대 잡음 비

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Dynamic Channel Management Scheme for Device-to-device Communication in Next Generation Downlink Cellular Networks (차세대 하향링크 셀룰러 네트워크에서 단말 간 직접 통신을 위한 유동적 채널관리 방법)

  • Se-Jin Kim
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.1-7
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    • 2023
  • Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

Trace-based Interpolation Using Machine Learning for Irregularly Missing Seismic Data (불규칙한 빠짐을 포함한 탄성파 탐사 자료의 머신러닝을 이용한 트레이스 기반 내삽)

  • Zeu Yeeh;Jiho Park;Soon Jee Seol;Daeung Yoon;Joongmoo Byun
    • Geophysics and Geophysical Exploration
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    • v.26 no.2
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    • pp.62-76
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    • 2023
  • Recently, machine learning (ML) techniques have been actively applied for seismic trace interpolation. However, because most research is based on training-inference strategies that treat missing trace gather data as a 2D image with a blank area, a sufficient number of fully sampled data are required for training. This study proposes trace interpolation using ML, which uses only irregularly sampled field data, both in training and inference, by modifying the training-inference strategies of trace-based interpolation techniques. In this study, we describe a method for constructing networks that vary depending on the maximum number of consecutive gaps in seismic field data and the training method. To verify the applicability of the proposed method to field data, we applied our method to time-migrated seismic data acquired from the Vincent oilfield in the Exmouth Sub-basin area of Western Australia and compared the results with those of the conventional trace interpolation method. Both methods showed high interpolation performance, as confirmed by quantitative indicators, and the interpolation performance was uniformly good at all frequencies.

Machine Learning-based Phase Picking Algorithm of P and S Waves for Distributed Acoustic Sensing Data (분포형 광섬유 센서 자료 적용을 위한 기계학습 기반 P, S파 위상 발췌 알고리즘 개발)

  • Yonggyu, Choi;Youngseok, Song;Soon Jee, Seol;Joongmoo, Byun
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.177-188
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    • 2022
  • Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO2 storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

A study on DEMONgram frequency line extraction method using deep learning (딥러닝을 이용한 DEMON 그램 주파수선 추출 기법 연구)

  • Wonsik Shin;Hyuckjong Kwon;Hoseok Sul;Won Shin;Hyunsuk Ko;Taek-Lyul Song;Da-Sol Kim;Kang-Hoon Choi;Jee Woong Choi
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.1
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    • pp.78-88
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    • 2024
  • Ship-radiated noise received by passive sonar that can measure underwater noise can be identified and classified ship using Detection of Envelope Modulation on Noise (DEMON) analysis. However, in a low Signal-to-Noise Ratio (SNR) environment, it is difficult to analyze and identify the target frequency line containing ship information in the DEMONgram. In this paper, we conducted a study to extract target frequency lines using semantic segmentation among deep learning techniques for more accurate target identification in a low SNR environment. The semantic segmentation models U-Net, UNet++, and DeepLabv3+ were trained and evaluated using simulated DEMONgram data generated by changing SNR and fundamental frequency, and the DEMONgram prediction performance of DeepShip, a dataset of ship-radiated noise recordings on the strait of Georgia in Canada, was compared using the trained models. As a result of evaluating the trained model with the simulated DEMONgram, it was confirmed that U-Net had the highest performance and that it was possible to extract the target frequency line of the DEMONgram made by DeepShip to some extent.

Study on the Various Size Dependence of Ionization Chamber in IMRT Measurement to Improve Dose-accuracy (세기조절 방사선치료(IMRT)의 환자 정도관리에서 다양한 이온전리함 볼륨이 정확도에 미치는 영향)

  • Kim, Sun-Young;Lee, Doo-Hyun;Cho, Jung-Keun;Jung, Do-Hyeung;Kim, Ho-Sick;Choi, Gye-Sook
    • The Journal of Korean Society for Radiation Therapy
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    • v.18 no.1
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    • pp.1-5
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    • 2006
  • Purpose: IMRT quality assurance(Q.A) is consist of the absolute dosimetry using ionization chamber and relative dosimetry using the film. We have in general used 0.015 cc ionization chamber, because small size and measure the point dose. But this ionization chamber is too small to give an accurate measurement value. In this study, we have examined the degree of calculated to measured dose difference in intensity modulated radiotherapy(IMRT) based on the observed/expected ratio using various kinds of ion chambers, which were used for absolute dosimetry. Materials and Methods: we peformed the 6 cases of IMRT sliding-window method for head and neck cases. Radiation was delivered by using a Clinac 21EX unit(Varian, USA) generating a 6 MV x-ray beam, which is equipped with an integrated multileaf collimator. The dose rate for IMRT treatment is set to 300 MU/min. The ion chamber was located 5cm below the surface of phantom giving 100cm as a source-axis distance(SAD). The various types of ion chambers were used including 0.015cc(pin point type 31014, PTW. Germany), 0.125 cc(micro type 31002, PTW, Germany) and 0.6 cc(famer type 30002, PTW, Germany). The measurement point was carefully chosen to be located at low-gradient area. Results: The experimental results show that the average differences between plan value and measured value are ${\pm}0.91%$ for 0.015 cc pin point chamber, ${\pm}0.52%$ for 0.125 cc micro type chamber and ${\pm}0.76%$ for farmer type 0.6cc chamber. The 0.125 cc micro type chamber is appropriate size for dose measure in IMRT. Conclusion: IMRT Q.A is the important procedure. Based on the various types of ion chamber measurements, we have demonstrated that the dose discrepancy between calculated dose distribution and measured dose distribution for IMRT plans is dependent on the size of ion chambers. The reason is small size ionization chamber have the high signal-to-noise ratio and big size ionization chamber is not located accurate measurement point. Therefore our results suggest the 0.125 cc farmer type chamber is appropriate size for dose measure in IMRT.

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Evaluation of Reasonable $^{18}F$-FDG Injected Dose for Maintaining the Image Quality in 3D WB PET/CT (PET/CT 검사에서 영상의 질을 유지하기 위한 적정한 $^{18}F$-FDG 투여량의 평가)

  • Moon, A-Reum;Lee, Hyuk;Kwak, In-Suk;Choi, Sung-Wook;Suk, Jae-Dong
    • The Korean Journal of Nuclear Medicine Technology
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    • v.15 no.2
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    • pp.36-40
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    • 2011
  • Purpose: $^{18}F$-FDG injected dose to the patient is quite different between the recommended dose from manufacturer and the actual dose applied to each of hospitals. injection of inappropriate $^{18}F$-FDG dose may not only increase the exposed dose to patients but also reduce the image quality. we thus evaluated the proper $^{18}F$-FDG injected dose to decrease the exposed dose to patients considering the image quality. Materials And Methods: NEMA Nu2-1994 phantom was filled with $^{18}F$-FDG increasing hot cylinder radioactivity concentration to 1, 3, 5, 7, 9 MBq/kg based on the ratio of 4:1 between the hot cylinder and background activity. after completing the transmission scan using ct, emission scan was acquired in 3D mode for 2 minutes 30 seconds/bed. ROI was set up on hot cylinder and background radioactivity region. after measuring $SUV_{max}$ those regions, then analyzed SNR at the points. clinical experiment has been conducted the object of patients who have came to smc from november 2009 to august 2010, 97 patients without having a hepatic lesions were selected. ROI was set up in the liver and thigh area. after measuring $SUV_{max}$, the image quality was compared following the injected dose. Results: in phantom study, as the injected radioactivity concentration per unit mass was 1, 3, 5, 7, 9 MBq/kg, $SUV_{max}$ was 23.1, 24.1, 24.3, 22.8, 23.6 and SNR was shown 0.48, 0.54, 0.56, 0.55, 0.55. according to increment of the injected dose, $SUV_{max}$ and SNR was increased under 5 MBq/kg but they were decreased over 7 MBq/kg. in case of clinical experiment, as increased the injected radioactivity concentration per unit mass was 4.72, 5.34, 6.16, 7.41, 8.68 MBq/kg, $SUV_{max}$ was 2.68, 2.67, 2.26, 1.88, 1.95 and SNR was shown 0.52, 0.53, 0.46, 0.46, 0.44. if the injected dose exceeds 5 MBq/kg, showed a decrease pattern as phantom study. Conclusion: increasing $^{18}F$-FDG injected dose considered patient's body weight improve image quality within a certain range. if it exceeds the range, it can be reduced image quality due to random and scatter coincidences. this study indicates that the optimal injected dose was 5 MBq/kg per unit mass the injected radioactivity concentration in 3d wb pet/ct.

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The Usefulness of Q.Clear Technique in PET / CT (PET/CT 검사에서 Q.Clear 기법의 유용성에 대한 고찰)

  • Choi, Yong Hoon;Kim, Jung Yul;Choi, Young Sook;Lim, Han Sang;Kim, Jae Sam
    • The Korean Journal of Nuclear Medicine Technology
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    • v.21 no.2
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    • pp.31-36
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    • 2017
  • Purpose Recently, the performance of PET/CT scanner has been improved and various techniques have been developed to increase the image quality such as Sensitivity and Resolution. The purpose of this study is to evaluate the usefulness of Q.Clear (a fully convergent iterative reconstruction) technique of GE Discovery IQ equipment to enhance the image quality. Materials and Methods All scans were acquired by Discovery IQ (GE Healthcare, MI, USA). In NEMA IEC Body Phantom test, Background to Hot-sphere (10 mm, 13 mm, 17 mm, 22 mm) ratio was 1:4 and scan time was 3 minutes. The images were reconstructed by VPHDs (VUE Point High-Definition + SharpIR) and Q.Clear to evaluate each Contrast. We injected 18F-FDG 187 M㏃ to PET/SPECT Performance Phantom. And then it was scanned for 4 minutes to evaluate Resolution and Uniformity. T-test statistical analysis was performed on SUVmax of small lesions less than 2 cm in 100 clinical patients regardless of disease type. Results In the NEMA IEC Body Phantom, the Contrast was $63.6{\pm}5.7%$ (VPHDs) and $75{\pm}4.8%$ (Q.Clear). In the PET/SPECT Performance Phantom, the Resolution was 9.2 mm (VPHDs) and 7.3 mm (Q.Clear). Uniformity of Q.Clear was 10.8% better than VPHDs. T-test statistic of the clinical patients showed a significant difference of p value of 0.021. Conclusion Both the phantom test and the clinical results showed that the quality of the image was improved in Q.Clear was applied. The SUVmax was highly measured in Q.Clear and the lesions were clearly distinguished visually. Therefore Q.Clear can be useful in various aspects such as dose-reduction, patients evaluation and image analysis.

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The Study of Affecting Image Quality according to forward Scattering Dose used Additional Filter in Diagnostic Imaging System (부가필터 사용 시 전방 산란선량에 따른 화질 영향에 대한 연구)

  • Choi, Il-Hong;Kim, Kyo-Tae;Heo, Ye-Ji;Park, Hyong-Hu;Kang, Sang-Sik;Noh, Si-Cheol;Park, Ji-Koon
    • Journal of the Korean Society of Radiology
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    • v.10 no.8
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    • pp.597-602
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    • 2016
  • Recent clinical field utilizes the aluminium filter in order to reduce the low-energy photons. However, the usage of the filter can cause adverse effect on the image quality because of the scattered dose that is generated by X-ray hardening phenomenon. Further, usage of filter with improper thickness can be a reason of dose creep phenomenon where unnecessary exposure is generated towards the patient. In this study, the author evaluated the RMS and the RSD analysis in order to have a quantitative evaluation for the effect of forward scattering dose by the filter on the image. as a result of the study, the FSR and the RSD was increased together with the increasing of thickness of the filter. In this study the RSD means the standard deviation of the mean value is relatively size. It can be understood that the signal-to-noise ratio decreases when the average value is taken as a signal and the standard deviation is judged as a noise. The signal-to-noise ratio can understanding as index of resolution at image. Based on these findings, it was quantitatively verified that there is a correlation of the image quality with the FSR by using an additional filter. The results, a 2.5 mmAl which is as recommended by NCRP in the tube voltage of 70 kVp or more showed the 14.6% on the RSD when the filter was not in used. these results are considered able to be utilized as basic data for the study about the filter to improve the quality of the image.

Impact of Deep-Learning Based Reconstruction on Single-Breath-Hold, Single-Shot Fast Spin-Echo in MR Enterography for Crohn's Disease (크론병에서 자기공명영상 장운동기록의 단일호흡 단발 고속 스핀 에코기법: 딥러닝 기반 재구성의 영향)

  • Eun Joo Park;Yedaun Lee;Joonsung Lee
    • Journal of the Korean Society of Radiology
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    • v.84 no.6
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    • pp.1309-1323
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    • 2023
  • Purpose To assess the quality of four images obtained using single-breath-hold (SBH), single-shot fast spin-echo (SSFSE) and multiple-breath-hold (MBH) SSFSE with and without deep-learning based reconstruction (DLR) in patients with Crohn's disease. Materials and Methods This study included 61 patients who underwent MR enterography (MRE) for Crohn's disease. The following images were compared: SBH-SSFSE with (SBH-DLR) and without (SBH-conventional reconstruction [CR]) DLR and MBH-SSFSE with (MBH-DLR) and without (MBH-CR) DLR. Two radiologists independently reviewed the overall image quality, artifacts, sharpness, and motion-related signal loss using a 5-point scale. Three inflammatory parameters were evaluated in the ileum, the terminal ileum, and the colon. Moreover, the presence of a spatial misalignment was evaluated. Signal-to-noise ratio (SNR) was calculated at two locations for each sequence. Results DLR significantly improved the image quality, artifacts, and sharpness of the SBH images. No significant differences in scores between MBH-CR and SBH-DLR were detected. SBH-DLR had the highest SNR (p < 0.001). The inter-reader agreement for inflammatory parameters was good to excellent (κ = 0.76-0.95) and the inter-sequence agreement was nearly perfect (κ = 0.92-0.94). Misalignment artifacts were observed more frequently in the MBH images than in the SBH images (p < 0.001). Conclusion SBH-DLR demonstrated equivalent quality and performance compared to MBH-CR. Furthermore, it can be acquired in less than half the time, without multiple BHs and reduce slice misalignments.

Image Quality Evaluation of CsI:Tl and Gd2O2S Detectors in the Indirect-Conversion DR System (간접변환방식 DR장비에서 CsI:Tl과 Gd2O2S의 검출기 화질 평가)

  • Kong, Changgi;Choi, Namgil;Jung, Myoyoung;Song, Jongnam;Kim, Wook;Han, Jaebok
    • Journal of the Korean Society of Radiology
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    • v.11 no.1
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    • pp.27-35
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    • 2017
  • The purpose of this study was to investigate the features of CsI:Tl and $Gd_2O_2S$ detectors with an indirect conversion method using phantom in the DR (digital radiography) system by obtaining images of thick chest phantom, medium thickness thigh phantom, and thin hand phantom and by analyzing the SNR and CNR. As a result of measuring the SNR and CNR according to the thickness change of the subject, the SNR and CNR were higher in CsI:Tl detector than in $Gd_2O_2S$ detector when the medium thickness thigh phantom and thin hand phantom were scanned. However, when the thick chest phantom was used, for the SNR at 80~125 kVp and the CNR at 80~110 kVp in the $Gd_2O_2S$ detector, the values were higher than those of CsI:Tl detector. The SNR and CNR both increased as the tube voltage increased. The SNR and CNR of CsI:Tl detector in the medium thickness thigh phantom increased at 40~50 kVp and decreased as the tube voltage increased. The SNR and CNR of $Gd_2O_2S$ detector increased at 40~60 kVp and decreased as the tube voltage increased. The SNR and CNR of CsI:Tl detctor in the thin hand phantom decreased at the low tube voltage and increased as the tube voltage increased, but they decreased again at 100~110 kVp, while the SNR and CNR of $Gd_2O_2S$ detector were found to decrease as the tube voltage increased. The MTF of CsI:Tl detector was 6.02~90.90% higher than that of $Gd_2O_2S$ detector at 0.5~3 lp/mm. The DQE of CsI:Tl detector was 66.67~233.33% higher than that of $Gd_2O_2S$ detector. In conclusion, although the values of CsI:Tl detector were higher than those of $Gd_2O_2S$ detector in the comparison of MTF and DQE, the cheaper $Gd_2O_2S$ detector had higher SNR and CNR than the expensive CsI:Tl detector at a certain tube voltage range in the thick check phantom. At chest X-ray, if the $Gd_2O_2S$ detector is used rather than the CsI:Tl detector, chest images with excellent quality can be obtained, which will be useful for examination. Moreover, price/performance should be considered when determining the detector type from the viewpoint of the user.