• 제목/요약/키워드: Root mean square value

검색결과 388건 처리시간 0.022초

7톤급 터보펌프 산화제펌프의 고주파 신호 분석 (High Frequency Signal Analysis of Oxidizer Pump for 7-tonf Turbopump)

  • 배준환;최창호;최종수
    • 한국추진공학회지
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    • 제24권6호
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    • pp.61-68
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    • 2020
  • 7톤급 터보펌프 실매질시험에서 계측된 고주파 신호인 가속도와 압력섭동에 대한 주파수 분석(waterfall, frequency spectrum), 실효값(RMS) 계산 등의 신호 처리를 통해 산화제펌프의 신뢰성을 평가하였다. 계측된 압력섭동 신호 분석을 통해 산화제펌프의 누설 유로에 위치한 산화제 후방 플로팅 링에 의한 강한 압력섭동이 발생하였고 이는 산화제펌프 입구 및 출구 압력과 가속도 신호에도 영향을 주는 것을 확인하였다. 터보펌프의 가속도 실효값 계산을 통해 정격 운용 조건에서의 터보펌프는 양호한 진동 성능을 보여주고 있으며 가속도 회전수 성분 중 축계에 영향을 주는 회전수 동기 주파수 성분이 강하게 나타나는 것을 확인하였다.

Uncertainty analysis of BRDF Modeling Using 6S Simulations and Monte-Carlo Method

  • Lee, Kyeong-Sang;Seo, Minji;Choi, Sungwon;Jin, Donghyun;Jung, Daeseong;Sim, Suyoung;Han, Kyung-Soo
    • 대한원격탐사학회지
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    • 제37권1호
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    • pp.161-167
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    • 2021
  • This paper presents the method to quantitatively evaluate the uncertainty of the semi-empirical Bidirectional Reflectance Distribution Function (BRDF) model for Himawari-8/AHI. The uncertainty of BRDF modeling was affected by various issues such as assumption of model and number of observations, thus, it is difficult that evaluating the performance of BRDF modeling using simple uncertainty equations. Therefore, in this paper, Monte-Carlo method, which is most dependable method to analyze dynamic complex systems through iterative simulation, was used. The 1,000 input datasets for analyzing the uncertainty of BRDF modeling were generated using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) Radiative Transfer Model (RTM) simulation with MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF product. Then, we randomly selected data according to the number of observations from 4 to 35 in the input dataset and performed BRDF modeling using them. Finally, the uncertainty was calculated by comparing reproduced surface reflectance through the BRDF model and simulated surface reflectance using 6S RTM and expressed as bias and root-mean-square-error (RMSE). The bias was negative for all observations and channels, but was very small within 0.01. RMSE showed a tendency to decrease as the number of observations increased, and showed a stable value within 0.05 in all channels. In addition, our results show that when the viewing zenith angle is 40° or more, the RMSE tends to increase slightly. This information can be utilized in the uncertainty analysis of subsequently retrieved geophysical variables.

Evaluating the Effects of Dose Rate on Dynamic Intensity-Modulated Radiation Therapy Quality Assurance

  • Kim, Kwon Hee;Back, Tae Seong;Chung, Eun Ji;Suh, Tae Suk;Sung, Wonmo
    • 한국의학물리학회지:의학물리
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    • 제32권4호
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    • pp.116-121
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    • 2021
  • Purpose: To investigate the effects of dose rate on intensity-modulated radiation therapy (IMRT) quality assurance (QA). Methods: We performed gamma tests using portal dose image prediction and log files of a multileaf collimator. Thirty treatment plans were randomly selected for the IMRT QA plan, and three verification plans for each treatment plan were generated with different dose rates (200, 400, and 600 monitor units [MU]/min). These verification plans were delivered to an electronic portal imager attached to a Varian medical linear accelerator, which recorded and compared with the planned dose. Root-mean-square (RMS) error values of the log files were also compared. Results: With an increase in dose rate, the 2%/2-mm gamma passing rate decreased from 90.9% to 85.5%, indicating that a higher dose rate was associated with lower radiation delivery accuracy. Accordingly, the average RMS error value increased from 0.0170 to 0.0381 cm as dose rate increased. In contrast, the radiation delivery time reduced from 3.83 to 1.49 minutes as the dose rate increased from 200 to 600 MU/min. Conclusions: Our results indicated that radiation delivery accuracy was lower at higher dose rates; however, the accuracy was still clinically acceptable at dose rates of up to 600 MU/min.

DNN을 활용한 부산지역 초미세먼지 예보방안 (A Study on the PM2.5 forcasting Method in Busan Using Deep Neural Network )

  • 도우곤;김동영;송희진;조갑제
    • 한국환경과학회지
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    • 제32권8호
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    • pp.595-611
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    • 2023
  • The purpose of this study is to improve the daily prediction results of PM2.5 from the air quality diagnosis and evaluation system operated by the Busan Institute of Health and Environment in real time. The air quality diagnosis and evaluation system is based on the photochemical numerical model, CMAQ (Community multiscale air quality modeling system), and includes a 3-day forecast at the end of the model's calculation. The photochemical numerical model basically has limitations because of the uncertainty of input data and simplification of physical and chemical processes. To overcome these limitations, this study applied DNN (Deep Neural Network), a deep learning technique, to the results of the numerical model. As a result of applying DNN, the r of the model was significantly improved. The r value for GFS (Global forecast system) and UM (Unified model) increased from 0.77 to 0.87 and 0.70 to 0.83, respectively. The RMSE (Root mean square error), which indicates the model's error rate, was also significantly improved (GFS: 5.01 to 6.52 ug/m3 , UM: 5.76 to 7.44 ug/m3 ). The prediction results for each concentration grade performed in the field also improved significantly (GFS: 74.4 to 80.1%, UM: 70.0 to 77.9%). In particular, it was confirmed that the improvement effect at the high concentration grade was excellent.

Research on data augmentation algorithm for time series based on deep learning

  • Shiyu Liu;Hongyan Qiao;Lianhong Yuan;Yuan Yuan;Jun Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권6호
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    • pp.1530-1544
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    • 2023
  • Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

Cinnamic acid derivatives as potential matrix metalloproteinase-9 inhibitors: molecular docking and dynamics simulations

  • Mohammad Hossein Malekipour;Farzaneh Shirani;Shadi Moradi;Amir Taherkhani
    • Genomics & Informatics
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    • 제21권1호
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    • pp.9.1-9.13
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    • 2023
  • Matrix metalloproteinase-9 (MMP-9) is a zinc and calcium-dependent proteolytic enzyme involved in extracellular matrix degradation. Overexpression of MMP-9 has been confirmed in several disorders, including cancers, Alzheimer's disease, autoimmune diseases, cardiovascular diseases, and dental caries. Therefore, MMP-9 inhibition is recommended as a therapeutic strategy for combating various diseases. Cinnamic acid derivatives have shown therapeutic effects in different cancers, Alzheimer's disease, cardiovascular diseases, and dental caries. A computational drug discovery approach was performed to evaluate the binding affinity of selected cinnamic acid derivatives to the MMP-9 active site. The stability of docked poses for top-ranked compounds was also examined. Twelve herbal cinnamic acid derivatives were tested for possible MMP-9 inhibition using the AutoDock 4.0 tool. The stability of the docked poses for the most potent MMP-9 inhibitors was assessed by molecular dynamics (MD) in 10 nanosecond simulations. Interactions between the best MMP-9 inhibitors in this study and residues incorporated in the MMP-9 active site were studied before and after MD simulations. Cynarin, chlorogenic acid, and rosmarinic acid revealed a considerable binding affinity to the MMP-9 catalytic domain (ΔGbinding < -10 kcal/ mol). The inhibition constant value for cynarin and chlorogenic acid were calculated at the picomolar scale and assigned as the most potent MMP-9 inhibitor from the cinnamic acid derivatives. The root-mean-square deviations for cynarin and chlorogenic acid were below 2 Å in the 10 ns simulation. Cynarin, chlorogenic acid, and rosmarinic acid might be considered drug candidates for MMP-9 inhibition.

e-Pharmacophore modeling and in silico study of CD147 receptor against SARS-CoV-2 drugs

  • Nisha Kumari Pandit;Simranjeet Singh Mann;Anee Mohanty;Sumer Singh Meena
    • Genomics & Informatics
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    • 제21권2호
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    • pp.17.1-17.12
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    • 2023
  • Coronavirus has left severe health impacts on the human population, globally. Still a significant number of cases are reported daily as no specific medications are available for its effective treatment. The presence of the CD147 receptor (human basigin) on the host cell facilitates the severe acute respiratory disease coronavirus 2 (SARS-CoV-2) infection. Therefore, the drugs that efficiently alter the formation of CD147 and spike protein complex could be the right drug candidate to inhibit the replication of SARS-CoV-2. Hence, an e-Pharmacophore model was developed based on the receptor-ligand cavity of CD147 protein which was further mapped against pre-existing drugs of coronavirus disease treatment. A total of seven drugs were found to be suited as pharmacophores out of 11 drugs screened which was further docked with CD147 protein using CDOCKER of Biovia discovery studio. The active site sphere of the prepared protein was 101.44, 87.84, and 97.17 along with the radius being 15.33 and the root-mean-square deviation value obtained was 0.73 Å. The protein minimization energy was calculated to be -30,328.81547 kcal/mol. The docking results showed ritonavir as the best fit as it demonstrated a higher CDOCKER energy (-57.30) with correspond to CDOCKER interaction energy (-53.38). However, authors further suggest in vitro studies to understand the potential activity of the ritonavir.

Chemical Vapor Deposition 공정으로 제작한 CuI p-type 박막 트랜지스터 (p-type CuI Thin-Film Transistors through Chemical Vapor Deposition Process)

  • 이승민;장성철;박지민;윤순길;김현석
    • 한국재료학회지
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    • 제33권11호
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    • pp.491-496
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    • 2023
  • As the demand for p-type semiconductors increases, much effort is being put into developing new p-type materials. This demand has led to the development of novel new p-type semiconductors that go beyond existing p-type semiconductors. Copper iodide (CuI) has recently received much attention due to its wide band gap, excellent optical and electrical properties, and low temperature synthesis. However, there are limits to its use as a semiconductor material for thin film transistor devices due to the uncontrolled generation of copper vacancies and excessive hole doping. In this work, p-type CuI semiconductors were fabricated using the chemical vapor deposition (CVD) process for thin-film transistor (TFT) applications. The vacuum process has advantages over conventional solution processes, including conformal coating, large area uniformity, easy thickness control and so on. CuI thin films were fabricated at various deposition temperatures from 150 to 250 ℃ The surface roughness root mean square (RMS) value, which is related to carrier transport, decreases with increasing deposition temperature. Hall effect measurements showed that all fabricated CuI films had p-type behavior and that the Hall mobility decreased with increasing deposition temperature. The CuI TFTs showed no clear on/off because of the high concentration of carriers. By adopting a Zn capping layer, carrier concentrations decreased, leading to clear on and off behavior. Finally, stability tests of the PBS and NBS showed a threshold voltage shift within ±1 V.

L-모멘트법에 의한 강우의 지역빈도분석 (Regional Frequency Analysis for Rainfall using L-Moment)

  • 고덕구;추태호;맹승진;찬다트리베디
    • 한국콘텐츠학회논문지
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    • 제8권3호
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    • pp.252-263
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    • 2008
  • 본 연구에서는 L-모멘트법에 의한 지역화 빈도분석에 따른 설계강우량 추정에 관한 연구를 수행하였다. 제주도와 울릉도의 강우관측소를 제외한 분석에 사용된 65개 강우관측소의 강우자료 수집과 선정된 강우관측지점의 강우자료의 지속시간, 즉 1, 3, 6, 12, 24, 36, 48 및 72시간 지속의 연최대치 계열을 구성하였다. 관측지점을 대상으로 Cluster분석을 실시한 결과 우리나라의 강우관측지점에 대한 합리적인 지역화로 5개의 지역으로 구분되었다. 지역화된 지역에 대한 지속기간별 극치강우자료의 적정분포모형 결정을 위한 6가지 분포모형의 적용하고 적용분포의 L-모멘트비를 산정하여 L-모멘트비도를 도시하고 K-S 검정에 의한 적정분포모형을 선정하였다. 선정된 적정분포는 GEV 분포이며 이 분포에 의해 강우관측치의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. Monte Carlo 기법에 의해 모의발생된 강우량의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. 실측치 및 모의발생치의 점빈도 및 지역빈도분석에 의한 설계강우량의 비교분석을 위해 상대제곱근오차와 상대편의오차에 의해 분석한 결과 점빈도 분석에 의한 설계강우량보다 지역빈도분석에 의한 설계강우량의 사용이 적정한 것으로 나타났다.

주파수 선택성 페이딩 환경하에서 $\frac{\pi}{4}$ shift QPSK 변조방식에 대한 다중파의 시간지역 검출법 제안 (A Multipath Delay Time Detection Method For $\frac{\pi}{4}$ Shift QPSK Modulation Under The Frequency Selective Fading Environment)

  • 조병진;김대영
    • 한국통신학회논문지
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    • 제16권10호
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    • pp.941-950
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    • 1991
  • 디지털 이동통신 전송로에 있어서 고속통신을 위한 시스템의 성능은 다중파 지연분산에 의해 크게 좌우된다. 본 논문에서는 최근 디지털 자동차 전화의 변복조방식으로 채택된 $\pi/4$ shift QPSK에 대해, 간이 다중파 지연시간 검출방법으로써 직교채널간섭량 (CCI)을 이용하는 방법을 제안하였다. $\pi/4$ shift QPSK신호는 원래 직교 채널에 정보를 갖고있기 때문에 BPSK변조방식처럼 Quadrature채널에서 간섭량을 얻기 위하여 주파수 체배기와 지연전파 방식을 제안하였다. 또한 다중파 전파환경하에서, 격렬하게 변하는 직교채널 간섭량으로 부터 정보를 얻는 방법으로서 절대치평균과 실효치 평균을 취하는 방법을 제안하였으며, 아울러 자연분산과 직교채널 간섭량과의 관계도 조사하였다. 이론적인 결과를 확인하기 위하여, 준정적인 2파 모델과 Rayleigh분포 2파모델하에서 computer simulation을 수행하였다. simulation결과 좋은 결과가 얻어졌으나. 본방식은 송신 대역제한에 어느정도 민감하다는 것이 밝혀졌다. 또한 H/W실현시 주요부분인 주파수 체배기에 대한 H/W구성 방안도 제안하였다.

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