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THE OBSERVATION OF ENHANCED RAMAN SCATTERING OF GASEOUS MOLECULES BY Hg MICRODROPLETS
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作者 Fa Ping ZHONG Han Xi YANG Zhong SHI Chuan Sin CHA (Dept.of Chemistry,Wuhan Univ.)Zhi Shan Xu Nian XIAO Rong Sen SHEN (Analytical Center,Wuhan Univ.) 《Chinese Chemical Letters》 SCIE CAS CSCD 1991年第7期549-550,共2页
ABSTRACT The Raman intensitics of gas molecules were found to be enormously enhanced in the presence of Hg-microdroplets.The enhancement factor for the molecules studied was found to be over 20.
关键词 HG the observation OF ENHANCED RAMAN SCATTERING OF GASEOUS MOLECULES BY Hg MICRODROPLETS SERS
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Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data 被引量:2
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作者 伍雪冬 王耀南 +1 位作者 刘维亭 朱志宇 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第6期546-551,共6页
On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random in... On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering (EKF) and the unscented Kalman filtering (UKF), which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network (RBFNN) prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent. 展开更多
关键词 prediction of time series with missing data random interruption failures in the observation neural network approximation
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Sparsity-based efficient simulation of cluster targets electromagnetic scattering
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作者 TIAN Yuguang LIU Yixin +3 位作者 CHEN Xuan CHEN Penghui WANG Jun CHEN Junwen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第2期299-306,共8页
An efficient and real-time simulation method is proposed for the dynamic electromagnetic characteristics of cluster targets to meet the requirements of engineering practical applications.First,the coordinate transform... An efficient and real-time simulation method is proposed for the dynamic electromagnetic characteristics of cluster targets to meet the requirements of engineering practical applications.First,the coordinate transformation method is used to establish a geometric model of the observation scene,which is described by the azimuth angles and elevation angles of the radar in the target reference frame and the attitude angles of the target in the radar reference frame.Then,an approach for dynamic electromagnetic scattering simulation is proposed.Finally,a fast-computing method based on sparsity in the time domain,space domain,and frequency domain is proposed.The method analyzes the sparsity-based dynamic scattering characteristic of the typical cluster targets.The error between the sparsity-based method and the benchmark is small,proving the effectiveness of the proposed method. 展开更多
关键词 geometric model of the observation scene dynamic electromagnetic scattering simulation sparsity-based method
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Energy modeling and data structure framework for Sustainable Human-Building Ecosystems (SHBE)- a review 被引量:1
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作者 Suraj TALELE Caleb TRAYLOR +16 位作者 Laura ARPAN Cali CURLEY Chien-Fei CHEN Julia DAY Richard FEIOCK Mirsad HADZIKADIC William J. TOLONE Stan INGMAN Dale YEATTS Omer T. KARAGUZEL Khee Poh LAM Carol MENASSA Svetlana PEVNITSKAYA Thomas SPIEGELHALTER Wei YAN Yimin ZHU Yong X. TAO 《Frontiers in Energy》 SCIE CSCD 2018年第2期314-332,共19页
This paper contributes an inclusive review of scientific studies in the field of sustainable human building ecosystems (SHBEs). Reducing energy consumption by making buildings more energy efficient has been touted a... This paper contributes an inclusive review of scientific studies in the field of sustainable human building ecosystems (SHBEs). Reducing energy consumption by making buildings more energy efficient has been touted as an easily attainable approach to promoting carbon-neutral energy societies. Yet, despite significant progress in research and technology development, for new buildings, as energy codes are getting more stringent, more and more technologies, e.g., LED lighting, VRF systems, smart plugs, occupancy-based controls, are used. Nevertheless, the adoption of energy efficient measures in buildings is still limited in the larger context of the developing countries and middle income/low-income population. The objective of Sustainable Human Building Ecosystem Research Coordination Network (SHBE-RCN) is to expand synergistic investigative podium in order to subdue barriers in engineering, architectural design, social and economic perspectives that hinder wider application, adoption and subsequent performance of sustainable building solutions by recognizing the essential role of human behaviors within building-scale ecosystems. Expected long-term outcomes of SHBE-RCN are collaborative ideas for transformative technologies, designs and methods of adoption for future design, construction and operation of sustainable buildings. 展开更多
关键词 SUSTAINABILITY building energy modeling(BEM) occupant behaviors (OB) sustainable ecosystems System for the observation of Populous Heterogeneous Information (SOPHI)
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