The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation...The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.展开更多
AIM: To evaluate the sources of variation influencing the microvascularization parameters measured by dynamic contrast-enhanced ultrasonography (DCE-US). METHODS: Firstly, we evaluated, in vitro , the impact of the ma...AIM: To evaluate the sources of variation influencing the microvascularization parameters measured by dynamic contrast-enhanced ultrasonography (DCE-US). METHODS: Firstly, we evaluated, in vitro , the impact of the manual repositioning of the ultrasound probe and the variations in flow rates. Experiments were conducted using a custom-made phantom setup simulating a tumor and its associated arterial input. Secondly, we evaluated, in vivo , the impact of multiple contrast agent injections and of examination day, as well as the influence of the size of region of interest (ROI) associated with the arterial input function (AIF). Experiments were conducted on xenografted B16F10 female nude mice. For all of the experiments, an ultrasound scanner along with a linear transducer was used to perform pulse inversion imaging based on linear raw data throughout the experiments. Semi-quantitative and quantitative analyses were performed using two signal-processing methods. RESULTS:In vitro , no microvascularization parameters, whether semi-quantitative or quantitative, were significantly correlated (P values from 0.059 to 0.860) with the repositioning of the probe. In addition, all semiquantitative microvascularization parameters were correlated with the flow variation while only one quantitative parameter, the tumor blood flow, exhibited P value lower than 0.05 (P = 0.004). In vivo , multiple contrast agent injections had no significant impact (P values from 0.060 to 0.885) on microvascularization parameters. In addition, it was demonstrated that semi-quantitative microvascularization parameters were correlated with the tumor growth while among the quantitative parameters, only the tissue blood flow exhibited P value lower than 0.05 (P = 0.015). Based on these results, it was demonstrated that the ROI size of the AIF had significant influence on microvascularization parameters: in the context of larger arterial ROI (from 1.17 ± 0.6 mm 3 to 3.65 ± 0.3 mm 3 ), tumor blood flow and tumor blood volume were correlated with the tumor growth, exhibiting P values lower than 0.001. CONCLUSION: AIF selection is an essential aspect of the deconvolution process to validate the quantitative DCE-US method.展开更多
This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observa...This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observations are assigned to the considered tracks.In real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done simply.In this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in computations.After DA,estimation and tracking should be done.Since in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is eliminated.This model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector.Some comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.展开更多
Input congestion very likely existed in rail transport. However, early works measuring the rail transport efficiencies rarely took the input congestion into account;hence, the proposed strategies for enhancing efficie...Input congestion very likely existed in rail transport. However, early works measuring the rail transport efficiencies rarely took the input congestion into account;hence, the proposed strategies for enhancing efficiencies can be misleading. This study revisited the rail transport efficiencies with consideration of input congestion. We employed data envelopment analysis extension method to investigate the input congestion for some selected 24 European Union (EU) railways in 2006. The results indicated that there is no strong congestion in these 24 railways. However, 12 railways have been diagnosed with weak congestion in the available capacity of freight transport as well as the number of locomotives, 7 railways in the available capacity of passenger transport, and 4 railways in the number of employees. Based on our findings, the managerial implication is to contract the available capacity of freight transport (tonnages) as the most critical strategy, rather than laying-off the excess number of employees suggested by most previous studies, which did not consider the input congestion effects while measuring the rail transport efficiencies.展开更多
为使设计人员更快更容易使用SPRD功能,Intergraph提供了一套基于Java技术开发SPRD(标准数据库)模块功能数据库SDB,用以建立材料编码、标准尺寸数据库、材料等级库。SDB平台数据需人工逐个逐行输入,在复杂几何尺寸数据的录入上费时费力,...为使设计人员更快更容易使用SPRD功能,Intergraph提供了一套基于Java技术开发SPRD(标准数据库)模块功能数据库SDB,用以建立材料编码、标准尺寸数据库、材料等级库。SDB平台数据需人工逐个逐行输入,在复杂几何尺寸数据的录入上费时费力,因此Intergraph又以.Net技术为基础开发的SPRD另一界面Smart Plant Reference Data Plus,与传统的Java技术开发的界面共同管理一个数据库,经过探索发现Smart Plant Reference Data Plus在数据量最大、耗时最长、最枯燥的外形尺寸的数据库录入中具备较大优势,尤其方便了复杂几何尺寸数据的建立。展开更多
To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-...To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.展开更多
Compared with channel estimation method based on explicit training sequences,bandwidth is saved for those methods using superimposed training sequences,while it is wasted when Cyclic Prefix(CP) is added.In previous wo...Compared with channel estimation method based on explicit training sequences,bandwidth is saved for those methods using superimposed training sequences,while it is wasted when Cyclic Prefix(CP) is added.In previous work of McLernon,the Mean Square Error(MSE) performance of Data-Dependent Superimposed Training(DDST) without CP for Single-Input Single-Output(SISO) system was analyzed under the assumption that the data-dependent sequence matrix was a circulant matrix and not interfered by others.In fact,for the system without CP,the data-dependent sequence matrix is not circulant any more and will be interfered.This paper derives the exact expression of MSE for the system without CP and also gives its extension to Multiple-Input Multiple-Output(MIMO) system without CP.展开更多
文摘The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.
文摘AIM: To evaluate the sources of variation influencing the microvascularization parameters measured by dynamic contrast-enhanced ultrasonography (DCE-US). METHODS: Firstly, we evaluated, in vitro , the impact of the manual repositioning of the ultrasound probe and the variations in flow rates. Experiments were conducted using a custom-made phantom setup simulating a tumor and its associated arterial input. Secondly, we evaluated, in vivo , the impact of multiple contrast agent injections and of examination day, as well as the influence of the size of region of interest (ROI) associated with the arterial input function (AIF). Experiments were conducted on xenografted B16F10 female nude mice. For all of the experiments, an ultrasound scanner along with a linear transducer was used to perform pulse inversion imaging based on linear raw data throughout the experiments. Semi-quantitative and quantitative analyses were performed using two signal-processing methods. RESULTS:In vitro , no microvascularization parameters, whether semi-quantitative or quantitative, were significantly correlated (P values from 0.059 to 0.860) with the repositioning of the probe. In addition, all semiquantitative microvascularization parameters were correlated with the flow variation while only one quantitative parameter, the tumor blood flow, exhibited P value lower than 0.05 (P = 0.004). In vivo , multiple contrast agent injections had no significant impact (P values from 0.060 to 0.885) on microvascularization parameters. In addition, it was demonstrated that semi-quantitative microvascularization parameters were correlated with the tumor growth while among the quantitative parameters, only the tissue blood flow exhibited P value lower than 0.05 (P = 0.015). Based on these results, it was demonstrated that the ROI size of the AIF had significant influence on microvascularization parameters: in the context of larger arterial ROI (from 1.17 ± 0.6 mm 3 to 3.65 ± 0.3 mm 3 ), tumor blood flow and tumor blood volume were correlated with the tumor growth, exhibiting P values lower than 0.001. CONCLUSION: AIF selection is an essential aspect of the deconvolution process to validate the quantitative DCE-US method.
文摘This paper presents augmented input estimation(AIE)for multiple maneuvering target tracking.Multi-target tracking(MTT)is based on two main parts,data association and estimation.In data association(DA),the best observations are assigned to the considered tracks.In real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done simply.In this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in computations.After DA,estimation and tracking should be done.Since in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is eliminated.This model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector.Some comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.
文摘Input congestion very likely existed in rail transport. However, early works measuring the rail transport efficiencies rarely took the input congestion into account;hence, the proposed strategies for enhancing efficiencies can be misleading. This study revisited the rail transport efficiencies with consideration of input congestion. We employed data envelopment analysis extension method to investigate the input congestion for some selected 24 European Union (EU) railways in 2006. The results indicated that there is no strong congestion in these 24 railways. However, 12 railways have been diagnosed with weak congestion in the available capacity of freight transport as well as the number of locomotives, 7 railways in the available capacity of passenger transport, and 4 railways in the number of employees. Based on our findings, the managerial implication is to contract the available capacity of freight transport (tonnages) as the most critical strategy, rather than laying-off the excess number of employees suggested by most previous studies, which did not consider the input congestion effects while measuring the rail transport efficiencies.
文摘为使设计人员更快更容易使用SPRD功能,Intergraph提供了一套基于Java技术开发SPRD(标准数据库)模块功能数据库SDB,用以建立材料编码、标准尺寸数据库、材料等级库。SDB平台数据需人工逐个逐行输入,在复杂几何尺寸数据的录入上费时费力,因此Intergraph又以.Net技术为基础开发的SPRD另一界面Smart Plant Reference Data Plus,与传统的Java技术开发的界面共同管理一个数据库,经过探索发现Smart Plant Reference Data Plus在数据量最大、耗时最长、最枯燥的外形尺寸的数据库录入中具备较大优势,尤其方便了复杂几何尺寸数据的建立。
基金Sponsored by the National Natural Science Foundation of China(60572120)
文摘To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.
基金Supported by the National Natural Science Foundation of China (No.60772087,No.50803016,No.60975004,No.60902023)the Foundation for the Author of National Excellent Doctoral Dissertation of P.R. China (No.200341)+1 种基金the National 863 High-Tech R&D Program (No.2007AA01Z 228)the open research fund of Key Laboratory of Information Coding and Transmission,Southwest Jiaotong University
文摘Compared with channel estimation method based on explicit training sequences,bandwidth is saved for those methods using superimposed training sequences,while it is wasted when Cyclic Prefix(CP) is added.In previous work of McLernon,the Mean Square Error(MSE) performance of Data-Dependent Superimposed Training(DDST) without CP for Single-Input Single-Output(SISO) system was analyzed under the assumption that the data-dependent sequence matrix was a circulant matrix and not interfered by others.In fact,for the system without CP,the data-dependent sequence matrix is not circulant any more and will be interfered.This paper derives the exact expression of MSE for the system without CP and also gives its extension to Multiple-Input Multiple-Output(MIMO) system without CP.
