物方多视影像密集匹配方法

针对多视影像由于遮挡导致的匹配不确定性问题,该文提出一种特征点和物方地面元相结合的多视影像密集匹配方法。该方法利用规则格网划分的空间平面作为基础,通过特征点匹配获取同名像点和高程赋值的格网平面,为后续匹配提供初始的DSM。在此基础上,利用铅垂线轨迹法对平面上规则分布的平面元进行匹配,加密特征点匹配结果。通过对某区域UCX影像的匹配实验表明,该文提出的算法能高效、准确地得到匹配结果,特别对较大影像计算快速,适用于实时处理。

A simulation study of sampling time point designing for therapeutic drug monitoring based on a population pharmacokinetic model

Aim To develop a method to estimate population pharmacokinetic parameters with the limited sampling time points provided clinically during therapeutic drug monitoring. Methods Various simulations were attempted using a one-compartment open model with the first order absorption to determine PK parameter estimates with different sampling strategies as a validation of the method. The estimated parameters were further verified by comparing to the observed values. Results The samples collected at the single time point close to the non-informative sampling time point designed by this method led to bias and inaccurate parameter estimations. Furthermore, the relationship between the estimated non-informative sampling time points and the values of the parameter was examined. The non-informative sampling time points have been developed under some typical occasions and the results were plotted to show the tendency. As a result, one non-informative time point was demonstrated to be appropriate for clearance and two for both volume of distribution and constant of absorption in the present study. It was found that the estimates of the non-informative sampling time points developed in the method increase with increases of volume of distribution and the decrease of clearance and constant of absorption. Conclusion A rational sampling strategy during therapeutic drug monitoring can be established using the method present in the study.

Mining Data Correlation from Multi-Faceted Sensor Data in Internet of Things

Sensors are ubiquitous in the Internet of Things for measuring and collecting data. Analyzing these data derived from sensors is an essential task and can reveal useful latent information besides the data. Since the Internet of Things contains many sorts of sensors, the measurement data collected by these sensors are multi-type data, sometimes contai- ning temporal series information. If we separately deal with different sorts of data, we will miss useful information. This paper proposes a method to dis- cover the correlation in multi-faceted data, which contains many types of data with temporal informa- tion, and our method can simultaneously deal with multi-faceted data. We transform high-dimensional multi-faeeted data into lower-dimensional data which is set as multivariate Gaussian Graphical Models, then mine the correlation in multi-faceted data by discover the structure of the multivariate Gausslan Graphical Models. With a real data set, we verifies our method, and the experiment demonstrates that the method we propose can correctly fred out the correlation among multi-faceted meas- urement data.

石油二次配送管理优化研究

本文旨在提出优化我国石油企业二次配送管理的措施和建议,分析了国内外石油二次配送的现状和特点,然后对从配送中心网络布局、信息化建设、管理部门结构建设和发展第三方物流等方面提出的优化措施进行具体论述,对我国石油销售企业降低物流成本,提高经济效益和市场竞争力具有重要的参考价值。

Dynamic Visualization Approach of the Multiphase Flow Using Electrical Capacitance Tomography

Identifying the flow patterns is vital for understanding the complicated physical mechanisms in multiphase flows.For this purpose,electrical capacitance tomography(ECT) technique is considered as a promising visualization method for the flow pattern identification,in which image reconstruction algorithms play an important role.In this paper,a generalized dynamic reconstruction model,which integrates ECT measurement information and physical evolution information of the objects of interest,was presented.A generalized objective functional that simultaneously considers the spatial constraints,temporal constraints and dynamic evolution information of the objects of interest was proposed.Numerical simulations and experiments were implemented to evaluate the feasibility and efficiency of the proposed algorithm.For the cases considered in this paper,the proposed algorithm can well reconstruct the flow patterns,and the quality of the reconstructed images is improved,which indicates that the proposed algorithm is competent to reconstruct the flow patterns in the visualization of multiphase flows.

Adaptive and local analysis of climate data

This paper focuses on how to extract physically meaningful information from climate data,with emphases placed on adaptive and local analysis. It is argued that many traditional statistical analysis methods with rigorous mathematical footing may not be efficient in extracting essential physical information from climate data;rather,adaptive and local analysis methods that agree well with fundamental physical principles are more capable of capturing key information of climate data. To illustrate the improved power of adaptive and local analysis of climate data,we also introduce briefly the empirical mode decomposition and its later developments.

Robust reliable H_∞ control for a class of uncertain time-delay systems

This paper deals with the problem of robust reliable H∞ control for a class of uncertain nonlinear systems with time-varying delays and actuator failures. The uncertainties in the system are norm-bounded and time-varying. Based on Lyapunov methods, a sufficient condition on quadratic stabilization independent of delay is obtained. With the help of LMIs (linear matrix inequalities) approaches, a linear state feedback controller is designed to quadratically stabilize the given systems with a H∞ performance constraint of disturbance attenuation for all admissible uncertainties and all actuator failures occurred within the prespecified subset. A numerical example is given to demonstrate the effect of the proposed design approach.

Bioinformatic Tools for Polyploid Crops

Polyploidy is common among agriculturally important crops. Popular genetic methods and their implementations cannot always be applied to polyploid genetic data. We give an overview about available tools and their limitations in terms of levels of ploidy, auto- and allo-ploidy. The main classes of tools are genotype calling, linkage mapping and haplotyping. The usability of the tools is discussed with a focus on their applicability to data sets produced by state of the art technologies. We show that many challenges remain until the toolset for polyploidy provides similar functionalities as those which are already available for diploids. Some tools have been developed over a decade ago and are now outdated. In addition, we discuss necessary steps to overcome this shortage in the future.

Regional Land Use Patterns and Water Consumption in the Jordan Valley Using Geographic Information Systems

Trends in land use and water consumption are crucial components in understanding the changing nature of agricultural production and water use in- the Northern Jordan Valley. The objective of this study is to examine current agricultural land uses in the Jordan Valley and their water consumption patterns as well as to examine the changes in land use and water consumption that occurred between the years 2002 and 2010. Farm level cropping patterns and total annual water use were analysed in order to examine inter-basin land use and water consumption characteristics as well as to estimate the amount of water consumed by each respective crop in total and per unit of land devoted to its production. It was found that citrus production dominated both land and water usage in every basin of the Northern Jordan Valley and that between 2002 and 2010 there were shifts toward increasing citrus production in almost every basin surveyed. It was found that agricultural irrigation water usage decreased overall between 2002 and 2010 by approximately 15 percent and irrigated land usage in the Jordan Valley increased by 5 percent. The role of citrus farming is becoming more important in the Jordan Valley as Jordan＇s agricultural economy shifts away from subsistence farming for staple food crops like wheat and vegetables toward more financially lucrative crops grown for an increasingly international market. This trend is at least partly due to the increasing cost of agricultural irrigation water from Jordan＇s national canal system.

A mirror-image protein-based information barcoding and storage technology

A mirror-image protein-based information barcoding and storage technology wherein D-amino acids are used to encode information into mirror-image proteins that are chemically synthesized is described.These mirror-image proteins were then fused into various materials from which information-encoded objects were produced.Subsequently,the mirror-image proteins were extracted from the objects using biotin-streptavidin resin-mediated specific enrichment and cleaved using an Ni(Ⅱ)-mediated selective peptide cleavage.Protein sequencing was accomplished using liquid chromatography/tandem mass spectrometry(LC-MS/MS)and then transcoded into the recorded information.We demonstrated the use of this technology to encode Chinese words into mirror-image proteins,which were then fused onto a poly(ethylene terephthalate)(PET)film and retrieved and decoded by LC-MS/MS sequencing.Compared to information barcoding and storage technologies using natural biopolymers,the mirrorimage biopolymers used in our technology may be more stable and durable.