基于K-SVD的星载GPS观测数据压缩方法

空间飞行器主要采用双频GPS精密定轨技术提高轨道预报精度,但需对双频GPS导航系统的观测数据进行预存储,为星载固存的存储资源增加负担;为此,文章提出了针对星载GPS观测数据的压缩方法,该方法引入稀疏表示理论,采用K奇异值分解(K-SVD,k-singular value decomposition)字典学习方法构建出压缩字典,GPS导航系统将采集的观测数据时间序列稀疏分解到K-SVD压缩字典中,达到数据压缩目的 ;通过地面仿真验证,该方法不仅具有高压缩比、低失真率等特点,还能够降低GPS观测数据的噪声水平,从而提升了0.2～0.36 mm的精密定轨精度,并且该方法适合不同轨道高度的低轨飞行器应用.     

一种基于改进客观聚类分析的模糊辨识方法

针对模糊辨识中采用迭代和人为决策法确定模糊规则数时易受噪声和人为因素的影响,而导致算法鲁棒性较差和计算量较高的问题,提出一种基于改进客观聚类分析的模糊辨识方法.首先引入并改进了客观聚类分析法,克服了迭代导致的规则数冗余,降低了人为因素对聚类结果的影响,从而减小了计算量并提高了鲁棒性;然后结合模糊聚类和稳态卡尔曼滤波法,分别辨识了前提和结论参数;最后通过Box-Jenkins仿真实例验证了所提方法的有效性.     

A novel edge detection method based on the maximizing objective function

This paper proposes a novel edge detection method for both gray level images and color images. The 3×3 mask in the image is considered and two pixel sets S₀ and S₁ in the mask are used to define an objective function. The values of the objective function corresponding to four directions determine the edge intensity and edge direction of each pixel in the mask. After all pixels in the image have been processed, the edge map and direction map are generated. Then we apply the non-maxima suppression method to the edge map and the direction map to extract the edge points. The proposed method can detect the edge successfully, while double edges, thick edges, and speckles can be avoided.     

A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting

Recently, resolving the problem of evaluation and ranking the potential suppliers has become as a key strategic factor for business firms. With the development of intelligent and automated information systems in the information era, the need for more efficient decision making methods is growing. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable criteria assuming that compromising is acceptable to resolve conflicts. On the other side objective weights based on Shannon entropy concept could be used to regulate subjective weights assigned by decision makers or even taking into account the end-users’ opinions. In this paper, we treat supplier selection as a group multiple criteria decision making (GMCDM) problem and obtain decision makers’ opinions in the form of linguistic terms. Then, these linguistic terms are converted to trapezoidal fuzzy numbers. We extended the VIKOR method with a mechanism to extract and deploy objective weights based on Shannon entropy concept. The final result is obtained through next steps based on factors R, S and Q. A numerical example is proposed to illustrate an application of the proposed method.     

A finite element based level-set method for multiphase flow applications

A numerical method for simulating incompressible two-dimensional multiphase flow is presented. The method is based on a level-set formulation discretized by a finite-element technique. The treatment of the specific features of this problem, such as surface tension forces acting at the interfaces separating two immiscible fluids, as well as the density and viscosity jumps that in general occur across such interfaces, have been integrated into the finite-element framework. Using a method based on the weak formulation of the Navier-Stokes equations has its advantages. In this formulation, the singular surface tension forces are included through line integrals along the interfaces, which are easily approximated quantities. In addition, differentiation of the discontinuous viscosity is avoided. The discontinuous density and viscosity are included in the finite element integrals. A strategy for the evaluation of integrals with discontinuous integrands has been developed based on a rigorous analysis of the errors associated with the evaluation of such integrals. Numerical tests have been performed. For the case of a rising buoyant bubble the results are in good agreement with results from a front-tracking method. The run presented here is a run including topology changes, where initially separated areas of one fluid merge in different stages due to buoyancy effects. Received: 1 March 1999 / Accepted: 17 June 1999     

结合变异粒子群和字典学习的遥感影像去噪

针对在线字典学习需将所有字典原子全部更新、优化方向难以进行估算等原因造成精度下降的不足,提出基于变异粒子群优化的在线字典学习算法。算法基于ODL的基础,在字典学习的迭代过程中对梯度下降函数进行优化。首先选出特殊字典原子,利用各个字典原子之间关系,线性表征当前选出的原子,以线性系数作为粒子群中的粒子位置。然后将基于变异粒子群的原子更新模式引入字典学习,利用变异粒子群优化算法进行粒子的适应度淘汰,选择更适合的粒子进行下一轮的字典更新。此外,利用中间变量将历史参考数据引入变异粒子群模型以引导其优化方向,提高字典的准确性和有效性。利用高分一号遥感影像进行实验,实验结果表明该算法优于同类方法,有更好的噪音抑制效果,同时也提高了大规模的遥感图像处理性能。     

A multiple-GPU based parallel independent coefficient reanalysis method and applications for vehicle design

The main limits of reanalysis method using CUDA (Compute Unified Device Architecture) for large-scale engineering optimization problems are low efficiency on single GPU and memory bottleneck of GPU. To breakthrough these bottlenecks, an efficient parallel independent coefficient (IC) reanalysis method is developed based on multiple GPUs platform. The IC reanalysis procedure is reconstructed to accommodate the use of multiple GPUs. The matrices and vectors are successfully partitioned and prepared for each GPU to achieve good load balance as well as little communication between GPUs. This study also proposes an effective technique to overlap the computation and communication by using non-blocking communication strategy. GPUs would continue their succeeding tasks while communication is still carried out simultaneously. Furthermore, the CSR format is used in each GPU for saving the memory. Finally, large-scale vehicle design problems are implemented by the developed solver. According to the test results, the multi-GPU based IC reanalysis method has potential capability for handling the real large scale problem and reducing the design cycle.     

A physically based satellite rainfall estimation method using fluid dynamics modelling

A cloud motion winds (CMW) method is presented for improving quantitative rainfall estimation advection schemes that use both infrared (IR) and passive microwave (PMW) satellite data. Advection schemes are used to provide quantitative rainfall estimates by combining more direct PMW rainfall estimates with more frequent IR cloud top temperature measures using a two‐step technique: (1) PMW estimates are transported along CMW trajectories calculated with an advection scheme at subpixel resolution; and (2) PMW estimates are calibrated using the IR gradient along those trajectories. These schemes outperform traditional methods of satellite rainfall estimation but no clear physical basis for the procedure has yet been described. Here, the physical basis for the image processing techniques used in advection techniques is described. It is shown that geostationary satellite‐derived CMW from IR sensors can be modelled in terms of fluid dynamics using Navier–Stokes equations. This approach allows for modelling the problem as equivalent to the flow of a brightness temperature field, also providing subpixel resolution and unlimited rotation/deformation possibilities. The method is illustrated with rainfall estimates from a numerical weather prediction (NWP) model and with 3‐hourly PMW products as simulation data, obtaining consistent results.     

基于北斗的气象自动观测系统数据编码设计

针对气象自动观测网数据传输需要,提出了基于北斗卫星导航系统的气象自动观测数据编码设计方案。该方案采用北斗短报文通信功能传输帧数据,从而实现自动观测数据的传输。采用该方案使得指挥终端能实时接收自动站发送的观测数据。采用北斗卫星导航系统能实现观测站点的快速部署和观测数据的高效获取。     

A method for objective edge detection evaluation and detector parameter selection

Subjective evaluation by human observers is usually used to analyze and select an edge detector parametric setup when real-world images are considered. We propose a statistical objective performance analysis and detector parameter selection, using detection results produced by different detector parameters. Using the correspondence between the different detection results, an estimated best edge map, utilized as an estimated ground truth (EGT), is obtained. This is done using both a receiver operating characteristics (ROC) analysis and a Chi-square test, and considers the trade off between information and noisiness in the detection results. The best edge detector parameter set (PS) is then selected by the same statistical approach, using the EGT. Results are demonstrated for several edge detection techniques, and compared to published subjective evaluation results. The method developed here suggests a general tool to assist in practical implementations of parametric edge detectors where an automatic process is required.     

A method for identifying Web applications

Web applications are ubiquitous in today’s businesses. The security of these applications is of utmost importance since security breaches might negatively impact good reputation, and even result in bankruptcy. There are different methods of assessing security of Web applications, mainly based on some automated method of scanning. One type of scan method feeds random data to the application and monitors its behavior. The other type uses a database with predefined vulnerabilities that are checked one by one until either a vulnerability is found, or it can be claimed that the application does not have any known vulnerabilities. The important step in latter type of scan process is the identification of the application since in this case we are narrowing number of checks and, as a consequence, the scan process is faster. This paper describes a method for Web application identification based on a black box principle. Our method is based on the invariance of certain characteristics of Web applications. We experimentally tested and confirmed the usefulness of this approach.     

基于HBase的领域本体存储方法及其应用研究

在分析民航突发事件应急管理领域本体及其存储特点的基础上,提出了一种基于HBase的领域本体存储方法,采用将领域本体元数据与RDF实例数据分开存储的方式,给出了描述领域本体类及属性信息的元数据和RDF实例数据的存储模型,及其基于MapReduce的领域本体RDF数据并行加载过程。结合应用实现了领域本体基于HBase API的基本图模式查询,并在Hadoop环境下进行了实验与效果分析,为民航应急管理领域本体的海量数据存储提供了理论与方法支撑。     

基于客观权重确定的数据中心网络性能评估方法

针对大规模数据中心网络如何有效监控网络、发现网络性能瓶颈和潜在故障点,为网络性能优化提供支持成为新的研究课题.然而影响网络性能的因素众多,性能因素的影响程度存在差异,如何给出一个准确的性能评估一直是比较困难的问题.针对上述问题,提出了网络性能评估指标体系,在此基础上进一步提出了一种基于客观权重确定的数据中心网络性能评估方法(PE-OWD).该方法通过采用基于客观权值确定方法动态计算性能权值,利用基于历史参数分布的数据归一化方法,建立了完善的网络性能健康度评估模型.针对天河2真实的网络环境,对网络设备的性能指标进行评估,验证了网络性能评估方法的有效性.     

A continuous adjoint method with objective function derivatives based on boundary integrals, for inviscid and viscous flows

A continuous adjoint formulation for inverse design problems in external aerodynamics and turbomachinery is presented. The advantage of the proposed formulation is that the objective function gradient does not depend upon the variation of field geometrical quantities, such as metrics variations in the case of structured grids. The final expression for the objective function gradient includes only boundary integrals which can readily be calculated in both structured and unstructured grids; this is feasible in design problems where the objective function is either a boundary integral (pressure deviation along the solid walls) or a field integral (the entropy generation over the flow domain). The formulation governs inviscid and viscous flows; it takes into account the streamtube thickness variation terms in quasi-3D cascade designs or rotational terms in rotating blade design problems. The application of the method is illustrated through a number of design problems concerning isolated airfoils, a 3D duct, 2D, quasi-3D and 3D, stationary and rotating turbomachinery blades.     

A practical satellite layout optimization design approach based on enhanced finite-circle method

Satellite layout optimization design problems with complicated performance constraints are studied in this paper. In addition to the traditional geometric constraint, system centroid constraint, inertia angles constraint and dynamics performance, more complex design factors based on practical engineering requirements are considered, including thermal performance, CMA (compatibility, maintainability and accessibility) constraint and the special rules of the placement of special components. An enhanced interference algorithm based on finite-circle method (FCM) is proposed to handle CMA constraint, which can effectively control the distance between any two components. Moreover, to provide system engineers with the information of design space about dynamics and thermal performance, the accelerated particle swarm optimization (APSO) is proposed to optimize the constructed layout model globally. Finally, the feasibility and effectiveness of the proposed methodology are validated by a numerical test and an engineering example.     

A new method for cross-calibration of two satellite sensors

Given that many operational satellite sensors are not calibrated, while a handful of research sensors are, cross-calibration between the two types of sensor is a cost-effective means of calibration. A new method of sensor cross-calibration is demonstrated here using the Chinese Multi-channel Visible Infrared Scanning radiometer (MVIRS) and the US Moderate Resolution Imaging Spectrometer (MODIS). MVIRS has six channels, equivalent to the current National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and four additional ones for remote sensing of ocean colour and moisture. The MVIRS on-board China's polar-orbiting meteorological satellite (FY-1D) was launched on 15 May 2002 with an earlier overpass time than Terra. The sensor has no on-board calibration assembly. This study attempts to calibrate MVIRS against the well-calibrated MODIS, by taking a series of measures to account for their differences. Clear-sky measurements made from the two sensors in July-October 2002 were first collocated. Using the 6S radiative transfer model, MODIS reflectances measured at the top-of-the atmosphere were converted into surface reflectances. They were corrected to the viewing geometry of the MVIRS using the bidirectional reflectance distribution function (BRDF) measured on the ground. The spectral response functions of the two sensors were employed to account for spectral discrepancies. After these corrections, very close linear correlations were found between radiances estimated from the MODIS and the digital readings from the MVIRS, from which the calibration gains were derived. The gains differ considerably from the pre-launch values and are subject to degradation over time. The calibration accuracy is estimated to be less than 5%, which is compatible to that obtained by the more expensive vicarious calibration approach.     

A genetic method for designing TSK models based on objective weighting: application to classification problems.

This paper proposes a genetic-based algorithm for generating simple and well-defined Takagi-Sugeno-Kang (TSK) models. The method handles several attributes simultaneously, such as the input partition, feature selection and estimation of the consequent parameters. The model building process comprises three stages. In stage one, structure learning is formulated as an objective weighting optimization problem. Apart from the mean square error (MSE) and the number of rules, three additional criteria are introduced in the fitness function for measuring the quality of the partitions. Optimization of these measures leads to models with representative rules, small overlapping and efficient data cover. To obtain models with good local interpretation, the consequent parameters are determined using a local MSE function while the overall model is evaluated on the basis of a global MSE function. The initial model is simplified at stage two using a rule base simplification routine. Similar fuzzy sets are merged and the “don’t care” premises are recognized. Finally, the simplified models are fine-tuned at stage three to improve the model performance. The suggested method is used to generate TSK models with crisp and polynomial consequents for two benchmark classification problems, the iris and the wine data. Simulation results reveal the effectiveness of our method. The resulting models exhibit simple structure, interpretability and superior recognition rates compared to other methods of the literature.     

Verification of dust forecast over the Indian region with satellite and ground based observations

This article presents the verification results of the dust forecast by a numerical model over India and neighbouring regions. National Centre for Medium Range Weather Forecasting Unified Model (NCUM) is a global numerical weather prediction (NWP) model with a prognostic dust scheme. Evaluation of the performance of dust forecast by NCUM is carried out in this study. Model forecast of dust optical depth (DOD) at 550 nm is validated against ground-based and satellite observations since optical depth measurements in mid-visible wavelength are easily available. Daily 5-day forecast based on 00 UTC initial condition during dust dominated pre-monsoon season (April–May) of 2014 is used in this study. Location specific and geographical distribution of dust forecast is validated against Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite retrieved DOD observation at 532 nm, Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD), Ozone Monitoring Instrument (OMI), aerosol index, and Aerosol Robotic Network (AERONET) station data of total and coarse mode AOD. The verification results indicate that NCUM dust forecast generally gives good representation of large scale geographical distribution of dust over the western region of India. DOD forecasts show good correlation with co-located CALIPSO DOD over the western part (0.71) compared to central (0.58) and eastern (0.61) part of India in April while it show similar trend in May with slightly improved correlation (0.68) over the eastern part of India. Results also show that DOD forecasts are better correlated to AERONET coarse mode AOD observations over Jaipur in April and over Kanpur in May. Vertical distribution of dust concentrations in the forecast show reasonably good agreement with attenuated backscatter and depolarization ratio from CALIPSO observations. The model is also able to simulate spatiotemporal distribution of dust during a major dust event as observed by CALIPSO, MODIS, and OMI.