A feasibility study of a direct-mapping parallel processing method to solve linear equations in load-flow calculation

With the growing size and complexity of power systems, system analysis—such as transients calculation—takes much time. Hence, fast calculation methods are required. Although parallel processing is a hopeful method, there have been difficulties in the parallel solution of linear equations which appear in power-flow calculations by the Newton-Raphson method. This paper aims at the fast calculation of the power-flow problem by means of parallel processing. In order to improve the suitability to the parallel solution of the differential equation in transients calculation, we assume the use of a direct-mapping parallel processing machine to map directly the network of a power system onto a network of processors. Under this assumption, we propose a new parallel-processing-oriented method in which the linear equation is solved by linear iterations between nodes with Aitken acceleration. We simulate the method on three model power systems and compare this Parallel Iterative Method (PIN) with a Parallel Direct Method (PDM) which uses the banded matrix according to the number of operations required. As a result, we can expect that PIM may solve linear equations faster than PDM with m processors, although the PIM might be inferior to the PDM with m × m processors, where m denotes the half-band width of the banded matrix.     

Satellite SAR Remote Sensing of Great Lakes Ice Cover,Part 2. Ice Classification and Mapping

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts.     

PIRF-Nav 2.0: Fast and online incremental appearance-based loop-closure detection in an indoor environment

This paper presents a fast and online incremental solution for an appearance-based loop-closure detection problem in a dynamic indoor environment. Closing the loop in a dynamic environment has been an important topic in robotics for decades. Recently, PIRF-Nav has been reported as being successful in achieving high recall rate at precision 1. However, PIRF-Nav has three main disadvantages: (i) the computational expense of PIRF-Nav is beyond real-time, (ii) it utilizes a large amount of memory in the redundant process of keeping signatures of places, and (iii) it is ill-suited to an indoor environment. These factors hinder the use of PIRF-Nav in a general environment for long-term, high-speed mobile robotic applications. Therefore, this paper proposes two techniques: (i) new modified PIRF extraction that makes the system more suitable for an indoor environment and (ii) new dictionary management that can eliminate redundant searching and conserve memory consumption. The results show that our proposed method can complete tasks up to 12 times faster than PIRF-Nav with only a slight percentage decline in recall. In addition, we collected additional data from a university canteen crowded during lunch time. Even in this crowded indoor environment, our proposed method has better real-time processing performance compared with other methods.     

对DAG-MAP算法的研究

DAG－MAP是一个面向延迟优化的FPGA工艺映射算法,其中的标记过程是该算法的核心.文章对原算法中的标记过程进行了研究,并且提出了一个改进的标记方法.通过对MCNC标准测试电路的实验结果表明该算法比原算法更为有效,并且算法所用时间没有明显的增加.     

Surface texture analysis based upon the visually acquired perturbation of surface normals

A novel technique has been developed for the textural analysis of Lambertian surfaces while in the presence of a variable albedo. The method has direct application for the surface quality determination of cosmetically sensitive components, and has particular application where more traditional methods may prove unsatisfactory. A photometric stereo technique is used to facilitate the isolation of localised irregular features, such as scratching, indentations or small protrusions, which may be obscured by a coincident, regular or random surface albedo. A generic lighting arrangement is employed, which obviates the need for a customised lighting configuration. This represents a significant advantage for the configuration of industrial vision-based inspection systems. Promising experimental results have been obtained using example components, and are presented in the paper.     

Optimal classification methods for mapping agricultural tillage practices

The classification of agricultural tillage systems has proven challenging in the past using traditional classification methods due to the similarity of spectral reflectance signatures of soils and senescent crop residues. In this study, five classification methods were examined to determine the most suitable classification algorithm for the identification of no-till (NT) and traditional tillage (TT) cropping methods: minimum distance (MD), Mahalanobis distance, Maximum Likelihood (ML), spectral angle mapping (SAM), and the cosine of the angle concept (CAC). A Landsat ETM+ image acquired over southern Michigan and northern Indiana was used to test these classification methods. Each classification method was validated with 293 ground truth sampling locations collected commensurate with the satellite overpass. Classification accuracy was then assessed using error matrix analysis, Kappa statistics, and tests for statistical significance. The results indicate that of the classification routines examined, the two spectral angle methods were superior to the others. The cosine of the angle concept algorithm outperformed all the other classification routines for tillage practice identification and mapping, yielding an overall accuracy of 97.2% (Kappa=0.959).     

Incident Light Metering in Computer Graphics

Every rendering process consists of two steps. The first is the computing of luminance values by methods like ray tracing or radiosity, and the second step is the mapping of the computed values to values appropriate for displaying. In the last years, as alternative to simple linear scaling which maps the average value to the medium luminance, some new ways of mapping were introduced. These new methods are based on photography analogies and on human vision models. All existing methods follow, implicitly or explicitly, the reflected light metering principle. The method introduced in this paper is the first that follows the incident light metering used in professional photography and in the movie industry. Actually the irradiances are measured using a set of diffusors, which are placed automatically in the scene, and a linear scale factor based on these measurements is used to map the computed radiances to the display device. The diffusors act as half space integrators, they collect the light energy from all half space directions. The light comes from the primary light sources, or it is the result of various interreflections. The newly introduced method reproduces original colors faithfully even for scenes with very low or very high average reflectivity.     

A novel intelligent verification platform based on a structured analysis model

An intelligent verification platform based on a structured analysis model is presented.Using an abstract model mechanism with specific signal interfaces for user callback,the unified structured analysis data,shared by the electronic system level design,functional verification,and performance evaluation,enables efficient management review,auto-generation of code,and modeling in the transaction level.We introduce the class tree,flow parameter diagram,structured flow chart,and event-driven finite state machine as structured analysis models.As a sand table to carry maps from different perspectives and levels via an engine,this highly reusable platform provides the mapping topology to search for unintended consequences and the graph theory for comprehensive coverage and smart test cases.Experimental results show that the engine generates efficient test sequences,with a sharp increase in coverage for the same vector count compared with a random test.     

The Migration of Multi-tier E-commerce Applications to an Enterprise Java Environment

As technology evolves, many organizations face the problem of migrating legacy applications from one technology base to another. We report on a case study involving the migration of legacy code into the IBM® WebSphere® Commerce Suite product. Specifically, we focus on the problem of migrating applications that use traditional database access techniques to applications using the Enterprise JavaBean (EJB) programming model. Our results include a practical methodology that facilitates such migration, as well as a tool that supports this methodology. The tool has been released on IBM's alphaWorks site.