9635460
Energy efficiency of two virtual infrastructures for MANETs
In a mobile ad hoc network (MANET), virtual infrastructures are helpful to network operations. There are two popular virtual infrastructures for MANETs, square-based and hexagon-based. The square-based infrastructure divides the network area into squares of the same kind, and forwarding is done from one square to four neighboring squares. The hexagon-based divides the area into hexagons and forwarding is six-directional. These two virtual infrastructures can be used to aid routing and to save energy. However, no performance analysis or comparison has been made between them. This paper compares energy efficiency of these two virtual infrastructures analytically and numerically. Theoretical analysis shows, with the same transmission range, the six-direction forwarding covers 40% more area than the four-direction forwarding does in a single hop, and in 95% of the cases, the six-direction forwarding has a shorter path, therefore less energy consumption. The simulation results support the analysis.
131063896
Change analysis of land surface temperature based on robust statistics in the estuarine area of Pearl River (China) from 1990 to 2000 by Landsat TM/ETM+ data
The estuarine area of Pearl River that has taken great changes in land cover since 1990 is a typical area for studying the change of land surface temperature (LST). The LST of the years 1990 and 2000 in this area was estimated from the data of Landsat TM/ETM+ band 6, respectively, and three scales, corresponding to high, normal and low temperature ranges, were divided by a robust statistical method. The results show that the area of high temperature range in 2000 has an increase of 250 km2 compared with the year 1990. The urban‐used land and the bare land are the main land cover types constituting the high temperature range area.
17770433
A generalized expansion matching based feature extractor
A novel and efficient generalized feature extraction method is presented based on the expansion matching (EXM) method and the Karhunen-Loueve (KL) transform. The EXM method is used to design optimal detectors for different features. The KL representation is used to define an optimal basis for representing these EXM feature detectors with minimum truncation error. Input images are then analyzed with the resulting KL basis set. The KL coefficients obtained from the analysis are used to efficiently reconstruct the response due to any combination of feature detectors. The method is applied to real images and successfully extracts a variety of arc and edge features as well as complex junction features formed by combining two or more arc or line features.
19349376
Automatically Generating Ada95 Codes for Concurrent Objects
33971177
Using stereo geometry towards accurate 3D reconstruction
This paper addresses the problem of threedimensional reconstruction and how the geometry of the stereo vision system affects the quality of such a reconstruction. We have considered the general case of non calibrated cameras with approximately known intrinsic parameters. The latter could be known either from previous experiments or from the manufacturer's specifications. In particular, the paper aims at finding the best geometric configuration of the stereo vision system(rotation and translation between the two cameras) that is the least sensitive to errors on the intrinsic parameters. Given that in most cases, in robotics for instance, we have the freedom to set-up the geometry of the stereo vision system, finding how cameras' geometry interacts with errors from different sources is a central issue. Furthermore, when the intrinsic parameters are completely unknown, we have used a single constraint from the scene that has allowed us to calculate the focal length and therefore, the Euclidean reconstruction. We have used extensive simulations where the stereo vision geometry has ranged from pure translation to general 3D motion. The obtained results have clearly shown that a pure translation is always better, as it is not significantly affected by errors on the intrinsic parameters. When assuming that the intrinsic parameters are not known, the use of the perpendicularity constraint from the scene has made it possible to avoid the classical and tedious calibration process.
15697716
Walk to here: a voice driven animation system
We present a novel interface for directing the actions of computer animated characters and camera movements. Our system takes spoken input in combination with mouse pointing to generate desired character animation based on motion capture data. The aim is to achieve a more natural animation interface by supporting the types of dialogue and pointing that might be used when one person is explaining a desired motion to another person. We compare our voice-driven system with a button-driven animation interface that has equivalent capabilities. An informal user study indicates that for the test scenarios, the voice-user interface (VUI) is faster than an equivalent graphical user interface (GUI). Potential applications include storyboarding for film or theatre, directing characters in video games, and scene reconstruction.
13369239
On Solving the Inverse Scattering Problem with RBF Neural Networks: Noise-Free Case
Neural networks are successfully used to determine small particle properties from knowledge of the scattered light – an inverse light scattering problem. This type of problem is inherently difficult to solve as it is represented by a highly ill-posed function mapping. This paper presents a technique that solves the inverse light scattering problem for spheres using Radial Basis Function (RBF) neural networks. A two-stage network architecture is arranged to enhance network approximation capability. In addition, a new approach to computing basis function parameters with respect to the inverse scattering problem is demonstrated. The technique is evaluated for noise-free data through simulations, in which a minimum 99.06% approximation accuracy is achieved. A comparison is made between the least square and the orthogonal least square training methods.