Decisive arrival law parameters and a general finite capacity queueing problem

This paper addresses the problem of finding the parameters of the arrival law which most significantly influence expected occupation and loss of a finite capacity queue. The input process is supposed to be ergodic and wide sense stationary. We show that it is mostly possible to fit an MMPP(2) to the decisive parameters of observational data. Numerical examples illustrate the importance of the decisive parameters, called key parameters, and also show the accuracy of the proposed fitting procedure. Finally, in the appendix we present the solution of the finite capacity queueing problem with Special Semi Markov Process (SSMP) arrivals and a general service strategy.     

A sensing strategy for the reverse engineering of machined parts

The reverse engineering of machined parts requires sensing an existing part and producing a design (and perhaps a manufacturing process) for it. We have developed a reverse engineering system that has proven effective with a set of machined parts. This paper describes the system, presents some results, and discusses strategy for a new system.This work was supported by ARPA under ARO grant number DAAH04-93-G-0420, DARPA grant N00014-91-J-4123, NSF grant CDA 9024721, and a University of Utah Research Committee grant. All opinions, findings, conclusions or recommendations expressed in this document are those of the authors and do not necessarily reflect the views of the sponsoring agencies.     

Impacts of spectral band difference effects on radiometric cross-calibration between satellite sensors in the solar-reflective spectral domain

In order for quantitative applications to make full use of the ever-increasing number of Earth observation satellite systems, data from the various imaging sensors involved must be on a consistent radiometric scale. This paper reports on an investigation of radiometric calibration errors due to differences in spectral response functions between satellite sensors when attempting cross-calibration based on near-simultaneous imaging of common ground targets in analogous spectral bands, a commonly used post-launch calibration methodology. Twenty Earth observation imaging sensors (including coarser and higher spatial resolution sensors) were considered, using the Landsat solar reflective spectral domain as a framework. Scene content was simulated using spectra for four ground target types (Railroad Valley Playa, snow, sand and rangeland), together with various combinations of atmospheric states and illumination geometries. Results were obtained as a function of ground target type, satellite sensor comparison, spectral region, and scene content. Overall, if spectral band difference effects (SBDEs) are not taken into account, the Railroad Valley Playa site is a “good” ground target for cross calibration between most but not all satellite sensors in most but not all spectral regions investigated. “Good” is defined as SBDEs within ± 3%. The other three ground target types considered (snow, sand and rangeland) proved to be more sensitive to uncorrected SBDEs than the RVPN site overall. The spectral characteristics of the scene content (solar irradiance, surface reflectance and atmosphere) are examined in detail to clarify why spectral difference effects arise and why they can be significant when comparing different imaging sensor systems. Atmospheric gas absorption features are identified as being the main source of spectral variability in most spectral regions. The paper concludes with recommendations on spectral data and tools that would facilitate cross-calibration between multiple satellite sensors.     

Nonlinear suboptimal filtration of pseudorandom sequences

The critical importance of studies of alternative methods of representation and processing of signals constructed from pseudorandom sequences of maximal period is demonstrated. For the first time, it is proposed that a multidimensional nonlinear finite-difference representation of an arbitrary pseudorandom sequence be employed. A suboptimal algorithm for nonlinear discrete Kalman filtration of a pseudorandom sequence is obtained. A numerical example of filtration of a sequence formed on the basis of a given recurrence rule is considered and its efficiency is demonstrated.     

An approach to integrating shape and biomedical attributes in vascular models

Computational models have been used widely in tissue engineering research and have proven to be powerful tools for bio-mechanical analysis (i.e., blood flow, growth models, drug delivery, etc). This paper focuses on developing higher-fidelity models for vascular structures and blood vessels that integrate computational shape representations with biomedical properties and features. Previous work in computer-aided vascular modeling comes from two communities. For those in biomedical imaging, the goal of past research has been to develop image understanding techniques for the interpretation of x-ray, magnetic resonance imaging (MRI), or other radiological data. These representations are predominantly discrete shape models that are not tied to physiological properties. The other corpus of existing work comes from those interested in developing physiological models for vascular growth and behavior based on bio-medical attributes. These models usually either have a highly simplified shape representation, or lack one entirely. Further, neither of these representations are suitable for the kind of interactive modeling required by tissue engineering applications.This paper aims to bridge these two approaches and develop a set of mathematical tools and algorithms for feature-based representation and computer-aided modeling of vascular trees for use in computer-aided tissue engineering applications. The paper offers a multi-scale representation based on swept volumes and a feature-based representation that can attribute the geometric representation with information about blood flow, pressure, and other biomedical properties. The paper shows how the resulting representation can be used as part of an overall approach for designing and visualizing vascular scaffolds. As a real-world example, we show how this computational model can be used to develop a tissue scaffold for liver tissue engineering. Such scaffolds may prove useful in a number of biomedical applications, including the growth of replacement tissue grafts and in vitro study of the pharmacological affects of new drugs on tissue cultures.     

Characteristics of Schottky Barrier Junction Based on Hexagonal Microtube ZnO

Hexagonal microtube ZnO was firstly grown on single crystal p-Si (111) substrates by hydrothermal method, and fabricated Ag/n-ZnO and Au/n-ZnO Schottky junction. Schottky effective barrier heights were calculated by I-V measurement. It is confirmed that the presence of a large amount of surface states related possibly to lattice imperfections existed near the surface leads to the pinning of the surface Fermi level at 0.35 eV below the conduction-band edge. Then the fabricated Schottky barrier junctions are evaluated for their use as UV photodetectors.     

计算机生成兵力中的人工智能技术

开发CGF的难点和重点在于CGF实体行为的生成,尤其是人类智能行为的实现。人类行为建模最重要的三个方面是知识获取、知识表示和决策机制,都与人工智能技术相关。该文主要介绍人类行为描述的知识表示和知识获取问题,讨论了人工智能技术在这两个方面的应用,并对将来的研究工作做了一个简单的展望。     

Conforming spectral methods for Poisson problems in cuboidal domains

A Chebyshev collocation strategy is introduced for the subdivision of cuboids into cuboidal subdomains (elements). These elements are conforming, which means that the approximation to the solution isC ⁰ continuous at all points across their interfaces.     

Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.