An adaptive multimodal biometric management algorithm

This paper presents an evolutionary approach to the sensor management of a biometric security system that improves robustness. Multiple biometrics are fused at the decision level to support a system that can meet more challenging and varying accuracy requirements as well as address user needs such as ease of use and universality better than a single biometric system or static multimodal biometric system. The decision fusion rules are adapted to meet the varying system needs by particle swarm optimization, which is an evolutionary algorithm. This paper focuses on the details of this new sensor management algorithm and demonstrates its effectiveness. The evolutionary nature of adaptive, multimodal biometric management (AMBM) allows it to react in pseudoreal time to changing security needs as well as user needs. Error weights are modified to reflect the security and user needs of the system. The AMBM algorithm selects the fusion rule and sensor operating points to optimize system performance in terms of accuracy.     

An image change detection algorithm based on Markov random field models

This paper addresses the problem of image change detection (ICD) based on Markov random field (MRF) models. MRF has long been recognized as an accurate model to describe a variety of image characteristics. Here, we use the MRF to model both noiseless images obtained from the actual scene and change images (CIs), the sites of which indicate changes between a pair of observed images. The optimum ICD algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Examples are presented for illustration and performance evaluation.     

An equicorrelation-based multiuser communication scheme for DS-CDMA systems

An equicorrelation-based multiuser communication (ECBMC) scheme for direct-sequence code-division multiple-access (DS-CDMA) systems is presented. The ECBMC receiver has low computational complexity that is comparable to that of the conventional detector. By using the equality of cross correlations, the ECBMC scheme can completely eliminate multiple-access interference (MAI) in a synchronous single-path DS-CDMA network. The system performance is independent of the number of active users. The scheme is extended to include the effects of multipath fading. It is able to suppress a major portion of the MAI. This proposed ECBMC scheme is quite attractive for an MAI-dominant environment.     

Further results on distributed Bayesian signal detection

The problem of distributed Bayesian signal detection is addressed. The problem is reformulated and a new design approach is presented that allows the use of efficient optimization algorithms     

Explanation of Temperature-Dependent Resistivity of Sm-Doped Cuprates by Electron–Phonon Scattering

The resistivity of electron-doped cuprate Sm_1.85Ce_0.15CuO_{4 –} is theoretically analyzed within the framework of electron–phonon i.e., Bloch–Gruneisen (BG) model of resistivity. Characteristic temperatures as the Debye temperature and the Einstein temperature were first derived from an overlap repulsive potential. The optical phonons of the oxygen-breathing mode yield a relatively larger contribution to the resistivity compared to the contribution of acoustic phonons above 220 K. While to that, below this temperature, acoustic phonon is a major cause of resistivity. Estimated contribution to resistivity by considering both phonons i.e., _ac (acoustic phonons) and _op (optical phonons), along with the zero limited resistivity, when subtracted from single crystal data, infers a quadratic temperature dependence over most of the temperature range (25 T 300). Power temperature dependence of _diff.{=[ _exp. – ( ₀ + _e-ph(= _ac + _op))]} points the contribution of electron–electron inelastic scattering. The present analysis allows us to infer that the single crystal experimental data is well approximated within the framework of BG electron–phonon model of resistivity. Further calculations of superconducting transition temperature and isotope effect exponent from Kresin's strong coupling theory indicates that the electron–phonon interaction plays an important role in the attractive pairing mechanism.     

Channel aware decision fusion in wireless sensor networks

Information fusion by utilizing multiple distributed sensors is studied in this work. Extending the classical parallel fusion structure by incorporating the fading channel layer that is omnipresent in wireless sensor networks, we derive the likelihood ratio based fusion rule given fixed local decision devices. This optimum fusion rule, however, requires perfect knowledge of the local decision performance indices as well as the fading channel. To address this issue, two alternative fusion schemes, namely, the maximum ratio combining statistic and a two-stage approach using the Chair-Varshney fusion rule, are proposed that alleviate these requirements and are shown to be the low and high signal-to-noise ratio (SNR) equivalents of the likelihood-based fusion rule. To further robustify the fusion rule and motivated by the maximum ratio combining statistics, we also propose a statistic analogous to an equal gain combiner that requires minimum a priori information. Performance evaluation is performed both analytically and through simulation.     

An experimental facility for determination of steady flame spread rate of materials employing the Quasi-stationary flame front technique

An experimental facility based on the Quasi-stationary Flame Front Technique for determination of steady flame spread rate of materials at discrete levels of external radiant heat flux was developed. The method employs an external radiant heat source in front of which an element of a specimen of the material is positioned at a location corresponding to the desired level of external radiant heat flux. A specimen movement assembly, which can be operated manually, was designed for moving the specimen towards the stationary external radiant heat source such that the flame front could be maintained quasi-stationary. The experimental technique employed is simple in operation yet is capable of yielding reliable flame fornt displacement–time data. In the paper the design considerations of the experimental facility, details of its components, calibration and typical experimental results obtained are presented.     

Decentralized Bayesian detection with feedback

A decentralized detection system with feedback and memory using the Bayesian formulation is investigated. The optimization of this system results in a likelihood ratio test at the local detectors for statistically independent observations. In addition, local detector thresholds and the system probability of error are shown to be a function of the fed back global decision. The issue of data transmission between local detectors and the fusion center is addressed. Two protocols are proposed and studied to reduce data transmissions. Numerical examples are also presented for illustration     

CO2 laser annealing of plasma-deposited high-T c superconducting thick films

Recent advances in the fabrication of high-T _c superconducting thick films demand processing techniques which can eliminate film/substrate interdifiusion that occurs during subsequent post-annealing heat treatment after the film is deposited, thereby limiting the application of the thick films for devices. The present study evaluates laser annealing techniques for plasma-deposited Y-Ba-Cu-O thick films using a high-energy CO₂ laser (10.6Μm) in a continuous wave mode. The results are compared with those obtained by conventional furnace annealing techniques necessary for post-heat treatment of as-deposited superconducting thick films. The high-T _c superconducting phase is recovered by cationic diffusion during subsequent post-annealing heat treatment. Crystallographic phases and microstructural characterization have been performed using XRD, SEM, and EPMA analytical techniques. The significance of the technology lies in the elimination of film/substrate interdiffusion problems, thereby resulting in high-quality superconducting thick films. The technology will significantly reduce the post-annealing times usually required by conventional furnace annealing techniques.     

An efficient and scalable parallel algorithm for out-of-core isosurface extraction and rendering

We consider the problem of isosurface extraction and rendering for large scale time-varying data. Such data sets have been appearing at an increasing rate especially from physics-based simulations, and can range in size from hundreds of gigabytes to tens of terabytes. Isosurface extraction and rendering is one of the most widely used visualization techniques to explore and analyze such data sets. A common strategy for isosurface extraction involves the determination of the so-called active cells followed by a triangulation of these cells based on linear interpolation, and ending with a rendering of the triangular mesh. We develop a new simple indexing scheme for out-of-core processing of large scale data sets, which enables the identification of the active cells extremely quickly, using more compact indexing structure and more effective bulk data movement than previous schemes. Moreover, our scheme leads to an efficient and scalable implementation on multiprocessor environments in which each processor has access to its own local disk. In particular, our parallel algorithm provably achieves load balancing across the processors independent of the isovalue, with almost no overhead in the total amount of work relative to the sequential algorithm. We conduct a large number of experimental tests on the University of Maryland Visualization Cluster using the Richtmyer–Meshkov instability data set, and obtain results that consistently validate the efficiency and the scalability of our algorithm.