Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) Descriptor for Iris Liveness Detection

Wireless Personal Communications - Biometric traits are frequently used by security agencies for automatic recognition of a person. There are numerous biometric traits used for person...     

Effects of strain on the high speed modulation of GaAs- andInP-based quantum-well lasers

A small-signal numerical analysis of pseudomorphic GaAs- and InP-based Fabry-Perot quantum-well lasers using calculated optical gain spectra with strain effects included is reported. Examination of the effect of lifetime broadening shows that the resonance frequency increases at a rate of ~250-MHz/meV reduction in the lifetime broadening for a GaAs-based strained layer laser. The modulation speed is limited by either device heating or facet damage. If the limitation is imposed by the optical power then the modulation speed increases as the laser cavity becomes shorter and the number of quantum wells increases. If the limitation is imposed by the injection current density, however, then the modulation speed decreases for the laser with shorter cavity length. The highest modulation speed is given by an optimum well number. A resonance frequency of ~16 GHz is predicted for a pseudomorphic GaAs-based laser with 30% excess In and average output power of ~5 mW     

Shrunken estimators of Weibull shape parameter from type-IIcensored samples

A shrunken estimator of the Weibull shape parameter for failure censored samples is suggested. This shrunken estimator is compared with shrunken estimators previously given. Even for sample sizes of five and ten this shrunken estimator, based on failure data censored at only three and four, respectively, can be used with advantage when one has a reasonable guess for the shape parameter. This estimator has higher efficiency and nearness than other estimators     

Learning-based ventricle detection from cardiac MR and CT images

The objective of this work is to investigate the issue of automatically detecting regions of interest (ROI's) in medical images. It is assumed that the regions to be detected can be roughly segmented by a threshold based on a likelihood measure of the ROI, First, an analysis of the global histogram is used to compute a preliminary threshold that is likely near the optimal one. The histogram analysis is motivated by the analytical result of a bell image intensity model proposed in this work. Then, the preliminary threshold is used to segment the input image, resulting in an attention map, which contains an attention region that approximates the ROI as well as many spurious ones. Due to the nonoptimality of the preliminary threshold, it can happen that the attention region contains a part of, or more regions than, the ROI. Learning takes place in two stages: (1) learning for automatic selection of the preliminary threshold value and (2) learning for automatically selecting the ROI from the attention map while dynamically tuning the threshold according to the learned-likelihood function. Experiments have been conducted to approximately locate the endocardium boundaries of the left and right ventricles from gradient-echo magnetic resonance (MR) images. Cardiac computed tomography (CT) images have also been used for testing. The boundary of the segmented region provided by this algorithm is not very accurate and is meant to be used for further fine tuning based on other application-specific measures     

A fault-tolerant protocol for election in chordal-ring networkswith fail-stop processor failures

In a distributed computer system, a group of processors is connected by communication links into a network. Each processor (node) of the network has an identity (a unique integer value) that is not related to its position in the network (its address). A processor's identity is known only to the processor. In the problem of leader election, exactly one processor among a network of processors has to be distinguished as the leader. Previously, many efficient election protocols have been proposed for networks with a sense of direction. In particular, the sequential search is used for election in a reliable complete network, and a multi-token search method is used in a faulty complete network. However, election protocols on a faulty ChRgN (chordal ring network) have not been investigated by other researchers. This paper addresses this issue by: studying the problem of leader election in an asynchronous ChRgN with a sense of direction and with the presence of undetectable fail-stop processor failures; proposing a new election protocol which (a) combines the concept of sequential search and multi-token search techniques, and (b) uses an efficient routing algorithm to reduce the total number of messages used; presenting a protocol for a ChRgN of n processors with I chords/processor and at most f fail-stop faulty processors, with message complexity O(n+(n/l)log(n)+k·f), where k is the number of processors starting the election process spontaneously and at most f相似文献   

On estimation of population mean using known coefficient of variation

For the estimation of population mean, a generalized class of estimators using known coefficient of variation C_y of the study variable y is proposed, its bias and mean square error (MSE) are found and its comparative study with the usual mean per unit estimator has been done. As an illustration, an empirical study is also included.     

First-Principles Investigation of Electronic Properties of GaAsxSb1 –x Ternary Alloys

Semiconductors - Compositional variations in GaAs based ternary alloys have exhibited wide range alterations in electronic properties. In the present paper, first-principles study of...     

Generating optimal adaptive fuzzy-neural models of dynamicalsystems with applications to control

The paper describes an approach to generating optimal adaptive fuzzy neural models from I/O data. This approach combines structure and parameter identification of Takagi-Sugeno-Kang (TSK) fuzzy models. We propose to achieve structure determination via a combination of modified mountain clustering (MMC) algorithm, recursive least squares estimation (RLSE), and group method of data handling (GMDH). Parameter adjustment is achieved by training the initial TSK model using the algorithm of an adaptive network based fuzzy inference system (ANFIS), which employs backpropagation (BP) and RLSE. Further, a procedure for generating locally optimal model structures is suggested. The structure optimization procedure is composed of two phases: 1) locally optimal rule premise variables subsets (LOPVS) are identified using MMC, GMDH, and a search tree (ST); and 2) locally optimal numbers of model rules (LONOR) are determined using MMC/RLSE along with parallel simulation mean square error (PSMSE) as a performance index. The effectiveness of the proposed approach is verified by a variety of simulation examples. The examples include modeling of a nonlinear dynamical process from I/O data and modeling nonlinear components of dynamical plants, followed by tracking control based on a model reference adaptive scheme (MRAC). Simulation results show that this approach is fast and accurate and leads to several optimal models     

A novel technique for RTP annealing of compound semiconductors

We introduce for the first time a novel rapid thermal processing (RTP) unit called Zapper™, which has recently been developed by MHI Inc. and the University of Florida, for high temperature thermal processing of semiconductors. This Zapper™ unit is capable of reaching much highertemperatures (>1500°C) than conventional tungsten–halogen lamp RTP equipment and achievinghigh ramp-up and ramp-down rates. We have conducted implant activation annealing studies ofSi⁺-implanted GaN thin films (with and without an AlN encapsulation layer) using the Zapper™ unit at temperatures up to 1500°C. The electrical property measurements of such annealed samples have led to the conclusion that high annealing temperatures and AlN encapsulation are needed for the optimum activation efficiency of Si⁺ implants in GaN. It has clearly been demonstrated that the Zapper™ unit has tremendous potential for RTP annealing of semiconductor materials, especially for wide band-gap (WBG) compound semiconductors that require very high processing temperatures.     

Transient plasma shielding effects during pulsed laser ablation of materials

The absorption of laser energy by the plasma during pulsed laser deposition of thin films has been analyzed theoretically. The amount of laser energy absorbed in the plasma termed as the “plasma shielding factor” is a function of the incident laser wavelength, and time dependent plasma dimensions and electron density. Due to time varying parameters, a quantitative analysis of the plasma absorption is difficult. A model which takes into account the absorption of laser energy by the plasma has been developed. In this model, the time-dependent plasma dimension is replaced by the time dependent ablation depth. Using simulated absorption coefficient values, the ablation characteristics of silicon and high T_c superconductors are computed and compared with experimental results. The plasma shielding factor was found to vary approximately linearly with absorbed laser energy. The calculations also showed that the plasma shielding was strongly dependent on the laser fluence but varies very weakly with the simulated plasma absorption coefficient values. Experimental results on plume shielding showed good agreement with the calculations.