A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.

High Resoulution Electron Microscopy of Chloritoid Minerals From Different Geological Melieu

Structural defects of three chloritoid minerals from distinet geologic melieu have been investigated by high resolution electron microscopy. X-ray powder and electron diffraction patterns indicate that the chloritoid from one geological source (A) is2M 1+2M2 monoclinic variant while those from another geological source (B) are 2M 2 monoclinic variants. In a typical one-dimensional lattice image of a crystal from sourceA, the 2M 2 matrix is broken by insertion of triclinic inter-growths. Another crystal with the 2M 2 matrix showed single, triple, quadruple and quintuple layers displaying an unusually high degree of disorder. Lattice images of 2M 2 monoclinic variants from sourceB yielded more homogeneous micrographs. The important finding from the present studies is that the chloritoid from sourceA is a severely disordered low-temperature intermediate phase in the conversion of the triclinic chloritoid to the high-temperature ordered monoclinic variants of sourceB. Severely disordered chloritoids, marking the beginning of low grade metamorphism, are generated as intermediates between the state of complete disordered arrangement towards the end of low grade metamorphism within the narrow stability range of 400°–500°C.

High On-Off Ratio Bilayer Graphene Complementary Field Effect Transistors

In this paper, we propose a novel S/D engineering for dual-gated Bilayer Graphene (BLG) Field Effect Transistor (FET) using doped semiconductors (with a bandgap) as source and drain to obtain unipolar complementary transistors. To simulate the device, a self-consistent Non-Equilibrium Green's Function (NEGF) solver has been developed and validated against published experimental data. Using the simulator, we predict an on-off ratio in excess of 10(4) and a subthreshold slope of similar to 110mV/decade with excellent scalability and current saturation, for a 20nm gate length unipolar BLG FET. However, the performance of the proposed device is found to be strongly dependent on the S/D series resistance effect. The obtained results show significant improvements over existing reports, marking an important step towards bilayer graphene logic devices.

Efficient method of moving shadow detection and vehicle classification

Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.