Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks

This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.Comment: in Ictact Journal On Communication Technology: Special Issue On Next Generation Wireless Networks And Applications, June 2011, Volume 2, Issue 2, Issn: 2229-6948(Online

Approximations of density matrices in N-electron valence state second-order perturbation theory (NEVPT2). II. The full rank NEVPT2 (FR-NEVPT2) formulation

In Paper I, the performances of pre-screening (PS), extended PS (EPS), and cumulant (CU) approximations to the fourth-order density matrix were examined in the context of second-order N-electron valence state perturbation theory (NEVPT2). It has been found that the CU, PS, and even EPS approximations with loose thresholds may introduce intruder states. In the present work, the origin of these “false intruder” states introduced by approximated density matrices is discussed. Canonical NEVPT2 implementations employ a rank reduction trick. By analyzing its residual error, we find that the omission of the rank reduction leads to a more stable multireference perturbation theory for incomplete active space reference wave functions. Such a full rank (FR)-NEVPT2 formulation is equivalent to the conventional NEVPT2 method for the complete active space self-consistent field/complete active space configuration interaction reference wave function. A major drawback of the FR-NEVPT2 formulation is the necessity of the fifth-order density matrix. To avoid the construction of the high-order density matrices, the combination of the FR-NEVPT2 with the CU approximation is studied. However, we find that the CU approximation remains problematic as it still introduces intruder states. The question of how to robustly and efficiently perform internally contracted multireference perturbation theories with approximate densities remains a challenging field of investigation

An efficient implementation of the NEVPT2 and CASPT2 methods avoiding higher-order density matrices

A factorization of the matrix elements of the Dyall Hamiltonian in N-electron valence state perturbation theory allowing their evaluation with a computational effort comparable to the one needed for the construction of the third-order reduced density matrix at the most is presented. Thus, the computational bottleneck arising from explicit evaluation of the fourth-order density matrix is avoided. It is also shown that the residual terms arising in the case of an approximate complete active space configuration interaction solution and containing even the fifth-order density matrix for two excitation classes can be evaluated with little additional effort by choosing again a favorable factorization of the corresponding matrix elements. An analogous argument is also provided for avoiding the fourth-order density matrix in complete active space second-order perturbation theory. Practical calculations indicate that such an approach leads to a considerable gain in computational efficiency without any compromise in numerical accuracy or stability

Drift Correction in a Porphyrin-coated ZnO Nanorods Gas Sensor

AbstractPhotoconductivity and gas sensitivity cooperate in porphyrins coated ZnO nanostructures. However, in organic coated semiconductors the former is regulated by a number of mechanisms, involving the charge transfer in the organic layer. Since organic layers are poor conductors these processes are quite slow and the sensor may exhibits a long time drift before to be operative as gas sensor. In this paper we show that under light modulation, the carrier frequency component of the signal is free of drift and it can readily indicate the interaction with volatile compounds

Gas Sensitivity of the Surface Potential of Hybrid Porphyrin-ZnO Nanorods

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Monocarboxy Tetraphenylporphyrin functionalized ZnO nanorods photoactivated gas sensor

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The Gas Sensing Properties of Porphyrins-coated Laterally Grown ZnO Nanorods

AbstractPorphyrins coated ZnO is an interesting material where the exposure to light and gas may cooperate to modulate the respective sensitivities. In this work, the gas sensing properties of porphyrins functionalized laterally grown ZnO nanorods are introduced. The porphyrin layer incompletely coats the semiconductor surface in order to keep both ZnO and porphyrins in contact with analyte. It is known that UV light may prompt the chemical sensitivity of ZnO replacing the high temperature condition. Here we demonstrate that because of the photo-injection of electrons from porphyrin to the ZnO, the same impact could be acquired with visible light

Riemannian Sparse Coding for Positive Definite Matrices

International audienceInspired by the great success of sparse coding for vector valued data, our goal is to represent symmetric positive definite (SPD) data matrices as sparse linear combinations of atoms from a dictionary, where each atom itself is an SPD matrix. Since SPD matrices follow a non-Euclidean (in fact a Riemannian) geometry, existing sparse coding techniques for Euclidean data cannot be directly extended. Prior works have approached this problem by defining a sparse coding loss function using either extrinsic similarity measures (such as the log-Euclidean distance) or kernelized variants of statistical measures (such as the Stein divergence, Jeffrey's divergence, etc.). In contrast, we propose to use the intrinsic Riemannian distance on the manifold of SPD matrices. Our main contribution is a novel mathematical model for sparse coding of SPD matrices; we also present a computationally simple algorithm for optimizing our model. Experiments on several computer vision datasets showcase superior classification and retrieval performance compared with state-of-the-art approaches

Areawise and gearwise production of cephalopods

The coasts of the maritime states of India have been divided into subareas and the annual and seasonal trends of the areawise and gearwise landings of cephalopods and CPUE have been studied in detail