Growth and characterization of single crystal cored fibers of organic nonlinear optical materials

The recent development of several organic materials with large nonlinear susceptibilities, high damage threshold and low melting points encouraged researchers to employ these materials in fiber form to efficiently couple diode laser pumps and obtain enhanced second harmonic generation (SHG). In this paper we report the growth of single crystal cored fibers of 4-nitro-4'-methylbenzylidene aniline, ethoxy methoxy chalcone and (-)2-((alpha) -methylbenzylamino)-5- nitropyridine by inverted Bridgman-Stockbarger technique. The fibers were grown in glass capillaries with varying internal diameters and lengths and were characterized using x-ray and polarizing microscope techniques. The propagation loss at 632.8 nm and 1300 nm were measured and SHG was studied using 1064 nm pump.

Dielectric function and optical conductivity of TiOx (0.8loss spectroscopy

Reflection electron energy-loss spectra are reported for the family of compounds TiOx over the entire homogeneity range (0.8 < a: < 1.3). The spectra exhibit a plasmon feature on the low-energy side, while several interband transitions are prominent at higher energies. The real and imaginary parts of dielectric functions and optical conductivity for these compounds are determined using the Kramers-Kronig analysis. The results exhibit systematic behavior with varying oxygen stoichiometry.

WLS method for parameter estimation in water distribution networks

The weighted-least-squares method based on the Gauss-Newton minimization technique is used for parameter estimation in water distribution networks. The parameters considered are: element resistances (single and/or group resistances, Hazen-Williams coefficients, pump specifications) and consumptions (for single or multiple loading conditions). The measurements considered are: nodal pressure heads, pipe flows, head loss in pipes, and consumptions/inflows. An important feature of the study is a detailed consideration of the influence of different choice of weights on parameter estimation, for error-free data, noisy data, and noisy data which include bad data. The method is applied to three different networks including a real-life problem.

Nonresonant microwave absorption studies of surface passivation of superconducting YBa2Cu3O7−δ thin films

The surfaces of laser ablated thin films of YBa2Cu3O7?? have been passivated with about 100 Å thick textured layer of Ca0.95Sr0.025Ba0.025Zr0.98Ta0.01Ti0.01O3. It is shown that this low loss dielectric material preserves the quality of the surface and also prolongs the aging process. The films (both passivated and as?deposited) have been studied for degradation on exposure to atmosphere and also on dipping directly in water. The technique of nonresonant microwave absorption is used to study the effects and extent of degradation in these films. © 1995 American Institute of Physics.

A fault-tolerant distributed deadlock detection algorithm

In this paper, we propose a new fault-tolerant distributed deadlock detection algorithm which can handle loss of any resource release message. It is based on a token-based distributed mutual exclusion algorithm. We have evaluated and compared the performance of the proposed algorithm with two other algorithms which belong to two different classes, using simulation studies. The proposed algorithm is found to be efficient in terms of average number of messages per wait and average deadlock duration compared to the other two algorithms in all situations, and has comparable or better performance in terms of other parameters.

A game theoretical multiple resource interaction approach to resource allocation in an air campaign

In this paper we propose a multiple resource interaction model in a game-theoretical framework to solve resource allocation problems in theater level military campaigns. An air raid campaign using SEAD aircraft and bombers against an enemy target defended by air defense units is considered as the basic platform. Conditions for the existence of saddle point in pure strategies is proved and explicit feedback strategies are obtained for a simplified model with linear attrition function limited by resource availability. An illustrative example demonstrates the key features.

Constraint loss under dynamic loading in rate independent plastic solids

The objectives of this paper are to examine the loss of crack tip constraint in dynamically loaded fracture specimens and to assess whether it can lead to enhancement in the fracture toughness at high loading rates which has been observed in several experimental studies. To this end, 2-D plane strain finite element analyses of single edge notched (tension) specimen and three point bend specimen subjected to time varying loads are performed. The material is assumed to obey the small strain J(2) flow theory of plasticity with rate independent behaviour. The results demonstrate that a valid J-Q field exists under dynamic loading irrespective of the crack length and specimen geometry. Further, the constraint parameter Q becomes strongly negative at high loading rates, particularly in deeply cracked specimens. The variation of dynamic fracture toughness K-dc with stress intensity rate K for cleavage cracking is predicted using a simple critical stress criterion. It is found that inertia-driven constraint loss can substantially enhance K-dc for (K) over dot > 10(5) MPa rootm/s.

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

In this paper we consider the problem of learning an n × n kernel matrix from m(1) similarity matrices under general convex loss. Past research have extensively studied the m = 1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc. The existing algorithms do not apply if one uses arbitrary losses and often can not handle m > 1 case. We present several provably convergent iterative algorithms, where each iteration requires either an SVM or a Multiple Kernel Learning (MKL) solver for m > 1 case. One of the major contributions of the paper is to extend the well knownMirror Descent(MD) framework to handle Cartesian product of psd matrices. This novel extension leads to an algorithm, called EMKL, which solves the problem in O(m2 log n 2) iterations; in each iteration one solves an MKL involving m kernels and m eigen-decomposition of n × n matrices. By suitably defining a restriction on the objective function, a faster version of EMKL is proposed, called REKL,which avoids the eigen-decomposition. An alternative to both EMKL and REKL is also suggested which requires only an SVMsolver. Experimental results on real world protein data set involving several similarity matrices illustrate the efficacy of the proposed algorithms.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

The role of sustainable agriculture and renewable-resource management in reducing greenhouse-gas emissions and increasing sinks in China and India

This paper contains an analysis of the technical options in agriculture for reducing greenhouse-gas emissions and increasing sinks, arising from three distinct mechanisms: (i) increasing carbon sinks in soil organic matter and above-ground biomass; (ii) avoiding carbon emissions from farms by reducing direct and indirect energy use; and (iii) increasing renewable-energy production from biomass that either substitutes for consumption of fossil fuels or replaces inefficient burning of fuelwood or crop residues, and so avoids carbon emissions, together with use of biogas digesters and improved cookstoves. We then review best-practice sustainable agriculture and renewable-resource-management projects and initiatives in China and India, and analyse the annual net sinks being created by these projects, and the potential market value of the carbon sequestered. We conclude with a summary of the policy and institutional conditions and reforms required for adoption of best sustainability practice in the agricultural sector to achieve the desired reductions in emissions and increases in sinks. A review of 40 sustainable agriculture and renewable-resource-management projects in China and India under the three mechanisms estimated a carbon mitigation potential of 64.8 MtC yr(-1) from 5.5 Mha. The potential income for carbon mitigation is $324 million at $5 per tonne of carbon. The potential exists to increase this by orders of magnitude, and so contribute significantly to greenhouse-gas abatement. Most agricultural mitigation options also provide several ancillary benefits. However, there are many technical, financial, policy, legal and institutional barriers to overcome.