Genetic search: Analysis using fitness moments

Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of applications with extremely large search spaces. The directed search mechanism employed in Genetic Algorithms performs a simultaneous and balanced, exploration of new regions in the search space and exploitation of already discovered regions.This paper introduces the notion of fitness moments for analyzing the working of Genetic Algorithms (GAs). We show that the fitness moments in any generation may be predicted from those of the initial population. Since a knowledge of the fitness moments allows us to estimate the fitness distribution of strings, this approach provides for a method of characterizing the dynamics of GAs. In particular the average fitness and fitness variance of the population in any generation may be predicted. We introduce the technique of fitness-based disruption of solutions for improving the performance of GAs. Using fitness moments, we demonstrate the advantages of using fitness-based disruption. We also present experimental results comparing the performance of a standard GA and GAs (CDGA and AGA) that incorporate the principle of fitness-based disruption. The experimental evidence clearly demonstrates the power of fitness based disruption.

Image analysis using multifractals

The efficacy of the multifractal spectrum as a tool for characterizing images has been studied. This spectrum has been computed for digitized images of the nucleus of human cervical cancer cells and it was observed that the entire spectrum is almost fully reproduced for a normal cell while only the right half (q<0) of the spectrum is reproduced for a cancerous cell. Cells in stages in between the two extremes show a shortening of the left half of the spectrum proportional to their condition. The extent of this shortening has been found to be sufficient to permit a classification between three classes of cells at varying distances from a basal cancerous layer-the superficial cells, the intermediate cells and the parabasal cells. This technique may be used for automatic screening of the population while also indicating the stage of malignancy

Preparation, Characterization And Properties Of C-60 And C-70 - Spectroscopy, Structure, Anions, Interaction With Electron-Donors And Superconductivity

Preparation and characterization of the fullerenes, C60 and C70, are described in detail, including the design of the generators fabricated locally. The characterization techniques employed are UV-visible, IR, Raman and C-13 NMR spectroscopies, scanning as well as transmission electron microscopy and mass spectrometry. The electron energy level diagram of C60 as well as the one-electron reductions of C60 and C70 leading to various anions are discussed. Electronic absorption spectra of C60- and C60(2-) are reported. Phase transitions from the plastic to the crystalline states of C60 and C70 are examined. Based on a C-13 NMR study in a mixture of nematic liquid crystals, it has been demonstrated that C60 retains its extraordinary symmetry in solution phase as well. Interaction of C60 and C70 with strong electron-donor molecules has been investigated employing cyclic voltammetry. Superconductivity of K(x)C60 has been studied by non-resonant microwave absorption; Na(x)C60 as well as K(c)C70 are shown to be non-superconducting. Doping C60 with iodine does not make it superconducting. Interaction of C60 with SbCl5 and liquid Br2 gives rise to halogenated products.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Spatial distribution of oil in groundnut and sunflower seeds by nuclear magnetic resonance imaging

The nuclear magnetic resonance imaging technique has been used to obtain images of different transverse and vertical sections in groundnut and sunflower seeds. Separate images have been obtained for oil and water components in the seeds. The spatial distribution of oil and water inside the seed has been obtained from the detailed analysis of the images. In the immature groundnut seeds obtained commercially, complementary oil and water distributions have been observed. Attempts have been made to explain these results.

Reflectivity and photoluminescence spectra of GaAs quantum wells in a magnetic field

We present photoluminescence and reflectance spectra of GaAs/Al-x Ga-1-x As quantum wells in a magnetic field for the Faraday geometry. The photoluminescence peaks recorded are among the most intense and narrow reported to date. This has allowed us to study the behavior of closely spaced bound exciton lines under a magnetic field. Several new features including magnetic field induced splitting of the bound exciton emission peaks are reported.

Weak molecular complexes as studied by NMR spectroscopy of oriented molecules

Weak molecular interactions such as those in pyridine-iodine, benzene-iodine and benzene-chloroform systems oriented in thermotropic liquid crystals have been studied from the changes of the order parameters as a result of complex formation. The results indicate the formation of at least two types of charge transfer complexes in pyridine-iodine solutions. The pi-complexes in benzene-chloroform and benzene-iodine mixtures have also been detected. No detectable changes in the inter-proton distances in these systems were observed.

Highly Efficient and Thermally Stable Second-Order Nonlinear Optical Chromophores and Electrooptic Polymers

Organic polymeric electro-optic (E-O) materials have attracted significant attention because of their potential use as fast and efficient components of integrated photonic devices (1,2). However, the practical application of these materials in optical devices is somewhat limited by the stringent material requirements imposed by the device design, fabrication processes and operating environments. Among the various material requirements, the most notable ones are large electro-optic coefficients (r(33)) and high thermal stability (3). The design of poled polymeric materials with high electro-optic activity (r(33)) involves the optimization of the percent incorporation of efficient (large beta mu) second order nonlinear optical (NLO) chromophores into the polymer matrices and the effective creation of poling-induced non-centrosymmetric structures. The factors that affect the material stability are a) the inherent thermal stability of the NLO chromophores, b) the chemical stability of the NLO chromophores during the polymer processing conditions, and c) the long-term dipolar alignment stability at high temperatures. Although considerable progress has been made in achieving these properties (4), organic polymeric materials suitable for practical E-O device applications are yet to be developed. This chapter highlights some of our approaches in the optimization of molecular and material nonlinear optical and thermal properties.

Liquid phase epitaxial growth of pure and doped GaSb layers: morphological evolution and native defects

Undoped and Te-doped gallium antimonide (GaSb) layers have been grown on GaSb bulk substrates by the liquid phase epitaxial technique from Ga-rich and Sb-rich melts. The nucleation morphology of the grown layers has been studied as a function of growth temperature and substrate orientation. MOS structures have been fabricated on the epilayers to evaluate the native defect content in the grown layers from the C-V characteristics. Layers grown from antimony rich melts always exhibit p-type conductivity. In contrast, a type conversion from p- to n- was observed in layers grown from gallium rich melts below 400 degrees C. The electron mobility of undoped n-type layers grown from Ga-rich melts and tellurium doped layers grown from Sb- and Ga-rich solutions has been evaluated.

New open-framework phosphate and phosphite compounds of gallium

Five new open-framework compounds of gallium have been synthesized by hydrothermal methods and their structures determined by single crystal X-ray diffraction studies. The compounds, C8N4H26]Ga6F4(PO4)(6)], I, C5N3H11]Ga3F2(PO4)(3)]center dot H2O, II, C6N3H19]Ga-4(C2O4)(PO4)(4)(H2PO4)]center dot 2H(2)O, III, Ga2F3(HPO4)(PO4)]center dot 2H(3)O, IV, and C3N2H5](2)Ga-4(H2O)(3)(HPO3)(7)], V, possess three-dimensional structures. All the compounds are formed by the connectivity between the Ga polyhedra and phosphite/phosphate units. The observation of SBU-6 (I and II) and spiro-5 (IV) secondary building units (SBUs) are noteworthy. The flexibility of the formation of gallium phosphate frameworks has been established by the isolation of two related structures (I and II) from the same SBU units but different organic amines. Some of the present structures have close resemblance to the gallium phosphate phases known earlier. The compounds have been characterized by CHN analysis, powder XRD, IR, and TGA. (C) 2011 Elsevier B. V. All rights reserved.

On an exact populationary model of genetic algorithms

Genetic algorithms (GAs) are search methods that are being employed in a multitude of applications with extremely large search spaces. Recently, there has been considerable interest among GA researchers in understanding and formalizing the working of GAs. In an earlier paper, we have introduced the notion of binomially distributed populations as the central idea behind an exact ''populationary'' model of the large-population dynamics of the GA operators for objective functions called ''functions of unitation.'' In this paper, we extend this populationary model of GA dynamics to a more general class of objective functions called functions of unitation variables. We generalize the notion of a binomially distributed population to a generalized binomially distributed population (GBDP). We show that the effects of selection, crossover, and mutation can be exactly modelled after decomposing the population into GBDPs. Based on this generalized model, we have implemented a GA simulator for functions of two unitation variables-GASIM 2, and the distributions predicted by GASIM 2 match with those obtained from actual GA runs. The generalized populationary model of GA dynamics not only presents a novel and natural way of interpreting the workings of GAs with large populations, but it also provides for an efficient implementation of the model as a GA simulator. (C) Elsevier Science Inc. 1997.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Improved large-MIMO detection based on damped belief propagation

In this paper, we consider the application of belief propagation (BP) to achieve near-optimal signal detection in large multiple-input multiple-output (MIMO) systems at low complexities. Large-MIMO architectures based on spatial multiplexing (V-BLAST) as well as non-orthogonal space-time block codes(STBC) from cyclic division algebra (CDA) are considered. We adopt graphical models based on Markov random fields (MRF) and factor graphs (FG). In the MRF based approach, we use pairwise compatibility functions although the graphical models of MIMO systems are fully/densely connected. In the FG approach, we employ a Gaussian approximation (GA) of the multi-antenna interference, which significantly reduces the complexity while achieving very good performance for large dimensions. We show that i) both MRF and FG based BP approaches exhibit large-system behavior, where increasingly closer to optimal performance is achieved with increasing number of dimensions, and ii) damping of messages/beliefs significantly improves the bit error performance.

Half-sandwich (eta(6)-arene)ruthenium(II) chiral Schiff base complexes: Analysis of the diastereomeric mixtures in solution by 2D-NMR spectroscopy

2D NMR spectroscopy has been used to determine the metal configuration in solution of three complexes, viz. [(eta(6)-p-cymene)Ru(L*)Cl] (1) and [(eta(6)-p-cymene)Ru(L*)(L')] (ClO4) (L' = H2O, 2; PPh3, 3), where L* is the anion of (S)-(1-phenylethyl)salicylaldimine. The complexes exist in two diastereomeric forms in solution. Both the (R-Ru,S-C)- and (S-Ru,S-C)-diastereomers display the presence of attractive, CH/pi interaction involving the phenyl group attached to the chiral carbon and the cymene ring hydrogens. This interaction restricts the rotation of the C*-N single bond and, as a result, two structural types with either the hydrogen atom attached to the chiral carbon (C*) or the methyl group attached to C* in close proximity of the cymene ring protons get stabilized. Using 2D NMR spectroscopy as a tool, the spatial interaction involving these protons are studied in order to obtain the metal configuration(s) of the diastereomeric complexes in solution. This technique has enabled us to determine the metal configuration as (R-Ru,S-C) for the major isomers of 1-3 in solution.

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An efficient strategy for identification of delamination in composite beams and connected structures is presented. A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain. A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation. For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented. Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost. This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems.