Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Molecular phylogeny of Hemidactylus geckos (Squamata: Gekkonidae) of the Indian subcontinent reveals a unique Indian radiation and an Indian origin of Asian house geckos

Represented by approximately 85 species, Hemidactylus is one of the most diverse and widely distributed genera of reptiles in the world. In the Indian subcontinent, this genus is represented by 28 species out of which at least 13 are endemic to this region. Here, we report the phylogeny of the Indian Hemidactylus geckos based on mitochondrial and nuclear DNA markers sequenced from multiple individuals of widely distributed as well as endemic congeners of India. Results indicate that a majority of the species distributed in India form a distinct clade whose members are largely confined to the Indian subcontinent thus representing a unique Indian radiation. The remaining Hemidactylus geckos of India belong to two other geographical clades representing the Southeast Asian and West-Asian arid zone species. Additionally, the three widely distributed, commensal species (H. brookii, H. frenatus and H. flaviviridis) are nested within the Indian radiation suggesting their Indian origin. Dispersal-vicariance analysis also supports their Indian origin and subsequent dispersal out-of-India into West-Asian arid zone and Southeast Asia. Thus, Indian subcontinent has served as an important arena for diversification amongst the Hemidactylus geckos and in the evolution and spread of its commensal geckos. (C) 2010 Elsevier Inc. All rights reserved.

Origin of the plateau in the low-temperature thermal conductivity of silica

Thermal conductivities of glasses at low temperatures show strikingly similar behavior irrespective of their chemical composition. While for T<1 K the thermal conductivity can be understood in the phenomenological tunneling model; the ‘‘universal plateau’’ in the temperature interval 15>T>2 K is totally unexplained. While Rayleigh scattering of phonons by structural disorder should be the natural cause for limiting the mean free path of phonons in this temperature range, it has been concluded before that in glasses a strong enough source of such scattering does not exist. In this study we show by a proper structural analysis in at least one material (namely, silica) that a strong enough source of Rayleigh scattering of phonons in glasses does exist so that the ‘‘universal plateau’’ can be explained without invoking any new mechanism. This may be for the first time that the low-temperature property of a structural glass has been correlated to its structure.

Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

Synthetic studies in aromatic hemiterpenes of natural origin, Part 5: Synthesis of 6-acetyl-2,2-dimethyl-8-methoxychromene via benzylic oxidation route

The synthesis of 6-acetyl-2,2-dimethyl-8-methoxychromene (lc), a naturally occurring isomer of encecalin (la)h~s been described startilag from 2,2,6- trimethyl-8-methoxyclaromene (2e) which was obtained from creosol (4) in two steps involving condensation of the phenol with malic acid to the coumarin (3), followed by Grignard reaction with CHaMgI. The transformation of (2e) to the natural product (lc) was effeeted by oxidative dehydrogenation by DDQ of the 6-meth~r function to the formyl group (2f), Grignard reaction to the carbinol (2g) and finally its oxidation to the acetyl moiety (lc), the sequence of the essential steps schematically summarised as : Ar-CHs --* Ar-CHO --* Ar-CH (OH) CHs --* Ar---COCHs.

Microcycle conidiation and its genetic basis in Neurospora crassa

Some wild isolates of Neurospora show microcycle conidiation in liquid culture under continuous agitation. Macroconidia from agar-grown mycelial cultures germinated in liquid and the germlings spontaneously produced conidia with no intervening mycelial phase. Three types of microcycle conidiation were seen among progeny of N. crassa Vickramam A x N. crassa a wild-type: (1) multinucleate blastoconidia produced by apical budding and septation, (2) multinucleate arthroconidia produced by holothallic septation and disarticulation of cells, and (3) uninucleate microconidia produced directly from conidiogenous cells of the germlings. Two genes were identified which control specific patterns of microcycle conidiogenesis. A single gene mcb in linkage group VR near al-3 (3.2% recombination) controls blastoconidiation. This gene is epistatic to gene mcm located in linkage group IIL, very near ro-7 (1.4%). mcm controls both microconidiation and arthroconidiation depending on temperature. Strains of genotype mcm produce microconidia almost exclusively at 18-22 degrees C, but arthroconidia with few or no microconidia at 30 degrees C. Because they result in rapid and synchronized conidiation in liquid culture, the two genes should be useful for studies of developmental gene regulation. mcm makes it possible to obtain large quantities of pure microconidia rapidly for experimentation.

Origin of nonmetallicity in PrBa2Cu3O7 from a study of Gd1−xPrxBa2Cu3O7 using soft x-ray absorption at the oxygen K-edge

We present the x-ray absorption data at the oxygen K-edge using total yield technique for Gd1−xPrxba2Cu3O7 (x= 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0). The data clearly to oxygen that the holes doped in the GdBa2Cu3O7 due to oxygen composition are not removed by Pr doping even for the x = 1.0 sample, suggesting that Pr is predominantly in the formally trivalent state. However, the data also clearly indicate the evidence of hybridization effects between the Pr3+ and the adjacent CuO2 layers. This is suggested to be responsible for the progressive suppression of Tc and the metallicity with Pr doping in these systems.

A Genetic Study of Immunoglobulin E and Atopic Disease Based on Families Ascertained through Asthmatic Children

In order to investigate the modes of inheritance of serum immunoglobulin E (IgE) levels and atopic disease, serum IgE levels and data on allergic disease were obtained from 42 families ascertained through asthmatic children visiting an allergy clinic. Although the mean IgE levels were elevated (mean 637 U/ml), the prevalence of atopic disease in this population was surprisingly low. When the data were analyzed using complex segregation analysis, no major locus could be detected. Moreover, the polygenic heritability was unexpectedly small even though the correlation between serum IgE levels and the liability to atopic disease was around 0.4. Given this unusual set of findings, it is postulated that parasitic infections in this population have (in accordance with well-established results of parasitic disease) caused both elevated levels of serum IgE and a decreased prevalence of allergic disease with the possible masking of the various genetic components of serum IgE levels and atopic disease.