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.

Artificial neural networks and multicriterion analysis for sustainable irrigation planning

The objective of the present paper is to select the best compromise irrigation planning strategy for the case study of Jayakwadi irrigation project, Maharashtra, India. Four-phase methodology is employed. In phase 1, separate linear programming (LP) models are formulated for the three objectives, namely. net economic benefits, agricultural production and labour employment. In phase 2, nondominated (compromise) irrigation planning strategies are generated using the constraint method of multiobjective optimisation. In phase 3, Kohonen neural networks (KNN) based classification algorithm is employed to sort nondominated irrigation planning strategies into smaller groups. In phase 4, multicriterion analysis (MCA) technique, namely, Compromise Programming is applied to rank strategies obtained from phase 3. It is concluded that the above integrated methodology is effective for modeling multiobjective irrigation planning problems and the present approach can be extended to situations where number of irrigation planning strategies are even large in number. (c) 2004 Elsevier Ltd. All rights reserved.

Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks

Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

Multiple imaging and multichannel optical processing with split lenses

The use of split lenses for multiple imaging and multichannel optical processing is demonstrated. Conditions are obtained for nonoverlapping of multipled images and avoiding crosstalk in the multichannel processing. Almost uniform intensity across the multipled images is an advantage here, while the low ƒ/No. of the split lens segments puts a limit in the resolution in image processing. Experimental results of multiple imaging and of a few multichannel processing are presented.

Artificial database for character recognition research

This paper describes a technique for artificial generation of learning and test sample sets suitable for character recognition research. Sample sets of English (Latin), Malayalam, Kannada and Tamil characters are generated easily through their prototype specifications by the endpoint co-ordinates, nature of segments and connectivity.

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.

A nonhelical, multiple β-turn conformation in a glycine-rich heptapeptide fragment of trichogin A IV containing a single central α-aminoisobutyric acid residue

The conformational properties of the protected seven-residue C-terminal fragment the lipopeptaibol antibiotic Trichogin A IV (Boc-Gly-Gly-Leu-Aib-Gly-Ile-Leu-OMe) has been examined in CDCl3 and (CD3)2SO by 1H-nmr. Evidence for a multiple β-turn conformation [type I′ at Gly(1)-Gly(2), type II at Leu(3)-Aib(4), and a type I′ at Aib(4)-Gly(5)] suggests that Leu(3) has preferred an extended or semiextended conformation over a helical conformation in CDCl3. This structure is thus in contrast to earlier observations of seven-residue peptides containing a single central Aib preferring helical conformations in both solution and crystalline slates. A structural transition to a frayed right-handed helix is absented in (CD3)2SO. These results suggest that nonhelical conformations may be important in Gly-rich peptides containing Aib. Further, the presence of amino acids with contradictory influences on backbone conformational freedom can lead to well-defined conformational transitions even in small peptides

Artificial commutation for inversion into a weak AC system in a multiterminal HVDC system

This paper deals with the application of artificial commutation for a normally rated inverter connecting a weak AC system in a multiterminal HVDC (MTDC) system. Artificial commutation is achieved using series capacitors. A modular digital simulation technique is developed to study the dynamic performance of the system. It is shown that by a proper selection of the value of the capacitor it is possible to limit the valve stresses and the DC harmonics to acceptable levels and achieve an improved performance during severe transient conditions. The determination of the value of the series capacitor is based on a parametric study.

Differential transcription of multiple copies of a silk worm gene encoding tRNA

Ten different tRNAGly1 genes from the silk worm, Bombyx mori, have been cloned and characterized. These genes were transcribed in vitro in homologous nuclear extracts from the posterior silk gland (PSG) or nuclear extracts derived from the middle silk gland or ovarian tissues. Although the transcription levels were much higher in the PSG nuclear extracts, the transcriptional efficiency of the individual genes followed a similar pattern in all the extracts. Based on the levels of in vitro transcription, the ten tRNAGly1 genes could be divided into three groups, viz., those which were transcribed at very high levels (e.g., clone pR8), high to medium levels (e.g., pBmil, pBmpl, pBmhl, pBmtl) and low to barely detectable levels (e.g., pBmsl, pBmjl and pBmkl). The coding sequences of all these tRNA genes being identical, the differential transcription suggested that the flanking sequences modulate their transcriptional efficiency. The presence of positive and negative regulatory elements in the 5' flanking regions of these genes was confirmed by transcription competition experiments. A positive element was present in the immediate upstream A + T-rich sequences in all the genes, but no consensus sequences correlating to the transcriptional status could be generated. The presence of negative elements on the other hand was indicated only in some of the genes and therefore may have a role in the differential transcription of these tRNAGly genes in vivo.

Mean-field results of the multiple-band extended Hubbard model for the square-planar CuO2 lattice

We obtain metal-insulator phase diagrams at half-filling for the five-band extended Hubbard model of the square-planar CuO2 lattice treated within a Hartree-Fock mean-field approximation, allowing for spiral spin-density waves. We indicate the existence of an insulating phase (covalent insulator) characterized by strong covalency effects, not identified in the earlier Zaanen-Sawatzky-Allen phase diagram. While the insulating phase is always antiferromagnetic, we also obtain an antiferromagnetic metallic phase for a certain range of interaction parameters. Performing a nonperturbative calculation of J(eff), the in-plane antiferromagnetic interaction is presented as a function of the parameters in the model. We also calculate the band gap and magnetic moments at various sites and discuss critically the contrasting interpretation of the electronic structure of high-T(c) materials arising from photoemission and neutron-scattering experiments.

Modelling multiple disulphide loop containing polypeptides by random conformation generation. The test cases of α-conotoxin GI and edothelin I

A general procedure for arriving at 3-D models of disulphiderich olypeptide systems based on the covalent cross-link constraints has been developed. The procedure, which has been coded as a computer program, RANMOD, assigns a large number of random, permitted backbone conformations to the polypeptide and identifies stereochemically acceptable structures as plausible models based on strainless disulphide bridge modelling. Disulphide bond modelling is performed using the procedure MODIP developed earlier, in connection with the choice of suitable sites where disulphide bonds could be engineered in proteins (Sowdhamini,R., Srinivasan,N., Shoichet,B., Santi,D.V., Ramakrishnan,C. and Balaram,P. (1989) Protein Engng, 3, 95-103). The method RANMOD has been tested on small disulphide loops and the structures compared against preferred backbone conformations derived from an analysis of putative disulphide subdatabase and model calculations. RANMOD has been applied to disulphiderich peptides and found to give rise to several stereochemically acceptable structures. The results obtained on the modelling of two test cases, a-conotoxin GI and endothelin I, are presented. Available NMR data suggest that such small systems exhibit conformational heterogeneity in solution. Hence, this approach for obtaining several distinct models is particularly attractive for the study of conformational excursions.

Crucial contribution of the multiple copies of the initiator tRNA genes in the fidelity of tRNA(fMet) selection on the ribosomal P-site in Escherichia coli

The accuracy of the initiator tRNA (tRNA(fMet)) selection in the ribosomal P-site is central to the fidelity of protein synthesis. A highly conserved occurrence of three consecutive G-C base pairs in the anticodon stem of tRNA(fMet) contributes to its preferential selection in the P-site. In a genetic screen, using a plasmid borne copy of an inactive tRNA(fMet) mutant wherein the three G-C base pairs were changed, we isolated Escherichia coli strains that allow efficient initiation with the tRNA(fMet) mutant. Here, extensive characterization of two such strains revealed novel mutations in the metZWV promoter severely compromising tRNA(fMet) levels. Low cellular abundance of the chromosomally encoded tRNA(fMet) allows efficient initiation with the tRNA(fMet) mutant and an elongator tRNA(Gln), revealing that a high abundance of the cellular tRNA(fMet) is crucial for the fidelity of initiator tRNA selection on the ribosomal P-site in E. coli. We discuss possible implications of the changes in the cellular tRNA(fMet) abundance in proteome remodeling.