Integrated sustainable irrigation planning with multiobjective Fuzzy optimization approach

Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.

Naphthalene Carbohydrazone Based Dizinc(II) Chemosensor for a Pyrophosphate Ion and Its DNA Assessment Application in Polymerase Chain Reaction Products

A new naphthalene carbohydrazone based dizinc(II) complex has been synthesized and investigated to act as a highly selective fluorescence and visual sensor for a pyrophosphate ion with a quite low detection limit of 155 ppb; this has also been used to detect the pyrophosphate ion released from polymerase-chain-reaction.

Chromium isotope variations (delta Cr-53/52) in mantle-derived sources and their weathering products: Implications for environmental studies and the evolution of delta Cr-53/52 in the Earth's mantle over geologic time

Here we report chromium isotope compositions, expressed as delta Cr-53/ 52 in per mil (&) relative to NIST 979, measured in selected Cr-rich minerals and rocks formed by the primary magmatic as well as the secondary metamorphic and weathering processes. The main objectives of this study were: (i) to further constrain the isotope composition of the Earth's mantle Cr inventory and its possible variation during geological history, based on the analysis of globally distributed and stratigraphically constrained mantle-derived chromites; and (ii) to investigate the magnitude and systematics of Cr isotope fractionation during oxidative weathering and secondary alteration (i. e., hydration, serpentinization) of the magmatic Cr sources. Specifically, we analyzed delta Cr-53/ 52 in a set of globally distributed mantle-derived chromites (FeMgCr2O4, n = 30) collected from various locations in Europe, Asia, Africa and South America, and our results confirm that a chromite-hosted Earth's mantle Cr inventory is uniform at - 0.079 +/- 0.129& (2SD), which we named here as a ` canonical' mantle d 53/ 52 Cr signature. Furthermore our dataset of stratigraphically constrained chromites, whose crystallization ages cover most of the Earth's geological history, indicate that the bulk Cr isotope composition of the chromite-hosted mantle inventory has remained uniform, within about +/- 0.100&, since at least the Early Archean times (similar to 3500 million years ago, Ma). To investigate the systematics of Cr isotope fractionation associated with alteration processes we analyzed a number of secondary Cr-rich minerals and variably altered ultramafic rocks (i. e., serpentinized harzburgites, lherzolites) that revealed large positive delta Cr-53/ 52 anomalies that are systematically shifted to higher values with an increasing degree of alteration and serpentinization. The degree of aqueous alteration and serpentinization was quantified by the abundances of fluid-mobile (Rb, K) elements, and by the Loss On Ignition (LOI) parameter, which determines the amount of structurally bound water (OH/ H2O) present in secondary hydrated minerals like serpentine. Overall, we observed that altered ultramafic rocks that yielded the highest LOI values, and the lowest amounts of fluid mobile elements, also yielded the heaviest delta Cr-53/ 52 signatures. Therefore, we conclude that secondary alteration (i.e., hydration, serpentinization) of ultramafic rocks in near-surface oxidative environments tend to shift the bulk Cr isotope composition of the weathered products to isotopically heavier values, pointing to a dynamic redox cycling of Cr in the Earth's crustal and near-surface environments. Hence, if validated by future

FUZZY CONIFOLD Y-F(6) AND MONOPOLES ON S-F(2) x S-F(2)

In this paper, we construct the fuzzy (finite-dimensional) analogs of the conifold Y-6 and its base X-5. We show that fuzzy X-5 is (the analog of) a principal U(1) bundle over fuzzy spheres S-F(2) x S-F(2) and explicitly construct the associated monopole bundles. In particular, our construction provides an explicit discretization of the spaces T-k,T-k and T-k,T-0.

Active yaw control of a vehicle using a Fuzzy logic algorithm

Yaw rate of a vehicle is highly influenced by the lateral forces generated at the tire contact patch to attain the desired lateral acceleration, and/or by external disturbances resulting from factors such as crosswinds, flat tire or, split-μ braking. The presence of the latter and the insufficiency of the former may lead to undesired yaw motion of a vehicle. This paper proposes a steer-by-wire system based on fuzzy logic as yaw-stability controller for a four-wheeled road vehicle with active front steering. The dynamics governing the yaw behavior of the vehicle has been modeled in MATLAB/Simulink. The fuzzy controller receives the yaw rate error of the vehicle and the steering signal given by the driver as inputs and generates an additional steering angle as output which provides the corrective yaw moment. The results of simulations with various drive input signals show that the yaw stability controller using fuzzy logic proposed in the current study has a good performance in situations involving unexpected yaw motion. The yaw rate errors of a vehicle having the proposed controller are notably smaller than an uncontrolled vehicle's, and the vehicle having the yaw stability controller recovers lateral distance and desired yaw rate more quickly than the uncontrolled vehicle.

Fuzzy Classification of Time Series Data

The problem of classification of time series data is an interesting problem in the field of data mining. Even though several algorithms have been proposed for the problem of time series classification we have developed an innovative algorithm which is computationally fast and accurate in several cases when compared with 1NN classifier. In our method we are calculating the fuzzy membership of each test pattern to be classified to each class. We have experimented with 6 benchmark datasets and compared our method with 1NN classifier.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Biodegradation of acrylamide by acrylamidase from Stenotrophomonas acidaminiphila MSU12 and analysis of degradation products by MALDI-TOF and HPLC

The present study examines an improved detoxification and rapid biological degradation of toxic pollutant acrylamide using a bacterium. The acrylamide degrading bacterium was isolated from the soil followed by its screening to know the acrylamide degrading capability. The minimal medium containing acrylamide (30 mM) served as a sole source of carbon and nitrogen for their active growth. The optimization of three different factors was analyzed by using Response Surface Methodology (RSM). The bacteria actively degraded the acrylamide at a temperature of 32 degrees C, with a maximum growth at 30 mM substrate (acrylamide) concentration at a pH of 7.2. The acrylamidase activity and degradation of acrylamide was determined by High Performance Liquid Chromatography (HPLC) and Matrix Assisted Laser Desorption and Ionization Time of Flight mass spectrometer (MALDI-TOF). Based on 168 rRNA analysis the selected strain was identified as Gram negative bacilli Stenotrophomonas acidaminiphila MSU12. The acrylamidase was isolated from bacterial extract and was purified by HPLC, whose mass spectrum showed a molecular mass of 38 kDa. (C) 2014 Elsevier Ltd. All rights reserved.

Rainbow Connection Number of Graph Power and Graph Products

Rainbow connection number, rc(G), of a connected graph G is the minimum number of colors needed to color its edges so that every pair of vertices is connected by at least one path in which no two edges are colored the same (note that the coloring need not be proper). In this paper we study the rainbow connection number with respect to three important graph product operations (namely the Cartesian product, the lexicographic product and the strong product) and the operation of taking the power of a graph. In this direction, we show that if G is a graph obtained by applying any of the operations mentioned above on non-trivial graphs, then rc(G) a parts per thousand currency sign 2r(G) + c, where r(G) denotes the radius of G and . In general the rainbow connection number of a bridgeless graph can be as high as the square of its radius 1]. This is an attempt to identify some graph classes which have rainbow connection number very close to the obvious lower bound of diameter (and thus the radius). The bounds reported are tight up to additive constants. The proofs are constructive and hence yield polynomial time -factor approximation algorithms.

Spectrum of the three-dimensional fuzzy well

We develop the formalism of quantum mechanics on three-dimensional fuzzy space and solve the Schrodinger equation for the free particle, finite and infinite fuzzy wells. We show that all results reduce to the appropriate commutative limits. A high energy cut-off is found for the free particle spectrum, which also results in the modification of the high energy dispersion relation. An ultra-violet/infra-red duality is manifest in the free particle spectrum. The finite well also has an upper bound on the possible energy eigenvalues. The phase shifts due to scattering around the finite fuzzy potential well are calculated.

Quantum entropy for the fuzzy sphere and its monopoles

Using generalized bosons, we construct the fuzzy sphere S-F(2) and monopoles on S-F(2) in a reducible representation of SU(2). The corresponding quantum states are naturally obtained using the GNS-construction. We show that there is an emergent nonabelian unitary gauge symmetry which is in the commutant of the algebra of observables. The quantum states are necessarily mixed and have non-vanishing von Neumann entropy, which increases monotonically under a bistochastic Markov map. The maximum value of the entropy has a simple relation to the degeneracy of the irreps that constitute the reducible representation that underlies the fuzzy sphere.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

Monopoles, Dirac operator, and index theory for fuzzy SU(3) / (U(1) x U(1))

The intersection of the ten-dimensional fuzzy conifold Y-F(10) with S-F(5) x S-F(5) is the compact eight-dimensional fuzzy space X-F(8). We show that X-F(8) is (the analogue of) a principal U(1) x U(1) bundle over fuzzy SU(3) / U(1) x U(1)) ( M-F(6)). We construct M-F(6) using the Gell-Mann matrices by adapting Schwinger's construction. The space M-F(6) is of relevance in higher dimensional quantum Hall effect and matrix models of D-branes. Further we show that the sections of the monopole bundle can be expressed in the basis of SU(3) eigenvectors. We construct the Dirac operator on M-F(6) from the Ginsparg-Wilson algebra on this space. Finally, we show that the index of the Dirac operator correctly reproduces the known results in the continuum.

LANDSCAPE DYNAMICS MODELING THROUGH INTEGRATED MARKOV, FUZZY-AHP AND CELLULAR AUTOMATA

Multi temporal land use information were derived using two decades remote sensing data and simulated for 2012 and 2020 with Cellular Automata (CA) considering scenarios, change probabilities (through Markov chain) and Multi Criteria Evaluation (MCE). Agents and constraints were considered for modeling the urbanization process. Agents were nornmlized through fiizzyfication and priority weights were assigned through Analytical Hierarchical Process (AHP) pairwise comparison for each factor (in MCE) to derive behavior-oriented rules of transition for each land use class. Simulation shows a good agreement with the classified data. Fuzzy and AHP helped in analyzing the effects of agents of growth clearly and CA-Markov proved as a powerful tool in modelling and helped in capturing and visualizing the spatiotemporal patterns of urbanization. This provided rapid land evaluation framework with the essential insights of the urban trajectory for effective sustainable city planning.

Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework

Regional frequency analysis is widely used for estimating quantiles of hydrological extreme events at sparsely gauged/ungauged target sites in river basins. It involves identification of a region (group of watersheds) resembling watershed of the target site, and use of information pooled from the region to estimate quantile for the target site. In the analysis, watershed of the target site is assumed to completely resemble watersheds in the identified region in terms of mechanism underlying generation of extreme event. In reality, it is rare to find watersheds that completely resemble each other. Fuzzy clustering approach can account for partial resemblance of watersheds and yield region(s) for the target site. Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach. Practitioners often defuzzify the matrix to form disjoint clusters (regions) and use them as the basis for quantile estimation. The defuzzification approach (DFA) results in loss of information discerned on partial resemblance of watersheds. The lost information cannot be utilized in quantile estimation, owing to which the estimates could have significant error. To avert the loss of information, a threshold strategy (TS) was considered in some prior studies. In this study, it is analytically shown that the strategy results in under-prediction of quantiles. To address this, a mathematical approach is proposed in this study and its effectiveness in estimating flood quantiles relative to DFA and TS is demonstrated through Monte-Carlo simulation experiments and case study on Mid-Atlantic water resources region, USA. (C) 2015 Elsevier B.V. All rights reserved.