A simulation model for the operation of multipurpose multireservoir system for River Narmada, India

This paper presents a simulation model for the operation of multipurpose multireservoir systems. The simulation model developed in this study has been applied to the Narmada River Reservoir System in India. The model has been formulated for the monthly operation of reservoirs to meet industrial, domestic, irrigation, and hydropower generation water requirements. The simulation model consists of four modules: inflow generation, minimum flow releases, simulation, and performance evaluation. The single-site Thomas–Fiering and multisite Lane's Applied Stochastic Techniques (LAST) inflow generation models have been used for the generation of a monthly inflow series. Five performance indicator indices have been formulated for evaluating the performance of the multipurpose multireservoir system: Volume Reliability Index (VRI), Time Reliability Index (TRI), Hydropower Production Index (HPI), Economic Benefits Index (ECBI), and Spill Prevention Index (SPPI). The trade-offs between the performance indicator indices have been obtained using the simulation model. The results from these trade-offs will assist decision makers in the operation of reservoirs, as well as with planning and comparing operation strategies.     

Effect of metal spiking on different chemical pools and chemically extractable fractions of heavy metals in sewage sludge

A laboratory experiment was conducted to study the effect of metal spiking and incubation on some properties and sequentially extractable chemical pools of some heavy metals (F1, two extractions with 0.1 M Sr(NO3)2; F2, one extraction with 1 M NaOAc (pH 5.0); F3, three extractions with 5% NaOCl (pH 8.5) at 90-95 degrees C; F4, three extractions with 0.2 M oxalic acid + 0.2 M ammonium oxalate + 0.1 M ascorbic acid (pH 3.0); and F5, dissolution of sample residue in HF-HClO4 (residual fraction,) and also 1 M CaCl2 and 0.005 M DTPA extractable heavy metals in sewage sludge. Metal spiking and incubation decreased pH and easily oxidizable organic C content of sludge but increased electrical conductivity. Metal spiking and incubation increased F1 fraction of all heavy metals, F2 fraction of Ni, Pb, Cu, and Cd, F3 fraction of Pb, Cu, and Cd, F4 or reducible fraction of Ni, Cu, and Cd and residual fraction of Zn and Pb, but decreased F2 fraction of Zn, F3 of Zn and Ni, F4 fraction of Zn and F5 fraction of Ni, Cu, and Cd. Metal spiking and incubation increased 1 M CaCl2 and 0.005 M DTPA extractable amounts of all heavy metals in sludge except for 0.005 M DTPA extractable Zn, which registered only very marginal decrease.     

Response surface modeling and optimization of tomato puree–casein bio-composite films

In this study, Box–Behnken response surface experimental design of response surface methodology (RSM) was adopted to investigate the simultaneous effects of tomato puree (1–3% w/v), casein (0.4–0.8% w/v) and drying time (10–12 h) on the physical and optical properties of a bio-composite film. Analysis of variance (ANOVA) showed that the experimental data was well-explained by the different models with high coefficient of determination (R²?>?0.90). The second-order polynomial models were fitted to all the response variables and three-dimensional response surface plots and equations were analyzed. It was found that all the process variables significantly affected (P?<?0.05) the response variables either linearly or quadratically, whereas the “Lack of Fit” was non-significantly relative to the pure error. On the basis of the ranges of different responses, a total of nine solutions were suggested, out of which, the film with 2.12% w/v tomato puree level, 0.59% w/v casein level and 11.99 h drying time was selected. At this optimum point, thickness, moisture, solubility, moisture absorption rate, water vapor transmission rate, density, transparency, hue angle, chroma value and whiteness index were found to be 0.143 mm, 24.49%, 77.69%, 10.22%, 0.03 g/cm² t, 1.472 g/mL, 40.72%, 78.70, 11.60 and 64.99, respectively, with a desirability value of 0.61. It can be concluded that the developed films with desirable characteristics can be successfully prepared and effectively applied in the food packaging industry.     

Generate‐map‐reduce: An extension to map‐reduce to support shared data and recursive computations

It is difficult to express the parallelism present in complex computations by using existing higher level abstractions such as MapReduce and Dryad. These computations include applications from wide variety of domains, like Artificial Intelligence, Decision Tree Algorithms, Association Rule Mining, Recommender Systems, Graph Algorithms, Clustering Algorithms, Compute Intensive Scientific Workflows, Optimization Algorithms, and so forth. Their execution graphs introduce new challenges in terms of programmer expressibility and runtime performance such as iterative and recursive computations, shared communication model, and so forth. We propose an extension to MapReduce, called Generate‐Map‐Reduce (GMR), targeted towards modeling these applications. GMR introduces a new Generate abstraction into the MapReduce framework that captures recursive computations. The runtime also supports iterative jobs and a distributed communication model by using shared data structures. We illustrate recursive computations with GMR by modeling complex applications such as simulated annealing, A* search, and adaptive quadrature computation that require recursive spawning of new tasks to handle variable degree of parallelism. GMR runtime supports caching of common data across iterations in memory and local disks. We illustrate how this caching helps in achieving significant speedup for iterative computations by modeling k‐means clustering. Copyright © 2013 John Wiley & Sons, Ltd.     

Particle Swarm Optimization for Solving Sine-Gordan Equation

The term ‘optimization’ refers to the process of maximizing the beneficial attributes of a mathematical function or system while minimizing the unfavorable ones. The majority of real-world situations can be modelled as an optimization problem. The complex nature of models restricts traditional optimization techniques to obtain a global optimal solution and paves the path for global optimization methods. Particle Swarm Optimization is a potential global optimization technique that has been widely used to address problems in a variety of fields. The idea of this research is to use exponential basis functions and the particle swarm optimization technique to find a numerical solution for the Sine-Gordan equation, whose numerical solutions show the soliton form and has diverse applications. The implemented optimization technique is employed to determine the involved parameter in the basis functions, which was previously approximated as a random number in the work reported till now in the literature. The obtained results are comparable with the results obtained in the literature. The work is presented in the form of figures and tables and is found encouraging.