70 resultados para performances


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Halloysite nanotubes (HNTs) of the dimension 50nm x 1-3 mu m (diameter x length) are utililized to fabricate the alloy composite by employing electroless/autocatalytic deposition technique. Electroless Ni-P-HNT binary alloy composite coatings are prepared successfully on low carbon steel. These nanotubes were made to get inserted/incorporated into nickel matrix and corresponding composites are examined for their electrochemical, mechanical and tribological performances and compared with that of plain Ni-P. The coatings were characterized using scanning electron microscopy (SEM) and Energy dispersive X-ray analysis (EDX) techniques to analyze surface nature and composition correspondingly. Small amount of incorporated HNTs made Ni-P deposits appreciable enhancement and betterment in corrosion resistance, hardness and friction resistance. This drastic improvement in the properties reflects the effect of addition of HNTs into Ni-P matrix leading to the development of high performance Ni-P-HNT composite coatings. (C) 2012 Elsevier B. V. All rights reserved.

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This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

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In this paper optical code-division multiple-access (O-CDMA) packet network is considered, which offers inherent security in the access networks. Two types of random access protocols are proposed for packet transmission. In protocol 1, all distinct codes and in protocol 2, distinct codes as well as shifted versions of all these codes are used. O-CDMA network performance using optical orthogonal codes (OOCs) 1-D and two-dimensional (2-D) wavelength/time single-pulse-per-row (W/T SPR) codes are analyzed. The main advantage of using 2-D codes instead of one-dimensional (1-D) codes is to reduce the errors due to multiple access interference among different users. SPR codes are chosen as they have nearly ideal correlation properties. In this paper, correlation receiver is considered in the analysis. Using analytical model, we compare the OOC and SPR code performances in O-CDMA networks. We compute packet-success probability and throughput for both the types of codes. The analysis shows improved performance with SPR codes as compared to OOC codes.

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Mobile WiMAX is a burgeoning network technology with diverse applications, one of them being used for VANETs. The performance metrics such as Mean Throughput and Packet Loss Ratio for the operations of VANETs adopting 802.16e are computed through simulation techniques. Next we evaluated the similar performance of VANETs employing 802.11p, also known as WAVE (Wireless Access in Vehicular Environment). The simulation model proposed is close to reality as we have generated mobility traces for both the cases using a traffic simulator (SUMO), and fed it into network simulator (NS2) based on their operations in a typical urban scenario for VANETs. In sequel, a VANET application called `Street Congestion Alert' is developed to assess the performances of these two technologies. For this application, TraCI is used for coupling SUMO and NS2 in a feedback loop to set up a realistic simulation scenario. Our inferences show that the Mobile WiMAX performs better than WAVE for larger network sizes.

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A series of fluoranthene derivatives (F1-F5) varied with nature and type of substituents were synthesized via Diels-Alder reaction followed by in situ decarbonylation. The solid state structures have been established through single crystal X-ray diffraction (XRD). The presence of extended conjugation and having two alkyloxy chains on phenyl rings induces flexibility to orient opposite to each other and interacts with another fluoranthene unit with weak pi-pi interactions and show unique supramolecular arrangements. The envisaged photophysical and DFT studies demonstrated that HOMO-LUMO levels were effectively tuned by different substituents with an optical band gap from 3.44 to 3.88 eV provoked to examine as sensitive fluorescent chemosensors for the detection of nitroaromatic compounds (NACs). The sensitivity toward the detection of NACs was evaluated through fluorescence quenching in solution (aqueous and non-aqueous) and solid state (vapor and contact mode). Fluorescence studies demonstrated that electron transfer occurs from the electron rich fluoranthene fluorophores to the electron deficient NACs by the dominant static quenching mechanism and the quenching process is reversible. It was found that the detection sensitivity increases with extent of conjugation on fluoranthene unit. The contact mode approach using thin layer silica chromatographic plates exhibits a femtogram (1.15 fg/cm(2)) detection limit for trinitrotoluene (TNT) and picric acid (PA), while the solution state fluorescence quenching shows for PA detection at the 2-20 ppb level. The sensing performance of fluoranthene thin films to NACs in aqueous solution reveals that fluorophores are highly selective towards the detection of PA. The smart performances of thin film fluorophores with high photostability have great advantage than those of conjugated polymers with superior sensitive detection of PA in groundwater.

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A supply chain ecosystem consists of the elements of the supply chain and the entities that influence the goods, information and financial flows through the supply chain. These influences come through government regulations, human, financial and natural resources, logistics infrastructure and management, etc., and thus affect the supply chain performance. Similarly, all the ecosystem elements also contribute to the risk. The aim of this paper is to identify both performances-based and risk-based decision criteria, which are important and critical to the supply chain. A two step approach using fuzzy AHP and fuzzy technique for order of preference by similarity to ideal solution has been proposed for multi-criteria decision-making and illustrated using a numerical example. The first step does the selection without considering risks and then in the next step suppliers are ranked according to their risk profiles. Later, the two ranks are consolidated into one. In subsequent section, the method is also extended for multi-tier supplier selection. In short, we are presenting a method for the design of a resilient supply chain, in this paper.

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Highly branched and porous graphene nanosheet synthesized over different substrates as anode for Lithium ion thin film battery. These films synthesized by microwave plasma enhanced chemical vapor deposition at temperature 700 degrees C. Scanning electron microscopy and X-ray photo electron spectroscopy are used to characterize the film surface. It is found that the graphene sheets possess a curled and flower like morphology. Electrochemical performances were evaluated in swezelock type cells versus metallic lithium. A reversible capacity of 520 mAh/g, 450 mAh/g and 637 mAh/g was obtained after 50 cycles when current rate at 23 mu A cm(2) for CuGNS, NiGNS and PtGNS electrodes, respectively. Electrochemical properties of thin film anode were measured at different current rate and gave better cycle life and rate capability. These results indicate that the prepared high quality graphene sheets possess excellent electrochemical performances for lithium storage. (C) 2013 Elsevier Ltd. All rights reserved.

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Single crystalline zinc oxide (ZnO) nanorod array has been used for the fabrication of CdSe/CdS/PbS/ZnO quantum dot sensitized solar cell (QDSSC). The ZnO nanorod array photoanodes are sensitized with consecutive layer of PbS, CdS and CdSe quantum dots by employing simple successive ion layer adsorption and reaction (SILAR) and chemical bath deposition (CBD) techniques. The performances of the QDSSCs are examined in detail using polysulfide electrolyte with copper sulfide (CuS) counter electrode. The combination of two successive layers of PbS with CdSe/CdS/ZnO shows an improved short circuit current density (12.223 mA cm(-2)) with a maximum power to conversion efficiency of 2.352% under 1 sun illumination. This enhancement is mainly attributed due to the better light harvesting ability of the PbS quantum dots and make large accumulation of photo-injected electrons in the conduction band of ZnO, and CdSe/CdS layers lower the recombination of photo-injected electrons with the electrolyte, these are well evidenced with the photovoltaic studies and electrochemical impedance spectroscopy. (C) 2013 Elsevier B.V. All rights reserved.

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Classification of pharmacologic activity of a chemical compound is an essential step in any drug discovery process. We develop two new atom-centered fragment descriptors (vertex indices) - one based solely on topological considerations without discriminating atomor bond types, and another based on topological and electronic features. We also assess their usefulness by devising a method to rank and classify molecules with regard to their antibacterial activity. Classification performances of our method are found to be superior compared to two previous studies on large heterogeneous data sets for hit finding and hit-to-lead studies even though we use much fewer parameters. It is found that for hit finding studies topological features (simple graph) alone provide significant discriminating power, and for hit-to-lead process small but consistent improvement can be made by additionally including electronic features (colored graph). Our approach is simple, interpretable, and suitable for design of molecules as we do not use any physicochemical properties. The singular use of vertex index as descriptor, novel range based feature extraction, and rigorous statistical validation are the key elements of this study.

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In this paper, a fractional order proportional-integral controller is developed for a miniature air vehicle for rectilinear path following and trajectory tracking. The controller is implemented by constructing a vector field surrounding the path to be followed, which is then used to generate course commands for the miniature air vehicle. The fractional order proportional-integral controller is simulated using the fundamentals of fractional calculus, and the results for this controller are compared with those obtained for a proportional controller and a proportional integral controller. In order to analyze the performance of the controllers, four performance metrics, namely (maximum) overshoot, control effort, settling time and integral of the timed absolute error cost, have been selected. A comparison of the nominal as well as the robust performances of these controllers indicates that the fractional order proportional-integral controller exhibits the best performance in terms of ITAE while showing comparable performances in all other aspects.

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Nanocrystalline titania are a robust candidate for various functional applications owing to its non-toxicity, cheap availability, ease of preparation and exceptional photochemical as well as thermal stability. The uniqueness in each lattice structure of titania leads to multifaceted physico-chemical and opto-electronic properties, which yield different functionalities and thus influence their performances in various green energy applications. The high temperature treatment for crystallizing titania triggers inevitable particle growth and the destruction of delicate nanostructural features. Thus, the preparation of crystalline titania with tunable phase/particle size/morphology at low to moderate temperatures using a solution-based approach has paved the way for further exciting areas of research. In this focused review, titania synthesis from hydrothermal/solvothermal method, conventional sol-gel method and sol-gel-assisted method via ultrasonication, photoillumination and ILs, thermolysis and microemulsion routes are discussed. These wet chemical methods have broader visibility, since multiple reaction parameters, such as precursor chemistry, surfactants, chelating agents, solvents, mineralizer, pH of the solution, aging time, reaction temperature/time, inorganic electrolytes, can be easily manipulated to tune the final physical structure. This review sheds light on the stabilization/phase transformation pathways of titania polymorphs like anatase, rutile, brookite and TiO2(B) under a variety of reaction conditions. The driving force for crystallization arising from complex species in solution coupled with pH of the solution and ion species facilitating the orientation of octahedral resulting in a crystalline phase are reviewed in detail. In addition to titanium halide/alkoxide, the nucleation of titania from other precursors like peroxo and layered titanates are also discussed. The nonaqueous route and ball milling-induced titania transformation is briefly outlined; moreover, the lacunae in understanding the concepts and future prospects in this exciting field are suggested.

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The reduction of the diffusion energy barrier for Li in electrodes is one of the required criteria to achieve better performances in Li ion batteries. Using density functional theory based calculations, we report a pressure induced manifold enhancement of Li-kinetics in bulk FCC fullerene. Scanning of the potential energy surface reveals a diffusion path with a low energy barrier of 0.62 eV, which reduces further under the application of hydrostatic pressure. The pressure induced reduction in the diffusion barrier continues till a uniform volume strain of 17.7% is reached. Further enhancement of strain increases the barrier due to the repulsion caused by C-C bond formation between two neighbouring fullerenes. The decrease in the barrier is attributed to the combined effect of charge transfer triggered by the enhanced interaction of Li with the fullerene as well as the change in profile of the local potential, which becomes more attractive for Li. The lowering of the barrier leads to an enhancement of two orders of magnitude in Li diffusivity at room temperature making pressurized bulk fullerene a promising artificial solid electrolyte interface (SEI) for a faster rechargeable battery.

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In this paper we present a massively parallel open source solver for Richards equation, named the RichardsFOAM solver. This solver has been developed in the framework of the open source generalist computational fluid dynamics tool box OpenFOAM (R) and is capable to deal with large scale problems in both space and time. The source code for RichardsFOAM may be downloaded from the CPC program library website. It exhibits good parallel performances (up to similar to 90% parallel efficiency with 1024 processors both in strong and weak scaling), and the conditions required for obtaining such performances are analysed and discussed. These performances enable the mechanistic modelling of water fluxes at the scale of experimental watersheds (up to few square kilometres of surface area), and on time scales of decades to a century. Such a solver can be useful in various applications, such as environmental engineering for long term transport of pollutants in soils, water engineering for assessing the impact of land settlement on water resources, or in the study of weathering processes on the watersheds. (C) 2014 Elsevier B.V. All rights reserved.

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Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

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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.