965 resultados para feature based cost


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For the purpose of water purification, novel and low-cost adsorbents which are promising replacements for activated carbon are being actively pursued. However, a single-phase material that adsorbs both cationic and anionic species remains elusive. Hence, a low-cost, multiphase adsorbent bed that purifies water containing both anionic and cationic pollutants is a desirable alternative. We choose anionic (Congo red, Orange G) and cationic (methylene blue, malachite green) dyes as model pollutants. These dyes are chosen since they are widely found in effluents from textile, leather, fishery, and pharmaceutical industries, and their carcinogenic, mutagenic, genotoxic, and cytotoxic impact on mammalian cells is well-established. We show that ZnO, (Zn0.24Cu0.76)O and cobalt ferrite based multiphase fixed adsorbent bed efficiently adsorbs model anionic (Congo red, Orange G) and cationic (methylene blue and malachite green) pollutants, and their complex mixtures. All adsorbent phases are synthesized using room-temperature, high-yield (similar to 96-100%), green chemical processes. The nanoadsorbents are characterized by using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, and zeta potential measurements. The constituent nanophases are deliberately chosen to be beyond 50 nm, in order to avoid the nanotoxic size regime of oxides. Adsorption characteristics of each of the phases are examined. Isotherm based analysis shows that adsorption is both spontaneous and highly favorable. zeta potential measurements indicate that electrostatic interactions are the primary driving force for the observed adsorption behavior. The isotherms obtained are best described using a composite Langmuir-Freundlich model. Pseudo-first-order, rapid kinetics is observed (with adsorption rate constants as high as 0.1-0.2 min(-1) in some cases). Film diffusion is shown to be the primary mechanism of adsorption.

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CuIn1-xAlxSe2 (CIASe) thin films were grown by a simple sol-gel route followed by annealing under vacuum. Parameters related to the spin-orbit (Delta(SO)) and crystal field (Delta(CF)) were determined using a quasi-cubic model. Highly oriented (002) aluminum doped (2%) ZnO, 100 nm thin films, were co-sputtered for CuIn1-xAlxSe2/AZnO based solar cells. Barrier height and ideality factor varied from 0.63 eV to 0.51 eV and 1.3186 to 2.095 in the dark and under 1.38 A. M 1.5 solar illumination respectively. Current-voltage characteristics carried out at 300 K were confined to a triangle, exhibiting three limiting conduction mechanisms: Ohms law, trap-filled limit curve and SCLC, with 0.2 V being the cross-over voltage, for a quadratic transition from Ohm's to Child's law. Visible photodetection was demonstrated with a CIASe/AZO photodiode configuration. Photocurrent was enhanced by one order from 3 x 10(-3) A in the dark at 1 V to 3 x 10(-2) A upon 1.38 sun illumination. The optimized photodiode exhibits an external quantum efficiency of over 32% to 10% from 350 to 1100 nm at high intensity 17.99 mW cm(-2) solar illumination. High responsivity R-lambda similar to 920 A W-1, sensitivity S similar to 9.0, specific detectivity D* similar to 3 x 10(14) Jones, make CIASe a potential absorber for enhancing the forthcoming technological applications of photodetection.

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Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

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This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

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Content Distribution Networks (CDNs) are widely used to distribute data to large number of users. Traditionally, content is being replicated among a number of surrogate servers, leading to high operational costs. In this context, Peer-to-Peer (P2P) CDNs have emerged as a viable alternative. An issue of concern in P2P networks is that of free riders, i.e., selfish peers who download files and leave without uploading anything in return. Free riding must be discouraged. In this paper, we propose a criterion, the Give-and-Take (G&T) criterion, that disallows free riders. Incorporating the G&T criterion in our model, we study a problem that arises naturally when a new peer enters the system: viz., the problem of downloading a `universe' of segments, scattered among other peers, at low cost. We analyse this hard problem, and characterize the optimal download cost under the G&T criterion. We propose an optimal algorithm, and provide a sub-optimal algorithm that is nearly optimal, but runs much more quickly; this provides an attractive balance between running time and performance. Finally, we compare the performance of our algorithms with that of a few existing P2P downloading strategies in use. We also study the computation time for prescribing the strategy for initial segment and peer selection for the newly arrived peer for various existing and proposed algorithms, and quantify cost-computation time trade-offs.

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Vertically aligned zinc oxide nanorods (ZnO NRs) were synthesized on kapton flexible sheets using a simple and cost-effective three-step process (electrochemical seeding, annealing under ambient conditions, and chemical solution growth). Scanning electron microscopy studies reveal that ZnO NRs grown on seed-layers, developed by electrochemical deposition at a negative potential of 1.5 V over a duration of 2.5 min and annealed at 200 degrees C for 2 h, consist of uniform morphology and good chemical stoichiometry. Transmission electron microscopy analyses show that the as-grown ZnO NRs have single crystalline hexagonal structure with a preferential growth direction of < 001 >. Highly flexible p-n junction diodes fabricated by using p-type conductive polymer exhibited excellent diode characteristics even under the fold state.

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For space applications, the weight of the liquid level sensors are of major concern as they affect the payload fraction and hence the cost. An attempt is made to design and test a light weight High Temperature Superconductor (HTS) wire based liquid level sensor for Liquid Oxygen (LOX) tank used in the cryostage of the spacecraft. The total resistance value measured of the HTS wire is inversely proportional to the liquid level. A HTS wire (SF12100) of 12mm width and 2.76m length without copper stabilizer has been used in the level sensor. The developed HTS wire based LOX level sensor is calibrated against a discrete diode array type level sensor. Liquid Nitrogen (LN2) and LOX has been used as cryogenic fluid for the calibration purpose. The automatic data logging for the system has been done using LabVIEW11. The net weight of the developed sensor is less than 1 kg.

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The partially exfoliated and reduced graphite oxide (PE-RGO) is prepared by low temperature thermal exfoliation of graphite oxide under air atmosphere. A symmetric carbon/carbon supercapacitor is studied in a Na2SO4 aqueous electrolyte. The discharge capacitance is 92 F g(-1), when symmetric cell is cycled between the potential ranges from 0 to 1.6 V. This system demonstrates a stable charge/discharge cycle behavior up to 3000 cycles when the cell is operated at a voltage window of 1.6 V. The utilization ratio of potential window is 90% for this system is attributed to the more negative value of electrodes potential when the cell voltage is set to 0 V. The low-temperature exfoliation approach is convenient for mass production of graphenes at low cost and it can be used as electrode material for energy storage applications. (C) 2014 Elsevier Ltd. All rights reserved.

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A Field Programmable Gate Array (FPGA) based hardware accelerator for multi-conductor parasitic capacitance extraction, using Method of Moments (MoM), is presented in this paper. Due to the prohibitive cost of solving a dense algebraic system formed by MoM, linear complexity fast solver algorithms have been developed in the past to expedite the matrix-vector product computation in a Krylov sub-space based iterative solver framework. However, as the number of conductors in a system increases leading to a corresponding increase in the number of right-hand-side (RHS) vectors, the computational cost for multiple matrix-vector products present a time bottleneck, especially for ill-conditioned system matrices. In this work, an FPGA based hardware implementation is proposed to parallelize the iterative matrix solution for multiple RHS vectors in a low-rank compression based fast solver scheme. The method is applied to accelerate electrostatic parasitic capacitance extraction of multiple conductors in a Ball Grid Array (BGA) package. Speed-ups up to 13x over equivalent software implementation on an Intel Core i5 processor for dense matrix-vector products and 12x for QR compressed matrix-vector products is achieved using a Virtex-6 XC6VLX240T FPGA on Xilinx's ML605 board.

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We propose two-photon excitation-based light-sheet technique for nano-lithography. The system consists of 2 -configured cylindrical lens system with a common geometrical focus. Upon superposition, the phase-matched counter-propagating light-sheets result in the generation of identical and equi spaced nano-bump pattern. Study shows a feature size of as small as few tens of nanometers with a inter-bump distance of few hundred nanometers. This technique overcomes some of the limitations of existing nano-lithography techniques, thereby, may pave the way for mass-production of nano-structures. Potential applications can also be found in optical microscopy, plasmonics, and nano-electronics. Microsc. Res. Tech. 78:1-7, 2015. (c) 2014 Wiley Periodicals, Inc.

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Graphene layers have been transferred directly on to paper without any intermediate layers to yield G-paper. Resistive gas sensors have been fabricated using strips of G-paper. These sensors achieved a remarkable lower limit of detection of similar to 300 parts per trillion (ppt) for NO2, which is comparable to or better than those from other paper-based sensors. Ultraviolet exposure was found to dramatically reduce the recovery time and improve response times. G-paper sensors are also found to be robust against minor strain, which was also found to increase sensitivity. G-paper is expected to enable a simple and inexpensive low-cost flexible graphene platform

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A simple colorimetric detection of melamine was studied using 15 nm (AuNPs-I), 30 nm (AuNPs-II), and 40 nm (AuNPs-III) citrate-capped gold nanoparticles (AuNPs). The AuNPs aggregated in aqueous solution in the presence of melamine, showing a visual color change from red to blue. This color change led to a shift in the absorption peak from 527 nm, 526 nm, and 525 nm to 638 nm, 626 nm, and 680 nm for AuNPs-I, AuNPs-II, and AuNPs-III, respectively. For all the three AuNPs, linearity was observed between the melamine concentration in aqueous solution and the absorbance ratios, A(638/527), A(626/525), and A(680/526), respectively. The limit of detection (LOD) for melamine for the AuNPs-II was found to be 2.37 x 10(-8) M (correlation coefficient R-2 = 0.9745), which showed better sensitivity as compared to the LOD of the AuNPs-I and AuNPs-III, which were 3.3 x 10(-8) M and 8.9 x 10(-8) M, respectively. The synthesis of AuNPs-II also involved a lower HAuCl4 concentration compared with the other two types of AuNPs, which may reduce the process cost. The AuNPs-II was selected to analyze melamine in pre-treated milk samples, and the recovery percentage was in the range of 91-106%. Thus, the efficient detection of melamine was possible using AuNPs-II for the on-site detection without the aid of expensive instruments.

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In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

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Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

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This paper reports on the effect of multiwall carbon nanotubes (CNTs) without and with chemical functionalization on the mechanical properties of Bisphenol E cyanate ester resin (BECy) based carbon fibre reinforced plastic (CFRP) laminated composites. BECy with its low viscosity, low moisture uptake and superior mechanical properties is selected for its application in CFRP laminates through the cost-effective Vacuum Assisted Resin Transfer Moulding (VARTM) process. However, unlike CNT-epoxy-CFRP composites, processing and performance issues such as dispersion of CNTs, chemical bonding with resin, functionalization effects, effects on mechanical properties, etc. for BECy-CNT-CFRP composite system are not well reported. The objective of this study is to improve the mechanical properties of BECy resin with small additions of CNTs and functionalized CNTs in CFRP laminates. CNTs and fCNTs are infused into BECy using ultrasonication and standard mixing methods. Improvements in Young's modulus and strength in tension, compression, shear, flexure and interlaminar shear strength are analysed. It is observed that addition of 0.5wt% CNTs effected for maximum mechanical properties of the resin and 1wt% CNTs for the mechanical properties of CNT-CFRP nanocomposite. Further, improvements obtained with fCNTs are marginal. Dispersion behaviour and effect of CNTs/fCNTs in load transfer corroborated with SEM pictures are presented. The enhanced mechanical properties realized in VARTM processing of BECy-CFRP laminate indicate clear advantage of CNT based modification of the process.