278 resultados para annealing algorithm


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In WSNs the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting simultaneously. Such a situation is known as spatially correlated contention. The random access method to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration, and therefore generating an optimal or suboptimal schedule is not very useful. Additionally, if an algorithm takes very long time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. In this paper, we present a distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph. The DTSS algorithm supports unicast, multicast, and broadcast scheduling, simultaneously without any modification in the protocol. We have analyzed the protocol for average case performance and also simulated it using Castalia simulator to evaluate its runtime performance. Both analytical and simulation results show that our protocol is able to considerably reduce the time required for scheduling.

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Routing is a very important step in VLSI physical design. A set of nets are routed under delay and resource constraints in multi-net global routing. In this paper a delay-driven congestion-aware global routing algorithm is developed, which is a heuristic based method to solve a multi-objective NP-hard optimization problem. The proposed delay-driven Steiner tree construction method is of O(n(2) log n) complexity, where n is the number of terminal points and it provides n-approximation solution of the critical time minimization problem for a certain class of grid graphs. The existing timing-driven method (Hu and Sapatnekar, 2002) has a complexity O(n(4)) and is implemented on nets with small number of sinks. Next we propose a FPTAS Gradient algorithm for minimizing the total overflow. This is a concurrent approach considering all the nets simultaneously contrary to the existing approaches of sequential rip-up and reroute. The algorithms are implemented on ISPD98 derived benchmarks and the drastic reduction of overflow is observed. (C) 2014 Elsevier Inc. All rights reserved.

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Pure alpha-Al2O3 exhibits a very high degree of thermodynamical stability among all metal oxides and forms an inert oxide scale in a range of structural alloys at high temperatures. We report that amorphous Al2O3 thin films sputter deposited over crystalline Si instead show a surprisingly active interface. On annealing, crystallization begins with nuclei of a phase closely resembling gamma-Alumina forming almost randomly in an amorphous matrix, and with increasing frequency near the substrate/film interface. This nucleation is marked by the signature appearance of sharp (400) and (440) reflections and the formation of a diffuse diffraction halo with an outer maximal radius of approximate to 0.23 nm enveloping the direct beam. The microstructure then evolves by a cluster-coalescence growth mechanism suggestive of swift nucleation and sluggish diffusional kinetics, while locally the Al ions redistribute slowly from chemisorbed and tetrahedral sites to higher anion coordinated sites. Chemical state plots constructed from XPS data and simple calculations of the diffraction patterns from hypothetically distorted lattices suggest that the true origins of the diffuse diffraction halo are probably related to a complex change in the electronic structure spurred by the a-gamma transformation rather than pure structural disorder. Concurrent to crystallization within the film, a substantially thick interfacial reaction zone also builds up at the film/substrate interface with the excess Al acting as a cationic source. (C) 2015 AIP Publishing LLC.

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Given a function from Z(n) to itself one can determine its polynomial representability by using Kempner function. In this paper we present an alternative characterization of polynomial functions over Z(n) by constructing a generating set for the Z(n)-module of polynomial functions. This characterization results in an algorithm that is faster on average in deciding polynomial representability. We also extend the characterization to functions in several variables. (C) 2015 Elsevier B.V. All rights reserved.

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A new successive displacement type load flow method is developed in this paper. This algorithm differs from the conventional Y-Bus based Gauss Seidel load flow in that the voltages at each bus is updated in every iteration based on the exact solution of the power balance equation at that node instead of an approximate solution used by the Gauss Seidel method. It turns out that this modified implementation translates into only a marginal improvement in convergence behaviour for obtaining load flow solutions of interconnected systems. However it is demonstrated that the new approach can be adapted with some additional refinements in order to develop an effective load flow solution technique for radial systems. Numerical results considering a number of systems-both interconnected and radial, are provided to validate the proposed approach.

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The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

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We consider nonparametric sequential hypothesis testing problem when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to a general family of distributions. We propose a simple algorithm to address the problem. Its performance is analysed and asymptotic properties are proved. The simulated and analysed performance of the algorithm is compared with an earlier algorithm addressing the same problem with similar assumptions. Finally, we provide a justification for our model motivated by a Cognitive Radio scenario and modify the algorithm for optimizing performance when information about the prior probabilities of occurrence of the two hypotheses is available.

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The present study addresses the evolution of texture and microstructure during annealing in a cryorolled copper. Transition from copper to brass texture during the cryo-rolling has been illustrated. Twinning and interaction between twins and shear bands have been found to play the important role in grain refinement and strengthening. The low temperature vacancy clustering and its effect on the recrystallization have been experimentally demonstrated. Fine scale twinning, and grain refinement have been attributed to the higher yield strength found in the case of samples subjected to cryo-rolling. (C) 2015 Elsevier B.V. All rights reserved.

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In this paper, sensing coverage by wireless camera-embedded sensor networks (WCSNs), a class of directional sensors is studied. The proposed work facilitates the autonomous tuning of orientation parameters and displacement of camera-sensor nodes in the bounded field of interest (FoI), where the network coverage in terms of every point in the FoI is important. The proposed work is first of its kind to study the problem of maximizing coverage of randomly deployed mobile WCSNs which exploits their mobility. We propose an algorithm uncovered region exploration algorithm (UREA-CS) that can be executed in centralized and distributed modes. Further, the work is extended for two special scenarios: 1) to suit autonomous combing operations after initial random WCSN deployments and 2) to improve the network coverage with occlusions in the FoI. The extensive simulation results show that the performance of UREA-CS is consistent, robust, and versatile to achieve maximum coverage, both in centralized and distributed modes. The centralized and distributed modes are further analyzed with respect to the computational and communicational overheads.

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We address the problem of separating a speech signal into its excitation and vocal-tract filter components, which falls within the framework of blind deconvolution. Typically, the excitation in case of voiced speech is assumed to be sparse and the vocal-tract filter stable. We develop an alternating l(p) - l(2) projections algorithm (ALPA) to perform deconvolution taking into account these constraints. The algorithm is iterative, and alternates between two solution spaces. The initialization is based on the standard linear prediction decomposition of a speech signal into an autoregressive filter and prediction residue. In every iteration, a sparse excitation is estimated by optimizing an l(p)-norm-based cost and the vocal-tract filter is derived as a solution to a standard least-squares minimization problem. We validate the algorithm on voiced segments of natural speech signals and show applications to epoch estimation. We also present comparisons with state-of-the-art techniques and show that ALPA gives a sparser impulse-like excitation, where the impulses directly denote the epochs or instants of significant excitation.

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In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

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The time division multiple access (TDMA) based channel access mechanisms perform better than the contention based channel access mechanisms, in terms of channel utilization, reliability and power consumption, specially for high data rate applications in wireless sensor networks (WSNs). Most of the existing distributed TDMA scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA scheduling algorithms is to improve the channel utilization by generating a schedule of smaller length. But, they usually take longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a novel scheme for TDMA scheduling in WSNs, which can generate a compact schedule similar to static scheduling algorithms, while its runtime performance can be matched with those of dynamic scheduling algorithms. Furthermore, the proposed distributed TDMA scheduling algorithm has the capability to trade-off schedule length with the time required to generate the schedule. This would allow the developers of WSNs, to tune the performance, as per the requirement of prevalent WSN applications, and the requirement to perform re-scheduling. Finally, the proposed TDMA scheduling is fault-tolerant to packet loss due to erroneous wireless channel. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA schedule. Simulation results show that the proposed algorithm generates a compact schedule in a very less time.

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A new automatic algorithm for the assessment of mixed mode crack growth rate characteristics is presented based on the concept of an equivalent crack. The residual ligament size approach is introduced to implementation this algorithm for identifying the crack tip position on a curved path with respect to the drop potential signal. The automatic algorithm accounting for the curvilinear crack trajectory and employing an electrical potential difference was calibrated with respect to the optical measurements for the growing crack under cyclic mixed mode loading conditions. The effectiveness of the proposed algorithm is confirmed by fatigue tests performed on ST3 steel compact tension-shear specimens in the full range of mode mixities from pure mode Ito pure mode II. (C) 2015 Elsevier Ltd. All rights reserved.

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8mol% yttria-stabilized zirconia (8YSZ) is an extensively studied solid electrolyte. But there is no consistency in the reported ionic conductivity values of 8YSZ thin films. Interfacial segregation in YSZ thin films can affect its ionic conductivity by locally altering the surface chemistry. This article presents the effects of annealing temperature and film thickness on free surface yttria segregation behavior in 8YSZ thin film by Angle Resolved XPS and its influence on the ionic conductivity of sputtered 8YSZ thin films. Surface yttria concentration of about 32, 20, and 9mol% have been found in 40nm 8YSZ films annealed at 1273, 1173, and 1073K, respectively. Yttria segregation is found to increase with increase in annealing temperature and film thickness. Ionic conductivities of 0.23, 0.16, and 0.08Scm(-1) are observed at 923K for 40nm 8YSZ films annealed at 1073, 1173, and 1273K, respectively. The decrease in conductivity with increase in annealing temperature is attributed to the increased yttria segregation with annealing. Neither segregation nor film thickness is found to affect the activation energy of oxygen ion conduction. Target purity is found to play a key role in determining free surface yttria segregation in 8YSZ thin films.

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Amorphous Silicon Germanium (a-SiGe) thin films of 500 nm thickness are deposited on silicon substrates using Plasma Enhanced Chemical Vapour Deposition (PECVD). To obtain polycrystalline nature of films, thermal annealing is done at various temperature (450-600 degrees C) and time (1-10 h). The surface morphology of the pre- and post-annealed films is investigated using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The crystallographic structure of the film is obtained by X-ray diffraction method. Raman spectroscopy is carried out to quantify the Ge concentration and the degree of strain relaxation in the film. Nano-indentation is performed to obtain the mechanical properties of the film. It is found that annealing reduces the surface roughness of the film and increases the Ge concentration in the film. The grain size of the film increases with increase in annealing temperature. The grain size is found to decrease with increase in annealing time up to 5 h and then increased. The results show that 550 degrees C for 5 h is the critical annealing condition for variation of structural and mechanical properties of the film. Recrystallization starts at this condition and results in finer grains. An increase in hardness value of 7-8 GPa has been observed. Grain growth occurs above this critical annealing condition and degrades the mechanical properties of the film. The strain in the film is only relaxed to about 55% even for 10 h of annealing at 600 degrees C. Transmission Electron Microscopy (TEM) observations show that the strain relaxation occurs by forming misfit dislocations and these dislocations are confined to the SiGe/Si interface. (C) 2015 Elsevier Ltd. All rights reserved.