40 resultados para nest location


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We propose a distribution-free approach to the study of random geometric graphs. The distribution of vertices follows a Poisson point process with intensity function n f(center dot), where n is an element of N, and f is a probability density function on R-d. A vertex located at x connects via directed edges to other vertices that are within a cut-off distance r(n)(x). We prove strong law results for (i) the critical cut-off function so that almost surely, the graph does not contain any node with out-degree zero for sufficiently large n and (ii) the maximum and minimum vertex degrees. We also provide a characterization of the cut-off function for which the number of nodes with out-degree zero converges in distribution to a Poisson random variable. We illustrate this result for a class of densities with compact support that have at most polynomial rates of decay to zero. Finally, we state a sufficient condition for an enhanced version of the above graph to be almost surely connected eventually.

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A wave-based method is developed to quantify the defect due to porosity and also to locate the porous regions, in a composite beam-type structure. Wave propagation problem for a porous laminated composite beam is modeled using spectral finite element method (SFEM), based on the modified rule of mixture approach, which is used to include the effect of porosity on the stiffness and density of the composite beam structure. The material properties are obtained from the modified rule of mixture model, which are used in a conventional SFEM to develop a new model for solving wave propagation problems in porous laminated composite beam. The influence of the porosity content on the group speed and also the effect of variation in theses parameters on the time responses are studied first, in the forward problem. The change in the time responses with the change in the porosity of the structure is used as a parameter to find the porosity content in a composite beam. The actual measured response from a structure and the numerically obtained time responses are used for the estimation of porosity, by solving a nonlinear optimization problem. The effect of the length of the porous region (in the propagation direction), on the time responses, is studied. The damage force indicator technique is used to locate the porous region in a beam and also to find its length, using the measured wave propagation responses. (C) 2012 Elsevier Ltd. All rights reserved.

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This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

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This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

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How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

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Hornbills, among the largest and most threatened tropical frugivores, provide important seed dispersal services. Hornbill nest site characteristics are known primarily from wet tropical forests. Nests of the Indian grey hornbill Ocyceros birostris and Oriental pied hornbill Anthracoceros albirostris were characterized in a tropical dry forest. Despite A. albirostris being twice the size of O. birostris, few of the nest cavity attributes were different. A. albirostris nests were surrounded by higher proportion of mixed forest and lower sal forest compared to O. birostris. In this landscape, the larger A. albirostris may prefer to nest in sites with more food plants compared to the smaller O. birostris.

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In order to obtain better materials, control over the precise location of nanoparticles is indispensable. It is shown here that ordered arrangements of nanoparticles, possessing different characteristics (electrical/ magnetic dipoles), in the blend structure can result in excellent microwave absorption. This is manifested from a high reflection loss of ca. -67 dB for the best blend structure designed here. To attenuate electromagnetic radiation, the key parameters of high electrical conductivity and large dielectric/magnetic loss are targeted here by including a conductive material multiwall carbon nanotubes, MWNTs], ferroelectric nanostructured material with associated relaxations in the GHz frequency barium titanate, BT] and lossy ferromagnetic nanoparticles nickel ferrite, NF]. In this study, bi-continuous structures were designed using 50/50 (by wt) blends of polycarbonate (PC) and polyvinylidene fluoride (PVDF). The MWNTs were modified using an electron acceptor molecule, a derivative of perylenediimide, which facilitates p-p stacking with the nanotubes and stimulates efficient charge transport in the blends. The nanoscopic materials have specific affinity towards the PVDF phase. Hence, by introducing surface-active groups, an ordered arrangement can be tailored. To accomplish this, both BT and NF were first hydroxylated followed by the introduction of amine-terminal groups on the surface. The latter facilitated nucleophilic substitution reactions with PC and resulted in their precise location. In this study, we have shown for the first time that by a compartmentalized approach, superior EM attenuation can be achieved. For instance, when the nanoparticles were localized exclusively in the PVDF phase or in both the phases, the minimum reflection losses were ca. -18 dB (for the MWNT/BT mixture) and -29 dB (for the MWNT/NF mixture), and the shielding occurred primarily through reflection. Interestingly, by adopting the compartmentalized approach wherein the lossy materials were in the PC phase and the conductive materials (MWNT) were in the PVDF phase, outstanding reflection losses of ca. -57 dB (for the BT and MWNT combination) and -67 dB (for the NF and MWNT combination) were noted and the shielding occurred primarily through absorption. Thus, the approach demonstrates that nanoscopic structuring in the blends can be achieved under macroscopic processing conditions and this strategy can further be explored to design microwave absorbers.

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The tropical easterly jet (TEJ) is a prominent atmospheric circulation feature observed during the Asian summer monsoon. It is generally assumed that sensible heating over the Tibetan Plateau directly influences the location of the TEJ. However, other studies have suggested the importance of latent heating in determining the jet location. In this paper, the relative importance of latent heating on the maintenance of the TEJ is explored through simulations with a general circulation model. The simulation of the TEJ by the Community Atmosphere Model, version 3.1 is discussed in detail. These simulations showed that the location of the TEJ is well correlated with the location of the precipitation. Significant zonal shifts in the location of the precipitation resulted in similar shifts in the zonal location of the TEJ. These zonal shifts had minimal effect on the large-scale structure of the jet. Further, provided that precipitation patterns were relatively unchanged, orography did not directly impact the location of the TEJ. These changes were robust even with changes in the cumulus parameterization. This suggests the potential important role of latent heating in determining the location and structure of the TEJ. These results were used to explain the significant differences in the zonal location of the TEJ in the years 1988 and 2002. To understand the contribution of the latitudinal location of latent heating on the strength of the TEJ, aqua-planet simulations were carried out. It has been shown that for similar amounts of net latent heating, the jet is stronger when heating is in the higher tropical latitudes. This may partly explain the reason for the jet to be very strong during the JJA monsoon season.