119 resultados para Hand-drawn concept map


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This paper deals with a batch service queue and multiple vacations. The system consists of a single server and a waiting room of finite capacity. Arrival of customers follows a Markovian arrival process (MAP). The server is unavailable for occasional intervals of time called vacations, and when it is available, customers are served in batches of maximum size ‘b’ with a minimum threshold value ‘a’. We obtain the queue length distributions at various epochs along with some key performance measures. Finally, some numerical results have been presented.

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We consider diffusively coupled map lattices with P neighbors (where P is arbitrary) and study the stability of the synchronized state. We show that there exists a critical lattice size beyond which the synchronized state is unstable. This generalizes earlier results for nearest neighbor coupling. We confirm the analytical results by performing numerical simulations on coupled map lattices with logistic map at each node. The above analysis is also extended to two-dimensional P-neighbor diffusively coupled map lattices.

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The hot deformation behaviour of Mg–3Al alloy has been studied using the processing-map technique. Compression tests were conducted in the temperature range 250–550 °C and strain rate range 3 × 10−4 to 102 s−1 and the flow stress data obtained from the tests were used to develop the processing map. The various domains in the map corresponding to different dissipative characteristics have been identified as follows: (i) grain boundary sliding (GBS) domain accommodated by slip controlled by grain boundary diffusion at slow strain-rates (<10−3 s−1) in the temperature range from 350 to 450 °C, (ii) two different dynamic recrystallization (DRX) domains with a peak efficiency of 42% at 550 °C/10−1 s−1 and 425 °C/102 s−1 governed by stress-assisted cross-slip and thermally activated climb as the respective rate controlling mechanisms and (iii) dynamic recovery (DRV) domain below 300 °C in the intermediate strain rate range from 3 × 10−2 to 3 × 10−1 s−1. The regimes of flow instability have also been delineated in the processing map using an instability criterion. Adiabatic shear banding at higher strain rates (>101 s−1) and solute drag by substitutional Al atoms at intermediate strain rates (3 × 10−2 to 3 × 10−1 s−1) in the temperature range (350–450 °C) are responsible for flow instability. The relevance of these mechanisms with reference to hot working practice of the material has been indicated. The processing maps of Mg–3Al alloy and as-cast Mg have been compared qualitatively to elucidate the effect of alloying with aluminum on the deformation behaviour of magnesium.

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We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

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We study the responses of a cultured neural network when it is exposed to epileptogenesis glutamate injury causing epilepsy and subsequent treatment with phenobarbital by constructing connectivity map of neurons using correlation matrix. This study is particularly useful in understanding the pharmaceutical drug induced changes in the neuronal network properties with insights into changes at the systems biology level. (C) 2010 American Institute of Physics. [doi:10.1063/1.3398025]

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We view association of concepts as a complex network and present a heuristic for clustering concepts by taking into account the underlying network structure of their associations. Clusters generated from our approach are qualitatively better than clusters generated from the conventional spectral clustering mechanism used for graph partitioning.

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Non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with hundreds of dimensions has been a challenge. In this paper, we present a probabilistic data association (PDA) based algorithm for decoding non-orthogonal STBCs with large dimensions. Our simulation results show that the proposed PDA-based algorithm achieves near SISO AWGN uncoded BER as well as near-capacity coded BER (within 5 dB of the theoretical capacity) for large non-orthogonal STBCs from CDA. We study the effect of spatial correlation on the BER, and show that the performance loss due to spatial correlation can be alleviated by providing more receive spatial dimensions. We report good BER performance when a training-based iterative decoding/channel estimation is used (instead of assuming perfect channel knowledge) in channels with large coherence times. A comparison of the performances of the PDA algorithm and the likelihood ascent search (LAS) algorithm (reported in our recent work) is also presented.

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A two-stage iterative algorithm for selecting a subset of a training set of samples for use in a condensed nearest neighbor (CNN) decision rule is introduced. The proposed method uses the concept of mutual nearest neighborhood for selecting samples close to the decision line. The efficacy of the algorithm is brought out by means of an example.

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The conformational analysis of a pair of two-linked peptide units in the anti-parallel arrangement is reported here with a view to study the effect of association of one chain with the other. The pair of two-linked peptide units were fixed in space through the hydrogen bonds between them, in accordance with certain hydrogen bond criteria. Model building was undertaken to ascertain whether the proximity of the side-chains could be used to eliminate any one of the right-hand twisted, left-hand twisted or regular β-structures. Stereochemically, it was found possible with all of them. The preference for a right-hand twisted β-structure, however, was indicated by the classical energy calculations. The relevance of the results thus obtained is discussed in the context of the preferential right-hand twist of the β-pleated sheets present in globular proteins. The agreement between the minimum energy conformations obtained for the pair of two-linked peptide units and the globular protein data is also indicated.

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A method for determining the mutual nearest neighbours (MNN) and mutual neighbourhood value (mnv) of a sample point, using the conventional nearest neighbours, is suggested. A nonparametric, hierarchical, agglomerative clustering algorithm is developed using the above concepts. The algorithm is simple, deterministic, noniterative, requires low storage and is able to discern spherical and nonspherical clusters. The method is applicable to a wide class of data of arbitrary shape, large size and high dimensionality. The algorithm can discern mutually homogenous clusters. Strong or weak patterns can be discerned by properly choosing the neighbourhood width.

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A nonparametric, hierarchical, disaggregative clustering algorithm is developed using a novel similarity measure, called the mutual neighborhood value (MNV), which takes into account the conventional nearest neighbor ranks of two samples with respect to each other. The algorithm is simple, noniterative, requires low storage, and needs no specification of the expected number of clusters. The algorithm appears very versatile as it is capable of discerning spherical and nonspherical clusters, linearly nonseparable clusters, clusters with unequal populations, and clusters with lowdensity bridges. Changing of the neighborhood size enables discernment of strong or weak patterns.

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It has been shown in an earlier paper that I-realizability of a unate function F of up to six variables corresponds to ' compactness ' of the plot of F on a Karnaugh map. Here, an algorithm has been presented to synthesize on a Karnaugh map a non-threahold function of up to Bix variables with the minimum number of threshold gates connected in cascade. Incompletely specified functions can also be treated. No resort to inequalities is made and no pre-processing (such as positivizing and ordering) of the given switching function is required.

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A new language concept for high-level distributed programming is proposed. Programs are organised as a collection of concurrently executing processes. Some of these processes, referred to as liaison processes, have a monitor-like structure and contain ports which may be invoked by other processes for the purposes of synchronisation and communication. Synchronisation is achieved by conditional activation of ports and also through port control constructs which may directly specify the execution ordering of ports. These constructs implement a path-expression-like mechanism for synchronisation and are also equipped with options to provide conditional, non-deterministic and priority ordering of ports. The usefulness and expressive power of the proposed concepts are illustrated through solutions of several representative programming problems. Some implementation issues are also considered.