938 resultados para Number of petals
Resumo:
The intention of this note is to motivate the researchers to study Hadwiger's conjecture for circular arc graphs. Let η(G) denote the largest clique minor of a graph G, and let χ(G) denote its chromatic number. Hadwiger's conjecture states that η(G)greater-or-equal, slantedχ(G) and is one of the most important and difficult open problems in graph theory. From the point of view of researchers who are sceptical of the validity of the conjecture, it is interesting to study the conjecture for graph classes where η(G) is guaranteed not to grow too fast with respect to χ(G), since such classes of graphs are indeed a reasonable place to look for possible counterexamples. We show that in any circular arc graph G, η(G)less-than-or-equals, slant2χ(G)−1, and there is a family with equality. So, it makes sense to study Hadwiger's conjecture for this family.
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Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.
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In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.
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The problem of determining a minimal number of control inputs for converting a programmable logic array (PLA) with undetectable faults to crosspoint-irredundant PLA for testing has been formulated as a nonstandard set covering problem. By representing subsets of sets as cubes, this problem has been reformulated as familiar problems. It is noted that this result has significance because a crosspoint-irredundant PLA can be converted to a completely testable PLA in a straightforward fashion, thus achieving very good fault coverage and easy testability.
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It is important to identify the ``correct'' number of topics in mechanisms like Latent Dirichlet Allocation(LDA) as they determine the quality of features that are presented as features for classifiers like SVM. In this work we propose a measure to identify the correct number of topics and offer empirical evidence in its favor in terms of classification accuracy and the number of topics that are naturally present in the corpus. We show the merit of the measure by applying it on real-world as well as synthetic data sets(both text and images). In proposing this measure, we view LDA as a matrix factorization mechanism, wherein a given corpus C is split into two matrix factors M-1 and M-2 as given by C-d*w = M1(d*t) x Q(t*w).Where d is the number of documents present in the corpus anti w is the size of the vocabulary. The quality of the split depends on ``t'', the right number of topics chosen. The measure is computed in terms of symmetric KL-Divergence of salient distributions that are derived from these matrix factors. We observe that the divergence values are higher for non-optimal number of topics - this is shown by a `dip' at the right value for `t'.
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Design of speaker identification schemes for a small number of speakers (around 10) with a high degree of accuracy in controlled environment is a practical proposition today. When the number of speakers is large (say 50–100), many of these schemes cannot be directly extended, as both recognition error and computation time increase monotonically with population size. The feature selection problem is also complex for such schemes. Though there were earlier attempts to rank order features based on statistical distance measures, it has been observed only recently that the best two independent measurements are not the same as the combination in two's for pattern classification. We propose here a systematic approach to the problem using the decision tree or hierarchical classifier with the following objectives: (1) Design of optimal policy at each node of the tree given the tree structure i.e., the tree skeleton and the features to be used at each node. (2) Determination of the optimal feature measurement and decision policy given only the tree skeleton. Applicability of optimization procedures such as dynamic programming in the design of such trees is studied. The experimental results deal with the design of a 50 speaker identification scheme based on this approach.
Resumo:
Ewing sarcoma is an aggressive and poorly differentiated malignancy of bone and soft tissue. It primarily affects children, adolescents, and young adults, with a slight male predominance. It is characterized by a translocation between chromosomes 11 and 22 resulting in the EWSR1-FLI1fusion transcription factor. The aim of this study is to identify putative Ewing sarcoma target genes through an integrative analysis of three microarray data sets. Array comparative genomic hybridization is used to measure changes in DNA copy number, and analyzed to detect common chromosomal aberrations. mRNA and miRNA microarrays are used to measure expression of protein-coding and miRNA genes, and these results integrated with the copy number data. Chromosomal aberrations typically contain also bystanders in addition to the driving tumor suppressor and oncogenes, and integration with expression helps to identify the true targets. Correlation between expression of miRNAs and their predicted target mRNAs is also evaluated to assess the results of post-transcriptional miRNA regulation on mRNA levels. The highest frequencies of copy number gains were identified in chromosome 8, 1q, and X. Losses were most frequent in 9p21.3, which also showed an enrichment of copy number breakpoints relative to the rest of the genome. Copy number losses in 9p21.3 were found have a statistically significant effect on the expression of MTAP, but not on CDKN2A, which is a known tumor-suppressor in the same locus. MTAP was also down-regulated in the Ewing sarcoma cell lines compared to mesenchymal stem cells. Genes exhibiting elevated expression in association with copy number gains and up-regulation compared to the reference samples included DCAF7, ENO2, MTCP1, andSTK40. Differentially expressed miRNAs were detected by comparing Ewing sarcoma cell lines against mesenchymal stem cells. 21 up-regulated and 32 down-regulated miRNAs were identified, includingmiR-145, which has been previously linked to Ewing sarcoma. The EWSR1-FLI1 fusion gene represses miR-145, which in turn targets FLI1 forming a mutually repressive feedback loop. In addition higher expression linked to copy number gains and compared to mesenchymal stem cells, STK40 was also found to be a target of four different miRNAs that were all down-regulated in Ewing sarcoma cell lines compared to the reference samples. SLCO5A1 was identified as the only up-regulated gene within a frequently gained region in chromosome 8. This region was gained in over 90 % of the cell lines, and also with a higher frequency than the neighboring regions. In addition, SLCO5A1 was found to be a target of three miRNAs that were down-regulated compared to the mesenchymal stem cells.
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The mechanical properties of composites of polymethylmethacrylate (PMMA) with two-dimensional graphene-like boron nitride (BN) have been investigated to explore the dependence of the properties on the number of BN layers. This study demonstrates that significantly improved mechanical properties are exhibited by the composite with the fewest number of BN layers. Thus, with incorporation of three BN layers, the hardness and elastic modulus of the composite showed an increase of 125% and 130%, respectively, relative to pure PMMA. (C) 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Resumo:
Higher level of inversion is achieved with a less number of switches in the proposed scheme. The scheme proposes a five-level inverter for an open-end winding induction motor which uses only two DC-link rectifiers of voltage rating of Vdc/4, a neutral-point clamped (NPC) three-level inverter and a two-level inverter. Even though the two-level inverter is connected to the high-voltage side, it is always in square-wave operation. Since the two-level inverter is not switching in a pulse width modulated fashion and the magnitude of switching transient is only half compared to the convention three-level NPC inverter, the switching losses and electromagnetic interference is not so high. The scheme is experimentally verified on a 2.5 kW induction machine.
Resumo:
Thiobacillus ferrooxidans MAL4-1, an isolate from Malanjkhand copper mines, India, was adapted to grow in the presence of high concentration (30 gL(-1)) of Cu2+, resulting in a 15-fold increase in its tolerance to Cu2+. While wild-type T. ferrooxidans MAL4-1 contained multiple plasmids, cultures adapted to Cu2+ concentrations of 20 gL(-1) or more showed a drastic reduction in the copy number of the plasmids. The reduction for three of the plasmids was estimated to be over 50-fold. Examination of the plasmid profiles of the strains adapted to high concentration of SO42- anion (as Na2SO4 or ZnSO4) indicated that the reduction in plasmid copy number is not owing to SO42- anion, but is specific for Cu2+. The effect of mercury on the plasmids was similar to that of copper. Deadaptation of the Cu2+- Or Hg2+-adapted T. ferrooxidans resulted in restoration of the plasmids to the original level within the first passage. The fact that the plasmid copy number, in general, is drastically reduced in Cu2+-adapted T. ferrooxidans suggests that resistance to copper is chromosome mediated. This is the first report of a selective negative influence of copper ions on the copy number of plasmids in T. ferrooxidans.
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Let G be an undirected graph with a positive real weight on each edge. It is shown that the number of minimum-weight cycles of G is bounded above by a polynomial in the number of edges of G. A similar bound holds if we wish to count the number of cycles with weight at most a constant multiple of the minimum weight of a cycle of G.