1,764 research outputs found

    Learning Transferable Architectures for Scalable Image Recognition

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    Developing neural network image classification models often requires significant architecture engineering. In this paper, we study a method to learn the model architectures directly on the dataset of interest. As this approach is expensive when the dataset is large, we propose to search for an architectural building block on a small dataset and then transfer the block to a larger dataset. The key contribution of this work is the design of a new search space (the "NASNet search space") which enables transferability. In our experiments, we search for the best convolutional layer (or "cell") on the CIFAR-10 dataset and then apply this cell to the ImageNet dataset by stacking together more copies of this cell, each with their own parameters to design a convolutional architecture, named "NASNet architecture". We also introduce a new regularization technique called ScheduledDropPath that significantly improves generalization in the NASNet models. On CIFAR-10 itself, NASNet achieves 2.4% error rate, which is state-of-the-art. On ImageNet, NASNet achieves, among the published works, state-of-the-art accuracy of 82.7% top-1 and 96.2% top-5 on ImageNet. Our model is 1.2% better in top-1 accuracy than the best human-invented architectures while having 9 billion fewer FLOPS - a reduction of 28% in computational demand from the previous state-of-the-art model. When evaluated at different levels of computational cost, accuracies of NASNets exceed those of the state-of-the-art human-designed models. For instance, a small version of NASNet also achieves 74% top-1 accuracy, which is 3.1% better than equivalently-sized, state-of-the-art models for mobile platforms. Finally, the learned features by NASNet used with the Faster-RCNN framework surpass state-of-the-art by 4.0% achieving 43.1% mAP on the COCO dataset

    Particle Motion and Scalar Field Propagation in Myers-Perry Black Hole Spacetimes in All Dimensions

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    We study separability of the Hamilton-Jacobi and massive Klein-Gordon equations in the general Myers-Perry black hole background in all dimensions. Complete separation of both equations is carried out in cases when there are two sets of equal black hole rotation parameters, which significantly enlarges the rotational symmetry group. We explicitly construct a nontrivial irreducible Killing tensor associated with the enlarged symmetry group which permits separation. We also derive first-order equations of motion for particles in these backgrounds and examine some of their properties.Comment: 16 pages, LaTeX2

    A stochastic model on the mean time to recruitment for a two graded manpower system associated with a univariate policy of recruitment involving combined thresholds using same geometric process for inter-decesion times

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    In this paper, an organization with two grades subjected to loss of manpower due to the policy decisions taken by the organization is considered. A mathematical model is constructed and an appropriate univariate recruitment policy, based on shock model approach involving combined optional thresholds and combined mandatory thresholds for the loss of manpower in the organization is suggested. The expected time for recruitment is obtained for different cases on the distribution of the thresholds when (i) the loss of manpower forms a sequence of independent and identically distributed exponential random variables and (ii) the inter-decision times for the two grades form the same geometric process. The analytical results are substantiated by numerical illustrations and relevant conclusions are presented

    Synthesis, Crystal Structure and Photophysical Properties of Lanthanide Coordination Polymers of 4- 4-(9H-Carbazol-9-Yl)Butoxy Benzoate: The Effect of Bidentate Nitrogen Donors on Luminescence

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    A new aromatic carboxylate ligand, 4-[4-(9H-carbazol-9-yl)butoxy]benzoic acid (HL), has been synthesized by the replacement of the hydroxyl hydrogen of 4-hydroxy benzoic acid with a 9-butyl-9H-carbazole moiety. The anion derived from HL has been used for the support of a series of lanthanide coordination compounds [Ln = Eu (1), Gd (2) and Tb (3)]. The new lanthanide complexes have been characterized by a variety of spectroscopic techniques. Complex 3 was structurally authenticated by single-crystal X-ray diffraction and found to exist as a solvent-free 1D coordination polymer with the formula [Tb(L)(3)](n). The structural data reveal that the terbium atoms in compound 3 reside in an octahedral ligand environment that is somewhat unusual for a lanthanide. It is interesting to note that each carboxylate group exhibits only a bridging-bidentate mode, with a complete lack of more complex connectivities that are commonly observed for extended lanthanide-containing solid-state structures. Examination of the packing diagram for 3 revealed the existence of two-dimensional molecular arrays held together by means of CH-pi interactions. Aromatic carboxylates of the lanthanides are known to exhibit highly efficient luminescence, thus offering the promise of applicability as optical devices. However, due to difficulties that arise on account of their polymeric nature, their practical application is somewhat limited. Accordingly, synthetic routes to discrete molecular species are highly desirable. For this purpose, a series of ternary lanthanide complexes was designed, synthesized and characterized, namely [Eu(L)(3)(phen)] (4), [Eu(L)(3)(tmphen)] (5), [Tb(L)(3)(phen)] (6) and [Tb(L)(3)(tmphen)] (7) (phen = 1,10-phenanthroline and tmphen = 3,4,7,8-tetramethyl-1,10-phenanthroline). The photophysical properties of the foregoing complexes in the solid state at room temperature have been investigated. The quantum yields of the ternary complexes 4 (9.65%), 5 (21.00%), 6 (14.07%) and 7 (32.42%), were found to be significantly enhanced in the presence of bidentate nitrogen donors when compared with those of the corresponding binary compounds 1 (0.11%) and 3 (1.45%). Presumably this is due to effective energy transfer from the ancillary ligands.Council of Scientific and Industrial Research (CSIR-TAPSUN Project) SSL, NWP-55CSIR, New DelhiRobert A. Welch Foundation F-0003Chemistr

    Variance of the Time to Recruitment in an Organization with Two Grades

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    In this paper, a two grade organization subjected to random exit of personal due to policy decisions taken by the organization is considered. There is an associated loss of manpower if a person quits. As the exit of personnel is unpredictable, a new recruitment policy involving two thresholds for each grade-one is optional and the other mandatory is suggested to enable the organization to plan its decision on recruitment. Based on shock model approach two mathematical models are constructed using an appropriate univariate policy of recruitment. Performance measures namely mean and variance of the time to recruitment are obtained for both the models when (i) the loss of manhours process forms a sequence of independent and identically distributed exponential random variables (ii) the inter-decision times are independent and identically distributed exponential random variables and (iii) the optional and mandatory thresholds are exponential random variables. The analytical results are substantiated by numerical illustrations and the influence of nodal parameters on the performance measures is also analyzed
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