9,594 research outputs found

    Asymmetric-valued Spectrum Auction and Competition in Wireless Broadband Services

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    We study bidding and pricing competition between two spiteful mobile network operators (MNOs) with considering their existing spectrum holdings. Given asymmetric-valued spectrum blocks are auctioned off to them via a first-price sealed-bid auction, we investigate the interactions between two spiteful MNOs and users as a three-stage dynamic game and characterize the dynamic game's equilibria. We show an asymmetric pricing structure and different market share between two spiteful MNOs. Perhaps counter-intuitively, our results show that the MNO who acquires the less-valued spectrum block always lowers his service price despite providing double-speed LTE service to users. We also show that the MNO who acquires the high-valued spectrum block, despite charing a higher price, still achieves more market share than the other MNO. We further show that the competition between two MNOs leads to some loss of their revenues. By investigating a cross-over point at which the MNOs' profits are switched, it serves as the benchmark of practical auction designs

    Hodge ideals and spectrum of isolated hypersurface singularities

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    We introduce Hodge ideal spectrum for isolated hypersurface singularities to see the difference between the Hodge ideals and the microlocal VV-filtration modulo the Jacobian ideal. Via the Tjurina subspectrum, we can compare the Hodge ideal spectrum with the Steenbrink spectrum which can be defined by the microlocal VV-filtration. As a consequence of a formula of Mustata and Popa, these two spectra coincide in the weighted homogeneous case. We prove sufficient conditions for their coincidence and non-coincidence in some non-weighted-homogeneous cases where the defining function is semi-weighted-homogeneous or with non-degenerate Newton boundary in most cases. We also show that the convenience condition can be avoided in a formula of Zhang for the non-degenerate case, and present an example where the Hodge ideals are not weakly decreasing even modulo the Jacobian ideal.Comment: 29 page

    Comparing Sample-wise Learnability Across Deep Neural Network Models

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    Estimating the relative importance of each sample in a training set has important practical and theoretical value, such as in importance sampling or curriculum learning. This kind of focus on individual samples invokes the concept of sample-wise learnability: How easy is it to correctly learn each sample (cf. PAC learnability)? In this paper, we approach the sample-wise learnability problem within a deep learning context. We propose a measure of the learnability of a sample with a given deep neural network (DNN) model. The basic idea is to train the given model on the training set, and for each sample, aggregate the hits and misses over the entire training epochs. Our experiments show that the sample-wise learnability measure collected this way is highly linearly correlated across different DNN models (ResNet-20, VGG-16, and MobileNet), suggesting that such a measure can provide deep general insights on the data's properties. We expect our method to help develop better curricula for training, and help us better understand the data itself.Comment: Accepted to AAAI 2019 Student Abstrac

    Batalin-Tyutin Quantization of the Chiral Schwinger Model

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    We quantize the chiral Schwinger Model by using the Batalin-Tyutin formalism. We show that one can systematically construct the first class constraints and the desired involutive Hamiltonian, which naturally generates all secondary constraints. For a>1a>1, this Hamiltonian gives the gauge invariant Lagrangian including the well-known Wess-Zumino terms, while for a=1a=1 the corresponding Lagrangian has the additional new type of the Wess-Zumino terms, which are irrelevant to the gauge symmetry.Comment: 15 pages, latex, no figures, to be published in Z. Phys. C (1995

    Flow-Induced Voltage Generation Over Monolayer Graphene in the Presence of Herringbone Grooves

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    While flow-induced voltage over a graphene layer has been reported, its origin remains unclear. In our previous study, we suggested different mechanisms for different experimental configurations: phonon dragging effect for the parallel alignment and an enhanced out-of-plane phonon mode for the perpendicular alignment (Appl. Phys. Lett. 102:063116, 2011). In order to further examine the origin of flow-induced voltage, we introduced a transverse flow component by integrating staggered herringbone grooves in the microchannel. We found that the flow-induced voltage decreased significantly in the presence of herringbone grooves in both parallel and perpendicular alignments. These results support our previous interpretation

    Microstructure and adhesion characteristics of a silver nanopaste screen-printed on Si substrate

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    The microstructural evolution and the adhesion of an Ag nanopaste screen-printed on a silicon substrate were investigated as a function of sintering temperature. Through the two thermal analysis methods, such as differential scanning calorimeter and thermo-gravimetric analysis, the sintering conditions were defined where the temperature was raised from 150°C to 300°C, all with a fixed sintering time of 30 min. The microstructure and the volume of the printed Ag nanopaste were observed using a field emission scanning electron microscope and a 3-D surface profiler, respectively. The apparent density of the printed Ag nanopaste was calculated depending on the sintering conditions, and the adhesion was evaluated by a scratch test. As the sintering temperature increased from 150°C to 300°C, the apparent density and the adhesion increased by 22.7% and 43%, respectively. It is confirmed that the printed Ag nanopaste sintered at higher temperatures showed higher apparent density in the microstructural evolution and void aggregation, resulting in the lower electrical resistivity and various scratched fractures
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