An accurate retrieval through R-MAC+ descriptors for landmark recognition

The landmark recognition problem is far from being solved, but with the use of features extracted from intermediate layers of Convolutional Neural Networks (CNNs), excellent results have been obtained. In this work, we propose some improvements on the creation of R-MAC descriptors in order to make the newly-proposed R-MAC+ descriptors more representative than the previous ones. However, the main contribution of this paper is a novel retrieval technique, that exploits the fine representativeness of the MAC descriptors of the database images. Using this descriptors called "db regions" during the retrieval stage, the performance is greatly improved. The proposed method is tested on different public datasets: Oxford5k, Paris6k and Holidays. It outperforms the state-of-the- art results on Holidays and reached excellent results on Oxford5k and Paris6k, overcame only by approaches based on fine-tuning strategies

On the Exploitation of Admittance Measurements for Wired Network Topology Derivation

The knowledge of the topology of a wired network is often of fundamental importance. For instance, in the context of Power Line Communications (PLC) networks it is helpful to implement data routing strategies, while in power distribution networks and Smart Micro Grids (SMG) it is required for grid monitoring and for power flow management. In this paper, we use the transmission line theory to shed new light and to show how the topological properties of a wired network can be found exploiting admittance measurements at the nodes. An analytic proof is reported to show that the derivation of the topology can be done in complex networks under certain assumptions. We also analyze the effect of the network background noise on admittance measurements. In this respect, we propose a topology derivation algorithm that works in the presence of noise. We finally analyze the performance of the algorithm using values that are typical of power line distribution networks.Comment: A version of this manuscript has been submitted to the IEEE Transactions on Instrumentation and Measurement for possible publication. The paper consists of 8 pages, 11 figures, 1 tabl

Real Business Cycles with Cournot Competition and Endogenous Entry

We introduce Cournot competition and endogenous entry in an oth- erwise neoclassical macroeconomic framework. First, we develop a model with exogenous savings à la Solow describing the dynamic path of busi- ness creation. Then, we develop a model à la Ramsey describing the dynamic interaction of consumption and business creation. Our models are able to explain why markups vary countercylically and pro?ts are procyclical. The analysis of permanent and temporary technology and preference shocks and of the second moments suggests that our model can outperform the Real Business Cycle framework in many dimensions.

Endogenous Market Structure and the Business Cycle

We introduce endogenous strategic interactions under competition in quantities and in prices together with endogenous entry in a dynamic stochastic general equilibrium model with flexible prices. The endogenous mark ups depend on the form of competition and on the degree of substitutability between goods, and they vary countercylically while profits are procyclical. Positive temporary shocks to productivity and government spending attract entry. Entry strengthens competition between firms, which temporary reduces mark ups and prices: this creates an intertemporal substitution effect which provides an extra boost to consumption. The model outperforms the standard RBC framework in matching impulse response functions and second moments for US data.Endogenous Market Structure, Firms?Entry, Business Cycle

Recent Developments in Productivity and the Role of Entrepreneurship in Italy: An Industry View

This paper explores the existing interplay between productivity trends across Italian industries, in the decade 1995-2005, and entrepreneurship, highlighting the urgent need for a revival in entrepreneurial capital in some industries. Initially, we consider as a measure of entrepreneurship the birth rates for different industries; this proxy proved to be a significant explanatory variable of a sector’s efficiency. We then attempt to extract a measure of managerial ability directly from the data, considering it as an unobservable and using Bayesian techniques to perform the estimation, which further reinforces the previous results.entrepreneurship, productivity growth, stochastic frontiers, Bayesian analysis, Gibbs sampling.

Quality-Aware Broadcasting Strategies for Position Estimation in VANETs

The dissemination of vehicle position data all over the network is a fundamental task in Vehicular Ad Hoc Network (VANET) operations, as applications often need to know the position of other vehicles over a large area. In such cases, inter-vehicular communications should be exploited to satisfy application requirements, although congestion control mechanisms are required to minimize the packet collision probability. In this work, we face the issue of achieving accurate vehicle position estimation and prediction in a VANET scenario. State of the art solutions to the problem try to broadcast the positioning information periodically, so that vehicles can ensure that the information their neighbors have about them is never older than the inter-transmission period. However, the rate of decay of the information is not deterministic in complex urban scenarios: the movements and maneuvers of vehicles can often be erratic and unpredictable, making old positioning information inaccurate or downright misleading. To address this problem, we propose to use the Quality of Information (QoI) as the decision factor for broadcasting. We implement a threshold-based strategy to distribute position information whenever the positioning error passes a reference value, thereby shifting the objective of the network to limiting the actual positioning error and guaranteeing quality across the VANET. The threshold-based strategy can reduce the network load by avoiding the transmission of redundant messages, as well as improving the overall positioning accuracy by more than 20% in realistic urban scenarios.Comment: 8 pages, 7 figures, 2 tables, accepted for presentation at European Wireless 201

Exact two-body quantum dynamics of an electron-hole pair in semiconductor coupled quantum wells: a time-dependent approach

We simulate the time-dependent coherent dynamics of a spatially indirect exciton (an electron-hole pair with the two particles confined in different layers) in a GaAs coupled quantum well system. We use a unitary wave-packet propagation method taking into account in full the four degrees of freedom of the two particles in a two-dimensional system, including both the long-range Coulomb attraction and arbitrary two-dimensional electrostatic potentials affecting the electron and/or the hole separately. The method has been implemented for massively parallel architectures to cope with the huge numerical problem, showing good scaling properties and allowing evolution for tens of picoseconds. We have investigated both transient time phenomena and asymptotic time transmission and reflection coefficients for potential profiles consisting of i) extended barriers and wells and ii) a single-slit geometry. We found clear signatures of the internal two-body dynamics, with transient phenomena in the picosecond time-scale which might be revealed by optical spectroscopy. Exact results have been compared with mean-field approaches which, neglecting dynamical correlations by construction, turn out to be inadequate to describe the electron-hole pair evolution in realistic experimental conditions.Comment: 12 two-column pages + 3 supplemental material pages, 9 figures, to appear on Phys.Rev.