EVN+MERLIN observations of microquasar candidates at low galactic latitudes

In an attempt to increase the number of known microquasars, Paredes et al. (2002) have presented a long-term project focused on the search for new objects of this type. They performed a cross-identification between X-ray and radio catalogs under very restrictive selection criteria for sources with |b|<5 degrees, and obtained a sample of 13 radio-emitting X-ray sources. Follow-up observations of 6 of these sources with the VLA provided accurate coordinates, which were used to discover optical counterparts for all of them. We have observed these six sources with the EVN and MERLIN at 5 GHz. Five of the six objects have been detected and imaged, presenting different morphologies: one source has a two-sided jet, three sources have one-sided jets, and one source is compact. With all the presently available information, we conclude that two of the sources are promising microquasar candidates in our Galaxy.

Platform pricing and consumer foresight: The case of airports

Airports have become platforms that derive revenues from both aeronautical and commercial activities. The demand for these services is characterized by a one-way complementarity in that only air travelers can purchase retail goods at the airport terminals. We analyze a model of optimal airport behavior in which this one-way complementarity is subject to consumer foresight, i.e., consumers may not anticipate in full the ex post retail surplus when purchasing a flight ticket. An airport sets landing fees, and, in addition, also chooses the retail market structure by selecting the number of retail concessions to be awarded. We find that, with perfectly myopic consumers, the airport chooses to attract more passengers via low landing fees, and also sets the minimum possible number of retailers in order to increase the concessions’ revenues, from which it obtains the largest share of profits. However, even a very small amount of anticipation of the consumer surplus from retail activities changes significantly the airport’s choices: the optimal airport policy is dependent on the degree of differentiation in the retail market. When consumers instead have perfect foresight, the airport establishes a very competitive retail market, where consumers enjoy a large surplus. This attracts passengers and it is exploited by the airport by charging higher landing fees, which then constitute the largest share of its profits. Overall, the airport’s profits are maximal when consumers have perfect foresight. Keywords: two-sided markets, platform pricing, one-way demand complementarity, consumer foresight. JEL classification: L1, L2, L93.

In Google we trust?

In a micro-founded model, we derive novel incentives for a monopoly search engine to distort its organic and its sponsored results on searches for online content and offline products. Distorting organic results towards content publishers with less effective display advertising and/or distorting sponsored results towards higher margin merchants (by underweighting consumer relevance in search auctions) increase per capita revenues but lower participation. The interplay of these incentives determines search bias and welfare. We also characterize how the welfare consequences of integration into display advertising, as intermediary or publisher, depend on asymmetries, monopolization and targeting.

Median stable matching for college admission

We give a simple and concise proof that so-called generalized median stable matchings are well-defined stable matchings for college admissions problems. Furthermore, we discuss the fairness properties of median stable matchings and conclude with two illustrative examples of college admissions markets, the lattices of stable matchings, and the corresponding generalized median stable matchings.

Procedurally fair and stable matching

We motivate procedural fairness for matching mechanisms and study two procedurally fair and stable mechanisms: employment by lotto (Aldershof et al., 1999) and the random order mechanism (Roth and Vande Vate, 1990, Ma, 1996). For both mechanisms we give various examples of probability distributions on the set of stable matchings and discuss properties that differentiate employment by lotto and the random order mechanism. Finally, we consider an adjustment of the random order mechanism, the equitable random order mechanism, that combines aspects of procedural and "endstate'' fairness. Aldershof et al. (1999) and Ma (1996) that exist on the probability distribution induced by both mechanisms. Finally, we consider an adjustment of the random order mechanism, the equitable random order mechanism.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

General preferences for consumption goods in the random matching model of commodity money

This paper generalizes the original random matching model of money byKiyotaki and Wright (1989) (KW) in two aspects: first, the economy ischaracterized by an arbitrary distribution of agents who specialize in producing aparticular consumption good; and second, these agents have preferences suchthat they want to consume any good with some probability. The resultsdepend crucially on the size of the fraction of producers of each goodand the probability with which different agents want to consume eachgood. KW and other related models are shown to be parameterizations ofthis more general one.

MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

Using the optical mouse sensor as a two-euro counterfeit coin detector

In this paper, the sensor of an optical mouse is presented as a counterfeit coin detector applied to the two-Euro case. The detection process is based on the short distance image acquisition capabilities of the optical mouse sensor where partial images of the coin under analysis are compared with some partial reference coin images for matching. Results show that, using only the vision sense, the counterfeit acceptance and rejection rates are very similar to those of a trained user and better than those of an untrained user.

Edge matching puzzles as hard SAT/CSP benchmarks

Recently, edge matching puzzles, an NP-complete problem, have rececived, thanks to money-prized contests, considerable attention from wide audiences. We consider these competitions not only a challenge for SAT/CSP solving techniques but also as an opportunity to showcase the advances in the SAT/CSP community to a general audience. This paper studies the NP-complete problem of edge matching puzzles focusing on providing generation models of problem instances of variable hardness and on its resolution through the application of SAT and CSP techniques. From the generation side, we also identify the phase transition phenomena for each model. As solving methods, we employ both; SAT solvers through the translation to a SAT formula, and two ad-hoc CSP solvers we have developed, with different levels of consistency, employing several generic and specialized heuristics. Finally, we conducted an extensive experimental investigation to identify the hardest generation models and the best performing solving techniques.

Comparing multiple criteria for species identification in two recently diverged seabirds

Correct species identification is a crucial issue in systematics with key implications for prioritising conservation effort. However, it can be particularly challenging in recently diverged species due to their strong similarity and relatedness. In such cases, species identification requires multiple and integrative approaches. In this study we used multiple criteria, namely plumage colouration, biometric measurements, geometric morphometrics, stable isotopes analysis (SIA) and genetics (mtDNA), to identify the species of 107 bycatch birds from two closely related seabird species, the Balearic (Puffinus mauretanicus) and Yelkouan (P. yelkouan) shearwaters. Biometric measurements, stable isotopes and genetic data produced two stable clusters of bycatch birds matching the two study species, as indicated by reference birds of known origin. Geometric morphometrics was excluded as a species identification criterion since the two clusters were not stable. The combination of plumage colouration, linear biometrics, stable isotope and genetic criteria was crucial to infer the species of 103 of the bycatch specimens. In the present study, particularly SIA emerged as a powerful criterion for species identification, but temporal stability of the isotopic values is critical for this purpose. Indeed, we found some variability in stable isotope values over the years within each species, but species differences explained most of the variance in the isotopic data. Yet this result pinpoints the importance of examining sources of variability in the isotopic data in a case-by-case basis prior to the cross-application of the SIA approach to other species. Our findings illustrate how the integration of several methodological approaches can help to correctly identify individuals from recently diverged species, as each criterion measures different biological phenomena and species divergence is not expressed simultaneously in all biological traits.

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

Peer-reviewed