Directly estimating non-classicality

We establish a method of directly measuring and estimating non-classicality - operationally defined in terms of the distinguishability of a given state from one with a positive Wigner function. It allows to certify non-classicality, based on possibly much fewer measurement settings than necessary for obtaining complete tomographic knowledge, and is at the same time equipped with a full certificate. We find that even from measuring two conjugate variables alone, one may infer the non-classicality of quantum mechanical modes. This method also provides a practical tool to eventually certify such features in mechanical degrees of freedom in opto-mechanics. The proof of the result is based on Bochner's theorem characterizing classical and quantum characteristic functions and on semi-definite programming. In this joint theoretical-experimental work we present data from experimental optical Fock state preparation, demonstrating the functioning of the approach.Comment: 4+1 pages, 2 figures, minor change

Pattern for Re-engineering a Classification Scheme, which Follows the Adjacency List Data Model, to a Taxonomy

This pattern for re-engineering non-ontological resources (pr-nor) fits in the schema re-engineering category proposed by [3]. The pattern defines a procedure that transforms the classification scheme components into ontology representational primitives. This pattern comes from the experience of ontology engineers in developing ontologies using classification schemes in several projects (seemp 1 , neon 2 , and knowledge web 3 ). The pattern is included in a pool of patterns, which is a key element of our method for re-engineering non-ontological resources into ontologies [2]. The patterns generate the ontologies at a conceptualization level, independent of the ontology implementation language

Spoof detection using time-delay shallow neural network and feature switching

Detecting spoofed utterances is a fundamental problem in voice-based biometrics. Spoofing can be performed either by logical accesses like speech synthesis, voice conversion or by physical accesses such as replaying the pre-recorded utterance. Inspired by the state-of-the-art \emph{x}-vector based speaker verification approach, this paper proposes a time-delay shallow neural network (TD-SNN) for spoof detection for both logical and physical access. The novelty of the proposed TD-SNN system vis-a-vis conventional DNN systems is that it can handle variable length utterances during testing. Performance of the proposed TD-SNN systems and the baseline Gaussian mixture models (GMMs) is analyzed on the ASV-spoof-2019 dataset. The performance of the systems is measured in terms of the minimum normalized tandem detection cost function (min-t-DCF). When studied with individual features, the TD-SNN system consistently outperforms the GMM system for physical access. For logical access, GMM surpasses TD-SNN systems for certain individual features. When combined with the decision-level feature switching (DLFS) paradigm, the best TD-SNN system outperforms the best baseline GMM system on evaluation data with a relative improvement of 48.03\% and 49.47\% for both logical and physical access, respectively

A Pattern Based Approach for Re-engineering Non-Ontological Resources into Ontologies

With the goal of speeding up the ontology development process, ontology engineers are starting to reuse as much as possible available ontologies and non-ontological resources such as classification schemes, thesauri, lexicons and folksonomies, that already have some degree of consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Non-ontological resources are highly heterogeneous in their data model and contents: they encode different types of knowledge, and they can be modeled and implemented in different ways. In this paper we present (1) a typology for non-ontological resources, (2) a pattern based approach for re-engineering non-ontological resources into ontologies, and (3) a use case of the proposed approach

An information theoretic approach to statistical dependence: copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set.Comment: to appear in Europhysics Letter

Pattern for Re-engineering a Term-based Thesaurus, which Follows the Record-based model, to a Lightweight Ontology

This pattern for re-engineering non-ontological resources (PR-NOR) fits in the Schema Re-engineering Category proposed by [3]. The pattern defines a procedure that transforms the term-based thesaurus components into ontology representational primitives. This pattern comes from the experience of ontology engineers in developing ontologies using thesauri in several projects (SEEMP 1 , NeOn 2 , and Knowledge Web 3 ). The pattern is included in a pool of patterns, which is a key element of our method for re-engineering non-ontological resources into ontologies [2]. The patterns generate the ontologies at a conceptualization level, independent of the ontology implementation language

Normal form decomposition for Gaussian-to-Gaussian superoperators

In this paper we explore the set of linear maps sending the set of quantum Gaussian states into itself. These maps are in general not positive, a feature which can be exploited as a test to check whether a given quantum state belongs to the convex hull of Gaussian states (if one of the considered maps sends it into a non positive operator, the above state is certified not to belong to the set). Generalizing a result known to be valid under the assumption of complete positivity, we provide a characterization of these Gaussian-to-Gaussian (not necessarily positive) superoperators in terms of their action on the characteristic function of the inputs. For the special case of one-mode mappings we also show that any Gaussian-to-Gaussian superoperator can be expressed as a concatenation of a phase-space dilatation, followed by the action of a completely positive Gaussian channel, possibly composed with a transposition. While a similar decomposition is shown to fail in the multi-mode scenario, we prove that it still holds at least under the further hypothesis of homogeneous action on the covariance matrix

A network of ontology networks for building e-employment advanced systems

This paper presents the development of a network of ontology networks that enables data mediation between the Employment Services (ESs) participating in a semantic interoperability platform for the exchange of Curricula Vitae (CVs) and job offers in different languages. Such network is formed by (1) a set of local ontology networks that are language dependent, in which each network represents the local and particular view that each ES has of the employment market; and (2) a reference ontology network developed in English that represents a standardized and agreed upon terminology of the European employment market. In this network each local ontology network is aligned with the reference ontology network so that search queries, CVs, and job offers can be mediated through these alignments from any ES. The development of the ontologies has followed the methodological guidelines issued by the NeOn Methodology and is focused mainly on scenarios that involve reusing and re-engineering knowledge resources already agreed upon by employment experts and standardization bodies. This paper explains how these methodological guidelines have been applied for building e-employment ontologies. In addition, it shows that the approach to building ontologies by reusing and re-engineering agreed upon non-ontological resources speeds the ontology development, reduces development costs, and retrieves knowledge already agreed upon by a community of people in a more formal representation

Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web

The uptake of Linked Data (LD) has promoted the proliferation of datasets and their associated ontologies bringing their semantic to the data being published. These ontologies should be evaluated at different stages, both during their development and their publication. As important as correctly modelling the intended part of the world to be captured in an ontology, is publishing, sharing and facilitating the (re)use of the obtained model. In this paper, 11 evaluation characteristics, with respect to publish, share and facilitate the reuse, are proposed. In particular, 6 good practices and 5 pitfalls are presented, together with their associated detection methods. In addition, a grid-based rating system is generated. Both contributions, the set of evaluation characteristics and the grid system, could be useful for ontologists in order to reuse existing LD vocabularies or to check the one being built