pinecone/core-2020-05-10-deduplication huggingface dataset:
You never surf alone. Ubiquitous tracking of users' browsing habits

In the early age of the internet users enjoyed a large level of anonymity. At the time web pages were just hypertext documents; almost no personalisation of the user experience was offered. The Web today has evolved as a world wide distributed system following specific architectural paradigms. On the web now, an enormous quantity of user generated data is shared and consumed by a network of applications and services, reasoning upon users expressed preferences and their social and physical connections. Advertising networks follow users’ browsing habits while they surf the web, continuously collecting their traces and surfing patterns. We analyse how users tracking happens on the web by measuring their online footprint and estimating how quickly advertising networks are able to profile users by their browsing habits.Postprint (author's final draft
Privacy Threats in E-Shopping (Position Paper)

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-29883-2_14E-shopping has grown considerably in the last years, providing
customers with convenience, merchants with increased sales, and
financial entities with an additional source of income. However, it may
also be the source of serious threats to privacy. In this paper, we review
the e-shopping process, discussing attacks or threats that have been analyzed
in the literature for each of its stages. By showing that there exist
threats to privacy in each of them, we argue our following position: “It is
not enough to protect a single independent stage, as is usually done in
privacy respectful proposals in this context. Rather, a complete solution
is necessary spanning the overall process, dealing also with the required
interconnections between stages.” Our overview also reflects the diverse
types of information that e-shopping manages, and the benefits (e.g.,
such as loyalty programs and fraud prevention) that system providers
extract from them. This also endorses the need for solutions that, while
privacy preserving, do not limit or remove these benefits, if we want
prevent all the participating entities from rejecting it.This work was supported by project S2013/ICE-3095-CM (CIBERDINE) of the Comunidad de Madrid and MINECO TIN2010-19607, TIN2012-30883, TIN2014-54580-R. The work of Seung Geol Choi was supported in part by the Office of Naval Research under Grant Number N0001415WX01232. The work of Moti Yung was done in part while visiting the Simons Institute for Theory of Computing, UC Berkeley. The work of Jesus Diaz was done in part while visiting the Network Security Lab at Columbia University
Time-Difference-of-Arrival Estimation Based on Cross Recurrence Plots, with Application to Underwater Acoustic Signals

International audienceThe estimation of the time difference of arrival (TDOA) consists of the determination of the travel-time of a wavefront between two spatially separated receivers , and it is the first step of processing systems dedicated to the identification, localization and tracking of radiating sources. This article presents a TDOA estima-tor based on cross recurrence plots and on recurrence quantification analysis. Six recurrence quantification analyses measures are considered for this purpose, including two new ones that we propose in this article. Simulated signals are used to study the influence of the parameters of the cross recurrence plot, such as the embedding dimension, the similarity function, and the recurrence threshold, on the reliability and effectiveness of the estimator. Finally, the proposed method is validated on real underwater acoustic data, for which the cross recurrence plot estimates correctly 77.6% of the TDOAs, whereas the classical cross-correlation estimates correctly only 70.2% of the TDOAs
Pedestrian Detection and Tracking in Challenging Surveillance Videos

In this chapter we propose a novel approach for real-time robust pedestrian tracking in surveillance images. Typical surveillance images are challenging to analyse since the overall image quality is low (e.g. low resolution and high compression). Furthermore often birds-eye viewpoint wide-angle lenses are used to achieve maximum coverage with a minimal amount of cameras. These specific viewpoints make it unfeasible to directly apply existing pedestrian detection techniques. Moreover, real-time processing speeds are required. To overcome these problems we introduce a pedestrian detection and tracking framework which exploits and integrates these scene constraints to achieve high accuracy results. We performed extensive experiments on publically available challenging real-life video sequences concerning both speed and accuracy. Our approach achieves excellent accuracy results while still meeting the stringent real-time demands needed for these surveillance applications, using only a single-core CPU implementation.status: publishe
TVL<sub>1</sub> Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within.\ud
\ud
This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy
Magnetic Laplacian in sharp three dimensional cones

The core result of this paper is an upper bound for the ground state energyof
the magnetic Laplacian with constant magnetic field on cones that are contained
in ahalf-space. This bound involves a weighted norm of the magnetic field
related to momentson a plane section of the cone. When the cone is sharp, i.e.
when its section is small, thisupper bound tends to 0. A lower bound on the
essential spectrum is proved for familiesof sharp cones, implying that if the
section is small enough the ground state energy is aneigenvalue. This
circumstance produces corner concentration in the semi-classical limit forthe
magnetic Schr\"odinger operator when such sharp cones are involved
Levinson’s Theorem: An Index Theorem in Scattering Theory

44 pagesInternational audienceA topological version of Levinson's theorem is presented. Its proof relies on a C *-algebraic framework which is introduced in detail. Various scattering systems are considered in this framework , and more coherent explanations for the corrections due to thresholds effects or for the regularization procedure are provided. Potential scattering, point interactions, Friedrichs model and Aharonov-Bohm operators are part of the examples which are presented. Every concepts from scattering theory or from K-theory are introduced from scratch
Hankel Matrices for Weighted Visibly Pushdown Automata

Hankel matrices (aka connection matrices) of word functions and graph
parameters have wide applications in automata theory, graph theory, and machine
learning. We give a characterization of real-valued functions on nested words
recognized by weighted visibly pushdown automata in terms of Hankel matrices on
nested words. This complements C. Mathissen's characterization in terms of
weighted monadic second order logic.Comment: 14 pages, 2 Figures. Originally appeared in the 10th International
  Conference on Language and Automata Theory and Applications (LATA 2016), with
  an imprecision in the proof. This version was made precise and simplifie
Scalar ambiguity and freeness in matrix semigroups over bounded languages

This paper was presented at LATA 2016: 10th International Conference on Language and Automata Theory and Applications http://grammars.grlmc.com/lata2016/. This is a pre‐copyedited version of a Lecture Notes in Computer Science published by Springer. The definitive authenticated\ud
version is available online via http://dx.doi.org/10.1007/978-3-319-30000-9_38There has been much research into freeness properties of\ud
finitely generated matrix semigroups under various constraints, mainly\ud
related to the dimensions of the generator matrices and the semiring over\ud
which the matrices are defined. A recent paper has also investigated freeness\ud
properties of matrices within a bounded language of matrices, which\ud
are of the form M1M2 · · · Mk ⊆ F\ud
n×n\ud
for some semiring F [9]. Most freeness\ud
problems have been shown to be undecidable starting from dimension\ud
three, even for upper-triangular matrices over the natural numbers.\ud
There are many open problems still remaining in dimension two.\ud
We introduce a notion of freeness and ambiguity for scalar reachability\ud
problems in matrix semigroups and bounded languages of matrices.\ud
Scalar reachability concerns the set {ρ\ud
TMτ |M ∈ S}, where ρ, τ ∈ F\ud
n\ud
are vectors and S is a finitely generated matrix semigroup. Ambiguity\ud
and freeness problems are defined in terms of uniqueness of factorizations\ud
leading to each scalar. We show various undecidability results
Integrity Constraints for General-Purpose Knowledge Bases

Integrity constraints in databases have been studied extensively since the
1980s, and they are considered essential to guarantee database integrity. In
recent years, several authors have studied how the same notion can be adapted
to reasoning frameworks, in such a way that they achieve the purpose of
guaranteeing a system's consistency, but are kept separate from the reasoning
mechanisms.
  In this paper we focus on multi-context systems, a general-purpose framework
for combining heterogeneous reasoning systems, enhancing them with a notion of
integrity constraints that generalizes the corresponding concept in the
database world.Comment: FoIKS 201
The Complexity of Non-Iterated Probabilistic Justification Logic

The logic PJ is a probabilistic logic defined by adding (non-iterated)
probability operators to the basic justification logic J. In this paper we
establish upper and lower bounds for the complexity of the derivability problem
in the logic PJ. The main result of the paper is that the complex- ity of the
derivability problem in PJ remains the same as the complexity of the
derivability problem in the underlying logic J, which is {\Pi}p2-complete. This
implies hat the probability operators do not increase the complex- ity of the
logic, although they arguably enrich the expressiveness of the language
A Logic for Non-Deterministic Parallel Abstract State Machines

We develop a logic which enables reasoning about single steps of
non-deterministic parallel Abstract State Machines (ASMs). Our logic builds
upon the unifying logic introduced by Nanchen and St\"ark for reasoning about
hierarchical (parallel) ASMs. Our main contribution to this regard is the
handling of non-determinism (both bounded and unbounded) within the logical
formalism. Moreover, we do this without sacrificing the completeness of the
logic for statements about single steps of non-deterministic parallel ASMs,
such as invariants of rules, consistency conditions for rules, or step-by-step
equivalence of rules.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0748
Anytime Algorithms for Solving Possibilistic MDPs and Hybrid MDPs

The ability of an agent to make quick, rational decisions in an uncertain environment is paramount for its applicability in realistic settings. Markov Decision Processes (MDP) provide such a framework, but can only model uncertainty that can be expressed as probabilities. Possibilistic counterparts of MDPs allow to model imprecise beliefs, yet they cannot accurately represent probabilistic sources of uncertainty and they lack the efficient online solvers found in the probabilistic MDP community. In this paper we advance the state of the art in three important ways. Firstly, we propose the first online planner for possibilistic MDP by adapting the Monte-Carlo Tree Search (MCTS) algorithm. A key component is the development of efficient search structures to sample possibility distributions based on the DPY transformation as introduced by Dubois, Prade, and Yager. Secondly, we introduce a hybrid MDP model that allows us to express both possibilistic and probabilistic uncertainty, where the hybrid model is a proper extension of both probabilistic and possibilistic MDPs. Thirdly, we demonstrate that MCTS algorithms can readily be applied to solve such hybrid models. © Springer International Publishing Switzerland 2016.This work is partially funded by EPSRC PACES project (Ref: EP/J012149/1).Peer Reviewe
On hamiltonian colorings of block graphs

A hamiltonian coloring c of a graph G of order p is an assignment of colors
to the vertices of G such that $D(u,v)+|c(u)-c(v)|\geq p-1$ for every two
distinct vertices u and v of G, where D(u,v) denoted the detour distance
between u and v. The value hc(c) of a hamiltonian coloring c is the maximum
color assigned to a vertex of G. The hamiltonian chromatic number, denoted by
hc(G), is the min{hc(c)} taken over all hamiltonian coloring c of G. In this
paper, we present a lower bound for the hamiltonian chromatic number of block
graphs and give a sufficient condition to achieve the lower bound. We
characterize symmetric block graphs achieving this lower bound. We present two
algorithms for optimal hamiltonian coloring of symmetric block graphs.Comment: 12 pages, 1 figure. A conference version appeared in the proceedings
  of WALCOM 201
Abstracting an Operational Semantics to Finite Automata

There is an apparent similarity between the descriptions of small-step operational semantics of imperative programs and the semantics of finite automata, so defining an abstraction mapping from semantics to automata and proving a simulation property seems to be easy. This paper aims at identifying the reasons why simple proofs break, among them artifacts in the semantics that lead to stuttering steps in the simulation. We then present a semantics based on the zipper data structure, with a direct interpretation of evaluation as navigation in the syntax tree. The abstraction function is then defined by an equivalence class construction
Onion routing in deterministic delay tolerant networks

Aquest volum de Lecture notes in computer science, amb el títol Foundations and Practice of Security, recull les actes al 8th International Symposium on Foundations & Practice of Security que va tenir lloc a Clermont-Ferrand (France), del 16 al 28 d'octubre de 2015Deterministic DTNs are networks where the behavior is known in advance or where a repetitive action occurs over time like in public transportation networks. This work proposes the application of an onion routing approach to deterministic DTNs to achieve anonymous communications. We show how the prior stage of path selection in onion routing can be achieved using the information provided by deterministic networks
GANGSTER: an Automated Negotiator Applying Genetic Algorithms

Negotiation is an essential skill for agents in a multiagent system. Much work has been published on this subject, but traditional approaches assume negotiators are able to evaluate all possible deals and pick the one that is best according\ud
to some negotiation strategy. Such an approach fails when the set of possible deals is too large to analyze exhaustively. For this reason the Annual Negotiating Agents Competition of 2014 has focused on negotiations over very large agreement spaces. In this paper we present a negotiating agent that explores the search space by means of a Genetic Algorithm. It has participated in the competition successfully and finished in 2nd and 3rd place in the two categories of the competition respectively.This work was supported by the Agreement Technologies CONSOLIDER project, contract CSD2007-0022 and INGENIO 2010 and CHIST-ERA project ACE and EU project 318770 PRAISE.Peer reviewe
A nervousness regulator framework for dynamic hybrid control architectures

Dynamic hybrid control architectures are a powerful paradigm that addresses the challenges of achieving both performance optimality and operations reactivity in discrete systems. This approach presents a dynamic mechanism that changes the control solution subject to continuous environment changes. However, these changes might cause nervousness behaviour and the system might fail to reach a stabilized-state. This paper proposes a framework of a nervousness regulator that handles the nervousness behaviour based on the defined nervousness-state. An example of this regulator mechanism is applied to an emulation of a flexible manufacturing system located at the University of Valenciennes. The results show the need for a nervousness mechanism in dynamic hybrid control architectures and explore the idea of setting the regulator mechanism according to the nervousness behaviour state.info:eu-repo/semantics/publishedVersio
Building a robotic cyber-physical production component

Cyber-physical systems are a network of integrated computational decisional com-ponents and physical elements. The integration of computational decisional components with the heterogeneous physical automation systems and devices is not transparent and constitutes a critical challenge for the success of this approach. The objective of the paper is to describe an approach to establish standard interfaces based on the use of the ISO 9506 Manufacturing Mes-sage Specification international standard. The proposed approach is exemplified by the con-struction of a robotic cyber-physical production component that is plug-in in a cyber-physical system for a small-scale production system based on Fischertechnik systems.info:eu-repo/semantics/publishedVersio
On tuning passive black-box macromodels of LTI systems via adaptive weighting

This paper discusses various approaches for tuning the accuracy of rational macromodels obtained via black-box identification or approximation of sampled frequency responses of some unknown Linear and Time-Invariant system. Main emphasis is on embedding into the model extraction process some information on the nominal terminations that will be connected to the model during normal operation, so that the corresponding accuracy is optimized. This goal is achieved through an optimization based on a suitably defined cost function, which embeds frequency-dependent weights that are adaptively refined during the model construction. A similar procedure is applied in a postprocessing step for enforcing model passivity. The advantages of proposed algorithm are illustrated on a few application examples related to power distribution networks in electronic system
Approximation Methods to Solve Stochastic Problems in Computational Electromagnetics

To account for uncertainties on model parameters, the stochastic approach can be used. The model parameters as well as the outputs are then random fields or variables. Several methods are available in the literature to solve stochastic models like sampling methods, perturbation methods or approximation methods. In this paper, we propose an overview on the solution of stochastic problems in computational electromagnetics using approximation methods. Some applications will be presented in order to illustrate the possibilities offered by the approximation methods but also their current limitations due to the curse of dimensionality. Finally, recent numerical techniques proposed in the literature to face the curse of dimensionality are presented for non-intrusive and intrusive approaches.This work has been supported by the pole MEDEE funded by the Nord Pas de Calais
Region and the European Union and also by the Arts et M´etiers Fundation
A 3D spinorial view of 4D exceptional phenomena

We discuss a Clifford algebra framework for discrete symmetry groups (such as
reflection, Coxeter, conformal and modular groups), leading to a surprising
number of new results. Clifford algebras allow for a particularly simple
description of reflections via `sandwiching'. This extends to a description of
orthogonal transformations in general by means of `sandwiching' with Clifford
algebra multivectors, since all orthogonal transformations can be written as
products of reflections by the Cartan-Dieudonn\'e theorem. We begin by viewing
the largest non-crystallographic reflection/Coxeter group $H_4$ as a group of
rotations in two different ways -- firstly via a folding from the largest
exceptional group $E_8$, and secondly by induction from the icosahedral group
$H_3$ via Clifford spinors. We then generalise the second way by presenting a
construction of a 4D root system from any given 3D one. This affords a new --
spinorial -- perspective on 4D phenomena, in particular as the induced root
systems are precisely the exceptional ones in 4D, and their unusual
automorphism groups are easily explained in the spinorial picture; we discuss
the wider context of Platonic solids, Arnold's trinities and the McKay
correspondence. The multivector groups can be used to perform concrete
group-theoretic calculations, e.g. those for $H_3$ and $E_8$, and we discuss
how various representations can also be constructed in this Clifford framework;
in particular, representations of quaternionic type arise very naturally.Comment: 15 pages, 3 figures, 3 tables. arXiv admin note: substantial text
  overlap with arXiv:1602.05985; text overlap with arXiv:1602.0600
Reduced-precision Algorithm-based Fault Tolerance for FPGA-implemented Accelerators

© Springer International Publishing Switzerland 2016.As the threat of fault susceptibility caused by mechanisms including variation and degradation increases, engineers must give growing consideration to error detection and correction. While the use of common fault tolerance strategies frequently causes the incursion of significant overheads in area, performance and/or power consumption, options exist that buck these trends. In particular, algorithm-based fault tolerance embodies a proven family of low-overhead error mitigation techniques able to be built upon to create self-verifying circuitry. In this paper, we present our research into the application of algorithm-based fault tolerance (ABFT) in FPGA-implemented accelerators at reduced levels of precision. This allows for the introduction of a previously unexplored tradeoff: sacrificing the observability of faults associated with low-magnitude errors for gains in area, performance and efficiency by reducing the bit-widths of logic used for error detection. We describe the implementation of a novel checksum truncation technique, analysing its effects upon overheads and allowed error. Our findings include that bit-width reduction of ABFT circuitry within a fault-tolerant accelerator used for multiplying pairs of 32 × 32 matrices resulted in the reduction of incurred area overhead by 16.7% and recovery of 8.27% of timing model fmax. These came at the cost of introducing average and maximum absolute output errors of 0.430% and 0.927%, respectively, of the maximum absolute output value under transient fault injection