pinecone/core-2020-05-10-deduplication huggingface dataset:
On the efficiency of estimating penetrating rank on large graphs

P-Rank (Penetrating Rank) has been suggested as a useful measure of structural similarity that takes account of both incoming and outgoing edges in ubiquitous networks. Existing work often utilizes memoization to compute P-Rank similarity in an iterative fashion, which requires cubic time in the worst case. Besides, previous methods mainly focus on the deterministic computation of P-Rank, but lack the probabilistic framework that scales well for large graphs. In this paper, we propose two efficient algorithms for computing P-Rank on large graphs. The first observation is that a large body of objects in a real graph usually share similar neighborhood structures. By merging such objects with an explicit low-rank factorization, we devise a deterministic algorithm to compute P-Rank in quadratic time. The second observation is that by converting the iterative form of P-Rank into a matrix power series form, we can leverage the random sampling approach to probabilistically compute P-Rank in linear time with provable accuracy guarantees. The empirical results on both real and synthetic datasets show that our approaches achieve high time efficiency with controlled error and outperform the baseline algorithms by at least one order of magnitude
Speeding-up $q$-gram mining on grammar-based compressed texts

We present an efficient algorithm for calculating $q$-gram frequencies on
strings represented in compressed form, namely, as a straight line program
(SLP). Given an SLP $\mathcal{T}$ of size $n$ that represents string $T$, the
algorithm computes the occurrence frequencies of all $q$-grams in $T$, by
reducing the problem to the weighted $q$-gram frequencies problem on a
trie-like structure of size $m = |T|-\mathit{dup}(q,\mathcal{T})$, where
$\mathit{dup}(q,\mathcal{T})$ is a quantity that represents the amount of
redundancy that the SLP captures with respect to $q$-grams. The reduced problem
can be solved in linear time. Since $m = O(qn)$, the running time of our
algorithm is $O(\min\{|T|-\mathit{dup}(q,\mathcal{T}),qn\})$, improving our
previous $O(qn)$ algorithm when $q = \Omega(|T|/n)$
Impact of digitalization of mammographic units on average glandular doses in the Flemish Breast Cancer Screening Program

The impact of digitalization on the average glandular doses in 49 mammographic units participating in the Flemish Breast Cancer Screening Program was studied. Screen-film was changed to direct digital radiography and computed radiography in 25 and 24 departments respectively. Average glandular doses were calculated before and after digitalization for different PMMA-phantom thicknesses and for groups of 50 successive patients. For the transition from screen-film to computed radiography both phantom and patient dose data show a significant increase of dose with digitalization. For the transition from screen-film to direct digital radiography the evolution of the average glandular dose depends on the phantom thickness. For 20mm PMMA a significant increase in dose was found, for 45mm and 70mm PMMA there was a significant decrease in dose. The median average glandular dose of the patient dosimetry showed a smaller but significant decrease
Joint registration and limited-angle reconstruction of digital breast tomosynthesis

Digital breast tomosynthesis (DBT), an emerging imaging modality, provides a pseudo-3D image of the breast. Algorithms to aid the human observer process these large datasets involve two key tasks: reconstruction and registration. Previous studies separated these steps, solving each task independently. This can be effective if reconstructing using a complete set of data, e.g., in cone beam CT, assuming that only simple deformations exist. However, for ill-posed limited-angle problems such as DBT, estimating the deformation is complicated by the significant artefacts associated with DBT reconstructions, leading to severe inaccuracies in the registration. In this paper, we present an innovative algorithm, which combines reconstruction of a pair of temporal DBT acquisitions with their simultaneous registration. Using various computational phantoms and in vivo DBT simulations, we show that, compared to the conventional sequential method, jointly estimating image intensities and transformation parameters gives superior results with respect to reconstruction fidelity and registration accuracy
Web Searching with Entity Mining at Query Time

In this paper we present a method to enrich the classical web searching with entity mining that is performed at query time. The results of entity mining (entities grouped in categories) can complement the query answers with useful for the user information which can be further exploited in a faceted search-like interaction scheme. We show that the application of entity mining over thesnippets of the top-hits of the answers, can be performed at real-time. However mining over the snippets returns less entities than mining over the full contents of the hits, and for this reason we report comparative results for these two scenarios. In addition, we show how Linked Data can be exploited for specifying the entities of interest and for providing further information about the identified entities, implementing a kind of entity-based integration of documents and (semantic) data. Finally, we discuss the applicability of this approach on professional search, specifically for the domains of fisheries/aquaculture and patents
On the joint security of signature and encryption schemes under randomness reuse: efficiency and security amplification

Lecture Notes in Computer Science, 7341We extend the work of Bellare, Boldyreva and Staddon on the systematic analysis of randomness reuse to construct multi-recipient encryption schemes to the case where randomness is reused across different cryptographic primitives. We find that through the additional binding introduced through randomness reuse, one can actually obtain a security amplification with respect to the standard black-box compositions, and achieve a stronger level of security. We introduce stronger notions of security for encryption and signatures, where challenge messages can depend in a restricted way on the random coins used in encryption, and show that two variants of the KEM/DEM paradigm give rise to encryption schemes that meet this enhanced notion of security. We obtain the most efficient signcryption scheme to date that is secure against insider attackers without random oracles
Go With The Flow: Hand Trajectories in 3D via Clustered Scene Flow

Tracking hands and estimating their trajectories is useful in a number of tasks, including sign language recognition and human computer interaction. Hands are extremely difficult objects to track, their deformability, frequent self occlusions and motion blur cause appearance variations too great for most standard object trackers to deal with robustly.\ud
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In this paper, the 3D motion field of a scene (known as the Scene Flow, in contrast to Optical Flow, which is it's projection onto the image plane) is estimated using a recently proposed algorithm, inspired by particle filtering. Unlike previous techniques, this scene flow algorithm does not introduce blurring across discontinuities, making it far more suitable for object segmentation and tracking. Additionally the algorithm operates several orders of magnitude faster than previous scene flow estimation systems, enabling the use of Scene Flow in real-time, and near real-time applications.\ud
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A novel approach to trajectory estimation is then introduced, based on clustering the estimated scene flow field in both space and velocity dimensions. This allows estimation of object motions in the true 3D scene, rather than the traditional approach of estimating 2D image plane motions. By working in the scene space rather than the image plane, the constant velocity assumption, commonly used in the prediction stage of trackers, is far more valid, and the resulting motion estimate is richer, providing information on out of plane motions. To evaluate the performance of the system, 3D trajectories are estimated on a multi-view sign-language dataset, and compared to a traditional high accuracy 2D system, with excellent results
Cortical multiscale line-edge disparity model

Most biological approaches to disparity extraction rely on
the disparity energy model (DEM). In this paper we present an alternative
approach which can complement the DEM model. This approach
is based on the multiscale coding of lines and edges, because surface
structures are composed of lines and edges and contours of objects often
cause edges against their background. We show that the line/edge approach
can be used to create a 3D wireframe representation of a scene
and the objects therein. It can also significantly improve the accuracy of
the DEM model, such that our biological models can compete with some
state-of-the-art algorithms from computer vision
Optimal “anti-Bayesian” parametric pattern classification for the exponential family using Order Statistics criteria

Published version of a chapter in the book: Image Analysis and Recognition. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31295-3_2This paper reports some pioneering results in which optimal parametric classification is achieved in a counter-intuitive manner, quite opposed to the Bayesian paradigm. The paper, which builds on the results of [1], demonstrates (with both theoretical and experimental results) how this can be done for some distributions within the exponential family. To be more specific, within a Bayesian paradigm, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding means, which in one sense, is the most central point in the respective distribution. In this paper, we shall show that we can obtain optimal results by operating in a diametrically opposite way, i.e., a so-called “anti-Bayesian” manner. Indeed, we shall show that by working with a very few (sometimes as small as two) points distant from the mean, one can obtain remarkable classification accuracies. These points, in turn, are determined by the Order Statistics of the distributions, and the accuracy of our method, referred to as Classification by Moments of Order Statistics (CMOS), attains the optimal Bayes’ bound! In this paper, we shall show the claim for two uni-dimensional members of the exponential family. The theoretical results, which have been verified by rigorous experimental testing, also present a theoretical foundation for the families of Border Identification (BI) reported algorithms
Go With The Flow: Hand Trajectories in 3D via Clustered Scene Flow

Tracking hands and estimating their trajectories is useful in a number of tasks, including sign language recognition and human computer interaction. Hands are extremely difficult objects to track, their deformability, frequent self occlusions and motion blur cause appearance variations too great for most standard object trackers to deal with robustly. In this paper, the 3D motion field of a scene (known as the Scene Flow, in contrast to Optical Flow, which is it’s projection onto the image plane) is estimated using a recently proposed algorithm, inspired by particle filtering. Unlike previous techniques, this scene flow algorithm does not introduce blurring across discontinuities, making it far more suitable for object segmentation and tracking. Additionally the algorithm operates several orders of magnitude faster than previous scene flow estimation systems, enabling the use of Scene Flow in real-time, and near real-time applications. A novel approach to trajectory estimation is then introduced, based on clustering the estimated scene flow field in both space and velocity dimensions. This allows estimation of object motions in the true 3D scene, rather than the traditional approach of estimating 2D image plane motions. By working in the scene space rather than the image plane, the constant velocity assumption, commonly used in the prediction stage of trackers, is far more valid, and the resulting motion estimate is richer, providing information on out of plane motions. To evaluate the performance of the system, 3D trajectories are estimated on a multi-view sign-language dataset, and compared to a traditional high accuracy 2D system, with excellent results
Part I - Landslide Inventory and Susceptibility and Hazard Zoning – Introduction

Landslide inventories and susceptibility and hazard maps are key tools for land use planning and management, civil protection plans, civil engineering works, and risk reduction programmes. Their importance helps understanding why approximately one sixth of all contributions to the Second World Landslide Forum were related to recent advances in these topics.
This volume presents the state of the art on landslide inventory and susceptibility and hazard zoning. It contains experiences, methods and techniques applied in different physiographic, geological and climate settings of the world and for different types of landslides, from site-specific investigations to global scale analysis.JRC.H.7-Climate Risk Managemen
Mapping a nation’s landslides: a novel multi-stage methodology

Through combining new technologies and traditional mapping techniques, the British Geological Survey (BGS) has developed a novel, multi-stage methodology for landslide mapping.  3-D aerial photograph interpretation, variable-perspective 3-D topographic visualisation and field mapping with digital data capture are being used to map the UK’s landslides.  The resulting ESRI ArcGIS polygons are published on BGS 1:50,000 geological maps and as digital data products.  Data collected during mapping are also uploaded directly into the National Landslides Database maintaining a systematic, nationally-uniform landslide inventory.  Repeat monitoring of selected landslides using terrestrial LIDAR and dGPS allows the database to be frequently updated and the proactive Landslide Response Team means that new landslide events can be mapped within days, if not hours, of their occurrence.  The long-term aim is to apply this methodology throughout the UK, providing a wealth of data for scientific research and hazard assessment.  This methodology is also suitable for application in an international context
On Elastoplastic Damage Modelling in Unsaturated Geomaterials

International audienceIn the context of nuclearwaste disposal, the modelling of the behaviour of host rocks and soils still needs improvement.Unsaturated porous geomaterials exhibit particular behaviourwhen exposed to suction. Their non-linear behaviour may result fromtwo different processes, plasticity which induces irreversible strains and damage which causes a deterioration of their elastic properties. Many elasto-plastic models are now available for unsaturated soils, most of them based on the Barcelona Basic Model (Alonso et al., 1990). They take into consideration a certain number of issues linkedwith the nature of unsatured soils.Models coupling damage and plasticity have also been proposed for continuous media. Since very few works have attempted to connect these two distinct fields, unsaturated soil mechanics and continuum damage mechanics, thiswork focuses on themain issues related to the development of amodel coupling elasto-plasticity and damage for unsaturated porous media
Unsaturated hydraulic conductivity of a silty\ud
sand with the instantaneous profile method

The unsaturated hydraulic conductivity of a silty sand at different initial void ratios is measured using the instantaneous profile method. The variation of the suction and volumetric water content is recorded during the infiltration process as a function of time. Accordingly, an infiltration column was developed with a height of 600 mm and an inner diameter of 170 mm. The suction and volumetric water content were measured simultaneously every 100 mm along the column by means of small tensiometers and TDRs, respectively. Hydraulic conductivity is calculated by dividing the water flow velocity by the hydraulic gradient. The soil is reconstituted from Ruedlingen (Canton Schaffhausen, Switzerland), where landslide triggering experiments were carried out in October 2008 and March 2009. The hydraulic conductivity functions are determined and the laboratory values are compared to the in-situ measurements of hydraulic conductivity carried out in the course of the landslide triggering experiments
The effects of hydraulic properties of bedrock\ud
on the stability of slopes

The transient process of rain infiltration in the soil and the effect of geometry and drainage properties of the bedrock on the pore pressure distribution and the stability of a slope are investigated. The simulated slope is a test field in northern Switzerland, where landslide triggering experiments were carried out. From geological point of view, the experimental site is located in the Swiss Molasse basin. The lithological units in the area are composed of horizontally layered and fractured sandstones intersected by marlstone. The stability of the slope is monitored at different stages of the infiltration using the limit equilibrium method of slices. Several cases were compared to study the effect of the fissures in the shallow bedrock on the stability of the slope. The approximate location and size of the fissures in the bedrock were determined by monitoring of spatial and temporal changes of electrical resistivity during rainfall and also geological investigations of the bedrock before and after the failure
SVM approximation of value function contours in target hitting problems

In a problem of target hitting, the capture basin at cost c is the set of states that can reach the target with a cost lower or equal than c, without breaking the viability constraints. The boundary of a c-capture basin is the c-contour of the problem value function. In this paper, we propose a new algorithm that solves target hitting problems, by iteratively approximating capture basins at successive costs. We show that, by a simple change of variables, minimising a cost may be reduced to the problem of time minimisation, and hence a recursive backward procedure can be set. Two variants of the algorithm are derived, one providing an approximation from inside (the approximation is included in the actual capture basin) and one providing a outer approximation, which allows one to assess the approximation error. We use a machine learning algorithm (as a particular case, we consider Support Vector Machines) trained on points of a grid with boolean labels, and we state the conditions on the machine learning procedure that guarantee the convergence of the approximations towards the actual capture basin when the resolution of the grid decreases to 0. Moreover, we define a control procedure which uses the set of capture basin approximations to drive a point into the target. When using the inner approximation, the procedure guarantees to hit the target, and when the resolution of the grid tends to 0, the controller tends to the optimal one (minimizing the cost to hit the target). We illustrate the method on two simple examples, Zermelo and car on the hill problems
Security protocols, constraint systems, and group theories

International audienceWhen formally analyzing security protocols it is often im- portant to express properties in terms of an adversary's inability to distinguish two protocols. It has been shown that this problem amounts to deciding the equivalence of two constraint systems, i.e., whether they have the same set of solutions. In this paper we study this equivalence problem when cryptographic primitives are modeled using a group equational theory, a special case of monoidal equational theories. The results strongly rely on the isomorphism between group theories and rings. This allows us to reduce the problem under study to the problem of solving systems of equations over rings. We provide several new decidability and complexity results, notably for equational theories which have applications in security protocols, such as exclusive or and Abelian groups which may additionally admit a unary, homomorphic symbol
A Calculus for Generating Ground Explanations

Full Paper: Applications II: Mathematical Structures, Explanation Generation, SecurityInternational audienceWe present a modification of the superposition calculus that is meant to generate explanations why a set of clauses is satisfiable. This process is related to abductive reasoning, and the explanations generated are clauses constructed over so-called abductive constants. We prove the correctness and completeness of the calculus in the presence of redundancy elimination rules, and develop a sufficient condition guaranteeing its termination; this sufficient condition is then used to prove that all possible explanations can be generated in finite time for several classes of clause sets, including many of interest to the SMT community. We propose a procedure that generates a set of explanations that should be useful to a human user and conclude by suggesting several extensions to this novel approach
Tableaux Modulo Theories Using Superdeduction

We propose a method that allows us to develop tableaux modulo theories using
the principles of superdeduction, among which the theory is used to enrich the
deduction system with new deduction rules. This method is presented in the
framework of the Zenon automated theorem prover, and is applied to the set
theory of the B method. This allows us to provide another prover to Atelier B,
which can be used to verify B proof rules in particular. We also propose some
benchmarks, in which this prover is able to automatically verify a part of the
rules coming from the database maintained by Siemens IC-MOL. Finally, we
describe another extension of Zenon with superdeduction, which is able to deal
with any first order theory, and provide a benchmark coming from the TPTP
library, which contains a large set of first order problems.Comment: arXiv admin note: substantial text overlap with arXiv:1501.0117
A Simplex-Based Extension of Fourier-Motzkin for Solving Linear Integer Arithmetic

International audienceThis paper describes a novel decision procedure for quantifier-free linear integer arithmetic. Standard techniques usually relax the initial problem to the rational domain and then proceed either by projection (e.g. Omega-Test) or by branching/cutting methods (branch-and-bound, branch-and-cut, Gomory cuts). Our approach tries to bridge the gap between the two techniques: it interleaves an exhaustive search for a model with bounds inference. These bounds are computed provided an oracle capable of finding constant positive linear combinations of affine forms. We also show how to design an efficient oracle based on the Simplex procedure. Our algorithm is proved sound, complete, and terminating and is implemented in the Alt-Ergo theorem prover. Experimental results are promising and show that our approach is competitive with state-of-the-art SMT solvers
Speeding up cylindrical algebraic decomposition by Gröebner Bases

Gröebner Bases and Cylindrical Algebraic Decomposition are generally thought of as two, rather different, methods of looking at systems of equations and, in the case of Cylindrical Algebraic Decomposition, inequalities. However, even for a mixed system of equalities and inequalities, it is possible to apply Gröebner basesto the (conjoined) equalities before invoking CAD. We see that this is, quite often but not always, a beneficial preconditioning of the CAD problem. It is also possible to precondition the (conjoined) inequalities with respect to the equalities, and this can also be useful in many cases