pinecone/core-2020-05-10-deduplication huggingface dataset:
SplineAPI: A REST API for NLP Services

Modern applications often use Natural Language Processing (NLP)
   techniques  and  algorithms  to  provide  sets  of  rich  features.  
   Researchers, who come up with these algorithms, often implement them for
  case studies, evaluation or as proof of concepts. These implementations
  are, in most cases, freely available for download and use.
  Nevertheless, these implementations do not comprise final software packages,
  with extensive installation instructions and detailed usage guides.
  Most lack a proper installation mechanism and library dependency tracking. 
   The  programming  interfaces  are,  usually,  limited  to  their  usage
  through command line, or with just a few programming languages support.
To overcome these shortcomings, this work aims to develop a new web
platform to make available a set of common operations to third party
applications  that  can  be  used  to  quickly  access NLP
based  processes. Of course this platform still relies on the same tools mentioned before,
as  a  base  support  to  specific  requests.  Nevertheless,  the  end  user  will
not  need  to  install  and  learn  their  specific  Application  Programming
Interfaces (API). For this to be possible, the architectural solution is to
implement a RESTful API that hides all the tool details in a simple API
that is common or, at least, coherent, across the different tools.FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/201
Experiments on enlarging a lexical ontology

This paper presents two simple experiments performed in order
to enlarge the coverage of PULO, a Lexical Ontology, based and
aligned with the Princeton WordNet.
The first experiment explores the 
triangulation of the Galician, Catalan and Castillian wordnets,
with translation dictionaries from the Apertium project. The second,
explores Dicionário-Aberto entries, in order to extract synsets from
its definitions. Although similar approaches were already applied for
different languages, this document aims at documenting
their results for the PULO case
WSDLUD: a metric to measure the understanding degree of WSDL descriptions

In this article, WSDL Understanding Degree (WSDLUD) a metric aimed at measuring a priori the understandability of WSDL (Web Services Description Language) descriptions is presented. In order
to compute WSDLUD, all the static information available in a WSDL description is collected. This information is submitted to an evaluation process based on a method named LSP (Logic Scoring of Preference).
This evaluation process outputs a Global Preference value that indicates the satisfaction level of the WSDL description regarding the evaluation focus, in this case, the understanding degree.This work has been supported by FCT–Fundação para a Ciência e a Tecnologia within the Project Scope: UID/CEC/00319/2013
A dangerous mix: Large-scale analysis of mixed-content websites

In this paper, we investigate the current state of practice about mixed-content websites, websites that are accessed using the HTTPS protocol, yet include some additional resources using HTTP. Through a large-scale experiment, we show that about half of the Internet’s most popular websites are currently using this practice and are thus vulnerable to a wide range of attacks, including the stealing of cookies and the injection of malicious JavaScript in the context of the vulnerable websites. Additionally, we investigate the default behavior of browsers on mobile devices and show that most of them, by default, allow the rendering of mixed content, which demonstrates that hundreds of thousands of mobile users are currently vulnerable to MITM attacks.status: publishe
An Arithmetical Interpretation of Verification and Intuitionistic
  Knowledge

Intuitionistic epistemic logic introduces an epistemic operator, which
reflects the intended BHK semantics of intuitionism, to intuitionistic logic.
The fundamental assumption concerning intuitionistic knowledge and belief is
that it is the product of verification. The BHK interpretation of
intuitionistic logic has a precise formulation in the Logic of Proofs and its
arithmetical semantics. We show here that this interpretation can be extended
to the notion of verification upon which intuitionistic knowledge is based,
thereby providing the systems of intuitionistic epistemic logic extended by an
epistemic operator based on verification with an arithmetical semantics too.Comment: Due to several publisher's errors the publisher failed to include a
  corrected version of the paper for publication. The paper published in LNCS
  9537 is an uncorrected proof which contains various errors introduced by the
  publisher, and lacks changes submitted to, and approved for inclusion by, the
  publisher. This should be considered the official on
Classical Logic with Mendler Induction: A Dual Calculus and Its Strong Normalization

We investigate (co-)induction in Classical Logic under the propositions-as-types paradigm, considering propositional, second-order, and (co-)inductive types. Specifically, we introduce an extension of the Dual Calculus with a Mendler-style (co-)iterator that remains strongly normalizing under head reduction. We prove this using a non-constructive realizability argument.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/978-3-319-27683-0_
Monocular Visual Teach and Repeat Aided by Local Ground Planarity

Visual Teach and Repeat (VT\&R) allows an autonomous vehicle to repeat a
previously traversed route without a global positioning system. Existing
implementations of VT\&R typically rely on 3D sensors such as stereo cameras
for mapping and localization, but many mobile robots are equipped with only 2D
monocular vision for tasks such as teleoperated bomb disposal. While
simultaneous localization and mapping (SLAM) algorithms exist that can recover
3D structure and motion from monocular images, the scale ambiguity inherent in
these methods complicates the estimation and control of lateral path-tracking
error, which is essential for achieving high-accuracy path following. In this
paper, we propose a monocular vision pipeline that enables kilometre-scale
route repetition with centimetre-level accuracy by approximating the ground
surface near the vehicle as planar (with some uncertainty) and recovering
absolute scale from the known position and orientation of the camera relative
to the vehicle. This system provides added value to many existing robots by
allowing for high-accuracy autonomous route repetition with a simple software
upgrade and no additional sensors. We validate our system over 4.3 km of
autonomous navigation and demonstrate accuracy on par with the conventional
stereo pipeline, even in highly non-planar terrain.Comment: In Proceedings of the International Conference on Field and Service
  Robotics (FSR'15), Toronto, Ontario, Canada, Jun. 24-26 201
Formative Quizzing and Learning Performance in Dutch First-Year Higher Education Students

In this research paper, a cross-sectional study into the effects of formative quizzing in higher education and its relation to learning performance is presented. For the current study, six online Formative Quizzing modules, consisting of texts, graphics and video clips followed by two or more test questions to reiterate the material, were provided to students. Students could not earn marks and were free to use the material, but were informed that in the final examination, questions relating to the material would be asked. Data analysis showed that students who completed all six modules had a statistical significant higher chance to score better on the final examination. This was true for high achieving students, but also, and even stronger, for low achieving students. The results therefore show in this particular set-up a potential causal relationship of online formative quizzing on learning performance in higher education
A Practical Procedure for the Construction and Reliability Analysis of Fixed Length Tests with Random Drawn Test Items

A procedure to construct valid and fair fixed-length tests with randomly drawn items from an item bank is described. The procedure provides guidelines for the set-up of a typical achievement test with regard to the number of items in the bank and the number of items for each position in a test. Further, a procedure is proposed to calculate the relative difficulty for individual tests and to correct the obtained score for each student based on the mean difficulty for all students and the particular test of a student. Also, two procedures are proposed for the problem to calculate the reliability of tests with randomly drawn items. The procedures use specific interpretations of regularly used methods to calculate Cronbach’s alpha and KR20 and the Spearman-Brown prediction formula. A simulation with R is presented to illustrate the accuracy of the calculation procedures and the effects on pass-fail decisions
Vocal Learning and Auditory-Vocal Feedback

Vocal learning is usually studied in songbirds and humans, species that can form auditory templates by listening to acoustic models and then learn to vocalize to match the template. Most other species are thought to develop vocalizations without auditory feedback. However, auditory input influences the acoustic structure of vocalizations in a broad distribution of birds and mammals. Vocalizations are dened here as sounds generated by forcing air past vibrating membranes. A vocal motor program may generate vocalizations such as crying or laughter, but auditory feedback may be required for matching precise acoustic features of vocalizations. This chapter discriminates limited vocal learning, which uses auditory input to fine-tune acoustic features of an inherited auditory template, from complex vocal learning, in which novel sounds are learned by matching a learned auditory template. Two or three songbird taxa and four or ve mammalian taxa are known for complex vocal learning. A broader range of mammals converge in the acoustic structure of vocalizations when in socially interacting groups, which qualifies as limited vocal learning. All birds and mammals tested use auditory-vocal feedback to adjust their vocalizations to compensate for the effects of noise, and many species modulate their signals as the costs and benefits of communicating vary. This chapter asks whether some auditory-vocal feedback may have provided neural substrates for the evolution of vocal learning. Progress will require more precise definitions of different forms of vocal learning, broad comparative review of their presence and absence, and behavioral and neurobiological investigations into the mechanisms underlying the skills.PostprintPeer reviewe
Toward building a content-based video recommendation system based on low-level features

One of the challenges in video recommendation systems is the New Item problem, which happens when the system is unable to recommend video items, that no information is available about them. For example, in the popular movie-sharing websites, such as Youtube, every-day, hundred millions of hours of videos are uploaded and big portion of these videos may not contain any meta-data, to be used by the system to generate recommendations. In this paper, we address this problem by proposing a method, that is based on automatic analysis of the video content in order to extract a number representative low-level visual features. Such features are then used to generate personalized content-based recommendations. Our evaluation shows that our proposed method can outperform the baselines, by producing more relevant recommendations. Hence, a set low-level features extracted automatically can be more descriptive and informative of the video content than a set of high-level expert annotated features
Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression

© Springer International Publishing Switzerland 2016.In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties
Static Analysis of Parity Games: Alternating Reachability Under Parity

It is well understood that solving parity games is equivalent, up to polynomial time, to model checking of the modal mu-calculus. It is a long-standing open problem whether solving parity games (or model checking modal mu-calculus formulas) can be done in polynomial time. A recent approach to studying this problem has been the design of partial solvers, algorithms that run in polynomial time and that may only solve parts of a parity game. Although it was shown that such partial solvers can completely solve many practical benchmarks, the design of such partial solvers was somewhat ad hoc, limiting a deeper understanding of the potential of that approach. We here mean to provide such robust foundations for deeper analysis through a new form of game, alternating reachability under parity. We prove the determinacy of these games and use this determinacy to define, for each player, a monotone fixed point over an ordered domain of height linear in the size of the parity game such that all nodes in its greatest fixed point are won by said player in the parity game. We show, through theoretical and experimental work, that such greatest fixed points and their computation leads to partial solvers that run in polynomial time. These partial solvers are based on established principles of static analysis and are more effective than partial solvers studied in extant work
An inequality type condition for quasinearly subharmonic functions and
  applications

Generalizing older works of Domar and Armitage and Gardiner, we give an
inequality for quasinearly subharmonic functions. As an application of this
inequality, we improve Domar's, Rippon's and our previous results concerning
the existence of the largest subharmonic minorant of a given function.
Moreover, and as an another application, we give a sufficient condition for a
separately quasinearly subharmonic function to be quasinearly subharmonic. Our
result contains the previous results of Lelong, of Avanissian, of Arsove, of
Armitage and Gardiner, and of ours.Comment: 17 pages, a talk in the conference Positivity VII, Leiden 22-26 July
  2013, Zaanen Centennial Conference, in: Trends in Mathematical Series,
  Birkh\"auser, to appea
Group Based Asymmetry – A Fast Saliency Algorithm

Manuscript version. Published version available at <a href=http://dx.doi.org/10.1007/978-3-319-27857-5_80>http://dx.doi.org/10.1007/978-3-319-27857-5_80</a>In this paper, we propose a saliency model that makes two major changes in a latest state-of-the-art model known as group based asymmetry. First, based on the properties of the dihedral group D4 we simplify the asymmetry calculations associated with the measurement of saliency. This results is an algorithm which reduces the number of calculations by at-least half that makes it the fastest among the six best algorithms used in this paper. Second, in order to maximize the information across different chromatic and multi-resolution features the color image space is de-correlated. We evaluate our algorithm against 10 state-of-the-art saliency models. Our results show that by using optimal parameters for a given data-set our proposed model can outperform the best saliency algorithm in the literature. However, as the differences among the (few) best saliency models are small we would like to suggest that our proposed fast GBA model is among the best and the fastest among the best
Lens Distortion Rectification using Triangulation based Interpolation

Nonlinear lens distortion rectification is a common first step in image
processing applications where the assumption of a linear camera model is
essential. For rectifying the lens distortion, forward distortion model needs
to be known. However, many self-calibration methods estimate the inverse
distortion model. In the literature, the inverse of the estimated model is
approximated for image rectification, which introduces additional error to the
system. We propose a novel distortion rectification method that uses the
inverse distortion model directly. The method starts by mapping the distorted
pixels to the rectified image using the inverse distortion model. The resulting
set of points with subpixel locations are triangulated. The pixel values of the
rectified image are linearly interpolated based on this triangulation. The
method is applicable to all camera calibration methods that estimate the
inverse distortion model and performs well across a large range of parameters.Comment: International Symposium on Visual Computing, 201
Generalized Wishart processes for interpolation over diffusion tensor
  fields

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive tool for
watching the microstructure of fibrous nerve and muscle tissue. From dMRI, it
is possible to estimate 2-rank diffusion tensors imaging (DTI) fields, that are
widely used in clinical applications: tissue segmentation, fiber tractography,
brain atlas construction, brain conductivity models, among others. Due to
hardware limitations of MRI scanners, DTI has the difficult compromise between
spatial resolution and signal noise ratio (SNR) during acquisition. For this
reason, the data are often acquired with very low resolution. To enhance DTI
data resolution, interpolation provides an interesting software solution. The
aim of this work is to develop a methodology for DTI interpolation that enhance
the spatial resolution of DTI fields. We assume that a DTI field follows a
recently introduced stochastic process known as a generalized Wishart process
(GWP), which we use as a prior over the diffusion tensor field. For posterior
inference, we use Markov Chain Monte Carlo methods. We perform experiments in
toy and real data. Results of GWP outperform other methods in the literature,
when compared in different validation protocols.Comment: 8 pages, 3 figures, 15 subfigure
Semantic URL Analytics to Support Efficient Annotation of Large Scale
  Web Archives

Long-term Web archives comprise Web documents gathered over longer time
periods and can easily reach hundreds of terabytes in size. Semantic
annotations such as named entities can facilitate intelligent access to the Web
archive data. However, the annotation of the entire archive content on this
scale is often infeasible. The most efficient way to access the documents
within Web archives is provided through their URLs, which are typically stored
in dedicated index files.The URLs of the archived Web documents can contain
semantic information and can offer an efficient way to obtain initial semantic
annotations for the archived documents. In this paper, we analyse the
applicability of semantic analysis techniques such as named entity extraction
to the URLs in a Web archive. We evaluate the precision of the named entity
extraction from the URLs in the Popular German Web dataset and analyse the
proportion of the archived URLs from 1,444 popular domains in the time interval
from 2000 to 2012 to which these techniques are applicable. Our results
demonstrate that named entity recognition can be successfully applied to a
large number of URLs in our Web archive and provide a good starting point to
efficiently annotate large scale collections of Web documents
Processing keyword queries under access limitations

The Deep Web is constituted by data accessible through Web pages, but not readily indexable by search engines, as they are returned in dynamic pages. In this paper we propose a framework for accessing Deep Web sources, represented as relational tables with so-called access limitations, with keyword-based queries. We formalize the notion of optimal answer and propose methods for query processing. To the best of our knowledge, ours is the first systematic approach to keyword search in such context
Building self-adaptive systems by adaptation patterns integrated into agent methodologies

Adopting patterns, i.e. reusable solutions to generic problems, turns out to be useful to rely on tested solutions and to avoid reinventing the wheel. To this aim, we proposed to use adaptation patterns to build systems that exhibit self-adaptive features. However, these patterns would be more usable if integrated in a methodology exploited to develop a system. In this paper we show how our Catalogue of adaptation patterns can be integrated into methodologies for adaptive systems; more in detail, we consider methodologies which support the development of multi-agent systems that can be considered good examples of adaptive systems. The paper, in particular, shows the integration of our Catalogue of adaptive patterns into the PASSI methodology, together with the graphical tool that we developed to support it
Astrophysical Fluids of Novae: High Resolution Pre-decay X-ray spectrum
  of V4743 Sagittarii

Eight X-ray observations of V4743 Sgr (2002), observed with Chandra and
XMM-Newton are presented. The nova turned off some time between days 301.9 and
371, and the X-ray flux subsequently decreased from day 301.9 to 526 following
an exponential decline time scale of $(96 \pm 3)$ days. We use the absorption
lines present in the SSS spectrum for diagnostic purposes, and characterize the
physics and the dynamics of the expanding atmosphere during the explosion of
the nova. The information extracted from this first stage is then used as input
for computing full photoionization models of the ejecta in V4743 Sgr. The SSS
spectrum is modeled with a simple black-body and multiplicative Gaussian lines,
which provides us of a general kinematical picture of the system, before it
decays to its faint phase (Ness et al. 2003). In the grating spectra taken
between days 180.4 and 370, we can resolve the line profiles of absorption
lines arising from H-like and He-like C, N, and O, including transitions
involving higher principal quantum numbers. Except for a few interstellar
lines, all lines are significantly blue-shifted, yielding velocities between
1000 and 6000 km/s which implies an ongoing mass loss. It is shown that
significant expansion and mass loss occur during this phase of the explosion,
at a rate $\dot{M} \approx (3-5) \times 10^{-4} ~ (\frac{L}{L_{38}}) ~
M_{\odot}/yr$. Our measurements show that the efficiency of the amount of
energy used for the motion of the ejecta, defined as the ratio between the
kinetic luminosity $L_{\rm kin}$ and the radiated luminosity $L_{\rm rad}$, is
of the order of one.Comment: 25 pages, 9 figures. Accepted in book: Recent Advances in Fluid
  Dynamics with Environmental Applications, pp.365-39