pinecone/core-2020-05-10-deduplication huggingface dataset:
Linear Superiorization for Infeasible Linear Programming

Linear superiorization (abbreviated: LinSup) considers linear programming
(LP) problems wherein the constraints as well as the objective function are
linear. It allows to steer the iterates of a feasibility-seeking iterative
process toward feasible points that have lower (not necessarily minimal) values
of the objective function than points that would have been reached by the same
feasiblity-seeking iterative process without superiorization. Using a
feasibility-seeking iterative process that converges even if the linear
feasible set is empty, LinSup generates an iterative sequence that converges to
a point that minimizes a proximity function which measures the linear
constraints violation. In addition, due to LinSup's repeated objective function
reduction steps such a point will most probably have a reduced objective
function value. We present an exploratory experimental result that illustrates
the behavior of LinSup on an infeasible LP problem.Comment: arXiv admin note: substantial text overlap with arXiv:1612.0653
A mobile and evolving tool to predict colorectal cancer survivability

In this work, a tool for the survivability prediction of patients with colon or rectal cancer, up to five years after diagnosis and treatment, is presented. Indeed, an accurate survivability prediction is a difficult task for health care professionals and of high concern to patients, so that they can make the most of the rest of their lives. The distinguishing features of the tool include a balance between the number of necessary inputs and prediction performance, being mobile-friendly, and featuring an online learning component that enables the automatic evolution of the prediction models upon the addition of new cases.This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope UID/CEC/00319/2013. The work of Tiago Oliveira is supported by a FCT grant with the reference SFRH/BD/85291/2012.info:eu-repo/semantics/publishedVersio
Exploiting short supports for improved encoding of arbitrary constraints into SAT

Encoding to SAT and applying a highly efficient modern SAT solver is an increasingly popular method of solving finite-domain constraint problems. In this paper we study encodings of arbitrary constraints where unit propagation on the encoding provides strong reasoning. Specifically, unit propagation on the encoding simulates generalised arc consistency on the original constraint. To create compact and efficient encodings we use the concept of short support. Short support has been successfully applied to create efficient propagation algorithms for arbitrary constraints. A short support of a constraint is similar to a satisfying tuple however a short support is not required to assign every variable in scope. Some variables are left free to take any value. In some cases a short support representation is smaller than the table of satisfying tuples by an exponential factor. We present two encodings based on short supports and evaluate them on a set of benchmark problems, demonstrating a substantial improvement over the state of the art.Postprin
Propagation via Kernelization: The Vertex Cover Constraint

The technique of kernelization consists in extracting, from an instance of a
problem, an essentially equivalent instance whose size is bounded in a
parameter k. Besides being the basis for efficient param-eterized algorithms,
this method also provides a wealth of information to reason about in the
context of constraint programming. We study the use of kernelization for
designing propagators through the example of the Vertex Cover constraint. Since
the classic kernelization rules often correspond to dominance rather than
consistency, we introduce the notion of "loss-less" kernel. While our
preliminary experimental results show the potential of the approach, they also
show some of its limits. In particular, this method is more effective for
vertex covers of large and sparse graphs, as they tend to have, relatively,
smaller kernels
Extending Broken Triangles and Enhanced Value-Merging

Broken triangles constitute an important concept not only  for solving constraint satisfaction problems in polynomial time, but also for variable elimination or domain reduction by merging domain values. Specifically, for a given variable in a binary arc-consistent CSP, if no broken triangle occurs on any pair of values, then this variable can be eliminated while preserving satisfiability. More recently, it has been shown that even when this rule cannot be applied, it could be possible that for a given pair of values no broken triangle occurs. In this case, we  can apply a domain-reduction operation which consists in merging these values while preserving satisfiability.  In this paper we show that under certain conditions, and even if there are some broken triangles on a pair of values, these values can be merged without changing the satisfiability of the instance. This allows us to  define a stronger merging operation and a new tractable class of binary CSP instances. We report experimental trials on benchmark instances
Big image of Galois representations associated with finite slope
  $p$-adic families of modular forms

We consider the Galois representation associated with a finite slope $p$-adic
family of modular forms. We prove that the Lie algebra of its image contains a
congruence Lie subalgebra of a non-trivial level. We describe the largest such
level in terms of the congruences of the family with $p$-adic CM forms.Comment: 23 pages; revision of Section 2 (see Remark 2.4) and improvement of
  Proposition 4.14, plus minor changes. Published in "Elliptic Curves, Modular
  Forms and Iwasawa Theory. In Honour of John H. Coates' 70th Birthday,
  Cambridge, UK, March 2015", Springer Proceedings in Mathematics & Statistics,
  Vol. 188, 201
Hyperelasticity of Soft Tissues and Related Inverse Problems

International audienceIn this chapter, we are interested in the constitutive equations used to model macroscopically the mechanical function of soft tissues. After reviewing some basics about nonlinear finite–strain constitutive relations, we present recent developments of experimental biomechanics and inverse methods aimed at quantifying consti-tutive parameters of soft tissues. A focus is given to in vitro characterization of hyperelastic parameters based on full-field data that can be collected with digital image correlation systems during the experimental tests. The specific use of these data for membrane-like tissues is first illustrated through the example of bulge inflation tests carried out onto pieces of aortic aneurysms. Then an inverse method, based on the principle of virtual power, is introduced to estimate regional variations of material parameters for more general applications
Electronic participation with a special reference to social media - a literature review

As a consequence of the interdisciplinary nature of Electronic Partici-pation (e-Participation), current research on the field is fragmented and scattered. The exciting blurry boundaries and the immature identity of the field are making difficult the understanding of the main domain themes being investigated, in par-ticular for “neophytes” researchers. In practice, several e-Participation initiatives often attract a wide audience but face serious limitations regarding involvement of those who attract. Recently, the potential of using social media to address cit-izens’ involvement deficit has been subject of academic debate. By consulting 44 e-Participation papers, considered highly relevant to the aforementioned chal-lenges, this paper produces a general overview of e-Participation research, par-ticularly through social media. The findings show that the e-Participation field still faces the challenge of identity and strive for gaining wider recognition as an independent research area. Concerning e-Participation through social media which seems to be partly overlooked in the field research, the politicians-citizen’s interaction has dominated scholars' attention and the adoption of such initiatives sponsored and driven by governments are rarely examine. Based on the findings, several research suggestions, which could play a significant contribution to advance future e-Participation research, are proposed
Toward a Play Management System for Play-Based Learning

International audienceThis position paper is dedicated to describing a preliminary model of an integrated system, called Play Management System (PMS). PMS is designed to support both players and teachers to deliver, use, manage and track play situations. This PMS model results from a design-based research methodology. Our approach focuses on (1) the learners and the situation that emerges when they play the game, rather than the system dedicated to play and (2) the teachers who want to manage a game-based learning situation. Thus, we argue for a shift from a game-based to a play-based perspective. 1 Introduction Within a context marked by the development of alternative pedagogies, this position paper aims to describe a model of an integrated system, called Play Management System (PMS), dedicated to support players and teachers to deliver, use, manage and track play situations. The purpose of this article is to propose an innovative approach for implementing a play-based learning approach by (1) focusing on the learners and taking into consideration the situation that emerges when they play rather than the artifact dedicated to play (play vs game) and (2) focusing on the teachers who want to implement and manage a play-based learning situation in their classroom (play management vs game design). Thus, we address the issue of teachers' requirements for the orchestration of a play situation within an educational context. In the first section of this paper, we advocate for a player-centered approach for game-based learning. The second section presents a game developed during the project and the design-based research methodology adopted for designing this game. The third section describe
(Mathematical) Logic for Systems Biology (Invited Paper)

We advocates here the use of (mathematical) logic for systems biology, as a
unified framework well suited for both modeling the dynamic behaviour of
biological systems, expressing properties of them, and verifying these
properties. The potential candidate logics should have a traditional proof
theoretic pedigree (including a sequent calculus presentation enjoying
cut-elimination and focusing), and should come with (certified) proof tools.
Beyond providing a reliable framework, this allows the adequate encodings of
our biological systems. We present two candidate logics (two modal extensions
of linear logic, called HyLL and SELL), along with biological examples. The
examples we have considered so far are very simple ones-coming with completely
formal (interactive) proofs in Coq. Future works includes using automatic
provers, which would extend existing automatic provers for linear logic. This
should enable us to specify and study more realistic examples in systems
biology, biomedicine (diagnosis and prognosis), and eventually neuroscience
Goal-Oriented Reduction of Automata Networks

We consider networks of finite-state machines having local transitions
conditioned by the current state of other automata. In this paper, we depict a
reduction procedure tailored for a given reachability property of the form
``from global state s there exists a sequence of transitions leading to a state
where an automaton g is in a local state T'. By exploiting a causality analysis
of the transitions within the individual automata, the proposed reduction
removes local transitions while preserving all the minimal traces that satisfy
the reachability property. The complexity of the procedure is polynomial in the
total number of local states and transitions, and exponential in the number of
local states within one automaton. Applied to automata networks modelling
dynamics of biological systems, we observe that the reduction shrinks down
significantly the reachable state space, enhancing the tractability of the
model-checking of large networks.Comment: Accepted at CMSB 201
PREMER: Parallel reverse engineering of biological networks with information theory

A common approach for reverse engineering biological networks from data is to deduce the existence of interactions among nodes from information theoretic measures. Estimating these quantities in a multidimensional space is computationally demanding for large datasets. This hampers the application of elaborate algorithms  which are crucial for discarding spurious interactions and determining causal relationships  to large-scale network inference problems. To alleviate this issue we have developed PREMER, a software tool which can automatically run in parallel and sequential environments, thanks to its implementation of OpenMP directives. It recovers network topology and estimates the strength and causality of interactions using information theoretic criteria, and allowing the incorporation of prior knowledge. A preprocessing module takes care of imputing missing data and correcting outliers if needed. PREMER (https://sites.google.com/site/premertoolbox/) runs on Windows, Linux and OSX, it is implemented in Matlab/Octave and Fortran 90, and it does not require any commercial software.AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C fellowship ED481B2014/133-0. KB was supported by the German Federal Ministry of Research and Education (BMBF, OncoPath consortium). JRB acknowledges funding from the Spanish government (MINECO) and the European Regional Development Fund (ERDF) through the project “SYNBIOFACTORY” (grant number DPI2014-55276-C5-2-R). This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 686282 (CanPathPro). We thank David R. Penas and David Henriques for assistance with the implementation
Persuasiveness of eWOM communications: Literature review and suggestions for future research

YesElectronic word-of-mouth (eWOM) plays an important part in consumer purchase decision. The way consumers perceive the persuasiveness of eWOM message can affect their attitude, and purchase intention, and hence sales. Thus, the topic of persuasiveness of eWOM communications has received much attention from scholars. The objective of this paper is to provide a brief review of the existing literature related to the effectiveness of eWOM communications and offer an overview of the determinants of eWOM persuasiveness. This paper contributes to the existing eWOM literature by reviewing the existing studies on eWOM communications, identifying gaps in the current research and providing directions for future research
Trust Management in Social Internet of Things: A Survey

Social Internet of Things is a new paradigm where Internet of Things merges with Social Networks, allowing people and devices to interact, facilitating information sharing and enabling a variety of attractive applications. However, face to this new paradigm, users remain suspicious and careful. They fear disclosure of their data and violation of their privacy. Without trustworthy technologies to ensure user's safe communications and trustworthy interactions, the SIoT will not reach enough popularity to be considered as a well-established technology. Accordingly, trust management becomes a major challenge to ensure reliable data analysis, qualified services and enhanced security. It helps people exceed their fears and promotes their acceptance and consumption on IoT services. However, current research still lacks a comprehensive study on trust management in SIoT. In this paper, we expose basic concepts, properties and models proposed for the trust management in SIOT environments. Furthermore, we discuss unsolved issues and future research trends
What Makes Your Writing Style Unique? Significant Differences Between Two Famous Romanian Orators

This paper introduces a novel, in-depth approach of analyzing the
differences in writing style between two famous Romanian orators, based on
automated textual complexity indices for Romanian language. The considered
authors are: (a) Mihai Eminescu, Romania’s national poet and a remarkable
journalist of his time, and (b) Ion C. Brătianu, one of the most important
Romanian politicians from the middle of the 18th century. Both orators have a
common journalistic interest consisting in their desire to spread the word about
political issues in Romania via the printing press, the most important public
voice at that time. In addition, both authors exhibit writing style particularities,
and our aim is to explore these differences through our ReaderBench framework
that computes a wide range of lexical and semantic textual complexity indices
for Romanian and other languages. The used corpus contains two collections of
speeches for each orator that cover the period 1857–1880. The results of this
study highlight the lexical and cohesive textual complexity indices that reflect
very well the differences in writing style, measures relying on Latent Semantic
Analysis (LSA) and Latent Dirichlet Allocation (LDA) semantic models.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187.  This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains
Detecting Satire in Italian Political Commentaries

This paper presents computational work to detect satire/sarcasm in long commentaries on Italian politics. It uses the lexica extracted from the manual annotation of some 30K word texts based on Appraisal Theory. The underlying hypothesis is that using this framework it is possible to pinpoint precisely ironic content through the deep semantic analysis of evaluative judgement and appreciation. The paper presents the manual annotation phase realized on 112 texts by two well-known Italian journalists. After a first  experimentation based on the lexicons extracted from the xml output files, we proceed to retag lexical entries dividing them up into two subclasses: with figurative or literal meaning. Eventually more fine-grained Appraisal features are derived and more experiments are carried out and compared to results obtained by a lean sentiment analysis. The final output is produced from held out texts to verify the usefulness of the lexica and the Appraisal theory in detecting ironic content
Query rewriting under linear EL knowledge bases

With the adoption of the recent SPARQL 1.1 standard, RDF databases are capable of directly answering more expressive queries than simple conjunctive queries. In this paper we exploit such capabilities to answer conjunctive queries (CQs) under ontologies expressed in the description logic called linear EL-lin, a restricted form of EL.  In particular, we show a query answering algorithm that rewrites a given CQ into a conjunctive regular path query (CRPQ) which, evaluated on the given instance, returns the correct answer.  Our technique is based on the representation of infinite unions of CQs by non-deterministic finite-state automata.  Our results achieve optimal data complexity, as well as producing rewritings straightforwardly implementable in SPARQL 1.1
A recursive paradigm for aligning observed behavior of large structured process models

The alignment of observed and modeled behavior is a crucial problem in process mining, since it opens the door for conformance checking and enhancement of process models. The state of the art techniques for the computation of alignments rely on a full exploration of the combination of the model state space and the observed behavior (an event log), which hampers their applicability for large instances. This paper presents a fresh view to the alignment problem: the computation of alignments is casted as the resolution of Integer Linear Programming models, where the user can decide the granularity of the alignment steps. Moreover, a novel recursive strategy is used to split\ud
the problem into small pieces, exponentially reducing the complexity of the ILP models to be solved. The contributions of this paper represent a promising alternative to fight the inherent complexity of computing alignments for large instances.Peer ReviewedPostprint (author's final draft
A unified approach for measuring precision and generalization based on anti-alignments

The holy grail in process mining is an algorithm that, given an event log, produces fitting, precise, properly generalizing and simple process models. While there is consensus on the existence of solid metrics for fitness and simplicity, current metrics for precision and generalization have important flaws, which hamper their applicability in a general setting. In this paper, a novel approach to measure precision and generalization is presented, which relies on the notion of antialignments. An anti-alignment describes highly deviating model traces with respect to observed behavior. We propose metrics for precision and generalization that resemble the leave-one-out cross-validation techniques, where individual traces of the log are removed and the computed anti-alignment assess the model’s capability to describe precisely or generalize the observed behavior. The metrics have been implemented in ProM and tested on several examples.Peer ReviewedPostprint (author's final draft
Discovering duplicate tasks in transition systems for the simplification of process models

This work presents a set of methods to improve the understandability of process models. Traditionally, simplification methods trade off quality metrics, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the\ud
paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on the transition system generated by the log. The method is able to discover duplicate tasks even in the presence of concurrency and choice. The second problem is the structural simplification of the model by identifying optional and repetitive tasks. The tasks are substituted by annotated events that allow the removal of silent tasks and reduce the complexity of the\ud
model. An important feature of the methods proposed in this paper is that they are independent from the actual miner used for process discovery.Peer ReviewedPostprint (author's final draft
Revisiting interval protection, a.k.a. partial cell suppression, for tabular data

The final publication is available at link.springer.comInterval protection or partial cell suppression was introduced in “M. Fischetti, J.-J. Salazar, Partial cell suppression: A new methodology for statistical disclosure control, Statistics and Computing, 13, 13–21, 2003” as a “linearization” of the difficult cell suppression problem. Interval protection replaces some cells by intervals containing the original cell value, unlike in cell suppression where the values are suppressed. Although the resulting optimization problem is still huge—as in cell suppression, it is linear, thus allowing the application of efficient procedures. In this work we present preliminary results with a prototype implementation of Benders decomposition for interval protection. Although the above seminal publication about partial cell suppression applied a similar methodology, our approach differs in two aspects: (i) the boundaries of the intervals are completely independent in our implementation, whereas the one of 2003 solved a simpler variant where boundaries must satisfy a certain ratio; (ii) our prototype is applied to a set of seven general and hierarchical tables, whereas only three two-dimensional tables were solved with the implementation of 2003.Peer ReviewedPostprint (author's final draft