pinecone/core-2020-05-10-deduplication huggingface dataset:
A mechanized proof of loop freedom of the (untimed) AODV routing
  protocol

The Ad hoc On-demand Distance Vector (AODV) routing protocol allows the nodes
in a Mobile Ad hoc Network (MANET) or a Wireless Mesh Network (WMN) to know
where to forward data packets. Such a protocol is 'loop free' if it never leads
to routing decisions that forward packets in circles. This paper describes the
mechanization of an existing pen-and-paper proof of loop freedom of AODV in the
interactive theorem prover Isabelle/HOL. The mechanization relies on a novel
compositional approach for lifting invariants to networks of nodes. We exploit
the mechanization to analyse several improvements of AODV and show that
Isabelle/HOL can re-establish most proof obligations automatically and identify
exactly the steps that are no longer valid.Comment: The Isabelle/HOL source files, and a full proof document, are
  available in the Archive of Formal Proofs, at
  http://afp.sourceforge.net/entries/AODV.shtm
First experiments in cultural alignment repair (extended version)

euzenat2014cInternational audienceAlignments between ontologies may be established through agents holding such ontologies attempting at communicating and taking appropriate action when communication fails. This approach, that we call cultural repair, has the advantage of not assuming that everything should be set correctly before trying to communicate and of being able to overcome failures. We test here the adaptation of this approach to alignment repair, i.e., the improvement of incorrect alignments. For that purpose, we perform a series of experiments in which agents react to mistakes in alignments. The agents only know about their ontologies and alignments with others and they act in a fully decentralised way. We show that cultural repair is able to converge towards successful communication through improving the objective correctness of alignments. The obtained results are on par with a baseline of a priori alignment repair algorithms
What are the Important Properties of an Entity? Comparing Users and Knowledge Graph Point of View

International audienceEntities play a key role in knowledge bases in general and in the Web of Data in particular. Entities are generally described with a lot of properties, this is the case for DBpedia. It is, however, difficult to assess which ones are more "important" than others for particular tasks such as visualizing the key facts of an entity or filtering out the ones which will yield better instance matching. In this paper, we perform a reverse engineering of the Google Knowledge graph panel to find out what are the most "important" properties for an entity according to Google. We compare these results with a survey we conducted on 152 users. We finally show how we can represent and explicit this knowledge using the Fresnel vocabulary
SemLAV: Querying Deep Web and Linked Open Data with SPARQL

International audienceSemLAV allows to execute SPARQL queries against the Deep Web and Linked Open Data data sources. It implements the mediator-wrapper architecture based on view definitions over remote data sources. SPARQL queries are expressed using a mediator schema vocabulary, and SemLAV selects relevant data sources and rank them. The ranking strat-egy is designed to deliver results quickly based only on view definitions, i.e., no statistics, nor probing on sources are required. In this demonstra-tion, we validate the effectiveness of SemLAV approach with real data sources from social networks and Linked Open Data. We show in differ-ent setups that materializing only a subset of ranked relevant views is enough to deliver significant part of expected results
Urbanization and Green Spaces—A Study on Jnana Bharathi Campus, Bangalore University

Global warming is amongst the most alarming problems of the new era. Carbon emission is evidently the strongest fundamental factor for global warming. So increasing carbon emission is one of today’s major concerns, which is well addressed in the Kyoto Protocol. Trees are amongst the most significant elements of any landscape, because of both biomass and diversity, and their key role in ecosystem dynamics is well known. Trees absorb the atmospheric carbon dioxide and act as a carbon sink, since 50 % of biomass is carbon itself and the importance of carbon sequestration in forest areas is already accepted, and well documented. With this background, a carbon sequestration potential study was carried out in Jnana Bharathi campus, Bangalore University using the Quadrat method. The total geographical area is about 449.74 ha with a rich vegetation sector and the total amount of both above ground carbon (AGC) and below ground carbon (BGC) was estimated as an average of 54.8 t/ha. The total amount of carbon dioxide assimilated into the vegetation in terms of both above ground and below ground biomass was estimated as an average of 200.9 t/ha. Urbanization and habitat fragmentation seem to be increasing worldwide, substantiated by a case study in Bangalore City. The analysis revealed that increase in built-up area at the city level was by about 164.62 km2, while the vegetation and water bodies decreased by about 285.72 and 7.2 km2 respectively. However, Bangalore University, Jnana Bharathi campus attains a good vegetation cover and is seen as one of the ‘green lungs’ of Bangalore city
SAKey: Scalable almost key discovery in RDF data

Exploiting identity links among RDF resources allows applications to efficiently integrate data. Keys can be very useful to discover these identity links. A set of properties is considered as a key when its values uniquely identify resources. However, these keys are usually not available. The approaches that attempt to automatically discover keys can easily be overwhelmed by the size of the data and require clean data. We present SAKey, an approach that discovers keys in RDF data in an efficient way. To prune the search space, SAKey exploits characteristics of the data that are dynamically detected during the process. Furthermore, our approach can discover keys in datasets where erroneous data or duplicates exist (i.e., almost keys). The approach has been evaluated on different synthetic and real datasets. The results show both the relevance of almost keys and the efficiency of discovering them
Answering SPARQL queries over databases under OWL 2 QL entailment regime

We present an extension of the ontology-based data access platform Ontop that supports answering SPARQL queries under the OWL 2 QL direct semantics entailment regime for data instances stored in relational databases. On the theoretical side, we show how any input SPARQL query, OWL 2 QL ontology and R2RML mappings can be rewritten to an equivalent SQL query solely over the data. On the practical side, we present initial experimental results demonstrating that by applying the Ontop technologies—the tree-witness query rewriting, T-mappings compiling R2RML mappings with ontology hierarchies, and T-mapping optimisations using SQL expressivity and database integrity\ud
constraints—the system produces scalable SQL queries
Model Reduction for DAEs with an Application to Flow Control

Direct numerical simulation of dynamical systems is of fundamental importance
in studying a wide range of complex physical phenomena. However, the
ever-increasing need for accuracy leads to extremely large-scale dynamical
systems whose simulations impose huge computational demands. Model reduction
offers one remedy to this problem by producing simpler reduced models that are
both easier to analyze and faster to simulate while accurately replicating the
original behavior. Interpolatory model reduction methods have emerged as
effective candidates for very large-scale problems due to their ability to
produce high-fidelity (optimal in some cases) reduced models for linear and
bilinear dynamical systems with modest computational cost. In this paper, we
will briefly review the interpolation framework for model reduction and
describe a well studied flow control problem that requires model reduction of a
large scale system of differential algebraic equations. We show that
interpolatory model reduction produces a feedback control strategy that matches
the structure of much more expensive control design methodologies.Comment: Accepted to appear in Active Flow and Combustion Control 2014,
  Springer-Verlag, in pres
Ergodicity, Decisions, and Partial Information

In the simplest sequential decision problem for an ergodic stochastic process
X, at each time n a decision u_n is made as a function of past observations
X_0,...,X_{n-1}, and a loss l(u_n,X_n) is incurred. In this setting, it is
known that one may choose (under a mild integrability assumption) a decision
strategy whose pathwise time-average loss is asymptotically smaller than that
of any other strategy. The corresponding problem in the case of partial
information proves to be much more delicate, however: if the process X is not
observable, but decisions must be based on the observation of a different
process Y, the existence of pathwise optimal strategies is not guaranteed.
  The aim of this paper is to exhibit connections between pathwise optimal
strategies and notions from ergodic theory. The sequential decision problem is
developed in the general setting of an ergodic dynamical system (\Omega,B,P,T)
with partial information Y\subseteq B. The existence of pathwise optimal
strategies grounded in two basic properties: the conditional ergodic theory of
the dynamical system, and the complexity of the loss function. When the loss
function is not too complex, a general sufficient condition for the existence
of pathwise optimal strategies is that the dynamical system is a conditional
K-automorphism relative to the past observations \bigvee_n T^n Y. If the
conditional ergodicity assumption is strengthened, the complexity assumption
can be weakened. Several examples demonstrate the interplay between complexity
and ergodicity, which does not arise in the case of full information. Our
results also yield a decision-theoretic characterization of weak mixing in
ergodic theory, and establish pathwise optimality of ergodic nonlinear filters.Comment: 45 page
The backbone decomposition for spatially dependent supercritical superprocesses

Consider any supercritical Galton-Watson process which may become extinct with positive probability. It is a well-understood and intuitively obvious phenomenon that, on the survival set, the process may be pathwise decomposed into a stochastically ‘thinner’ Galton-Watson process, which almost surely survives and which is decorated with immigrants, at every time step, initiating independent copies of the original Galton-Watson process conditioned to become extinct. The thinner process is known as the backbone and characterizes the genealogical lines of descent of prolific individuals in the original process. Here, prolific means individuals who have at least one descendant in every subsequent generation to their ownn. Starting with Evans and O’Connell (Can Math Bull 37:187–196, 1994), there exists a cluster of literature, (Engländer and Pinsky, Ann Probab 27:684–730, 1999; Salisbury and Verzani, Probab Theory Relat Fields 115:237–285, 1999; Duquesne and Winkel, Probab Theory Relat Fields 139:313–371, 2007; Berestycki, Kyprianou and Murillo-Salas, Stoch Proc Appl 121:1315–1331, 2011; Kyprianou and Ren, Stat Probab Lett 82:139–144, 2012),describing the analogue of this decomposition (the so-called backbone decomposition) for a variety of different classes of superprocesses and continuous-state branching processes. Note that the latter family of stochastic processes may be seen as the total mass process of superprocesses with non-spatially dependent branching mechanism.In this article we consolidate the aforementioned collection of results concerning backbone decompositions and describe a result for a general class of supercritical superprocesses with spatially dependent branching mechanisms. Our approach exposes the commonality and robustness of many of the existing arguments in the literature
A Multi-Modal Utility to Assist Powered Mobility Device Navigation Tasks

This paper presents the development of a shared control system for power mobility device users of varying capability in order to reduce carer oversight in navigation. Weighting of a user’s joystick input against a short-tem trajectory prediction and obstacle avoidance algorithm is conducted by taking into consideration proximity to obstacles and smoothness of user driving, resulting in capable users rewarded greater levels of manual control for undertaking maneuvres that can be considered more challenging. An additional optional comparison with a Vector Field Histogram applied to leader-tracking provides further activities, such as completely autonomous following and a task for the user to follow a leading entity. Indoor tests carried out on university campus demonstrate the viability of this work, with future trials at a care home for the disabled intended to show the system functioning in one of its intended settings
A novel culture-dependent gesture selection system for a humanoid robot performing greeting interaction

This definitive published version of this article is available from: http://dx.doi.org/10.1007/978-3-319-11973-1_35In human-robot interaction, it is important for the robots to adapt to\ud
our ways of communication. As humans, rules of non-verbal communication,\ud
including greetings, change depending on our culture. Social robots should\ud
adapt to these specific differences in order to communicate effectively, as a correct\ud
way of approaching often results into better acceptance of the robot. In this\ud
study, a novel greeting gesture selection system is presented and an experiment\ud
is run using the robot ARMAR-IIIb. The robot performs greeting gestures appropriate\ud
to Japanese culture; after interacting with German participants, the selection\ud
should become appropriate to German culture. Results show that the\ud
mapping of gesture selection evolves successfully
SVG-to-RDF image semantization

The goal of this work is to provide an original (semi-automatic) annotation framework titled SVG-to-RDF whichconverts a collection of raw Scalable vector graphic (SVG) images into a searchable semantic-based RDF graph structure that encodes relevant features and contents. Using a dedicated knowledge base, SVG-to-RDF offers the user possible semantic annotations for each geometric object in the image, based on a combination of shape, color, and position similarity measures. Our method presents several advantages, namely i) achieving complete semantization of image content, ii) allowing semantic-based data search and processing using standard RDF technologies, iii) while being compliant with Web standards (i.e., SVG and RDF) in displaying images and annotation results in any standard Web browser, as well as iv) coping with different application domains. Our solution is of linear complexity in the size of the image and knowledge base structures used. Using our prototype SVG2RDF, several experiments have been conducted on a set of panoramic dental x-ray images to underline our approach’s effectiveness, and its applicability to different application domains.N/
A Fuzzy System for Concept-Level Sentiment Analysis

Winner for Task 1 and Most Innovative ApproachInternational audienceAn emerging field within Sentiment Analysis concerns the investiga-tion about how sentiment concepts have to be adapted with respect to the different domains in which they are used. In the context of the Concept-Level Sentiment Analysis Challenge, we presented a system whose aims are twofold: (i) the implementation of a learning approach able to model fuzzy functions used for building the relationships graph representing the appropriateness between sentiment concepts and different domains (Task 1); and (ii) the development of a semantic resource based on the connection between an extended version of WordNet, SenticNet, and ConceptNet, that has been used both for extracting concepts (Task 2) and for classifying sentences within specific domains (Task 3)
Improving conflict support environments with information regarding social relationships

"Advances in artificial intelligence : IBERAMIA 2014 : 14th Ibero-American Conference on AI, Santiago de Chile, Chile, November 24-27, 2014, proceedings", ISBN 978-3-319-12026-3Having knowledge about social interactions as a basis for informed
decision support in situations of conflict can be determinant. However, lower attention
is given to the social network interpretation process in conflict management
approaches. The main objective of the work presented here is to identify
how the parties’ social networks correlate to their negotiation performance and
how this can be formalized. Therefore, an experiment was set up in which was
tried to streamline all the relevant aspects of the interaction between the individual
and its environment that occur in a rich sensory environment (where the
contextual modalities were monitored). This research explicitly focuses on the
idea that an Ambient Intelligence system can create scenarios that augment the
possibilities of reaching a positive outcome taking into account the role of contextualized
social relationships in various conflict management strategies.This work is part-funded by ERDF - European Regional Development Fund through the
COMPETE Programme (operational programme for competitiveness) and by National
Funds through the FCT - Fundac¸ ˜ao para a Ciˆencia e a Tecnologia (Portuguese Foundation
for Science and Technology) within project FCOMP-01-0124-FEDER-028980
(PTDC/EEI-SII/1386/2012) and project PEst-OE/EEI/UI0752/2014
Towards the cloudification of the social networks analytics

In the last years, with the increase of the available data from social networks and the rise of big data technologies, social data has emerged as one of the most profitable market for companies to increase their benefits. Besides, social computation scientists see such data as a vast ocean of information to study modern human societies. Nowadays, enterprises and researchers are developing their own mining tools in house, or they are outsourcing their social media mining needs to specialised companies with its consequent economical cost. In this paper, we present the first cloud computing service to facilitate the deployment of social media analytics applications to allow data practitioners to use social mining tools as a service. The main advantage of this service is the possibility to run different queries at the same time and combine their results in real time. Additionally, we also introduce twearch, a prototype to develop twitter mining algorithms as services in the cloud.Peer ReviewedPostprint (author’s final draft
Visual consensus feedback mechanism for group decision making with complementary linguistic preference relations

A visual consensus feedback mechanism for group decision making (GDM) problems with complementary linguistic preference relations is presented. Linguistic preferences are modelled using  triangular fuzzy membership functions, and the concepts of similarity degree (SD) between two experts as well as the proximity degree (PD) between an expert and the rest of experts in the group are defined and used to measure the consensus level (CL). A feedback mechanism is proposed to identify experts, alternatives and corresponding preference values that contribute less to consensus. The novelty of this feedback mechanism is that it provides experts with visual representations of their consensus status to easily see their consensus position within the group as well as to identify the alternatives and preference values that should be reconsidered for changing in the subsequent consensus round. The feedback mechanism also includes individualised recommendations to those identified  experts on changing their identified preference values and visual graphical simulation of future consensus status if the recommended values were to be implemented
3D Interactive Ultrasound Image Deformation for Realistic Prostate Biopsy Simulation

International audienceRealistic medical procedure simulators improve the learn-ing curve of the clinicians if they can reproduce real conditions and use. This paper describes the improvement of a transrectal ultrasound guided prostate biopsy simulator by adding the simulation of real-time prostate movements and deformations. A discrete bio-mechanical model is used to modify a 3D texture of an ultrasound image volume in order to quickly simulate the actual displacements and deformations. This pa-per describes this model and presents how the mesh deformation is used to induce the UltraSound volume deformation. The validation of the method is based on both a quantitative and a qualitative assessment. Experimental images acquired on a phantom are compared using mutual information metrics to the resulting generated images. This comparison shows that the proposed method offers realistic deformed 3D ultrasound images at interactive time. The method was successfully integrated to improve the transrectal ultrasound simulator
Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices al-lowed to develop new therapies for severe cardiac diseases like arrhyth-mias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Vir-tual reality simulators can reduce this burden by allowing to practice such procedures without consequences on patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, includ-ing pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative mul-tithreading approach, we reach high computational performances that allow to account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular poten-tial measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. This works is a step towards computerized medical learning curriculum
Intra-operative Registration for Stereotactic Procedures driven by a combined Biomechanical Brain and CSF Model

International audienceDuring stereotactic neurosurgery, the brain shift could affect the accuracy of the procedure. However, this deformation of the brain is not often considered in the pre-operative planning step or intra-operatively, and may lead to surgical complications, side effects or ineffectiveness. In this paper, we present a method to update the pre-operative planning based on a physical simulation of the brain shift. Because the simulation requires unknown input parameters, the method relies on a parameter estimation process to compute the intracranial state that matches the partial data taken from intra-operative modalities. The simulation is based on a biomechanical model of the brain and the cerebro-spinal fluid. In this paper, we show on an anatomical atlas that the method is numerically sound
Implementing cryptographic pairings at standard security levels

International audienceThis study reports on an implementation of cryptographic pairings in a general purpose computer algebra system. For security levels equivalent to the different AES flavours, we exhibit suitable curves in parametric families and show that optimal ate and twisted ate pairings exist and can be efficiently evaluated. We provide a correct description of Miller's algorithm for signed binary expansions such as the NAF and extend a recent variant due to Boxall et al. to addition-subtraction chains. We analyse and compare several algorithms proposed in the literature for the final exponentiation. Finally, we give recommendations on which curve and pairing to choose at each security level