pinecone/core-2020-05-10-deduplication huggingface dataset:
Fast Structuring of Radio Networks for Multi-Message Communications

We introduce collision free layerings as a powerful way to structure radio
networks. These layerings can replace hard-to-compute BFS-trees in many
contexts while having an efficient randomized distributed construction. We
demonstrate their versatility by using them to provide near optimal distributed
algorithms for several multi-message communication primitives.
  Designing efficient communication primitives for radio networks has a rich
history that began 25 years ago when Bar-Yehuda et al. introduced fast
randomized algorithms for broadcasting and for constructing BFS-trees. Their
BFS-tree construction time was $O(D \log^2 n)$ rounds, where $D$ is the network
diameter and $n$ is the number of nodes. Since then, the complexity of a
broadcast has been resolved to be $T_{BC} = \Theta(D \log \frac{n}{D} + \log^2
n)$ rounds. On the other hand, BFS-trees have been used as a crucial building
block for many communication primitives and their construction time remained a
bottleneck for these primitives.
  We introduce collision free layerings that can be used in place of BFS-trees
and we give a randomized construction of these layerings that runs in nearly
broadcast time, that is, w.h.p. in $T_{Lay} = O(D \log \frac{n}{D} +
\log^{2+\epsilon} n)$ rounds for any constant $\epsilon>0$. We then use these
layerings to obtain: (1) A randomized algorithm for gathering $k$ messages
running w.h.p. in $O(T_{Lay} + k)$ rounds. (2) A randomized $k$-message
broadcast algorithm running w.h.p. in $O(T_{Lay} + k \log n)$ rounds. These
algorithms are optimal up to the small difference in the additive
poly-logarithmic term between $T_{BC}$ and $T_{Lay}$. Moreover, they imply the
first optimal $O(n \log n)$ round randomized gossip algorithm
Toward a General Framework for Information Fusion

Depending on the representation setting, different combination rules have been proposed for fusing information from distinct sources. Moreover in each setting, different sets of axioms that combination rules should satisfy have been advocated, thus justifying the existence of alternative rules (usually motivated by situations where the behavior of other rules was found unsatisfactory). These sets of axioms are usually purely considered in their own settings, without in-depth analysis of common properties essential for all the settings. This paper introduces core properties that, once properly instantiated, are meaningful in different representation settings ranging from logic to imprecise probabilities. The following representation settings are especially considered: classical set representation, possibility theory, and evidence theory, the latter encompassing the two other ones as special cases. This unified discussion of combination rules across different settings is expected to provide a fresh look on some old but basic issues in information fusion
Comparative preferences induction methods for conversational recommenders

In an era of overwhelming choices, recommender systems aim at recommending the most suitable items to the user. Preference handling is one of the core issues in the design of recommender systems and so it is important for them to catch and model the user’s preferences as accurately as possible. In previous work, comparative preferences-based patterns were developed to handle preferences deduced by the system. These patterns assume there are only two values for each feature. However, real-world features can be multi-valued. In this paper, we develop preference induction methods which aim at capturing several preference nuances from the user feedback when features have more than two values. We prove the efficiency of the proposed methods through an experimental study
Development of software tool support for enterprise architecture in small and medium-sized enterprises

Throughout recent years a lot of research has been done to develop enterprise architecture (EA) approaches for large and complex enterprises. Consequently, an array of tools has been developed for these large enterprises to aid in EA management. However, traditional small and medium-sized enterprises (SMEs), which are very important for economy, have to a great extent been neglected. Recently research has been done towards a new EA approach for SMEs. The approach is called CHOOSE. As tool support is almost indispensable in complex environments, the need for tool support was quickly experienced while doing case studies in SMEs. Unfortunately, tool support is already rated low on usability by EA practitioners in large companies. A different approach was required to provide tool support for managers in SMEs. The developed software tool already received positive feedback from managers
First-Order Provenance Games

We propose a new model of provenance, based on a game-theoretic approach to
query evaluation. First, we study games G in their own right, and ask how to
explain that a position x in G is won, lost, or drawn. The resulting notion of
game provenance is closely related to winning strategies, and excludes from
provenance all "bad moves", i.e., those which unnecessarily allow the opponent
to improve the outcome of a play. In this way, the value of a position is
determined by its game provenance. We then define provenance games by viewing
the evaluation of a first-order query as a game between two players who argue
whether a tuple is in the query answer. For RA+ queries, we show that game
provenance is equivalent to the most general semiring of provenance polynomials
N[X]. Variants of our game yield other known semirings. However, unlike
semiring provenance, game provenance also provides a "built-in" way to handle
negation and thus to answer why-not questions: In (provenance) games, the
reason why x is not won, is the same as why x is lost or drawn (the latter is
possible for games with draws). Since first-order provenance games are
draw-free, they yield a new provenance model that combines how- and why-not
provenance
Ideal Chaotic Pattern Recognition is achievable: The Ideal-M-AdNN - its design and properties

Published version of a chapter in the book: Transactions on Computational Collective Intelligence XI. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-41776-4_2This paper deals with the relatively new field of designing a Chaotic Pattern Recognition (PR) system. The benchmark of such a system is the following: First of all, one must be able to train the system with a set of “training” patterns. Subsequently, as long as there is no testing pattern, the system must be chaotic. However, if the system is, thereafter, presented with an unknown testing pattern, the behavior must ideally be as follows. If the testing pattern is not one of the trained patterns, the system must continue to be chaotic. As opposed to this, if the testing pattern is truly one of the trained patterns (or a noisy version of a trained pattern), the system must switch to being periodic, with the specific trained pattern appearing periodically at the output. This is truly an ambitious goal, with the requirement of switching from chaos to periodicity being the most demanding. Some related work has been done in this regard. The Adachi Neural Network (AdNN) [1-5] has properties which are pseudo-chaotic, but it also possesses limited PR characteristics. As opposed to this, the Modified Adachi Neural Network (M-AdNN) proposed by Calitoiu et al [6], is a fascinating NN which has been shown to possess the required periodicity property desirable for PR applications. However, in this paper, we shall demonstrate that the PR properties claimed in [6] are not as powerful as originally reported. Indeed, the claim of the authors of [6] is true, in that it resonates periodically for trained input patterns. But unfortunately, the M-AdNN also resonates for unknown patterns and produces these unknown patterns at the output periodically. However, we describe how the parameters of the M-AdNN for its weights, steepness and external inputs, can be specified so as to yield a new NN, which we shall refer to as the Ideal-M-AdNN. Using a rigorous Lyapunov analysis, we shall analyze the chaotic properties of the Ideal-M-AdNN, and demonstrate its chaotic characteristics. Thereafter, we shall verify that the system is also truly chaotic for untrained patterns. But most importantly, we demonstrate that it is able to switch to being periodic whenever it encounters patterns with which it was trained. Apart from being quite fascinating, as far as we know, the theoretical and experimental results presented here are both unreported and novel. Indeed, we are not aware of any NN that possesses these properties
A Framework for an adaptive grid scheduling: an  organizational perspective

Grid systems are complex computational organizations made of several interacting components evolving in an unpredictable and dynamic environment. In such context, scheduling is a key component and should be adaptive to face the numerous disturbances of the grid while guaranteeing its robustness and efficiency. In this context, much work remains at low-level focusing on the scheduling component taken individually. However, thinking the scheduling adaptiveness at a macro level with an organizational view, through its interactions with the other components, is also important. Following this view, in this paper we model a grid system as an agent-based organization and scheduling as a cooperative activity. Indeed, agent technology provides high level organizational concepts (groups, roles, commitments, interaction protocols) to structure, coordinate and ease the adaptation of distributed systems efficiently. More precisely, we make the following contributions. We provide a grid conceptual model that identifies the concepts and entities involved in the cooperative scheduling activity. This model is then used to define a typology of adaptation including perturbing events and actions to undertake in order to adapt. Then, we provide an organizational model, based on the Agent Group Role (AGR) meta-model of Freber, to support an adaptive scheduling at the organizational level. Finally, a simulator and an experimental evaluation have been realized to demonstrate the feasibility of our approach
Multimodal biometric fusion: A study on vulnerabilities to indirect attacks

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-41827-3_45Proceedings of 18th Iberoamerican Congress, CIARP 2013, Havana, CubaFusion of several biometric traits has traditionally been regarded as more secure than unimodal recognition systems. However, recent research works have proven that this is not always the case. In the present article we analyse the performance and robustness of several fusion schemes to indirect attacks. Experiments are carried out on a multimodal system based on face and iris, a user-friendly trait combination, over the publicly available multimodal Biosecure DB. The tested system proves to have a high vulnerability to the attack regardless of the fusion rule considered. However, the experiments prove that not necessarily the best fusion rule in terms of performance is the most robust to the type of attack considered.This work has been partially supported by projects Contexts (S2009/TIC-1485) from CAM, Bio-Challenge (TEC2009-11186) and Bio-Shield (TEC2012-34881) from Spanish MINECO, TABULA RASA (FP7-ICT-257289) and BEAT (FP7-SEC-284989) from EU, and Cátedra UAM-Telefónica
Local Optima Networks: A New Model of Combinatorial Fitness Landscapes

This chapter overviews a recently introduced network-based model of
combinatorial landscapes: Local Optima Networks (LON). The model compresses the
information given by the whole search space into a smaller mathematical object
that is a graph having as vertices the local optima and as edges the possible
weighted transitions between them. Two definitions of edges have been proposed:
basin-transition and escape-edges, which capture relevant topological features
of the underlying search spaces. This network model brings a new set of metrics
to characterize the structure of combinatorial landscapes, those associated
with the science of complex networks. These metrics are described, and results
are presented of local optima network extraction and analysis for two selected
combinatorial landscapes: NK landscapes and the quadratic assignment problem.
Network features are found to correlate with and even predict the performance
of heuristic search algorithms operating on these problems
Minimizing Human Effort in Reconciling Match Networks

Schema and ontology matching is a process of establishing correspondences between schema attributes and ontology concepts, for the purpose of data integration. Various commercial and academic tools have been developed to support this task. These tools provide impressive results on some datasets. However, as the matching is inherently uncertain, the developed heuristic techniques give rise to results that are not completely correct. In practice, post-matching human expert effort is needed to obtain a correct set of correspondences. We study this post-matching phase with the goal of reducing the costly human effort. We formally model this human-assisted phase and introduce a process of matching reconciliation that incrementally leads to identifying the correct correspondences. We achieve the goal of reducing the involved human effort by exploiting a network of schemas that are matched against each other.We express the fundamental matching constraints present in the network in a declarative formalism, Answer Set Programming that in turn enables to reason about necessary user input. We demonstrate empirically that our reasoning and heuristic techniques can indeed substantially reduce the necessary human involvement.Full Tex
Former students' perception of improvement potential of conceptual modeling in practice

Several authors have pointed out a significant gap between Conceptual Modeling (CM) theory and practice. It is then natural that we try to find answers to questions such as: What is the nature of the gap? Which is the magnitude of the gap? Why does the gap exist? and What could be done to narrow the gap? In this paper, we try to answer those questions from the point of view of the former students of a Requirements Engineering and Conceptual Modeling course that have been involved in professional projects. We have surveyed over 70 former students to know how they perceive the degree to which a set of four conceptual modeling artifacts are created in practice, and how they perceive the improvement potential of the creation of those artifacts in practice. For each artifact, we asked a question on the use of the artifact, and one on the recommendation of use of the artifact. We believe that there may be an improvement opportunity of the CM practice when a significant number of respondents would have recommended the creation of an artifact in the cases in which it was not created. We try to identify the reasons why the artifacts were not created, and what would be needed to convince stakeholders and developers to create the artifact, when it is recommended to do it.Postprint (author’s final draft
Visualization of Frequent Itemsets with Nested Circular Layout and Bundling Algorithm

Frequent itemset mining is one of the major data mining issues. Once generated by algorithms, the itemsets can be automatically processed, for instance to extract association rules. They can also be explored with visual tools, in order to analyze the emerging patterns. Graphical itemsets representation is a convenient way to obtain an overview of the global interaction structure. However, when the complexity of the database increases, the network may become unreadable. In this paper, we propose to display itemsets on concentric circles, each one being organized to lower the intricacy of the graph through an optimization process. Thanks to a graph bundling algorithm, we finally obtain a compact representation of a large set of itemsets that is easier to exploit. Colors accumulation and interaction operators facilitate the exploration of the new bundle graph and to illustrate how much an itemset is supported by the data
Recognition of voice commands using hybrid approach

Computerized systems with voice user interfaces could save time and ease the work of healthcare practitioners. To achieve this goal voice user interface should be reliable (to recognize the commands with high enough accuracy) and properly designed (to be convenient for the user). The paper deals with hybrid approach implementation issues for the voice commands recognition. By the hybrid approach we assume the combination of several different recognition methods to achieve higher recognition accuracy. The experimental results show that most voice commands are recognized good enough but there is some set of voice commands which recognition is more complicated. In this paper the novel method is proposed for the combination of several recognition methods based on the Ripper algorithm. Experimental evaluation showed that this method allows achieve higher recognition accuracy than application of blind combination rule
Optimizing Transportation Sequence in Warehouse with Genetic Algorithms

International audienceOptimizing transportation sequence is crucial to reduce material handling costs in warehouse operations and thus in total logistics costs. Transportation sequence is the ordering of storage and retrieval jobs that a material handling device has to perform to finish an order list. In many studies, the optimization of transportation sequence has been simplified as an order-picking problem, and accordingly solved as a classical traveling salesman problem. However, transportation sequence is a double-cycle storage and retrieval problem (DCSRP) in itself, meaning that the combination of storage and retrieval jobs into double cycles has to be considered simultaneously. In this paper, we propose formulating the DCSRP as a permutation problem and applying several genetic algorithms to solve the formulated problem. Extensive computational experiments were performed to demonstrate the capability of the approach. The experimental analysis confirms that our approach could solve the problem efficiently on the one hand, and addresses the question of which genetic operators are best applied to the formulated DCSRP on the other hand
Spacetime Singularities

We present here an overview of our basic understanding and recent
developments on spacetime singularities in the Einstein theory of gravity.
Several issues related to physical significance and implications of
singularities are discussed. The nature and existence of singularities are
considered which indicate the formation of super ultra-dense regions in the
universe as predicted by the general theory of relativity. Such singularities
develop during the gravitational collapse of massive stars and in cosmology at
the origin of the universe. Possible astrophysical implications of the
occurrence of singularities in the spacetime universe are indicated. We discuss
in some detail the profound and key fundamental issues that the singularities
give rise to, such as the cosmic censorship and predictability in the universe,
naked singularities in gravitational collapse and their relevance in black hole
physics today, and their astrophysical implications in modern relativistic
astrophysics and cosmology.Comment: 45 pages, LaTex; Invited Review article for the `Springer Handbook of
  Spacetime' (eds A. Ashtekar and V. Petkov
Probing dynamical spacetimes with gravitational waves

This decade will see the first direct detections of gravitational waves by
observatories such as Advanced LIGO and Virgo. Among the prime sources are
coalescences of binary neutron stars and black holes, which are ideal probes of
dynamical spacetime. This will herald a new era in the empirical study of
gravitation. For the first time, we will have access to the genuinely
strong-field dynamics, where low-energy imprints of quantum gravity may well
show up. In addition, we will be able to search for effects which might only
make their presence known at large distance scales, such as the ones that
gravitational waves must traverse in going from source to observer. Finally,
coalescing binaries can be used as cosmic distance markers, to study the
large-scale structure and evolution of the Universe.
  With the advanced detector era fast approaching, concrete data analysis
algorithms are being developed to look for deviations from general relativity
in signals from coalescing binaries, taking into account the noisy detector
output as well as the expectation that most sources will be near the threshold
of detectability. Similarly, several practical methods have been proposed to
use them for cosmology. We explain the state of the art, including the
obstacles that still need to be overcome in order to make optimal use of the
signals that will be detected. Although the emphasis will be on
second-generation observatories, we will also discuss some of the science that
could be done with future third-generation ground-based facilities such as
Einstein Telescope, as well as with space-based detectors.Comment: 38 pages, 9 figures. Book chapter for the Springer Handbook of
  Spacetime (Springer Verlag, to appear in 2013
Quantum Gravity via Causal Dynamical Triangulations

"Causal Dynamical Triangulations" (CDT) represent a lattice regularization of
the sum over spacetime histories, providing us with a non-perturbative
formulation of quantum gravity. The ultraviolet fixed points of the lattice
theory can be used to define a continuum quantum field theory, potentially
making contact with quantum gravity defined via asymptotic safety. We describe
the formalism of CDT, its phase diagram, and the quantum geometries emerging
from it. We also argue that the formalism should be able to describe a more
general class of quantum-gravitational models of Horava-Lifshitz type.Comment: To appear in "Handbook of Spacetime", Springer Verlag. 31 page
String theory and primordial cosmology

String cosmology aims at providing a reliable description of the very early
Universe in the regime where standard-model physics is no longer appropriate,
and where we can safely apply the basic ingredients of superstring models such
as dilatonic and axionic forces, duality symmetries, winding modes, limiting
sizes and curvatures, higher-dimensional interactions among elementary extended
object. The sought target is that of resolving (or at least alleviating) the
big problems of standard and inflationary cosmology like the spacetime
singularity, the physics of the trans-Planckian regime, the initial condition
for inflation, and so on.Comment: 17 pages, 5 figures, published in "Springer Handbook of Spacetime",
  ed. by A. Ashtekar and V. Petkov (Springer-Verlag, Berlin Heidelberg, 2014,
  Chapter 3
Families of fast elliptic curves from Q-curves

International audienceWe construct new families of elliptic curves over \(\FF_{p^2}\) with efficiently computable endomorphisms, which can be used to accelerate elliptic curve-based cryptosystems in the same way as Gallant--Lambert--Vanstone (GLV) and Galbraith--Lin--Scott (GLS) endomorphisms. Our construction is based on reducing \(\QQ\)-curves---curves over quadratic number fields without complex multiplication, but with isogenies to their Galois conjugates---modulo inert primes. As a first application of the general theory we construct, for every \(p > 3\), two one-parameter families of elliptic curves over \(\FF_{p^2}\) equipped with endomorphisms that are faster than doubling. Like GLS (which appears as a degenerate case of our construction), we offer the advantage over GLV of selecting from a much wider range of curves, and thus finding secure group orders when \(p\) is fixed. Unlike GLS, we also offer the possibility of constructing twist-secure curves. Among our examples are prime-order curves equipped with fast endomorphisms, with almost-prime-order twists, over \(\FF_{p^2}\) for \(p = 2^{127}-1\) and \(p = 2^{255}-19\)