pinecone/core-2020-05-10-deduplication huggingface dataset:
Nuclear Alpha-Particle Condensates

The $\alpha$-particle condensate in nuclei is a novel state described by a
product state of $\alpha$'s, all with their c.o.m. in the lowest 0S orbit. We
demonstrate that a typical $\alpha$-particle condensate is the Hoyle state
($E_{x}=7.65$ MeV, $0^+_2$ state in $^{12}$C), which plays a crucial role for
the synthesis of $^{12}$C in the universe. The influence of antisymmentrization
in the Hoyle state on the bosonic character of the $\alpha$ particle is
discussed in detail. It is shown to be weak. The bosonic aspects in the Hoyle
state, therefore, are predominant. It is conjectured that $\alpha$-particle
condensate states also exist in heavier $n\alpha$ nuclei, like $^{16}$O,
$^{20}$Ne, etc. For instance the $0^+_6$ state of $^{16}$O at $E_{x}=15.1$ MeV
is identified from a theoretical analysis as being a strong candidate of a
$4\alpha$ condensate. The calculated small width (34 keV) of $0^+_6$,
consistent with data, lends credit to the existence of heavier Hoyle-analogue
states. In non-self-conjugated nuclei such as $^{11}$B and $^{13}$C, we discuss
candidates for the product states of clusters, composed of $\alpha$'s,
triton's, and neutrons etc. The relationship of $\alpha$-particle condensation
in finite nuclei to quartetting in symmetric nuclear matter is investigated
with the help of an in-medium modified four-nucleon equation. A nonlinear order
parameter equation for quartet condensation is derived and solved for $\alpha$
particle condensation in infinite nuclear matter. The strong qualitative
difference with the pairing case is pointed out.Comment: 71 pages, 41 figures, review article, to be published in "Cluster in
  Nuclei (Lecture Notes in Physics) - Vol.2 -", ed. by C. Beck,
  (Springer-Verlag, Berlin, 2011
Organizational Semantic Web based Portals

This paper tries to treat organizational semantic web based portals. The first part of the paper focuses on concepts regarding semantic web based portals. After discussing some concepts we treat the basic functionalities that a semantic web based portal must have and we finish by presenting these functionalities by actual examples.
We present semantic web based portals after studying the necessary implementations from literature and practice. We develop some examples that use semantic web based technologies.
Isotropic 2D Quadrangle Meshing with Size and Orientation Control

18 pagesInternational audienceWe propose an approach for automatically generating isotropic 2D quadrangle meshes from arbitrary domains with a fine control over sizing and orientation of the elements. At the heart of our algorithm is an optimization procedure that, from a coarse initial tiling of the 2D domain, enforces each of the desirable mesh quality criteria (size, shape, orientation, degree, regularity) one at a time, in an order designed not to undo previous enhancements. Our experiments demonstrate how well our resulting quadrangle meshes conform to a wide range of input sizing and orientation fields
Data reliability assessment in a data warehouse opened on the Web

International audienceThis paper presents an ontology-driven workflow that feeds and queries a data warehouse opened on the Web. Data are extracted from data tables in Web documents. As web documents are very heterogeneous in nature, a key issue in this workflow is the ability to assess the reliability of retrieved data. We first recall the main steps of our method to annotate and query Web data tables driven by a domain ontology. Then we propose an original method to assess Web data table reliability from a set of criteria by the means of evidence theory. Finally, we show how we extend the workflow to integrate the reliability assessment step
Network regularity and the influence of asycnhronism on the evolution of cooperation

In a population of interacting agents, the update dynamics
defines the temporal relation between the moments at which agents update
the strategies they use when they interact with other agents. The
update dynamics is said to be synchronous if this process occurs simultaneously
for all the agents and asynchronous if this is not the case. On
the other hand, the network of contacts defines who may interact with
whom. In this paper, we investigate the features of the network of contacts
that play an important role in the influence of the update dynamics
on the evolution of cooperative behaviors in a population of agents. First
we show that asynchronous dynamics is detrimental to cooperation only
when 1) the network of contacts is highly regular and 2) there is no noise
in the strategy update process. We then show that, among the different
features of the network of contacts, network regularity plays indeed a
major role in the influence of the update dynamics, in combination with
the temporal scale at which clusters of cooperator agents grow
Providing location everywhere

Anacleto R., Figueiredo L., Novais P., Almeida A., Providing Location Everywhere, in Progress in Artificial Intelligence, Antunes L., Sofia Pinto H. (eds), Lecture Notes in Artificial Intelligence 7026, Springer-Verlag, ISBN 978-3-540-24768-2, (Proceedings of the 15th Portuguese conference on Artificial Intelligence - EPIA 2011, Lisboa, Portugal), pp 15-28, 2011.The ability to locate an individual is an essential part of many applications, specially the mobile ones. Obtaining this location
in an open environment is relatively simple through GPS (Global Positioning System), but indoors or even in dense environments this type of
location system doesn’t provide a good accuracy. There are already systems that try to suppress these limitations, but most of them need the
existence of a structured environment to work. Since Inertial Navigation Systems (INS) try to suppress the need of a structured environment we
propose an INS based on Micro Electrical Mechanical Systems (MEMS) that is capable of, in real time, compute the position of an individual everywhere
Developing dynamic conflict resolution models based on the interpretation of personal conflict styles

Proceedings of the 15th Portuguese conference on Artificial Intelligence - (EPIA 2011), Lisboa, Portugal, 2011.Conflict resolution is a classic field of Social Science research. However, with conflicts now also emerging in virtual environments, a new field of research has been developing in which Artificial Intelligence and particularly Ambient Intelligence are interesting. As result, the field of Online Dispute Resolution emerged as the use (in part or entirely) of technological tools to solve disputes. In this paper we focus on developing conflict resolution models that are able to adapt strategies in real time according to changes in the personal conflict styles of the parties. To do it we follow a novel approach in which an intelligent environment supports the lifecycle of the conflict resolution model with the provision of important context knowledge. The presented framework is able to react to important changes in the context of interaction, resulting in a conflict resolution approach that is able to perceive the parties and consequently achieve better outcomes.The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal
Collaboration-based function prediction in protein-protein interaction networks

acceptance rate 27%The cellular metabolism of a living organism is among the most complex systems that man is currently trying to understand. Part of it is described by so-called protein-protein interaction (PPI) networks, and much effort is spent on analyzing these networks. In particular, there has been much interest in predicting certain properties of nodes in the network (in this case, proteins) from the other information in the network. In this paper, we are concerned with predicting a protein’s functions. Many approaches to this problem exist. Among the approaches that predict a protein’s functions purely from its environment in the network, many are based on the assumption that neighboring proteins tend to have the same functions. In this work we generalize this assumption: we assume that certain neighboring proteins tend to have “collaborative”, but not necessarily the same, functions. We propose a few methods that work under this new assumption. These methods yield better results than those previously considered, with improvements in F-measure ranging from 3% to 17%. This shows that the commonly made assumption of homophily in the network (or “guilt by association”), while useful, is not necessarily the best one can make. The assumption of collaborativeness is a useful generalization of it; it is operational (one can easily define methods that rely on it) and can lead to better results.status: publishe
Graphical feature selection for multilabel classification tasks

Multilabel was introduced as an extension of multi-class classification to cope with complex learning tasks in different application fields as text categorization, video o music tagging or bio-medical labeling of gene functions or diseases. The aim is to predict a set of classes (called labels in this context) instead of a single one. In this paper we deal with the problem of feature selection in multilabel classification. We use a graphical model to represent the relationships among labels and features. The topology of the graph can be characterized in terms of relevance in the sense used in feature selection tasks. In this framework, we compare two strategies implemented with different multilabel learners. The strategy that considers simultaneously the set of all labels outperforms the method that considers each label separatel
On the Performance of Secret Entropy Coding: A Perspective Beyond Security

In this paper, we study the overall performance of two main forms of secret entropy coding – secret Huffman coding and secret arithmetic coding, as solutions to multimedia encryption. We consider a set of criteria, which include not only security but also other aspects of the performance. We draw the conclusion that neither can fulfill all the criteria, but secret arithmetic coding can offer a better solution. We also point out the possibility of amending existing multimedia coding standards to facilitate multimedia encryption
Highlighting metabolic strategies using network analysis over strain optimization results

The field of Metabolic Engineering has been growing, sup- ported by the increase in the number of annotated genomes and genome- scale metabolic models. In silico strain optimization methods allow to create mutant strains able to overproduce certain metabolites of interest in Biotechnology. Thus, it is possible to reach (near-) optimal solutions, i.e. strains that provide the desired phenotype in computational pheno- type simulations. However, the validation of the results involves under- standing the strategies followed by these mutant strains to achieve the desired phenotype, studying the different use of reactions/ pathways by the mutants. This is quite complex given the size of the networks and the interactions between (sometimes distant) components. The manual verification and comparison of phenotypes is typically impossible.
Here, automatic methods are proposed to analyse large sets of mutant strains, by taking the phenotypes of a large number of possible solutions and identifying shared patterns, using methods from network topology analysis. The topological comparison between the networks provided by the wild type and mutant strains highlights the major changes that lead to successful mutants. The methods are applied to a case study consider- ing E. coli and aiming at the production of succinate, optimizing the set of gene knockouts to apply to the wild type. Solutions provided by the use of Simulated Annealing and Evolutionary Algorithms are analyzed. The results show that these methods can help in the identification of the strategies leading to the overproduction of succinate.This work is supported by project PTDC/EIA-EIA/115176/2009, funded by Portuguese FCT and Programa COMPETE.José Pedro Pinto work is funded by a PhD grant from the Portuguese FCT (ref. SFRH/BD/41763/2007)
The Machine Learning and Traveling Repairman Problem

The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but the failure probabilities are not known and must be estimated. If there is uncertainty in the failure probability estimates, we take this uncertainty into account in an unusual way; from the set of acceptable models, we choose the model that has the lowest cost of applying it to the subsequent routing task. In a sense, this procedure agrees with a managerial goal, which is to show that the data can support choosing a low-cost solution.Second International Conference, ADT 2011, Piscataway, NJ, USA, October 26-28, 2011. ProceedingsFulbright Program (International Fulbright Science and Technology Award)Massachusetts Institute of Technology. Energy InitiativeNational Science Foundation (U.S.) (Grant IIS-1053407
Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable
Geometry  vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger
Towards learning inverse kinematics with a neural network based tracking controller

Learning an inverse kinematic model of a robot is a well studied subject. However, achieving this without information about the geometric characteristics of the robot is less investigated. In this work, a novel control approach is presented based on a recurrent neural network. Without any prior knowledge about the robot, this control strategy learns to control the iCub’s robot arm online by solving the inverse kinematic problem in its control region. Because of its exploration strategy the robot starts to learn by generating and observing random motor behavior. The modulation and generalization capabilities of this approach are investigated as well
Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis

The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis approach to investigate and extract second-order statistics from the observed network traffic records. These second-order statistics extracted by the proposed analysis approach can provide important correlative information hiding among the features. By making use of this hidden information, the detection accuracy can be significantly enhanced. The effectiveness of the proposed multivariate correlation analysis approach is evaluated on the KDD CUP 99 dataset. The evaluation shows encouraging results with average 99.96% detection rate and 2.08% false positive rate. Comparisons also show that our multivariate correlation analysis based detection approach outperforms some other current researches in detecting DoS attacks
A Quantum Cognition Analysis of the Ellsberg Paradox

The 'expected utility hypothesis' is one of the foundations of classical
approaches to economics and decision theory and Savage's 'Sure-Thing Principle'
is a fundamental element of it. It has been put forward that real-life
situations exist, illustrated by the 'Allais' and 'Ellsberg paradoxes', in
which the Sure-Thing Principle is violated, and where also the expected utility
hypothesis does not hold. We have recently presented strong arguments for the
presence of a double layer structure, a 'classical logical' and a 'quantum
conceptual', in human thought and that the quantum conceptual mode is
responsible of the above violation. We consider in this paper the Ellsberg
paradox, perform an experiment with real test subjects on the situation
considered by Ellsberg, and use the collected data to elaborate a model for the
conceptual landscape surrounding the decision situation of the paradox. We show
that it is the conceptual landscape which gives rise to a violation of the
Sure-Thing Principle and leads to the paradoxical situation discovered by
Ellsberg.Comment: 11 page
Quantum Structure in Cognition: Why and How Concepts are Entangled

One of us has recently elaborated a theory for modelling concepts that uses
the state context property (SCoP) formalism, i.e. a generalization of the
quantum formalism. This formalism incorporates context into the mathematical
structure used to represent a concept, and thereby models how context
influences the typicality of a single exemplar and the applicability of a
single property of a concept, which provides a solution of the 'Pet-Fish
problem' and other difficulties occurring in concept theory. Then, a quantum
model has been worked out which reproduces the membership weights of several
exemplars of concepts and their combinations. We show in this paper that a
further relevant effect appears in a natural way whenever two or more concepts
combine, namely, 'entanglement'. The presence of entanglement is explicitly
revealed by considering a specific example with two concepts, constructing some
Bell's inequalities for this example, testing them in a real experiment with
test subjects, and finally proving that Bell's inequalities are violated in
this case. We show that the intrinsic and unavoidable character of entanglement
can be explained in terms of the weights of the exemplars of the combined
concept with respect to the weights of the exemplars of the component concepts.Comment: 10 page
Making polygons by simple folds and one straight cut

We give an efficient algorithmic characterization of simple polygons whose edges can be aligned onto a common line, with nothing else on that line, by a sequence of all-layers simple folds. In particular, such alignments enable the cutting out of the polygon and its complement with one complete straight cut. We also show that these makeable polygons include all convex polygons possessing a line of symmetry.Computational Geometry, Graphs and Applications 9th International Conference, CGGA 2010, Dalian, China, November 3-6, 2010, Revised Selected Paper
Common unfoldings of polyominoes and polycubes

This paper studies common unfoldings of various classes of polycubes, as well as a new type of unfolding of polyominoes. Previously, Knuth and Miller found a common unfolding of all tree-like tetracubes. By contrast, we show here that all 23 tree-like pentacubes have no such common unfolding, although 22 of them have a common unfolding. On the positive side, we show that there is an unfolding common to all “non-spiraling” k-ominoes, a result that extends to planar non-spiraling k-cubes.Computational Geometry, Graphs and Applications 9th International Conference, CGGA 2010, Dalian, China, November 3-6, 2010, Revised Selected Paper
Introducing non-linear analysis into sustained speech characterization to improve sleep apnea detection

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-25020-0_28Proceedings of 5th International Conference on Nonlinear Speech Processing, NOLISP 2011, Las Palmas de Gran Canaria (Spain)We present a novel approach for detecting severe obstructive sleep apnea (OSA) cases by introducing non-linear analysis into sustained speech characterization. The proposed scheme was designed for providing additional information into our baseline system, built on top of state-of-the-art cepstral domain modeling techniques, aiming to improve accuracy rates. This new information is lightly correlated with our previous MFCC modeling of sustained speech and uncorrelated with the information in our continuous speech modeling scheme. Tests have been performed to evaluate the improvement for our detection task, based on sustained speech as well as combined with a continuous speech classifier, resulting in a 10% relative reduction in classification for the first and a 33% relative reduction for the fused scheme. Results encourage us to consider the existence of non-linear effects on OSA patients’ voices, and to think about tools which could be used to improve short-time analysis.The activities described in this paper were funded by the Spanish Ministry of Science and Innovation as part of the TEC2009-14719-C02-02 (PriorSpeech) project