pinecone/core-2020-05-10-deduplication huggingface dataset:
Load Balancing in Distributed Applications Based on Extremal Optimization

10 pagesInternational audiencehe paper shows how to use Extremal Optimization in load balancing of distributed applications executed in clusters of multicore processors interconnected by a message passing network. Composed of iterative optimization phases which improve program task placement on processors, the proposed load balancing method discovers dynamically the candidates for migration with the use of an Extremal Optimization algorithm and a special quality model which takes into account the computation and communication parameters of the constituent parallel tasks. Assessed by experiments with simulated load balancing of distributed program graphs, a comparison of the proposed Extremal Optimization approach against a deterministic approach based on a similar load balancing theoretical model is provided
A flexible framework for probabilistic models of social trust

In social networks, notions such as trust, fondness, or respect between users can be expressed by associating a strength with each tie. This  provides a view of social interaction as a weighted graph. Sociological models for such weighted networks can differ significantly in their basic motivations and intuitions. In this paper, we present a flexible framework for probabilistic modeling of social networks that allows one to represent these different models and more. The framework, probabilistic soft logic (PSL), is particularly well-suited for this domain, as it combines a declarative, first-order logic-based syntax for describing relational models with a  soft-logic representation, which maps naturally to the non-discrete strength of social trust. We demonstrate the flexibility and effectiveness of PSL for trust prediction using two different approaches: a structural balance model based on social triangles, and a social status model based on a consistent status hierarchy. We test these models on real social network data and find that PSL is an effective tool for trust prediction.status: publishe
Coauthor prediction for junior researchers

Research collaboration can bring in different perspectives and generate more productive results. However, finding an appropriate collaborator can be difficult due to the lacking of sufficient information. Link prediction is a related technique for collaborator discovery; but its focus has been mostly on the core authors who have relatively more publications. We argue that junior researchers actually need more help in finding collaborators. Thus, in this paper, we focus on coauthor prediction for junior researchers. Most of the previous works on coauthor prediction considered global network feature and local network feature separately, or tried to combine local network feature and content feature. But we found a significant improvement by simply combing local network feature and global network feature. We further developed a regularization based approach to incorporate multiple features simultaneously. Experimental results demonstrated that this approach outperformed the simple linear combination of multiple features. We further showed that content features, which were proved to be useful in link prediction, can be easily integrated into our regularization approach. © 2013 Springer-Verlag
Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms

A significant challenge in nature-inspired algorithmics is the identification
of specific characteristics of problems that make them harder (or easier) to
solve using specific methods. The hope is that, by identifying these
characteristics, we may more easily predict which algorithms are best-suited to
problems sharing certain features. Here, we approach this problem using fitness
landscape analysis. Techniques already exist for measuring the "difficulty" of
specific landscapes, but these are often designed solely with evolutionary
algorithms in mind, and are generally specific to discrete optimisation. In
this paper we develop an approach for comparing a wide range of continuous
optimisation algorithms. Using a fitness landscape generation technique, we
compare six different nature-inspired algorithms and identify which methods
perform best on landscapes exhibiting specific features.Comment: 10 pages, 1 figure, submitted to the 11th International Conference on
  Adaptive and Natural Computing Algorithm
Linear Support Vector Machines for Error Correction in Optical Data Transmission

Reduction of bit error rates in optical transmission systems is an important task that is difficult to achieve. As speeds increase, the difficulty in reducing bit error rates also increases. Channels have differing characteristics, which may change over time, and any error correction employed must be capable of operating at extremely high speeds. In this paper, a linear support vector machine is used to classify large-scale data sets of simulated optical transmission data in order to demonstrate their effectiveness at reducing bit error rates and their adaptability to the specifics of each channel. For the classification, LIBLINEAR is used, which is related to the popular LIBSVM classifier. It is found that is possible to reduce the error rate on a very noisy channel to about 3 bits in a thousand. This is done by a linear separator that can be built in hardware and can operate at the high speed required of an operationally useful decode
Electric vehicles on-board battery charger for the future smart grids

The recent and massive investments in Electric Vehicles (EVs) reveal a change of paradigm in the transports sector and the proliferation of EVs will contribute to an effective reduction in the emissions of greenhouse gases. Nevertheless, for the electrical power grids EVs will be extra loads, which will require the demand energy to charge their batteries. With the advent of the Smart Grids, besides the usual battery charging mode (Grid-to-Vehicle – G2V), where the batteries receives energy from the power grid, arises a new concept for the users of EVs and for the power grid market, denominated as Vehicle-to-Grid (V2G). In the V2G operation mode, EVs return to the power grid part of the energy stored in their batteries. The V2G concept requires the use of battery chargers for the EVs with bidirectional power flow capability and bidirectional communication with the Smart Grids through Information and Communication Technology (ICT) applications. It is important to highlight that the proliferation of EVs and the impact of their battery chargers on the power grid quality is a matter of concern, since conventional chargers present current harmonics and power factor problems. In this paper it is presented the preliminary studies resulting from a PhD work about a bidirectional battery charger for EVs, which was designed to operate in collaboration with the power grid as G2V and V2G through an ICT application. In this way, it is expectable to contribute to the technological innovation of the electric mobility in Smart Grids. To assess the behavior of the proposed battery charger under different scenarios of operation, a prototype has been developed, and some simulation and experimental results of the battery charger are presented.Fundação para a Ciência e a Tecnologia (FCT); FEDER Funds, through the Operational Programme for  Competitiveness Factors  –  COMPETE, and by National Funds through FCT  –  Foun- dation for Science and Technology of Portugal, under the projects: FCOMP-01-0124- FEDER-022674 an d PTDC/EEA-EEL/104569/200
Chiral Magnetic Effect in Hydrodynamic Approximation

We review derivations of the chiral magnetic effect (ChME) in hydrodynamic
approximation. The reader is assumed to be familiar with the basics of the
effect. The main challenge now is to account for the strong interactions
between the constituents of the fluid. The main result is that the ChME is not
renormalized: in the hydrodynamic approximation it remains the same as for
non-interacting chiral fermions moving in an external magnetic field. The key
ingredients in the proof are general laws of thermodynamics and the
Adler-Bardeen theorem for the chiral anomaly in external electromagnetic
fields. The chiral magnetic effect in hydrodynamics represents a macroscopic
manifestation of a quantum phenomenon (chiral anomaly). Moreover, one can argue
that the current induced by the magnetic field is dissipation free and talk
about a kind of "chiral superconductivity". More precise description is a
ballistic transport along magnetic field taking place in equilibrium and in
absence of a driving force. The basic limitation is exact chiral limit while
the temperature--excitingly enough- does not seemingly matter. What is still
lacking, is a detailed quantum microscopic picture for the ChME in
hydrodynamics. Probably, the chiral currents propagate through
lower-dimensional defects, like vortices in superfluid. In case of superfluid,
the prediction for the chiral magnetic effect remains unmodified although the
emerging dynamical picture differs from the standard one.Comment: 35 pages, prepared for a volume of the Springer Lecture Notes in
  Physics "Strongly interacting matter in magnetic fields" edited by D.
  Kharzeev, K. Landsteiner, A. Schmitt, H.-U. Ye
Chiral Magnetic Effect on the Lattice

We review recent progress on the lattice simulations of the chiral magnetic
effect. There are two different approaches to analyze the chiral magnetic
effect on the lattice. In one approach, the charge density distribution or the
current fluctuation is measured under a topological background of the gluon
field. In the other approach, the topological effect is mimicked by the chiral
chemical potential, and the induced current is directly measured. Both
approaches are now developing toward the exact analysis of the chiral magnetic
effect.Comment: to appear in Lect. Notes Phys. "Strongly interacting matter in
  magnetic fields" (Springer), edited by D. Kharzeev, K. Landsteiner, A.
  Schmitt, H.-U. Ye
Magnetism in Dense Quark Matter

We review the mechanisms via which an external magnetic field can affect the
ground state of cold and dense quark matter. In the absence of a magnetic
field, at asymptotically high densities, cold quark matter is in the
Color-Flavor-Locked (CFL) phase of color superconductivity characterized by
three scales: the superconducting gap, the gluon Meissner mass, and the
baryonic chemical potential. When an applied magnetic field becomes comparable
with each of these scales, new phases and/or condensates may emerge. They
include the magnetic CFL (MCFL) phase that becomes relevant for fields of the
order of the gap scale; the paramagnetic CFL, important when the field is of
the order of the Meissner mass, and a spin-one condensate associated to the
magnetic moment of the Cooper pairs, significant at fields of the order of the
chemical potential. We discuss the equation of state (EoS) of MCFL matter for a
large range of field values and consider possible applications of the magnetic
effects on dense quark matter to the astrophysics of compact stars.Comment: To appear in Lect. Notes Phys. "Strongly interacting matter in
  magnetic fields" (Springer), edited by D. Kharzeev, K. Landsteiner, A.
  Schmitt, H.-U. Ye
Quantum Criticality via Magnetic Branes

Holographic methods are used to investigate the low temperature limit,
including quantum critical behavior, of strongly coupled 4-dimensional gauge
theories in the presence of an external magnetic field, and finite charge
density. In addition to the metric, the dual gravity theory contains a Maxwell
field with Chern-Simons coupling. In the absence of charge, the magnetic field
induces an RG flow to an infrared AdS$_3 \times {\bf R}^2$ geometry, which is
dual to a 2-dimensional CFT representing strongly interacting fermions in the
lowest Landau level. Two asymptotic Virasoro algebras and one chiral Kac-Moody
algebra arise as {\sl emergent symmetries} in the IR. Including a nonzero
charge density reveals a quantum critical point when the magnetic field reaches
a critical value whose scale is set by the charge density. The critical theory
is probed by the study of long-distance correlation functions of the boundary
stress tensor and current. All quantities of major physical interest in this
system, such as critical exponents and scaling functions, can be computed
analytically. We also study an asymptotically AdS$_6$ system whose magnetic
field induced quantum critical point is governed by a IR Lifshitz geometry,
holographically dual to a D=2+1 field theory. The behavior of these holographic
theories shares important similarities with that of real world quantum critical
systems obtained by tuning a magnetic field, and may be relevant to materials
such as Strontium Ruthenates.Comment: To appear in Lect. Notes Phys. "Strongly interacting matter in
  magnetic fields" (Springer), edited by D. Kharzeev, K. Landsteiner, A.
  Schmitt, H.-U. Ye
Holography, Fractionalization and Magnetic Fields

Four dimensional gravity with a U(1) gauge field, coupled to various fields
in asymptotically anti-de Sitter spacetime, provides a rich arena for the
holographic study of the strongly coupled (2+1)-dimensional dynamics of finite
density matter charged under a global U(1). As a first step in furthering the
study of the properties of fractionalized and partially fractionalized degrees
of freedom in the strongly coupled theory, we construct electron star solutions
at zero temperature in the presence of a background magnetic field. We work in
Einstein-Maxwell-dilaton theory. In all cases we construct, the magnetic source
is cloaked by an event horizon. A key ingredient of our solutions is our
observation that starting with the standard Landau level structure for the
density of states, the electron star limits reduce the charge density and
energy density to that of the free fermion result. Using this result we
construct three types of solution: One has a star in the infra-red with an
electrically neutral horizon, another has a star that begins at an electrically
charged event horizon, and another has the star begin a finite distance from an
electrically charged horizon.Comment: 18 pages, 2 figures. Submitted to Springer Lecture Notes: Strongly
  interacting matter in magnetic fields. v2: Updated references and adjusted
  some phrasing in the introductio
Electromagnetic superconductivity of vacuum induced by strong magnetic
  field

The quantum vacuum may become an electromagnetic superconductor in the
presence of a strong external magnetic field of the order of 10^{16} Tesla. The
magnetic field of the required strength (and even stronger) is expected to be
generated for a short time in ultraperipheral collisions of heavy ions at the
Large Hadron Collider. The superconducting properties of the new phase appear
as a result of a magnetic-field-assisted condensation of quark-antiquark pairs
with quantum numbers of electrically charged rho mesons. We discuss
similarities and differences between the suggested superconducting state of the
quantum vacuum, a conventional superconductivity and the Schwinger pair
creation. We argue qualitatively and quantitatively why the superconducting
state should be a natural ground state of the vacuum at the sufficiently strong
magnetic field. We demonstrate the existence of the superconducting phase using
both the Nambu-Jona-Lasinio model and an effective bosonic model based on the
vector meson dominance (the rho-meson electrodynamics). We discuss various
properties of the new phase such as absence of the Meissner effect, anisotropy
of superconductivity, spatial inhomogeneity of ground state, emergence of a
neutral superfluid component in the ground state and presence of new
topological vortices in the quark-antiquark condensates.Comment: 37 pages, 14 figures, to appear in Lect. Notes Phys. "Strongly
  interacting matter in magnetic fields" (Springer), edited by D. Kharzeev, K.
  Landsteiner, A. Schmitt, H.-U. Ye
Lattice QCD Simulations in External Background Fields

We discuss recent results and future prospects regarding the investigation,
by lattice simulations, of the non-perturbative properties of QCD and of its
phase diagram in presence of magnetic or chromomagnetic background fields.
After a brief introduction to the formulation of lattice QCD in presence of
external fields, we focus on studies regarding the effects of external fields
on chiral symmetry breaking, on its restoration at finite temperature and on
deconfinement. We conclude with a few comments regarding the effects of
electromagnetic background fields on gluodynamics.Comment: 31 pages, 10 figures, minor changes and references added. To appear
  in Lect. Notes Phys. "Strongly interacting matter in magnetic fields"
  (Springer), edited by D. Kharzeev, K. Landsteiner, A. Schmitt, H.-U. Ye
Views of the Chiral Magnetic Effect

My personal views of the Chiral Magnetic Effect are presented, which starts
with a story about how we came up with the electric-current formula and
continues to unsettled subtleties in the formula. There are desirable features
in the formula of the Chiral Magnetic Effect but some considerations would lead
us to even more questions than elucidations. The interpretation of the produced
current is indeed very non-trivial and it involves a lot of confusions that
have not been resolved.Comment: 19 pages, no figure; typos corrected, references significantly
  updated, to appear in Lect. Notes Phys. "Strongly interacting matter in
  magnetic fields" (Springer), edited by D. Kharzeev, K. Landsteiner, A.
  Schmitt, H.-U. Ye
Efficient and Scalable 4-th order Match Propagation

International audienceWe propose a robust method to match image feature points taking into account geometric consistency. It is a careful adaptation of the match propagation principle to 4th-order geometric constraints (match quadruple consistency). With our method, a set of matches is explained by a network of locally-similar affinities. This approach is useful when simple descriptor-based matching strategies fail, in particular for highly ambiguous data, e.g., with repetitive patterns or where texture is lacking. As it scales easily to hundreds of thousands of matches, it is also useful when denser point distributions are sought, e.g., for high-precision rigid model estimation. Experiments show that our method is competitive (efficient, scalable, accurate, robust) against state-of-the-art methods in deformable object matching, camera calibration and pattern detection
Extending Scalasca's analysis features

Scalasca is a performance analysis tool, which parses the trace of an application run for certain patterns that indicate performance inefficiencies. In this paper, we present recently developed new features in Scalasaca. In particular, we describe two newly implemented analysis methods: the root cause analysis which tries to identify the cause of a delay and the critical path analysis, which analyses the path of execution that determines the application runtime. Furthermore, we present time-series profiling, a method that allows to explore time-dependent behavior of an application. Finally, we extended the means of Scalasca and its output format CUBE to define and display topologies
Wheel of B2C E-commerce Development in Saudi Arabia

Online retailing (a model of B2C e-commerce) is growing world-wide, with companies in many countries showing increased sales and productivity as a result. It has great potential within the global economy. This paper looks at the current status of online retailing in Saudi Arabia, with particular focus on what inhibits or enables both the customers and retailers. It also analyses the status of Government involvement and proposes a layered model, known as the Wheel of Online Retailing which illustrates how Government intervention can benefit the e-commerce in Saudi Arabia.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Tuned X-HYBRIDJOIN for Near-real-time Data Warehousing

Near-real-time data warehousing defines how updates from data sources are combined and transformed for storage in a data warehouse as soon as the updates occur. Since these updates are not in warehouse format, they need to be transformed and a join operator is usually required to implement this transformation. A stream-based algorithm called X-HYBRIDJOIN (Extended Hybrid Join), with a favorable asymptotic runtime behavior, was previously proposed. However, X-HYBRIDJOIN does not tune its components under limited available memory resources and without assigning an optimal division of memory to each join component the performance of the algorithm can be suboptimal. This paper presents a variant of X-HYBRIDJOIN called Tuned X-HYBRIDJOIN. The paper shows that after proper tuning the algorithm performs significantly better than that of the previous X-HYBRIDJOIN, and also better as other join operators proposed for this application found in the literature. The tuning approach has been presented, based on measurement techniques and a revised cost model. The experimental results demonstrate the superior performance of Tuned X-HYBRIDJOIN
Fixed failure rate ambiguity validation methods for GPS\ud
and compass

Ambiguity resolution plays a crucial role in real time kinematic GNSS positioning which gives centimetre precision positioning results if all the ambiguities in each epoch are correctly fixed to integers. However, the incorrectly fixed ambiguities can result in large positioning offset up to several meters without notice. Hence, ambiguity validation is essential to control the ambiguity resolution quality. Currently, the most popular ambiguity validation is ratio test. The criterion of ratio test is often empirically determined. Empirically determined criterion can be dangerous, because a fixed criterion cannot fit all scenarios and does not directly control the ambiguity resolution risk.  In practice, depending on the underlying model strength, the ratio test criterion can be too conservative for some model and becomes too risky for others.\ud
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A more rational test method is to determine the criterion according to the underlying model and user requirement.  Miss-detected incorrect integers will lead to a hazardous result, which should be strictly controlled. In ambiguity resolution miss-detected rate is often known as failure rate. In this paper, a fixed failure rate ratio test method is presented and applied in analysis of GPS and Compass positioning scenarios. A fixed failure rate approach is derived from the integer aperture estimation theory, which is theoretically rigorous. The criteria table for ratio test is computed based on extensive data simulations in the approach. The real-time users can determine the ratio test criterion by looking up the criteria table. This method has been applied in medium distance GPS ambiguity resolution but multi-constellation and high dimensional scenarios haven't been discussed so far. \ud
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In this paper, a general ambiguity validation model is derived based on hypothesis test theory, and fixed failure rate approach is introduced, especially the relationship between ratio test threshold and failure rate is examined. In the last, Factors that influence fixed failure rate approach ratio test threshold is discussed according to extensive data simulation. The result shows that fixed failure rate approach is a more reasonable ambiguity validation method with proper stochastic model
Colorimetric Correction for Stereoscopic Camera Arrays

International audienceColorimetric correction is a necessary task to generate comfortable stereoscopic images. This correction is usually performed with a 3D lookup table that can correct images in real-time and can deal with the non-independence of the colour channels. In this paper, we present a method to compute such 3D lookup table with a non-linear process that minimizes the colorimetric properties of the images. This lookup table is represented by a polynomial basis to reduce the number of required parameters. We also describe some optimizations to speedup the processing time