39,867 research outputs found
Determinations of upper critical field in continuous Ginzburg-Landau model
Novel procedures to determine the upper critical field have been
proposed within a continuous Ginzburg-Landau model. Unlike conventional
methods, where is obtained through the determination of the smallest
eigenvalue of an appropriate eigen equation, the square of the magnetic field
is treated as eigenvalue problems so that the upper critical field can be
directly deduced. The calculated from the two procedures are
consistent with each other and in reasonably good agreement with existing
theories and experiments. The profile of the order parameter associated with
is found to be Gaussian-like, further validating the methodology
proposed. The convergences of the two procedures are also studied.Comment: Revtex4, 8 pages, 4 figures, references modified, figures and table
embedde
Flavor Mixing in the Gauge-Higgs Unification
Gauge-Higgs unification is the fascinating scenario solving the hierarchy
problem without supersymmetry. In this scenario, the Standard Model (SM) Higgs
doublet is identified with extra component of the gauge field in higher
dimensions and its mass becomes finite and stable under quantum corrections due
to the higher dimensional gauge symmetry. On the other hand, Yukawa coupling is
provided by the gauge coupling, which seems to mean that the flavor mixing and
CP violation do not arise at it stands. In this talk, we discuss that the
flavor mixing is originated from simultaneously non-diagonalizable bulk and
brane mass matrices. Then, this mechanism is applied to various flavor changing
neutral current (FCNC) processes via Kaluza-Klein (KK) gauge boson exchange at
tree level and constraints for compactification scale are obtained.Comment: 5 pages, prepared for the proceedings of the International Workshop
on Grand Unified Theories (GUT2012) held at Yukawa Institute for Theoretical
Physics, March 15-17 2012, Kyoto, Japa
Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions
Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe
Learning Points and Routes to Recommend Trajectories
The problem of recommending tours to travellers is an important and broadly
studied area. Suggested solutions include various approaches of
points-of-interest (POI) recommendation and route planning. We consider the
task of recommending a sequence of POIs, that simultaneously uses information
about POIs and routes. Our approach unifies the treatment of various sources of
information by representing them as features in machine learning algorithms,
enabling us to learn from past behaviour. Information about POIs are used to
learn a POI ranking model that accounts for the start and end points of tours.
Data about previous trajectories are used for learning transition patterns
between POIs that enable us to recommend probable routes. In addition, a
probabilistic model is proposed to combine the results of POI ranking and the
POI to POI transitions. We propose a new F score on pairs of POIs that
capture the order of visits. Empirical results show that our approach improves
on recent methods, and demonstrate that combining points and routes enables
better trajectory recommendations
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