43,246 research outputs found

    Environment identification based memory scheme for estimation of distribution algorithms in dynamic environments

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    Copyright @ Springer-Verlag 2010.In estimation of distribution algorithms (EDAs), the joint probability distribution of high-performance solutions is presented by a probability model. This means that the priority search areas of the solution space are characterized by the probability model. From this point of view, an environment identification-based memory management scheme (EI-MMS) is proposed to adapt binary-coded EDAs to solve dynamic optimization problems (DOPs). Within this scheme, the probability models that characterize the search space of the changing environment are stored and retrieved to adapt EDAs according to environmental changes. A diversity loss correction scheme and a boundary correction scheme are combined to counteract the diversity loss during the static evolutionary process of each environment. Experimental results show the validity of the EI-MMS and indicate that the EI-MMS can be applied to any binary-coded EDAs. In comparison with three state-of-the-art algorithms, the univariate marginal distribution algorithm (UMDA) using the EI-MMS performs better when solving three decomposable DOPs. In order to understand the EI-MMS more deeply, the sensitivity analysis of parameters is also carried out in this paper.This work was supported by the National Nature Science Foundation of China (NSFC) under Grant 60774064, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01

    Pulsar slow glitches in a solid quark star model

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    A series of five unusual slow glitches of the radio pulsar B1822-09 (PSR J1825-0935) were observed over the 1995-2005 interval. This phenomenon is understood in a solid quark star model, where the reasonable parameters for slow glitches are presented in the paper. It is proposed that, because of increasing shear stress as a pulsar spins down, a slow glitch may occur, beginning with a collapse of a superficial layer of the quark star. This layer of material turns equivalently to viscous fluid at first, the viscosity of which helps deplete the energy released from both the accumulated elastic energy and the gravitation potential. This performs then a process of slow glitch. Numerical calculations show that the observed slow glitches could be reproduced if the effective coefficient of viscosity is ~10^2 cm^{2}/s and the initial velocity of the superficial layer is order of 10^{-10} cm/s in the coordinate rotating frame of the star.Comment: 5 pages, 5 figures, accepted for publication in MNRAS (Main Journal

    Mass formulae and strange quark matter

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    We have derived the popularly used parametrization formulae for quark masses at low densities and modified them at high densities within the mass-density-dependent model. The results are applied to investigate the lowest density for the possible existence of strange quark matter at zero temperature.Comment: 9 pages, LATeX with ELSART style, one table, no figures. Improvement on the derivation of qark mass formula

    Engineering direct-indirect band gap transition in wurtzite GaAs nanowires through size and uniaxial strain

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    Electronic structures of wurtzite GaAs nanowires in the [0001] direction were studied using first-principles calculations. It was found that the band gap of GaAs nanowires experience a direct-to-indirect transition when the diameter of the nanowires is smaller than ~28 {\AA}. For those thin GaAs nanowires with an indirect band gap, it was found that the gap can be tuned to be direct if a moderate external uniaxial strain is applied. Both tensile and compressive strain can trigger the indirect-to-direct gap transition. The critical strains for the gap-transition are determined by the energy crossover of two states in conduction bands.Comment: 4 pages, 4 figure

    Enhanced web log based recommendation by personalized retrieval

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    University of Technology, Sydney. Faculty of Engineering and Information Technology.With the rapid development of the Internet and WWW, it is more and more important for people to access quality web information. Thus the problem of enabling users to quickly and accurately find information has become an urgent issue. As one of the basic ways to solve this problem, personalized information services have been focusing on fulfilling the personalized information requirements of different users based on their actual demands, preference characteristics, behaviour patterns, etc. This thesis focuses on enhancing web log based recommendation by personalized retrieval, and its main works and innovations include: • For personalized retrieval, the thesis proposes two models to improve user experience and optimize search performance. The first is a query suggestion model based on query semantics and click-through data. This model calculates the subject relevance between queries, and then combines the semantic information and the relevance of the query-click matrix model as this can effectively eliminate the ambiguity and input errors of reminder queries. The second is a collaborative filtering retrieval model based on local and global features. By the integration of the local and global characteristics of the accessed information, this model overcomes the limitations of a single feature, and increases the degree of application of the retrieval model. • For recommendation by personalized retrieval, we propose two recommendation models based on the web log. The first is based on the user’s atomic retrieval transaction sequence and the browse characteristics. This model decomposes search transactions, and calculates the user’s degree of interest on the search term, which allows users to query information more clearly. Further, it incorporates the user feedback on the search results evaluation value, which overcomes the shortcomings of the model based on content filtering. The second model is based on user interests association findings, which can be used to: find the relationship between resources accessed by users, extract the associations of user interests, and address the problem of user interests isolation
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