Numerical scheme for a spatially inhomogeneous matrix-valued quantum Boltzmann equation

We develop an efficient algorithm for a spatially inhomogeneous matrix-valued quantum Boltzmann equation derived from the Hubbard model. The distribution functions are $2 \times 2$ matrix-valued to accommodate the spin degree of freedom, and the scalar quantum Boltzmann equation is recovered as special case when all matrices are proportional to the identity. We use Fourier discretization and fast Fourier transform to efficiently evaluate the collision kernel with spectral accuracy, and numerically investigate periodic, Dirichlet and Maxwell boundary conditions. Model simulations quantify the convergence to local and global thermal equilibrium.Comment: 9 figure

Applications of concurrent access patterns in web usage mining

This paper builds on the original data mining and modelling research which has proposed the discovery of novel structural relation patterns, applying the approach in web usage mining. The focus of attention here is on concurrent access patterns (CAP), where an overarching framework illuminates the methodology for web access patterns post-processing. Data pre-processing, pattern discovery and patterns analysis all proceed in association with access patterns mining, CAP mining and CAP modelling. Pruning and selection of access pat-terns takes place as necessary, allowing further CAP mining and modelling to be pursued in the search for the most interesting concurrent access patterns. It is shown that higher level CAPs can be modelled in a way which brings greater structure to bear on the process of knowledge discovery. Experiments with real-world datasets highlight the applicability of the approach in web navigation

XML data integrity based on concatenated hash function

Data integrity is the fundamental for data authentication. A major problem for XML data authentication is that signed XML data can be copied to another document but still keep signature valid. This is caused by XML data integrity protecting. Through investigation, the paper discovered that besides data content integrity, XML data integrity should also protect element location information, and context referential integrity under fine-grained security situation. The aim of this paper is to propose a model for XML data integrity considering XML data features. The paper presents an XML data integrity model named as CSR (content integrity, structure integrity, context referential integrity) based on a concatenated hash function. XML data content integrity is ensured using an iterative hash process, structure integrity is protected by hashing an absolute path string from root node, and context referential integrity is ensured by protecting context-related elements. Presented XML data integrity model can satisfy integrity requirements under situation of fine-grained security, and compatible with XML signature. Through evaluation, the integrity model presented has a higher efficiency on digest value-generation than the Merkle hash tree-based integrity model for XML data

Microscopic analysis of the octupole phase transition in Th isotopes

A shape phase transition between stable octupole deformation and octupole vibrations in Th nuclei is analyzed in a microscopic framework based on nuclear density functional theory. The relativistic functional DD-PC1 is used to calculate axially-symmetric quadrupole-octupole constrained energy surfaces. Observables related to order parameters are computed using an interacting-boson Hamiltonian, with parameters determined by mapping the microscopic energy surfaces to the expectation value of the Hamiltonian in the boson condensate. The systematics of constrained energy surfaces and low-energy excitation spectra point to the occurrence of a phase transition between octupole-deformed shapes and shapes characterized by octupole-soft potentials.Comment: 6 pages, 5 figures, accepted for publication in Physical Review C, Rapid Communicatio

Domain wall switching: optimizing the energy landscape

It has recently been suggested that exchange spring media offer a way to increase media density without causing thermal instability (superparamagnetism), by using a hard and a soft layer coupled by exchange. Victora has suggested a figure of merit xi = 2 E_b/mu_0 m_s H_sw, the ratio of the energy barrier to that of a Stoner-Wohlfarth system with the same switching field, which is 1 for a Stoner-Wohlfarth (coherently switching) particle and 2 for an optimal two-layer composite medium. A number of theoretical approaches have been used for this problem (e.g., various numbers of coupled Stoner-Wohlfarth layers and continuum micromagnetics). In this paper we show that many of these approaches can be regarded as special cases or approximations to a variational formulation of the problem, in which the energy is minimized for fixed magnetization. The results can be easily visualized in terms of a plot of the energy as a function of magnetic moment m_z, in which both the switching field [the maximum slope of E(m_z)] and the stability (determined by the energy barrier E_b) are geometrically visible. In this formulation we can prove a rigorous limit on the figure of merit xi, which can be no higher than 4. We also show that a quadratic anistropy suggested by Suess et al comes very close to this limit.Comment: Acccepted for proceedings of Jan. 2007 MMM Meeting, paper BE-0

Towards Big data processing in IoT: network management for online edge data processing

Heavy data load and wide cover range have always been crucial problems for internet of things (IoT). However, in mobile-edge computing (MEC) network, the huge data can be partly processed at the edge. In this paper, a MEC-based big data analysis network is discussed. The raw data generated by distributed network terminals are collected and processed by edge servers. The edge servers split out a large sum of redundant data and transmit extracted information to the center cloud for further analysis. However, for consideration of limited edge computation ability, part of the raw data in huge data sources may be directly transmitted to the cloud. To manage limited resources online, we propose an algorithm based on Lyapunov optimization to jointly optimize the policy of edge processor frequency, transmission power and bandwidth allocation. The algorithm aims at stabilizing data processing delay and saving energy without knowing probability distributions of data sources. The proposed network management algorithm may contribute to big data processing in future IoT