Classification using log Gaussian Cox processes

McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing properties. Conditioned on the covariates, the distribution over labels is given by a type of conditional Markov random field. In the supervised case, computation of the predictive probability of a single test point scales linearly with the number of training points and the multiclass generalization is straightforward. We show new links between the supervised method and classical nonparametric methods. We give a detailed analysis of the pairwise graph representable Markov random field, which we use to extend the model to semi-supervised learning problems, and propose an inference method based on graph min-cuts. We give the first experimental analysis on supervised and semi-supervised datasets and show good empirical performance.

Design of triangular lattice photonic crystals using genetic algorithms

Genetic Algorithms (GAs) were used to design triangular lattice photonic crystals with large absolute band-gap. Considering fabricating issues, the algorithms represented the unit cell with large pixels and took the largest absolute band-gap under the fifth band as the objective function. By integrating Fourier transform data storage mechanism, the algorithms ran efficiently and effectively and optimized a triangular lattice photonic crystal with scatters in the shape of 'dielectric-air rod'. It had a large absolute band gap with relative width (ratio of gap width to midgap) 23.8%.

New algorithms of the TSM and TOM methods for calibrating microwave test fixtures

Based on the conventional through-short-match (TSM) method, an improved TSM method has been proposed in this Letter. This method gives an analytical solution and has almost all the advantages of conventional TSM methods. For example, it has no phase uncertainty and no bandwidth limitation. The experimental results show that the accuracy can be significantly improved with this method. The proposed theory can be applied to the through-open-match (TOM) method. (C) 2002 Wiley Periodicals. Inc.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

scenario-based interactive intention understanding in pen-based user interfaces

Interactive intention understanding is important for Pen-based User Interface (PUI). Many works on this topic are reported, and focus on handwriting or sketching recognition algorithms at the lexical layer. But these algorithms cannot totally solve the problem of intention understanding and can not provide the pen-based software with high usability. Hence, a scenario-based interactive intention understanding framework is presented in this paper, and is used to simulate human cognitive mechanisms and cognitive habits. By providing the understanding environment supporting the framework, we can apply the framework to the practical PUI system. The evaluation of the Scientific Training Management System for the Chinese National Diving Team shows that the framework is effective in improving the usability and enhancing the intention understanding capacity of this system.

algorithms for computing weak bisimulation equivalence

IEEE Comp Soc, IFIP, Tianjin Normal Univ

Impact of Brunswick river mouth training walls on adjacent beaches, Brunswick heads, New South Wales, Australia

River training walls have been built at scores of locations along the NSW coast and their impacts on shoreline change are still not fully understood. In this study, the Brunswick River entrance and adjacent beaches are selected for examination of the impact of the construction of major training walls. Thirteen sets of aerial photographs taken between 1947 and 1994 are used in a CIS approach to accurately determine tire shoreline Position, beach contours and sand volumes, and their changes in both time and space, and then to assess the contribution of both tire structures and natural hydrodynamic conditions to large scale (years-decades and kilometres) beach changes. The impact of the training walls can be divided into four stages: natural conditions prior to their construction (pre 1959), major downdrift erosion and updrift accretion during and. following the construction of the walls in 1959 similar to 1962 and 1966. diminishing impact of the walls between 1966 and 1987, and finally no apparent impact between 1987 similar to 1994. The impact extends horizontally about 8 km updrift and 17 km downdrift, and temporally up to 25 years..

The statistic inversion algorithms of water constituents for the Huanghai Sea and the East China Sea

A group of statistical algorithms are proposed for the inversion of the three major components of Case-H waters in the coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ data collected in the spring of 2003 with strict quality assurance according to NASA ocean bio-optic protocols. These algorithms are the first ones with quantitative confidence that can be applied for the area. The average relative error of the inversed and in situ measured components' concentrations are: Chl-a about 37%, total suspended matter (TSM) about 25%, respectively. This preliminary result is quite satisfactory for Case-H waters, although some aspects in the model need further study. The sensitivity of the input error of 5% to remote sensing reflectance (Rrs) is also analyzed and it shows the algorithms are quite stable. The algorithms show a large difference with Tassan's local SeaWiFS algorithms for different waters, except for the Chl-a algorithm.