Generalized pseudo-likelihood estimates for markov random fields on lattice

In this paper we generalize Besag's pseudo-likelihood function for spatial statistical models on a region of a lattice. The correspondingly defined maximum generalized pseudo-likelihood estimates (MGPLEs) are natural extensions of Besag's maximum pseudo-likelihood estimate (MPLE). The MGPLEs connect the MPLE and the maximum likelihood estimate. We carry out experimental calculations of the MGPLEs for spatial processes on the lattice. These simulation results clearly show better performances of the MGPLEs than the MPLE, and the performances of differently defined MGPLEs are compared. These are also illustrated by the application to two real data sets.

Chromatic and luminance losses with multiple sclerosis and optic neuritis measured using dynamic random luminance contrast noise

We measured thresholds for detecting changes in colour and in luminance contrast in observers with multiple sclerosis (MS) and/or optic neuritis (ON) to determine whether reduced sensitivity occurs principally in red-green or blue-yellow second-stage chromatic channels or in an achromatic channel. Colour thresholds for the observers with MS/ON were higher in the red-green direction than in the blue-yellow direction, indicating greater levels of red-green loss than blue-yellow loss. Achromatic thresholds were raised less than either red-green or blue-yellow thresholds, showing less luminance-contrast loss than chromatic loss. With the MS/ON observers, blue-yellow and red-green thresholds were positively correlated but increasing impairment was associated with more rapid changes in red-green thresholds than blue-yellow thresholds. These findings indicate that demyelinating disease selectively reduces sensitivity to colour vision over luminance vision and red-green colours over blue-yellow colours.

Class library ranlip for multivariate nonuniform random variate generation

This paper describes generation of nonuniform random variates from Lipschitz-continuous densities using acceptance/rejection, and the class library _ranlip which implements this method. It is assumed that the required distribution has Lipschitz-continuous density, which is either given analytically or as a black box. The algorithm builds a piecewise constant upper approximation to the density (the hat function), using a large number of its values and subdivision of the domain into hyperrectangles. The class library _ranlip provides very competitive preprocessing and generation times, and yields small rejection constant, which is a measure of efficiency of the generation step. It exhibits good performance for up to five variables, and provides the user with a black box nonuniform random variate generator for a large class of distributions, in particular, multimodal distributions. It will be valuable for researchers who frequently face the task of sampling from unusual distributions, for which specialized random variate generators are not available.

Universal nonuniform random vector generator based on acceptance-rejection

The acceptance/rejection approach is widely used in universal nonuniform random number generators. Its key part is an accurate approximation of a given probability density from above by a hat function. This article uses a piecewise constant hat function, whose values are overestimates of the density on the elements of the partition of the domain. It uses a sawtooth overestimate of Lipschitz continuous densities, and then examines all local maximizers of such an overestimate. The method is applicable to multivariate multimodal distributions. It exhibits relatively short preprocessing time and fast generation of random variates from a very large class of distributions

Representing traumatic space

This presentation will begin by the screening of Traum a Dream (2003, 7 mins, Digital Video, Sound)

A representation of traumatised space, depicting a person who is consumed by a body of pain, consumed by fire. Slowly something is remembered (Festival Catalogue: Transmediale.03. February 2003).

The screening will allow a discussion of some of the material embedded in and ideas used in the film's construction. This includes Atwood's view of the colony as victim, Peter pan and never-never-land, Kroker's concept of the panicked body as it relates to the cinema of Mike Hoolboom's hyper-collage and also the use of the abstract and repetition to depict the process of remembering, re-ordering and forgetting. It is also suggested that Random Access Memory as a method of information storage in Digital Media can provide a model for the architecture of traumatised space and Post Traumatic Stress Disorder.

Simulation of dynamic recrystallization using random grid cellular automata

Computer simulation is a powerful tool to predict microstructure and its evolution in dynamic and post-dynamic recrystallization. CAFE proposed as an appropriate approach by combining finite element (FE) method and cellular automata (CA) for recrystallization simulation. In the current study, a random grid cellular automaton (CA), as micro-scale model, based on finite element (FE), as macro-scale method, has been used to study initial and evolving microstructural features; including nuclei densities, dislocation densities, grain size and grain boundary movement during dynamic recrystallization in a C-Mn steel. An optimized relation has been established between mechanical variables and evolving microstructure features during recrystallization and grain growth. In this model, the microstructure is defined as cells located within grains and grain boundaries while dislocations are randomly dispersed throughout microstructure. Changes of dislocation density during deformation are described considering hardening, recovery and recrystallization. Recrystallization is assumed to initiate near grain boundaries and nucleation rate was considered constant (site-saturated condition). The model produced a mathematical formulation which captured the initial and evolving microstructural entities and linked their effects to measurable macroscopic variables (e.g. stress).

Face classification by a random forest

This paper presents a random forest-based face image classification method. The random forest is an ensemble learning method that grows many classification trees. Each tree gives a classification. The forest selects the classification that has the most votes. Three experiments are performed. The random forest-based method together with several existing approaches are trained and evaluated. The experimental results are presented and discussed.

Monetary models of exchange rates and the random walk

Three alternative monetary models of exchange rate are tested using data on the Italian lira - US doIIar exchange rate. II is shown that up to the early 1990s these economic models perform better than the random walk model in out-of-sample forecasts.

Sense of community in science fiction random, part 1: Understanding sense of community in an international community of interest

Within the discipline of community psychology there is debate as to the dimensions underlying the construct psychological sense of community (PSOC). One of the few theoretical discussions is that of McMillan and Chavis (1986), who hypothesized four dimensions: Belonging; Fulfillment of Needs; Influence; and Shared Connections. Discussion has also emerged in the literature regarding the role of identification within PSOC. It has been suggested that differences in PSOC may be understood in terms of the degree to which members identify with their community (Fisher & Sonn, 1999). However, few studies have explored the place of identification in PSOC. In addition, while PSOC has been applied to both communities of interest and geographical communities, little research has looked in depth at PSOC within communities of interest. The current study therefore explored PSOC in science fiction fandom, a community of interest with membership from all over the world, by means of a questionnaire distributed at an international science fiction convention (N = 359). In an endeavor to clarify the underlying dimensions of PSOC, the questionnaire included several measures of PSOC, and measures of identification with the community. Results showed that science fiction fandom reported high levels of PSOC. Support emerged for McMillan and Chavis' (1986) four dimensions of PSOC, with the addition of a fifth dimension, that of Conscious Identification. These results, and implications for PSOC research, are discussed.

Methodology for extracting quasi-random samples from world wide web domains

The purpose of this paper is to describe a process for sampling specific domain name zones on the World Wide Web. Because of the size of the Web, sampling strategies must be employed in order to effectively model and study the Web business environment.  This paper discusses Various efforts employed to sample the Web, which ranged from random generation of Internet Protocol Addresses and domain names, to the process finally
employed to create descriptive models of the dot-com domain name zones. The paper suggests that sampling the Web Top Level Domains offers a reasonable alternative for business researchers because it requires only familiarity with the use of the simple Web utilities such as File Transfer
Protocols to obtain initial domain name listings.

Appraisal of random and systematic land cover transitions for regional water balance and revegetation strategies

This study describes the use of landscape transition analysis as a means for effective basin management. Land cover transitions from 1995 to 2002 were analyzed using a cross-tabulation matrix for an important economic zone in south-west Victoria, Australia. Specifically, the matrix was used to determine whether the transitions were random or systematic. Random landscape transitions occur when a land cover replaces other land covers in proportion to their availability. Systematic landscape transitions occur when there are deviations from random patterns, and land use types ‘target’ other land use types for replacement. The analysis was conducted with 11 land cover categories and showed that dryland pastures have been systematically losing area to dryland crops and blue gum (Eucalyptus globulus) plantations. Dryland crops have systematically expanded in the north-east of the catchment, an area where increasing in-stream salinization has occurred concurrently with this transition. The systematic expansion of the blue gum plantations has been predominantly in the south-west of the catchment and has the potential to reduce stream flows and groundwater recharge in an already water-stressed region, as blue gums use more water than the dryland pastures they are replacing. All other transitions were largely random. These findings have implications for land use planning in the study area for regional water balance and revegetation strategies. Landscape transition analysis is a cost-effective means of contributing to the management of water resources at a regional scale, and is highly recommended for future basin planning.

Physical education, sport and hyper-masculinity in schools

Among widening social anxieties about practices and performances of contemporary masculinity are questions about the place of hyper-masculine (contact) sports, such as games of football. Foremost are concerns about some of the values and attitudes that appear to circulate within such contexts. With their historical leaning towards character attributes aligned to hardness, solidarity and stoicism, there is growing pressure on coaches and teachers to manage and mediate the participation of young males in this arena. Against this backdrop, this paper explores some of the tensions that emerge in schools when the codes and mores frequently associated with a hyper-masculine sporting identity are seen to flourish. Foremost here is the emergence of cultures of entitlement, abuse and exclusion. Following the illumination of such cultures across three research narratives, this paper discusses the sorts of reforms that are needed to promote more educative and responsible engagement with hyper-masculine sports in, and beyond, schools.

Subcellular localisation of proteins in fluorescent microscope images using a random forest

This paper presents a system that employs random forests to formulate a method for subcellular localisation of proteins. A random forest is an ensemble learner that grows classification trees. Each tree produces a classification decision, and an integrated output is calculated. The system classifies the protein-localisation patterns within fluorescent microscope images. 2D images of HeLa cells that include all major classes of subcellular structures, and the associated feature set are used. The performance of the developed system is compared against that of the support vector machine and decision tree approaches. Three experiments are performed to study the influence of the training and test set size on the performance of the examined methods. The calculated classification errors and execution times are presented and discussed. The lowest classification error (2.9%) has been produced by the developed system.

A random forest for lung nodule identification

A method is presented for identification of lung nodules. It includes three stages: image acquisition, background removal, and nodule detection. The first stage improves image quality. The second stage extracts long lobe regions. The third stage detects lung nodules. The method is based on the random forest learner. Training set contains nodule, non-nodule, and false-positive patterns. Test set contains randomly selected images. The developed method is compared against the support vector machine. True-positives of 100% and 85.9%, and false-positives of 1.27 and 1.33 per image were achieved by the developed method and the support vector machine, respectively.