Model-based object recognition from a complex binary imagery using genetic algorithm

This paper describes a technique for model-based object recognition in a noisy and cluttered environment, by extending the work presented in an earlier study by the authors. In order to accurately model small irregularly shaped objects, the model and the image are represented by their binary edge maps, rather then approximating them with straight line segments. The problem is then formulated as that of finding the best describing match between a hypothesized object and the image. A special form of template matching is used to deal with the noisy environment, where the templates are generated on-line by a Genetic Algorithm. For experiments, two complex test images have been considered and the results when compared with standard techniques indicate the scope for further research in this direction

Percolation in three-dimensional random field Ising magnets

The structure of the three-dimensional random field Ising magnet is studied by ground state calculations. We investigate the percolation of the minority spin orientation in the paramagnetic phase above the bulk phase transition, located at [Delta/J]_c ~= 2.27, where Delta is the standard deviation of the Gaussian random fields (J=1). With an external field H there is a disorder strength dependent critical field +/- H_c(Delta) for the down (or up) spin spanning. The percolation transition is in the standard percolation universality class. H_c ~ (Delta - Delta_p)^{delta}, where Delta_p = 2.43 +/- 0.01 and delta = 1.31 +/- 0.03, implying a critical line for Delta_c < Delta <= Delta_p. When, with zero external field, Delta is decreased from a large value there is a transition from the simultaneous up and down spin spanning, with probability Pi_{uparrow downarrow} = 1.00 to Pi_{uparrow downarrow} = 0. This is located at Delta = 2.32 +/- 0.01, i.e., above Delta_c. The spanning cluster has the fractal dimension of standard percolation D_f = 2.53 at H = H_c(Delta). We provide evidence that this is asymptotically true even at H=0 for Delta_c < Delta <= Delta_p beyond a crossover scale that diverges as Delta_c is approached from above. Percolation implies extra finite size effects in the ground states of the 3D RFIM.Comment: replaced with version to appear in Physical Review

Intelligent decision support system based geo-information technology and spatial planning for sustainable water management in Flanders, Belgium

The paper outlines the main features of an intelligent decision support system based on existing and planned tools for optimising water management and flood risk reduction. Up to now, flood risk is increasing and environmental degradation is continuing; this requires developing robotic algorithms that can provide a degree of functionality for spatial representation and flexibility suitable for creating real-time solutions that maximize the urban flood protection measures. Moreover, the volume of data collected is growing rapidly and sophisticated means to efficiently optimise the data are essential. There is a need to develop a shared information system for flood management which will promote model and systems integration, monitoring, and decision making in strategic planning and emergency situations. This advanced area of research is a promising direction for producing an effective time-efficient solution to flood risk reduction where other methods failed. Therefore, the objective of this paper is to bring together innovative methods in the field of artificial intelligence, geo-information technology and spatial and environmental planning to achieve more effective water management and flood risk reduction in Flanders

The three-dimensional random field Ising magnet: interfaces, scaling, and the nature of states

The nature of the zero temperature ordering transition in the 3D Gaussian random field Ising magnet is studied numerically, aided by scaling analyses. In the ferromagnetic phase the scaling of the roughness of the domain walls, $w\sim L^\zeta$, is consistent with the theoretical prediction $\zeta = 2/3$. As the randomness is increased through the transition, the probability distribution of the interfacial tension of domain walls scales as for a single second order transition. At the critical point, the fractal dimensions of domain walls and the fractal dimension of the outer surface of spin clusters are investigated: there are at least two distinct physically important fractal dimensions. These dimensions are argued to be related to combinations of the energy scaling exponent, $\theta$, which determines the violation of hyperscaling, the correlation length exponent $\nu$, and the magnetization exponent $\beta$. The value $\beta = 0.017\pm 0.005$ is derived from the magnetization: this estimate is supported by the study of the spin cluster size distribution at criticality. The variation of configurations in the interior of a sample with boundary conditions is consistent with the hypothesis that there is a single transition separating the disordered phase with one ground state from the ordered phase with two ground states. The array of results are shown to be consistent with a scaling picture and a geometric description of the influence of boundary conditions on the spins. The details of the algorithm used and its implementation are also described.Comment: 32 pp., 2 columns, 32 figure

A longitudinal investigation of repressive coping and ageing

This is an Accepted Manuscript of an article published by Taylor & Francis in Aging & Mental Health on October 2016, available online: http://www.tandfonline.com/doi/full/10.1080/13607863.2015.1060941.Two studies investigated the possibility that repressive coping is more prevalent in older adults and that this represents a developmental progression rather than a cohort effect. Study 1 examined repressive coping and mental health cross-sectionally in young and old adults. Study 2 examined whether there was a developmental progression of repressive coping prevalence rates in a longitudinal sample of older adults.Peer reviewedFinal Accepted Versio

Revisiting the scaling of the specific heat of the three-dimensional random-field Ising model

We revisit the scaling behavior of the specific heat of the three-dimensional random-field Ising model with a Gaussian distribution of the disorder. Exact ground states of the model are obtained using graph-theoretical algorithms for different strengths = 268 3 spins. By numerically differentiating the bond energy with respect to h, a specific-heat-like quantity is obtained whose maximum is found to converge to a constant in the thermodynamic limit. Compared to a previous study following the same approach, we have studied here much larger system sizes with an increased statistical accuracy. We discuss the relevance of our results under the prism of a modified Rushbrooke inequality for the case of a saturating specific heat. Finally, as a byproduct of our analysis, we provide high-accuracy estimates of the critical field hc = 2.279(7) and the critical exponent of the correlation exponent ν = 1.37(1), in excellent agreement to the most recent computations in the literature