An artificial intelligence examination of the influence of geological conditions and changes in climate on damage to light structures in Victoria

Damage to light structures in the state of Victoria can be caused by movements of expansive soils. The presentation will present the results of an examination of reports of increasing complaints of house damage in Victoria and particularly in the Melbourne area. The examination analyses the influence of geology and change in climate using Neural Network and Genetic Algorithm approaches and assesses their relative importance in contributing to the cause of the damage.

Designing adaptive artificial agents for an economic production and conflict model

Production and conflict models have been used over the past 30 years to represent the effects of unproductive resource allocation in economics. Their major applications are in modelling the assignment of property rights, rentseeking and defense economics. This paper describes the process of designing an agent used in a production and conflict model. Using the capabilities of an agent-based approach to economic modelling, we have enriched a simple decision-maker of the kind used in classic general equilibrium economic models, to build an adaptive and interactive agent which uses its own attributes, its neighbors’ parameters and information from its environment to make resource allocation decisions. Our model presents emergent and adaptive behaviors than cannot be captured using classic production and conflict agents. Some possible extensions for future applications are also recommended.

Provision of artificial shelter on beaches is associated with improved shorebird fledging success

Artificial chick shelters might improve productivity of beach-nesting birds threatened by anthropogenic disturbance. We investigated the efficacy of three different chick shelter designs against four criteria: accessibility to chicks over time, thermal insulation, conspicuousness to beach-goers, and practicality (cost and ease of transport). One design (‘A-frame’) was selected because it offered the greatest thermal insulation, was the least conspicuous, most cost effective, and performed equally well in terms of accessibility. We deployed these artificial shelters on Hooded Plover Thinornis rubricollis territories where broods were present (n 5 11), and compared the behaviour and survival rate of chicks to that at control sites (n 5 10). We were unable to discern any difference in the behaviour of broods when artificial shelters were available. However, the survival rate of chicks to fledging was 71.8% higher where an artificial shelter was provided (n 5 21 broods). This was validated by analysing data from a larger sample of broods monitored as part of an active volunteer-based management programme; shelters conferred a 42.8%increase in survival to fledging (n 5 81 broods). Thus, artificial shelters have the potential to increase survival rates of threatened shorebird chicks, though the mechanisms through which survival is increased require further investigation.

Immobilized artificial membrane chromatography : quantitative structure-retention relationships of structurally diverse drugs

The chromatographic capacity factors (log k‘) for 32 structurally diverse drugs were determined by high performance liquid chromatography (HPLC) on a stationary phase composed of phospholipids, the so-called immobilized artificial membrane (IAM). In addition, quantitative structure-retention relationships (QSRR) were developed in order to explain the dependence of retention on the chemical structure of the neutral, acidic, and basic drugs considered in this study. The obtained retention data were modeled by means of multiple regression analysis (MLR) and partial least squares (PLS) techniques. The structures of the compounds under study were characterized by means of calculated physicochemical properties and several nonempirical descriptors. For the carboxylic compounds included in the analysis, the obtained results suggest that the IAM-retention is governed by hydrophobicity factors followed by electronic effects due to polarizability in second place. Further, from the analysis of the results obtained of two developed quantitative structure-permeability studies for 20 miscellaneous carboxylic compounds, it may be concluded that the balance between polarizability and hydrophobic effects is not the same toward IAM phases and biological membranes. These results suggest that the IAM phases could not be a suitable model in assessing the acid-membrane interactions. However, it is not possible to generalize this observation, and further work in this area needs to be done to obtain a full understanding of the partitioning of carboxylic compounds in biological membranes. For the non-carboxylic compounds included in the analysis, this work shows that the hydrophobic factors are of prime importance for the IAM-retention of these compounds, while the specific polar interactions, such as electron pair donor−acceptor interactions and electrostatic interactions, are also involved, but they are not dominant.

Modelling optimal risk allocation in PPP projects using artificial neural networks

This paper aims to establish, train, validate, and test artificial neural network (ANN) models for modelling risk allocation decision-making process in public-private partnership (PPP) projects, mainly drawing upon transaction cost economics. An industry-wide questionnaire survey was conducted to examine the risk allocation practice in PPP projects and collect the data for training the ANN models. The training and evaluation results, when compared with those of using traditional MLR modelling technique, show that the ANN models are satisfactory for modelling risk allocation decision-making process. The empirical evidence further verifies that it is appropriate to utilize transaction cost economics to interpret risk allocation decision-making process. It is recommended that, in addition to partners' risk management mechanism maturity level, decision-makers, both from public and private sectors, should also seriously consider influential factors including partner's risk management routines, partners' cooperation history, partners' risk management commitment, and risk management environmental uncertainty. All these factors influence the formation of optimal risk allocation strategies, either by their individual or interacting effects.

Active surface shaping for artificial skins

Artificial skins exhibit different mechanical properties in compare to natural skins. This drawback makes physical interaction with artificial skins to be different from natural skin. Increasing the performance of the artificial skins for robotic hands and medical applications is addressed in the present paper. The idea is to add active controls within artificial skins in order to improve their dynamic or static behaviors. This directly results into more interactivity of the artificial skins. To achieve this goal, a piece-wise linear anisotropic model for artificial skins is derived. Then a model of matrix of capacitive MEMS actuators for the control purpose is coupled with the model of artificial skin. Next an active surface shaping control is applied through the control of the capacitive MEMS actuators which shapes the skin with zero error and in a desired time. A simulation study is presented to validate the idea of using MEMS actuator for active artificial skins. In the simulation, we actively control 128 capacitive micro actuators for an artificial fingertip. The fingertip provides the required shape in a required time which means the dynamics of the skin is improved.

The effect of artificial night light on the abundance of nocturnal birds

Urbanisation is increasing rapidly, impacting on a broad range of species. The proliferation of electric light has transformed the night time environment; however, our understanding on the effects of artificial night lighting on fauna, including nocturnal birds, is extremely limited. The aim ofthis research was to determine whether artificial night light affected the abundance of nocturnal birds. Spotlighting surveys were undertaken in Research Park, Melbourne, Victoria, along three 300 m transects. Each transect was surveyed five times during three light treatments: when lights were on, 20 minutes after lights were turned off and when lights were absent, over a period often nights. A total of 123 nocturnal birds was detected during survey nights. Two species were recorded - the Southern Boobook Ninox novaeseelandiae and the Tawny Frogmouth Podargus strigoides. The Tawny Frogmouth was detected along all three transects (n=121); however, the Southern Boobook was detected along one transect only (n=2). None of the light treatments had a significant effect on bird abundance. Neither did location, habitat or the combined effects of light treatments, location and habitat. The results of this research will contribute to a growing body of knowledge and support future conservation activities for species in areas undergoing urbanisation. {The Victorian Naturalist 127 (5) 2010, 192-195).

Prediction of Drug Dissolution Profiles Using Artificial Neural Networks

This paper investigates the efficacy and reliability of Artificial Neural Networks (ANNs) as an intelligent decision support tool for pharmaceutical product formulation. Two case studies have been employed to evaluate capabilities of the Multilayer Perceptron network in predicting drug dissolution/release profiles. Performances of the network were evaluated using similarity factor (&fnof[sub 2]) — an index recommended by the United States Food and Drug Administration for profile comparison in pharmaceutical research. In addition, the bootstrap method was applied to assess the network prediction reliability by estimating confidence intervals associated with the results. The Multilayer Perceptron network also demonstrated a superior performance in comparison with multiple regression models. The results reveal that the ANN system has potentials to be a decision support tool for profile prediction in pharmaceutical experimentation, and the bootstrap method could be used as a means to assess reliability of the network prediction. [ABSTRACT FROM AUTHOR].