Representation of Perfect and Local MV-algebras

We describe representation theorems for local and perfect MV-algebras in terms of ultraproducts involving the unit interval [0,1]. Furthermore, we give a representation of local Abelian lattice-ordered groups with strong unit as quasi-constant functions on an ultraproduct of the reals. All the above theorems are proved to have a uniform version, depending only on the cardinality of the algebra to be embedded, as well as a definable construction in ZFC. The paper contains both known and new results and provides a complete overview of representation theorems for such classes

Naval Mine Detection and Seabed Segmentation in Sonar Images with Deep Learning

Underwater mines are a cost-effective method in asymmetric warfare, and are commonly used to block shipping lanes and restrict naval operations. Consequently, they threaten commercial and military vessels, disrupt humanitarian aids, and damage sea environments. There is a strong international interest in using sonars and AI for mine countermeasures and undersea surveillance. High-resolution imaging sonars are well-suited for detecting underwater mines and other targets. Compared to other sensors, sonars are more effective for undersea environments with low visibility. This project aims to investigate deep learning algorithms for two important tasks in undersea surveillance: naval mine detection and seabed terrain segmentation. Our goal is to automatically classify the composition of the seabed and localise naval mines. This research utilises the real sonar data provided by the Defence Science and Technology Group (DSTG). To conduct the experiments, we annotated 150 sonar images for semantic segmentation; the annotation is guided by experts from the DSTG.We also used 152 sonar images with mine detection annotations prepared by members of Centre for Signal and Information Processing at the University of Wollongong. Our results show Faster-RCNN to achieve the highest performance in object detection. We evaluated transfer learning and data augmentation for object detection. Each method improved our detection models mAP by 11.9% and 16.9% and mAR by 17.8% and 21.1%, respectively. Furthermore, we developed a data augmentation algorithm called Evolutionary Cut-Paste which yielded a 20.2% increase in performance. For segmentation, we found highly-tuned DeepLabV3 and U-Nett++models perform best. We evaluate various configurations of optimisers, learning rate schedules and encoder networks for each model architecture. Additionally, model hyper-parameters are tuned prior to training using various tests. Finally, we apply Median Frequency Balancing to mitigate model bias towards frequently occurring classes. We favour DeepLabV3 due to its reliable detection of underrepresented classes as opposed to the accurate boundaries produced by U-Nett++. All of the models satisfied the constraint of real-time operation when running on an NVIDIA GTX 1070

Water confined in nanopores: spontaneous formation of microcavities

Molecular Dynamics simulations of water confined in nanometer sized, hydrophobic channels show that water forms localized cavities for pore diameter ~ 2.0 nm. The cavities present non-spherical shape and lay preferentially adjacent to the confining wall inducing a peculiar form to the liquid exposed surface. The regime of localized cavitation appears to be correlated with the formation of a vapor layer, as predicted by the Lum-Chandler-Weeks theory, implying partial filling of the pore

From soil remediation to biofuel. Process simulation of bioethanol production from Arundo donax

A range of energy crops can be grown on marginal land (i.e. land that is not suitable for food crop production or contaminated site) to provide feedstocks for bioenergy, non-food products and biofuels. The food versus fuel debate had a significant negative impact in Europe on first generation biofuels production from food crops (i.e. wheat, rapeseed, etc). A new approach involving the use of marginal land for the production of lignocellulosic species for the production of bioethanol is now pursued in Italy and in many other countries, where the demand for high quality water resources, arable land, food and fossil fuels is rapidly growing. With an emerging “feed versus fuel debate” there is a pressing need to find options for the use of marginal lands and wastewaters or saline ground waters to produce second generation biofuel or bio paper crops. Arundo donax was selected as a potential crop for use in these areas, since it produces more cellulosic biomass and sequesters more contaminants, using less land and pesticides than any other alternative crops reported in the literature. The objective of this paper is to evaluate economically a simplified process for the production of second generation bioethanol from A. donax. Process calculations and economic analyses are performed using the software SuperPro Designer®

The role of the terrain geometry on the flames propagation through a vegetative fuel bed

When a wildland fire occurs the domain geometry is a key parameter in governing the way the fire spreads across the terrain. The effect of this variable on the rate of flames propagation was investigated in this work by means of a computational fluid dynamics software specifically designed to simulate fires in wildland environment. The physics-based model - i.e. relied on the laws of conservation of momentum, energy and mass – was adopted under two different domain configurations (double-slope domains and canyon); the capability of the computational code to correctly predict the fire behaviour was verified by comparison with results of experimental tests available in the literature

Firm-bank credit networks, business cycle and macroprudential policy

We present an agent-based model to study firm-bank credit market interactions in different phases of the business cycle. The business cycle is exogenously set and it can give rise to various scenarios. Compared to other models in this literature strand, we improve the mechanism according to which the dividends are distributed, including the possibility of stock repurchase by firms. In addition, we locate firms and banks over a space and firms may ask credit to many banks, resulting in a complex spatial network. The model reproduces a long list of stylized facts and their dynamic evolution as described by the cross-correlations among model variables. The model allows us to test the effectiveness of rules designed by the current financial regulation, such as the Basel 3 countercyclical capital buffer. We find that the effectiveness of this rule changes in different business cycle environments and this should be considered by policy makers