Anisotropy-based robust performance analysis of finite horizon linear discrete time varying systems

We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.

Gas dispersion measurements in industrial flotation cells

For nearly 100 years, the flotation plant metallurgist has often wondered what is happening ‘beneath the froth’. To assist in unravelling this mystery, new technology has been developed as part of the Australian Mineral Industries Research Association (AMIRA) P9 project, to measure gas dispersion characteristics (such as gas hold-up, superficial gas velocity and bubble size) in industrial flotation cells. These measurements have been conducted in a large number of cells of different types and sizes by researchers from the Julius Kruttschnitt Mineral Research Centre (JKMRC) and JKTech. A large database has been developed and the contents of this database are described in this paper. Typical cell characterisation measurements show a wide spread in values, even in the same cell types and sizes performing similar duties. In conventional flotation cells, the typical gas hold-up values range from 3 - 20 per cent, bubble sizes range between 1 and 2 mm, and superficial gas velocity ranges from 1 to 2.5 cm/s. The ranges of cell characterisation measurements given in this paper will enable plant personnel to compare their operation to other similar types of operations from around Australia and the rest of the world, giving opportunities for further improvement to flotation plant operations.

Optimization of microcavity OLED by varying the thickness of multi-layered mirror

We optimized the emission efficiency from a microcavity OLEDs consisting of widely used organic materials, N,N'-di(naphthalene-1-yl)-N,N'-diphenylbenzidine (NPB) as a hole transport layer and tris (8-hydroxyquinoline) (Alq(3)) as emitting and electron transporting layer. LiF/Al was considered as a cathode, while metallic Ag anode was used. TiO2 and Al2O3 layers were stacked on top of the cathode to alter the properties of the top mirror. The electroluminescence emission spectra, electric field distribution inside the device, carrier density, recombination rate and exciton density were calculated as a function of the position of the emission layer. The results show that for certain TiO2 and Al2O3 layer thicknesses, light output is enhanced as a result of the increase in both the reflectance and transmittance of the top mirror. Once the optimum structure has been determined, the microcavity OLED devices can be fabricated and characterized, and comparisons between experiments and theory can be made.

Comparisons of the structural and catalytic properties of Ti-HMS synthesized using the hydrothermal and molecular designed dispersion methods

Titanium containing wormhole-like mesoporous silicas, denoted Ti-HMS, synthesized both via the hydrothermal synthesis route and the post synthesis grafting technique, known as molecular designed dispersion, have been successfully applied in the gas phase oxidation of Toluene to CO and CO2. Selectivity towards CO2 for all catalysts, at temperatures between 400-600degreesC, was above 80%. Benzene and benzaldehyde were observed at temperatures above 450degreesC, but in very low concentrations. The conversion of toluene was shown to increase significantly when the V-TEX/N-MESO ratios were increased from 0.07 to 0.84. No significant difference in catalytic activity was observed for catalysts prepared via the different synthesis techniques. The catalytic activity also depends on the concentration of tetrahedrally coordinated titanium atoms and not on the total concentration of titanium in the catalyst.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).