Ionisation and discharge in cloud-forming atmospheres of brown dwarfs and extrasolar planets

Brown dwarfs and giant gas extrasolar planets have cold atmospheres with rich chemical compositions from which mineral cloud particles form. Their properties, like particle sizes and material composition, vary with height, and the mineral cloud particles are charged due to triboelectric processes in such dynamic atmospheres. The dynamics of the atmospheric gas is driven by the irradiating host star and/or by the rotation of the objects that changes during its lifetime. Thermal gas ionisation in these ultra-cool but dense atmospheres allows electrostatic interactions and magnetic coupling of a substantial atmosphere volume. Combined with a strong magnetic field , a chromosphere and aurorae might form as suggested by radio and x-ray observations of brown dwarfs. Non-equilibrium processes like cosmic ray ionisation and discharge processes in clouds will increase the local pool of free electrons in the gas. Cosmic rays and lighting discharges also alter the composition of the local atmospheric gas such that tracer molecules might be identified. Cosmic rays affect the atmosphere through air showers in a certain volume which was modelled with a 3D Monte Carlo radiative transfer code to be able to visualise their spacial extent. Given a certain degree of thermal ionisation of the atmospheric gas, we suggest that electron attachment to charge mineral cloud particles is too inefficient to cause an electrostatic disruption of the cloud particles. Cloud particles will therefore not be destroyed by Coulomb explosion for the local temperature in the collisional dominated brown dwarf and giant gas planet atmospheres. However, the cloud particles are destroyed electrostatically in regions with strong gas ionisation. The potential size of such cloud holes would, however, be too small and might occur too far inside the cloud to mimic the effect of, e.g. magnetic field induced star spots.

Investigations of Cloud Microphysical Response to Mixing Using Digital Holography

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the `single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other `bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a `humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.

Complementarity and the uncertainty principle as aesthetic principles : the practice and performance of The Physics Project

Using the generative processes developed over two stages of creative development and the performance of The Physics Project at the Loft at the Creative Industries Precinct at the Queensland University of Technology (QUT) from 5th – 8th April 2006 as a case study, this exegesis considers how the principles of contemporary physics can be reframed as aesthetic principles in the creation of contemporary performance. The Physics Project is an original performance work that melds live performance, video and web-casting and overlaps an exploration of personal identity with the physics of space, time, light and complementarity. It considers the acts of translation between the language of physics and the language of contemporary performance that occur via process and form. This exegesis also examines the devices in contemporary performance making and contemporary performance that extend the reach of the performance, including the integration of the live and the mediated and the use of metanarratives.

Political theory and theoretical physics

This paper explains, somewhat along a Simmelian line, that political theory may produce practical and universal theories like those developed in theoretical physics. The reasoning behind this paper is to show that the Element of Democracy Theory may be true by way of comparing it to Einstein’s Special Relativity – specifically concerning the parameters of symmetry, unification, simplicity, and utility. These parameters are what make a theory in physics as meeting them not only fits with current knowledge, but also produces paths towards testing (application). As the Element of Democracy Theory meets these same parameters, it could settle the debate concerning the definition of democracy. This will be shown firstly by discussing why no one has yet achieved a universal definition of democracy; secondly by explaining the parameters chosen (as in why these and not others confirm or scuttle theories); and thirdly by comparing how Special Relativity and the Element of Democracy match the parameters.

Political theory and theoretical physics [Revised]

This paper explains, somewhat along a Simmelian line, that political theory may produce practical and universal theories like those developed in theoretical physics. The reasoning behind this paper is to show that the Element of Democracy Theory may be true by way of comparing it to Einstein’s Special Relativity – specifically concerning the parameters of symmetry, unification, simplicity, and utility. These parameters are what make a theory in physics as meeting them not only fits with current knowledge, but also produces paths towards testing (application). As the Element of Democracy Theory meets these same parameters, it could settle the debate concerning the definition of democracy. This will be shown firstly by discussing why no one has yet achieved a universal definition of democracy; secondly by explaining the parameters chosen (as in why these and not others confirm or scuttle theories); and thirdly by comparing how Special Relativity and the Element of Democracy match the parameters.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

QoS-oriented sesource allocation and scheduling of multiple composite web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

A cooperative coevolutionary algorithm for the composite SaaS Placement Problem in the Cloud

Cloud computing has become a main medium for Software as a Service (SaaS) hosting as it can provide the scalability a SaaS requires. One of the challenges in hosting the SaaS is the placement process where the placement has to consider SaaS interactions between its components and SaaS interactions with its data components. A previous research has tackled this problem using a classical genetic algorithm (GA) approach. This paper proposes a cooperative coevolutionary algorithm (CCEA) approach. The CCEA has been implemented and evaluated and the result has shown that the CCEA has produced higher quality solutions compared to the GA.

The Queensland Cancer Physics Collaborative and the Quantitative Biomedical Imaging & Characterisation (Q-BIC) Research Group

a presentation about immersive visualised simulation systems, image analysis and GPGPU Techonology

Mutual protection in a cloud computing environment

The term “cloud computing” has emerged as a major ICT trend and has been acknowledged by respected industry survey organizations as a key technology and market development theme for the industry and ICT users in 2010. However, one of the major challenges that faces the cloud computing concept and its global acceptance is how to secure and protect the data and processes that are the property of the user. The security of the cloud computing environment is a new research area requiring further development by both the academic and industrial research communities. Today, there are many diverse and uncoordinated efforts underway to address security issues in cloud computing and, especially, the identity management issues. This paper introduces an architecture for a new approach to necessary “mutual protection” in the cloud computing environment, based upon a concept of mutual trust and the specification of definable profiles in vector matrix form. The architecture aims to achieve better, more generic and flexible authentication, authorization and control, based on a concept of mutuality, within that cloud computing environment.