Synchronisation and commonalities in metropolitan housing market cycles

This paper examines the degree of commonalities present in the cyclical behavior of the eight largest metropolitan housing markets in Australia. Using two techniques originally in the business cycle literature we consider the degree of synchronization present and secondly decompose the series’ into their permanent and cyclical components. Both empirical approaches reveal similar results. Sydney and Melbourne are closely related to each other and are relatively segmented from the smaller metropolitan areas. In contrast, there is substantial evidence of commonalities in the cyclical behavior of the remaining cities, especially those on the Eastern and Southern coasts of Australia.

Neurocognitive control in dance perception and performance

Dance is a rich source of material for researchers interested in the integration of movement and cognition. The multiple aspects of embodied cognition involved in performing and perceiving dance have inspired scientists to use dance as a means for studying motor control, expertise, and action-perception links. The aim of this review is to present basic research on cognitive and neural processes implicated in the execution, expression, and observation of dance, and to bring into relief contemporary issues and open research questions. The review addresses six topics: 1) dancers’ exemplary motor control, in terms of postural control, equilibrium maintenance, and stabilization; 2) how dancers’ timing and on-line synchronization are influenced by attention demands and motor experience; 3) the critical roles played by sequence learning and memory; 4) how dancers make strategic use of visual and motor imagery; 5) the insights into the neural coupling between action and perception yielded through exploration of the brain architecture mediating dance observation; and 6) a neuroaesthetics perspective that sheds new light on the way audiences perceive and evaluate dance expression. Current and emerging issues are presented regarding future directions that will facilitate the ongoing dialogue between science and dance.

Conditioning of the weak-constraint variational data assimilation problem for numerical weather prediction

4-Dimensional Variational Data Assimilation (4DVAR) assimilates observations through the minimisation of a least-squares objective function, which is constrained by the model flow. We refer to 4DVAR as strong-constraint 4DVAR (sc4DVAR) in this thesis as it assumes the model is perfect. Relaxing this assumption gives rise to weak-constraint 4DVAR (wc4DVAR), leading to a different minimisation problem with more degrees of freedom. We consider two wc4DVAR formulations in this thesis, the model error formulation and state estimation formulation. The 4DVAR objective function is traditionally solved using gradient-based iterative methods. The principle method used in Numerical Weather Prediction today is the Gauss-Newton approach. This method introduces a linearised `inner-loop' objective function, which upon convergence, updates the solution of the non-linear `outer-loop' objective function. This requires many evaluations of the objective function and its gradient, which emphasises the importance of the Hessian. The eigenvalues and eigenvectors of the Hessian provide insight into the degree of convexity of the objective function, while also indicating the difficulty one may encounter while iterative solving 4DVAR. The condition number of the Hessian is an appropriate measure for the sensitivity of the problem to input data. The condition number can also indicate the rate of convergence and solution accuracy of the minimisation algorithm. This thesis investigates the sensitivity of the solution process minimising both wc4DVAR objective functions to the internal assimilation parameters composing the problem. We gain insight into these sensitivities by bounding the condition number of the Hessians of both objective functions. We also precondition the model error objective function and show improved convergence. We show that both formulations' sensitivities are related to error variance balance, assimilation window length and correlation length-scales using the bounds. We further demonstrate this through numerical experiments on the condition number and data assimilation experiments using linear and non-linear chaotic toy models.

Recurrence and higher ergodic properties for quenched random Lorentz tubes in dimension bigger than two

We consider the billiard dynamics in a non-compact set of ℝ d that is constructed as a bi-infinite chain of translated copies of the same d-dimensional polytope. A random configuration of semi-dispersing scatterers is placed in each copy. The ensemble of dynamical systems thus defined, one for each global realization of the scatterers, is called quenched random Lorentz tube. Under some fairly general conditions, we prove that every system in the ensemble is hyperbolic and almost every system is recurrent, ergodic, and enjoys some higher chaotic properties.

Assessing the performance of dynamical trajectory estimates

Estimating trajectories and parameters of dynamical systems from observations is a problem frequently encountered in various branches of science; geophysicists for example refer to this problem as data assimilation. Unlike as in estimation problems with exchangeable observations, in data assimilation the observations cannot easily be divided into separate sets for estimation and validation; this creates serious problems, since simply using the same observations for estimation and validation might result in overly optimistic performance assessments. To circumvent this problem, a result is presented which allows us to estimate this optimism, thus allowing for a more realistic performance assessment in data assimilation. The presented approach becomes particularly simple for data assimilation methods employing a linear error feedback (such as synchronization schemes, nudging, incremental 3DVAR and 4DVar, and various Kalman filter approaches). Numerical examples considering a high gain observer confirm the theory.

My generation(s): cycles, branding and renewal in E4’s 'Skins'

In an era of fragmenting audience and diversified viewing platforms, youth television needs to move fast and make a lot of noise in order to capture and maintain the attention of the teenage viewer. British ensemble youth drama Skins (E4, 2007-2013) calls attention to itself with its high doses of drugs, chaotic parties and casual attitudes towards sexuality. It also moves quickly, shedding its cast every two seasons as they graduate from school, then renewing itself with a fresh generation of 16 year old characters - three cycles in total. This essay will explore the challenges of maintaining audience connections whilst resetting the narrative clock with each cycle. I suggest that the development of the Skins brand was key to the programme’s success. Branding is particularly important for an audience demographic who increasingly consume their television outside of broadcast flow and essential for a programme which renews its cast every two years. The Skins brand operate as a framework, as the central audience draw, have the strength to maintain audience connections when it ‘graduates’ those characters they identify with at the close of each cycle and starts again from scratch. This essay will explore how the Skins brand constructs a cohesive identity across its multiple generations, yet also consider how the cyclic form poses challenges for the programme’s representations and narratives. This cyclic form allows Skins to repeatedly reach out to a new audience who comes of age alongside each new generation and to reflect shifts in British youth culture. Thus Skins remains ever-youthful, seeking to maintain an at times painfully hip identity. Yet the programme has a somewhat schizophrenic identity, torn between its roots in British realist drama and surrealist comedy and an escapist aspirational glamour that shows the influence of US Teen TV. This combination results in a tendency towards a heightened melodrama at odds with Skins claims for authenticity - its much vaunted teenage advisors and young writers - with the cyclic structure serving to amplify the programme’s excessive tendencies. Each cycle wrestles with a need for continuity and familiarity - partly maintained through brand, aesthetic and setting - yet a desire for freshness and originality, to assert difference from what has gone before. I suggest that the inevitable need for each cycle to ‘top’ what has gone before results in a move away from character-based intimacy and the everyday to high-stakes drama and violence which sits uncomfortably within British youth television.

Scalable and fault tolerant failure detection and consensus

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.