Entertainment architecture : constructing a framework for the creation of an emerging transmedia form

The topic of this research is a novel entertainment form currently emerging from the youngest human communication technology, the Internet. This form, products based on it, and the conceptual framework describing it are all referred to as Entertainment Architecture (‘entarch,’ for short). Entarch is classified as Internet-native transmedia entertainment — it fully utilises the unique communicative characteristics of the Internet and is not based on just one medium. A number of entarch examples are explored through ‘immersive’ textual analysis — a new mode of textual analysis required for research into this kind of entertainment. As a secondary priority, entarch is related to the movie — which is chosen as an exemplary existing entertainment form finding itself in a radically uncertain formal, business, and industrial environment, and accordingly is struggling financially. Throughout, formal, business, and industrial consequences of the emergence of Entertainment Architecture are explored. This research is an example of applied cultural science, as it treats culture as a source of innovation and a complex dynamic system with technological as well as human characteristics. It analyses the dynamics of cultural change in the context of business development, consumer experience, and economic evolution — with an intrinsically transdisciplinary methodology.

Wide area control through aggregation of power systems

This thesis was a step forward in improving the stability of power systems by applying new control and modelling techniques. The developed methods use the data obtained from voltage angle measurement devices which are synchronized with GPS signals to stabilize the system and avoid system-wide blackouts in the event of severe faults. New approaches were developed in this research for identifying and estimating reduced dynamic system models using phasor measurement units. The main goal of this research is achieved by integrating the developed methods to obtain a feasible wide-area control system for stabilizing the power systems.

Filter and control performance bounds in the presence of model uncertainties with aerospace applications

This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide a theoretical justification for the widespread application of approximate filters and controllers in the common situation where system models are not known with complete certainty. This research also provides useful tools for approximate filter designs, which are applied to hybrid filtering of uncertain nonlinear systems. As a contribution towards applications, this thesis also investigates air traffic separation control in the presence of measurement uncertainties.

The application of BESS in load shedding scheme

With new developments in battery technologies, increasing application of Battery Energy Storage System (BESS) in power system is anticipated in near future. BESS has already been used for primary frequency regulation in the past. This paper examines the feasibility of using BESS with load shedding, in application for large disturbances in power system. Load shedding is one of the conventional ways during large disturbances, and the performance of frequency control will increase in combination with BESS application. According to the latest news, BESS which are applied in high power side will be employed in practice in next 5 year. A simple low order SMR model is used as a test system, while an incremental model of BESS is applied in this paper. As continuous disturbances are not the main concern in this paper, df/dt is not considered in article.

A Hybrid Queue-based Bayesian Network framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Corporate fraud culture: Re-examining the corporate governance and performance relation

We analyse the corporate governance and performance relation, when conditioning on corporate fraud, for fraud firms during 2000 – 2007. Fraud firms are identified as either self- reported fraud events, or subject to regulatory investigation. We use the inverse Mills ratio procedure to account for firms' (unobservable) fraud culture in the dynamic system GMM model of the performance- governance relation. We find that corporate governance is an endogenously determined characteristic that has no causal impact on firm performance when conditioning on fraud. Fraud is a significant regulatory event but its overall economic impact at the firm level is highly variable.

Evaluation of driving ability of the disabled persons in the context of the psychological activity theory

In the future the number of the disabled drivers requiring a special evaluation of their driving ability will increase due to the ageing population, as well as the progress of adaptive technology. This places pressure on the development of the driving evaluation system. Despite quite intensive research there is still no consensus concerning what is the factual situation in a driver evaluation (methodology), which measures should be included in an evaluation (methods), and how an evaluation has to be carried out (practise). In order to find answers to these questions we carried out empirical studies, and simultaneously elaborated upon a conceptual model for driving and a driving evaluation. The findings of empirical studies can be condensed into the following points: 1) A driving ability defined by the on-road driving test is associated with different laboratory measures depending on the study groups. Faults in the laboratory tests predicted faults in the on-road driving test in the novice group, whereas slowness in the laboratory predicted driving faults in the experienced drivers group. 2) The Parkinson study clearly showed that even an experienced clinician cannot reliably accomplish an evaluation of a disabled person’s driving ability without collaboration with other specialists. 3) The main finding of the stroke study was that the use of a multidisciplinary team as a source of information harmonises the specialists’ evaluations. 4) The patient studies demonstrated that the disabled persons themselves, as well as their spouses, are as a rule not reliable evaluators. 5) From the safety point of view, perceptible operations with the control devices are not crucial, but correct mental actions which the driver carries out with the help of the control devices are of greatest importance. 6) Personality factors including higher-order needs and motives, attitudes and a degree of self-awareness, particularly a sense of illness, are decisive when evaluating a disabled person’s driving ability. Personality is also the main source of resources concerning compensations for lower-order physical deficiencies and restrictions. From work with the conceptual model we drew the following methodological conclusions: First, the driver has to be considered as a holistic subject of the activity, as a multilevel hierarchically organised system of an organism, a temperament, an individuality, and a personality where the personality is the leading subsystem from the standpoint of safety. Second, driving as a human form of a sociopractical activity, is also a hierarchically organised dynamic system. Third, in an evaluation of driving ability it is a question of matching these two hierarchically organised structures: a subject of an activity and a proper activity. Fourth, an evaluation has to be person centred but not disease-, function- or method centred. On the basis of our study a multidisciplinary team (practitioner, driving school teacher, psychologist, occupational therapist) is recommended for use in demanding driver evaluations. Primary in a driver’s evaluations is a coherent conceptual model while concrete methods of evaluations may vary. However, the on-road test must always be performed if possible.

Beyond fractional derivatives: local approximation of other convolution integrals

Dynamic systems involving convolution integrals with decaying kernels, of which fractionally damped systems form a special case, are non-local in time and hence infinite dimensional. Straightforward numerical solution of such systems up to time t needs O(t(2)) computations owing to the repeated evaluation of integrals over intervals that grow like t. Finite-dimensional and local approximations are thus desirable. We present here an approximation method which first rewrites the evolution equation as a coupled in finite-dimensional system with no convolution, and then uses Galerkin approximation with finite elements to obtain linear, finite-dimensional, constant coefficient approximations for the convolution. This paper is a broad generalization, based on a new insight, of our prior work with fractional order derivatives (Singh & Chatterjee 2006 Nonlinear Dyn. 45, 183-206). In particular, the decaying kernels we can address are now generalized to the Laplace transforms of known functions; of these, the power law kernel of fractional order differentiation is a special case. The approximation can be refined easily. The local nature of the approximation allows numerical solution up to time t with O(t) computations. Examples with several different kernels show excellent performance. A key feature of our approach is that the dynamic system in which the convolution integral appears is itself approximated using another system, as distinct from numerically approximating just the solution for the given initial values; this allows non-standard uses of the approximation, e. g. in stability analyses.

Bond graph model of doubly fed three phase induction motor using the Axis Rotator element for frame transformation

Induction motor is a typical member of a multi-domain, non-linear, high order dynamic system. For speed control a three phase induction motor is modelled as a d–q model where linearity is assumed and non-idealities are ignored. Approximation of the physical characteristic gives a simulated behaviour away from the natural behaviour. This paper proposes a bond graph model of an induction motor that can incorporate the non-linearities and non-idealities thereby resembling the physical system more closely. The model is validated by applying the linearity and idealities constraints which shows that the conventional ‘abc’ model is a special case of the proposed generalised model.

Sensitivity of Eigen Value to Damage and Its Identification

The reduction in natural frequencies,however small, of a civil engineering structure, is the first and the easiest method of estimating its impending damage. As a first level screening for health-monitoring, information on the frequency reduction of a few fundamentalmodes can be used to estimate the positions and the magnitude of damage in a smeared fashion. The paper presents the Eigen value sensitivity equations, derived from first-order perturbation technique, for typical infra-structural systems like a simply supported bridge girder, modelled as a beam, an endbearing pile, modelled as an axial rod and a simply supported plate as a continuum dynamic system. A discrete structure, like a building frame is solved for damage using Eigen-sensitivity derived by a computationalmodel. Lastly, neural network based damage identification is also demonstrated for a simply supported bridge beam, where the known-pairs of damage-frequency vector is used to train a neural network. The performance of these methods under the influence of measurement error is outlined. It is hoped that the developed method could be integrated in a typical infra-structural management program, such that magnitudes of damage and their positions can be obtained using acquired natural frequencies, synthesized from the excited/ambient vibration signatures.

Sliding Modes for the Simulation of Mechanical and Electrical Systems Defined by Differential-Algebraic Equations

We offer a technique, motivated by feedback control and specifically sliding mode control, for the simulation of differential-algebraic equations (DAEs) that describe common engineering systems such as constrained multibody mechanical structures and electric networks. Our algorithm exploits the basic results from sliding mode control theory to establish a simulation environment that then requires only the most primitive of numerical solvers. We circumvent the most important requisite for the conventionalsimulation of DAEs: the calculation of a set of consistent initial conditions. Our algorithm, which relies on the enforcement and occurrence of sliding mode, will ensure that the algebraic equation is satisfied by the dynamic system even for inconsistent initial conditions and for all time thereafter. [DOI:10.1115/1.4001904]

Robust/Optimal Temperature Profile Control of a High-Speed Aerospace Vehicle Using Neural Networks

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A I-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Stability and Limit Oscillations of a Control Event-Based Sampling Criterion

This paper investigates the presence of limit oscillations in an adaptive sampling system. The basic sampling criterion operates in the sense that each next sampling occurs when the absolute difference of the signal amplitude with respect to its currently sampled signal equalizes a prescribed threshold amplitude. The sampling criterion is extended involving a prescribed set of amplitudes. The limit oscillations might be interpreted through the equivalence of the adaptive sampling and hold device with a nonlinear one consisting of a relay with multiple hysteresis whose parameterization is, in general, dependent on the initial conditions of the dynamic system. The performed study is performed on the time domain.

Simulação biofisicoquímica em reservatório tropical polimítico

O reservatório do Lobo, localizado no estado de São Paulo, é um sistema dinâmico no qual se desenvolve um ciclo diurno de estratificação e mistura, de modo similar ao que tem sido observado em outros lagos tropicais. Utilizou-se simulação 3D computacional com os softwares ELCOM (Estuary and Lake Computer Model) acoplado ao CAEDYM (Computacional Aquatic Ecosystem Dynamics Model), ambos desenvolvidos pelo CWR (Center for Water Research) da Universidade da Austrália. Foram realizadas cinco simulações: Piloto Primavera baseada em dados reais da estação no ano primavera no reservatório para o ano de 2007; Primavera-P em que as concentrações de fósforo total, fosfato inorgânico e fosfato total dissolvido foram aumentadas em 100% no reservatório (coluna de água e sedimento) e nos rios tributários; Primavera-V na qual a intensidade dos ventos foi aumentada em 50%; Primavera-T onde a temperatura da água (reservatório e tributários) e do ar foram aumentadas em 10C e, Primavera-X, onde a temperatura da água (reservatório e tributários) e do ar sofreu aumento em 10C, as concentrações de fósforo total, fosfato inorgânico e fosfato total dissolvido foram aumentadas em 100% e a velocidade do vento aumentada em 50%. A concentração de clorofila a foi representada pelos grupos cianobactérias e clorofíceas. O espaço de tempo das simulações representou 90 dias. As clorofíceas apresentaram maior desenvolvimento populacional do que as cianobactérias em todas as simulações. No reservatório, a mistura vertical é ocasionada diariamente pelo vento ou por processos convectivos causados pela perda de calor no corpo de água. A oxigenação do reservatório é maior com a ocorrência de ventos e de grupos fotossintéticos. As concentrações totais de fósforo e nitrogênio apresentaram aumento em todas as simulações.