The importance of forest area and configuration relative to local habitat factors for conserving forest mammals: A case study of koalas in Queensland, Australia

The loss and fragmentation of forest habitats by human land use are recognised as important factors influencing the decline of forest-dependent fauna. Mammal species that are dependent upon forest habitats are particularly sensitive to habitat loss and fragmentation because they have highly specific habitat requirements, and in many cases have limited ability to move through and utilise the land use matrix. We addressed this problem using a case study of the koala (Phascolarctos cinereus) surveyed in a fragmented rural-urban landscape in southeast Queensland, Australia. We applied a logistic modelling and hierarchical partitioning analysis to determine the importance of forest area and its configuration relative to site (local) and patch-level habitat variables. After taking into account spatial auto-correlation and the year of survey, we found koala occurrence increased with the area of all forest habitats, habitat patch size and the proportion of primary Eucalyptus tree species; and decreased with mean nearest neighbour distance between forest patches, the density of forest patches, and the density of sealed roads. The difference between the effect of habitat area and configuration was not as strong as theory predicts, with the configuration of remnant forest becoming increasingly important as the area of forest habitat declines. We conclude that the area of forest, its configuration across the landscape, as well as the land use matrix, are important determinants of koala occurrence, and that habitat configuration should not be overlooked in the conservation of forest-dependent mammals, such as the koala. We highlight the implications of these findings for koala conservation. (c) 2006 Elsevier Ltd. All rights reserved.

Essays on the Economics of Networks Under Incomplete Information

Social networks constitute a major channel for the diffusion of information and the formation of attitudes in a society. Introducing a dynamic model of social learning, the first part of this thesis studies the emergence of socially influential individuals and groups, and identifies the characteristics that make them influential. The second part uses a Bayesian network game to analyse the role of social interaction and conformism in the making of decisions whose returns or costs are ex ante uncertain.

Tracking of non-stationary time-series using resource allocating RBF networks

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Using electricity load data and training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise and forgetting factors for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. We also find that a recently-proposed alternative novelty criterion, found to be more robust in stationary environments, does not fare so well in the non-stationary case due to the need for filter adaptability during training.

A three dimensional surface measurement and reconstruction system for respiratory function analysis

Respiration is a complex activity. If the relationship between all neurological and skeletomuscular interactions was perfectly understood, an accurate dynamic model of the respiratory system could be developed and the interaction between different inputs and outputs could be investigated in a straightforward fashion. Unfortunately, this is not the case and does not appear to be viable at this time. In addition, the provision of appropriate sensor signals for such a model would be a considerable invasive task. Useful quantitative information with respect to respiratory performance can be gained from non-invasive monitoring of chest and abdomen motion. Currently available devices are not well suited in application for spirometric measurement for ambulatory monitoring. A sensor matrix measurement technique is investigated to identify suitable sensing elements with which to base an upper body surface measurement device that monitors respiration. This thesis is divided into two main areas of investigation; model based and geometrical based surface plethysmography. In the first instance, chapter 2 deals with an array of tactile sensors that are used as progression of existing and previously investigated volumetric measurement schemes based on models of respiration. Chapter 3 details a non-model based geometrical approach to surface (and hence volumetric) profile measurement. Later sections of the thesis concentrate upon the development of a functioning prototype sensor array. To broaden the application area the study has been conducted as it would be fore a generically configured sensor array. In experimental form the system performance on group estimation compares favourably with existing system on volumetric performance. In addition provides continuous transient measurement of respiratory motion within an acceptable accuracy using approximately 20 sensing elements. Because of the potential size and complexity of the system it is possible to deploy it as a fully mobile ambulatory monitoring device, which may be used outside of the laboratory. It provides a means by which to isolate coupled physiological functions and thus allows individual contributions to be analysed separately. Thus facilitating greater understanding of respiratory physiology and diagnostic capabilities. The outcome of the study is the basis for a three-dimensional surface contour sensing system that is suitable for respiratory function monitoring and has the prospect with future development to be incorporated into a garment based clinical tool.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

Strategic innovation networks

This thesis draws on two key areas of the innovation literature, the strategic management of technology (SMOT) and innovation networks. The aim is to integrate these two areas of the management of innovation literature to develop a framework which I describe as the Strategic Innovation Network (SIN). The key proposition that the revised framework (SIN) aims to address is based on the work of Chandler (1962). Chandler's (1962) conclusion that 'structure follows strategy' is examined in relation to the interaction between corporate/technology strategy and network structure. The SIN is intended to address weaknesses in both the SMOT and network literature. The research data is based on five detailed longitudinal case studies. The organisations are defined as mid-corporate firms operating in traditional manufacturing sectors. Each organisation was chosen on the basis that it was aiming to develop its innovative capacity through product or process innovation projects. The research was carried out over an 18 month period with interviews being held regularly to develop the longitudinal aspect of the study analysis. The data for each individual case study is examined using the SIN framework. The longitudinal approach addresses the objective to provide a dynamic model of the innovation processes by mapping the changes in network structure during the course of individual projects. The network structural changes are examined in relation to each organisation's strategy and five key dynamic network stages are identified in relation to the innovation process. These network stages show the influence strategy has on the structures adopted by the five case studies.

Management information:design of a system for change identification

This thesis deals with the problem of Information Systems design for Corporate Management. It shows that the results of applying current approaches to Management Information Systems and Corporate Modelling fully justify a fresh look to the problem. The thesis develops an approach to design based on Cybernetic principles and theories. It looks at Management as an informational process and discusses the relevance of regulation theory to its practice. The work proceeds around the concept of change and its effects on the organization's stability and survival. The idea of looking at organizations as viable systems is discussed and a design to enhance survival capacity is developed. It takes Ashby's theory of adaptation and developments on ultra-stability as a theoretical framework and considering conditions for learning and foresight deduces that a design should include three basic components: A dynamic model of the organization- environment relationships; a method to spot significant changes in the value of the essential variables and in a certain set of parameters; and a Controller able to conceive and change the other two elements and to make choices among alternative policies. Further considerations of the conditions for rapid adaptation in organisms composed of many parts, and the law of Requisite Variety determine that successful adaptive behaviour requires certain functional organization. Beer's model of viable organizations is put in relation to Ashby's theory of adaptation and regulation. The use of the Ultra-stable system as abstract unit of analysis permits developing a rigorous taxonomy of change; it starts distinguishing between change with in behaviour and change of behaviour to complete the classification with organizational change. It relates these changes to the logical categories of learning connecting the topic of Information System design with that of organizational learning.

Thin film bearings with phase change of lubricant

The possible evaporation of lubricant in fluid film bearings has been investigated theoretically and by experiment using a radial flow hydrostatic bearing supplied with liquid refrigerant R114. Good correlation between measured and theoretical values was obtained using a bespoke computational fluid dynamic model in which the flow was assumed to be laminar and adiabatic. The effects of viscous dissipation and vapour generation within the fluid film are fully accounted for by applying a fourth order Runge-Kutta routine to satisfy the radial and filmwise transverse constraints of momentum, energy and mass conservation. The results indicate that the radial velocity profile remains parabolic while the flow remains in the liquid phase and that the radial rate of enthalpy generation is then constant across the film at a given radius. The results also show that evaporation will commence at a radial location determined by geometry and flow conditions and in fluid layers adjacent to the solid boundaries. Evaporation is shown to progress in the radial direction and the load carrying capacity of such a bearing is reduced significantly. Expressions for the viscosity of the liquid/vapour mixture found in the literature survey have not been tested against experimental data. A new formulation is proposed in which the suitable choice of a characteristic constant yields close representation to any of these expressions. Operating constraints imposed by the design of the experimental apparatus limited the extent of the surface over which evaporation could be obtained, and prevented clear identification of the most suitable relationship for the viscosity of the liquid/vapour mixture. The theoretical model was extended to examine the development of two phase flow in a rotating shaft face seal of uniform thickness. Previous theoretical analyses have been based on the assumption that the radial velocity profile of the flow is always parabolic, and that the tangential component of velocity varies linearly from the value at the rotating surface, to zero at the stationary surface. The computational fluid dynamic analysis shows that viscous shear and dissipation in the fluid adjacent to the rotating surface leads to developing evaporation with a consequent reduction in tangential shear forces. The tangential velocity profile is predicted to decay rapidly through the film, exhibiting a profile entirely different to that assumed by previous investigators. Progressive evaporation takes place close to the moving wall and does not occur completely at a single radial location, as has been claimed in earlier work.

Modelling the dynamics of cutting during turning

This thesis presents an approach to cutting dynamics during turning based upon the mechanism of deformation of work material around the tool nose known as "ploughing". Starting from the shearing process in the cutting zone and accounting for "ploughing", new mathematical models relating turning force components to cutting conditions, tool geometry and tool vibration are developed. These models are developed separately for steady state and for oscillatory turning with new and worn tools. Experimental results are used to determine mathematical functions expressing the parameters introduced by the steady state model in the case of a new tool. The form of these functions are of general validity though their coefficients are dependent on work and tool materials. Good agreement is achieved between experimental and predicted forces. The model is extended on one hand to include different work material by introducing a hardness factor. The model provides good predictions when predicted forces are compared to present and published experimental results. On the other hand, the extension of the ploughing model to taming with a worn edge showed the ability of the model in predicting machining forces during steady state turning with the worn flank of the tool. In the development of the dynamic models, the dynamic turning force equations define the cutting process as being a system for which vibration of the tool tip in the feed direction is the input and measured forces are the output The model takes into account the shear plane oscillation and the cutting configuration variation in response to tool motion. Theoretical expressions of the turning forces are obtained for new and worn cutting edges. The dynamic analysis revealed the interaction between the cutting mechanism and the machine tool structure. The effect of the machine tool and tool post is accounted for by using experimental data of the transfer function of the tool post system. Steady state coefficients are corrected to include the changes in the cutting configuration with tool vibration and are used in the dynamic model. A series of oscillatory cutting tests at various conditions and various tool flank wear levels are carried out and experimental results are compared with model—predicted forces. Good agreement between predictions and experiments were achieved over a wide range of cutting conditions. This research bridges the gap between the analysis of vibration and turning forces in turning. It offers an explicit expression of the dynamic turning force generated during machining and highlights the relationships between tool wear, tool vibration and turning force. Spectral analysis of tool acceleration and turning force components led to define an "Inertance Power Ratio" as a flank wear monitoring factor. A formulation of an on—line flank wear monitoring methodology is presented and shows how the results of the present model can be applied to practical in—process tool wear monitoring in • turning operations.

Investigation of EDFA power transients in circuit-switched and packet-switched optical networks

Erbium-doped fibre amplifiers (EDFA’s) are a key technology for the design of all optical communication systems and networks. The superiority of EDFAs lies in their negligible intermodulation distortion across high speed multichannel signals, low intrinsic losses, slow gain dynamics, and gain in a wide range of optical wavelengths. Due to long lifetime in excited states, EDFAs do not oppose the effect of cross-gain saturation. The time characteristics of the gain saturation and recovery effects are between a few hundred microseconds and 10 milliseconds. However, in wavelength division multiplexed (WDM) optical networks with EDFAs, the number of channels traversing an EDFA can change due to the faulty link of the network or the system reconfiguration. It has been found that, due to the variation in channel number in the EDFAs chain, the output system powers of surviving channels can change in a very short time. Thus, the power transient is one of the problems deteriorating system performance. In this thesis, the transient phenomenon in wavelength routed WDM optical networks with EDFA chains was investigated. The task was performed using different input signal powers for circuit switched networks. A simulator for the EDFA gain dynamicmodel was developed to compute the magnitude and speed of the power transients in the non-self-saturated EDFA both single and chained. The dynamic model of the self-saturated EDFAs chain and its simulator were also developed to compute the magnitude and speed of the power transients and the Optical signal-to-noise ratio (OSNR). We found that the OSNR transient magnitude and speed are a function of both the output power transient and the number of EDFAs in the chain. The OSNR value predicts the level of the quality of service in the related network. It was found that the power transients for both self-saturated and non-self-saturated EDFAs are close in magnitude in the case of gain saturated EDFAs networks. Moreover, the cross-gain saturation also degrades the performance of the packet switching networks due to varying traffic characteristics. The magnitude and the speed of output power transients increase along the EDFAs chain. An investigation was done on the asynchronous transfer mode (ATM) or the WDM Internet protocol (WDM-IP) traffic networks using different traffic patterns based on the Pareto and Poisson distribution. The simulator is used to examine the amount and speed of the power transients in Pareto and Poisson distributed traffic at different bit rates, with specific focus on 2.5 Gb/s. It was found from numerical and statistical analysis that the power swing increases if the time interval of theburst-ON/burst-OFF is long in the packet bursts. This is because the gain dynamics is fast during strong signal pulse or with long duration pulses, which is due to the stimulatedemission avalanche depletion of the excited ions. Thus, an increase in output power levelcould lead to error burst which affects the system performance.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

Understanding dynamics of strategic decision-making in venture creation:a process study of effectuation and causation

This study draws upon effectuation and causation as examples of planning-based and flexible decision-making logics, and investigates dynamics in the use of both logics. The study applies a longitudinal process research approach to investigate strategic decision-making in new venture creation over time. Combining qualitative and quantitative methods, we analyze 385 decision events across nine technology-based ventures. Our observations suggest a hybrid perspective on strategic decision-making, demonstrating how effectuation and causation logics are combined, and how entrepreneurs’ emphasis on these logics shifts and re-shifts over time. We induce a dynamic model which extends the literature on strategic decision-making in venture creation.

Parameter Identification of a Fed-Batch Cultivation of S. Cerevisiae using Genetic Algorithms

Fermentation processes as objects of modelling and high-quality control are characterized with interdependence and time-varying of process variables that lead to non-linear models with a very complex structure. This is why the conventional optimization methods cannot lead to a satisfied solution. As an alternative, genetic algorithms, like the stochastic global optimization method, can be applied to overcome these limitations. The application of genetic algorithms is a precondition for robustness and reaching of a global minimum that makes them eligible and more workable for parameter identification of fermentation models. Different types of genetic algorithms, namely simple, modified and multi-population ones, have been applied and compared for estimation of nonlinear dynamic model parameters of fed-batch cultivation of S. cerevisiae.

Psychic Punishment Costs and Deterrence

In this paper we analyze criminal deterrence in the presence of specific psychic costs of punishments. We consider a dynamic model with three players, analyzing the choices of a representative lawmaker, potential criminal and judge. In our setting the lawmaker decides whether to introduce a fixed punishment enhancement above a chosen threshold of crime level, depending on its popularity among the voters. In reaction, the judge, who is influenced by her own preferences as well as the opinion of her peer group, might change the probability of punishment, through affecting the standard of reasonable doubt. Our results suggest that large discontinuous and mandatory increases in punishment can have unintended effects that are contrary to the stated goal of such punishment enhancements. In equilibrium, when either the judge or her peer group is "anti-punishment" enough, the level of criminal activity might increase in response to the punishment enhancement. This perverse effect is less likely to occur if there is a higher number of peer groups within the "elite", so that a greater extent of self-selection by judges can occur. Our results have relevance for a number of areas outside the traditional criminal justice system as well, such as special courts (such as ecclesiastical or military courts), or the strictness and enforcement of regulations.

Essays in environmental economic valuation and decision making in the presence of an environmental disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.