Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively.

Silylation of layered double hydroxides via an induced hydrolysis method

A series of layered double hydroxides (LDHs) based composites were synthesized by using induced hydrolysis silylation method (IHS), surfactant precursor method, in-situ coprecipitation method, and direct silylation method. Their structures, morphologies, bonding modes and thermal stabilities can be readily adjusted by changing the parameters during preparation and drying processing of the LDHs. The characterization results show that the direct silylation reaction cannot occur between the dried LDHs and 3-aminopropyltriethoxysilane (APS) in an ethanol medium. However, the condensation reaction can proceed with heating process between adsorbed APS and LDHs plates. While using wet state substrates with and without surfactant and ethanol as the solvent, the silylation process can be induced by hydrolysis of APS on the surface of LDHs plates. Surfactants improve the hydrophobicity of the LDHs during the process of nucleation and crystallization, resulting in fluffy shaped crystals; meanwhile, they occupy the surface –OH positions and leave less “free –OH” available for the silylation reaction, favoring formation of silylated products with a higher population in the hydrolyzed bidentate (T2) and tridentate (T3) bonding forms. These bonding characteristics lead to spherical aggregates and tightly bonded particles. All silylated products show higher thermal stability than those of pristine LDHs.

Quantifying axial deformations of core shear walls using modal parameters

Differential axial deformation between column elements and shear wall elements of cores increase with building height and geometric complexity. Adverse effects due to the differential axial deformation reduce building performance and life time serviceability. Quantifying axial deformations using ambient measurements from vibrating wire, external mechanical and electronic strain gauges in order to acquire adequate provisions to mitigate the adverse effects is well established method. However, these gauges require installing in or on elements to acquire continuous measurements and hence use of these gauges is uneconomical and inconvenient. This motivates to develop a method to quantify the axial deformations. This paper proposes an innovative method based on modal parameters to quantify axial deformations of shear wall elements in cores of buildings. Capabilities of the method are presented though an illustrative example.

Queue protection parameters’ fine-tuning for variable speed limits

Any incident on motorways potentially can be followed by secondary crashes. Rear-end crashes also could happen as a result of queue formation downstream of high speed platoons. To decrease the occurrence of secondary crashes and rear-end crashes, Variable Speed Limits (VSL) can be applied to protect queue formed downstream. This paper focuses on fine tuning the Queue Protection algorithm of VSL. Three performance indicators: activation time, deactivation time and number of false alarms are selected to optimise the Queue Protection algorithm. A calibrated microscopic traffic simulation model of Pacific Motorway in Brisbane is used for the optimisation. Performance of VSL during an incident and heavy congestion and the benefit of VSL will be presented in the paper.

A new control-volume finite-element scheme for heterogeneous porous media : application to the drying of softwood

An improved mesoscopic model is presented for simulating the drying of porous media. The aim of this model is to account for two scales simultaneously: the scale of the whole product and the scale of the heterogeneities of the porous medium. The innovation of this method is the utilization of a new mass-conservative scheme based on the Control-Volume Finite-Element (CV-FE) method that partitions the moisture content field over the individual sub-control volumes surrounding each node within the mesh. Although the new formulation has potential for application across a wide range of transport processes in heterogeneous porous media, the focus here is on applying the model to the drying of small sections of softwood consisting of several growth rings. The results conclude that, when compared to a previously published scheme, only the new mass-conservative formulation correctly captures the true moisture content evolution in the earlywood and latewood components of the growth rings during drying.

Dynamics of attacker–defender dyads in Association Football : parameters influencing decision-making

Previous work on pattern-forming dynamics of team sports has investigated sub-phases of basketball and rugby union by focussing on one-versus-one (1v1) attacker-defender dyads. This body of work has identified the role of candidate control parameters, interpersonal distance and relative velocity, in predicting the outcomes of team player interactions. These two control parameters have been described as functioning in a nested relationship where relative velocity between players comes to the fore within a critical range of interpersonal distance. The critical influence of constraints on the intentionality of player behaviour has also been identified through the study of 1v1 attacker-defender dyads. This thesis draws from previous work adopting an ecological dynamics approach, which encompasses both Dynamical Systems Theory and Ecological Psychology concepts, to describe attacker-defender interactions in 1v1 dyads in association football. Twelve male youth association football players (average age 15.3 ± 0.5 yrs) performed as both attackers and defenders in 1v1 dyads in three field positions in an experimental manipulation of the proximity to goal and the role of players. Player and ball motion was tracked using TACTO 8.0 software (Fernandes & Caixinha, 2003) to produce two-dimensional (2D) trajectories of players and the ball on the ground. Significant differences were found for player-to-ball interactions depending on proximity to goal manipulations, indicating how key reference points in the environment such as the location of the goal may act as a constraint that shapes decision-making behaviour. Results also revealed that interpersonal distance and relative velocity alone were insufficient for accurately predicting the outcome of a dyad in association football. Instead, combined values of interpersonal distance, ball-to-defender distance, attacker-to-ball distance, attacker-to-ball relative velocity and relative angles were found to indicate the state of dyad outcomes.

Influence of physical and chemical parameters on the treatment of heavy metals in polluted stormwater using zeolite : A review

Zeolite-based technology can provide a cost effective solution for stormwater treatment for the removal of toxic heavy metals under increasing demand of safe water from alternative sources. This paper reviews the currently available knowledge relating to the effect of properties of zeolites such as pore size, surface area and Si:Al ratio and the physico-chemical conditions of the system such as pH, temperature, initial metal concentration and zeolite concentration on heavy metal removal performance. The primary aims are, to consolidate available knowledge and identify knowledge gaps. It was established that an in-depth understanding of operational issues such as, diffusion of metal ions into the zeolite pore structure, pore clogging, zeolite surface coverage by particulates in stormwater as well as the effect of pH on stormwater quality in the presence of zeolites is essential for developing a zeolite-based technology for the treatment of polluted stormwater. The optimum zeolite concentration to treat typical volumes of stormwater and initial heavy metal concentrations in stormwater should also be considered as operational issues in this regard. Additionally, leaching of aluminium and sodium ions from the zeolite structure to solution were identified as key issues requiring further research in the effort to develop cost effective solutions for the removal of heavy metals from stormwater.

Performance control of distributed generation using digital estimation of signal parameters

The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.