A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

Determination of a set of surrogate parameters to assess urban stormwater quality

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

Estimation of WGEN Weather Generation Parameters in Arid Climates

This research discusses some of the issues encountered while developing a set of WGEN parameters for Chile and advice for others interested in developing WGEN parameters for arid climates. The WGEN program is a commonly used and a valuable research tool; however, it has specific limitations in arid climates that need careful consideration. These limitations are analysed in the context of generating a set of WGEN parameters for Chile. Fourteen to 26 years of precipitation data are used to calculate precipitation parameters for 18 locations in Chile, and 3–8 years of temperature and solar radiation data are analysed to generate parameters for seven of these locations. Results indicate that weather generation parameters in arid regions are sensitive to erroneous or missing precipitation data. Research shows that the WGEN-estimated gamma distribution shape parameter (α) for daily precipitation in arid zones will tend to cluster around discrete values of 0 or 1, masking the high sensitivity of these parameters to additional data. Rather than focus on the length in years when assessing the adequacy of a data record for estimation of precipitation parameters, researchers should focus on the number of wet days in dry months in a data set. Analysis of the WGEN routines for the estimation of temperature and solar radiation parameters indicates that errors can occur when individual ‘months’ have fewer than two wet days in the data set. Recommendations are provided to improve methods for estimation of WGEN parameters in arid climates.

A two-Dimensional finite volume method for variable density flow and solute transport through saturated-unsaturated media

Extensive groundwater withdrawal has resulted in a severe seawater intrusion problem in the Gooburrum aquifers at Bundaberg, Queensland, Australia. Better management strategies can be implemented by understanding the seawater intrusion processes in those aquifers. To study the seawater intrusion process in the region, a two-dimensional density-dependent, saturated and unsaturated flow and transport computational model is used. The model consists of a coupled system of two non-linear partial differential equations. The first equation describes the flow of a variable-density fluid, and the second equation describes the transport of dissolved salt. A two-dimensional control volume finite element model is developed for simulating the seawater intrusion into the heterogeneous aquifer system at Gooburrum. The simulation results provide a realistic mechanism by which to study the convoluted transport phenomena evolving in this complex heterogeneous coastal aquifer.

Pressure filtration of Australian bagasse pulp

A one-dimensional pressure filtration model that can be used to predict the behaviour of bagasse pulp has been developed and verified in this study.The dynamic filtration model uses steady state compressibility parameters determined experimentally by uniaxial loading. The compressibility parameters M and N for depithed bagasse pulp were determined to be in the ranges 3000–8000kPa and 2.5–3.0 units, respectively. The model also incorporates experimentally determined steady state permeability data from separate experiments to predict the pulp concentration and fibre pressure throughout a pulp mat during dynamic filtration. Under steady state conditions, a variable Kozeny factor required different values for the permeability parameters when compared to a constant Kozeny factor. The specific surface area was 25–30% lower and the swelling factor was 20–25% higher when a variable Kozeny factor was used. Excellent agreement between experimental data and the dynamic filtration model was achieved when a variable Kozeny factor was used.

Investigation on parameters used in warning systems for rain-induced embankment instability

A number of instrumented laboratory-scale soil embankment slopes were subjected to artificial rainfall until they failed. The factor of safety of the slope based on real-time measurements of pore-water pressure (suction) and laboratory measured soil properties were calculated as the rainfall progressed. Based on the experiment measurements and slope stability analysis, it was observed that slope displacement measurements can be used to warn the slope failure more accurately. Further, moisture content/pore-water pressure measurements near the toe of the slope and the real-time factor of safety can also be used for prediction of rainfall-induced embankment failures with adequate accuracy.

Models of collective cell spreading with variable cell aspect ratio : a motivation for degenerate diffusion models

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multi-scale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (pme). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the pme to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

Performance analysis of hybrid liquid desiccant solar cooling system

This thesis investigates the coefficient of performance (COP) of a hybrid liquid desiccant solar cooling system. This hybrid cooling system includes three sections: 1) conventional air-conditioning section; 2) liquid desiccant dehumidification section and 3) air mixture section. The air handling unit (AHU) with mixture variable air volume design is included in the hybrid cooling system to control humidity. In the combined system, the air is first dehumidified in the dehumidifier and then mixed with ambient air by AHU before entering the evaporator. Experiments using lithium chloride as the liquid desiccant have been carried out for the performance evaluation of the dehumidifier and regenerator. Based on the air mixture (AHU) design, the electrical coefficient of performance (ECOP), thermal coefficient of performance (TCOP) and whole system coefficient of performance (COPsys) models used in the hybrid liquid desiccant solar cooing system were developed to evaluate this system performance. These mathematical models can be used to describe the coefficient of performance trend under different ambient conditions, while also providing a convenient comparison with conventional air conditioning systems. These models provide good explanations about the relationship between the performance predictions of models and ambient air parameters. The simulation results have revealed the coefficient of performance in hybrid liquid desiccant solar cooling systems substantially depends on ambient air and dehumidifier parameters. Also, the liquid desiccant experiments prove that the latent component of the total cooling load requirements can be easily fulfilled by using the liquid desiccant dehumidifier. While cooling requirements can be met, the liquid desiccant system is however still subject to the hysteresis problems.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

Variability of input parameters related to pollutants build-up in stormwater quality modelling

The variability of input parameters is the most important source of overall model uncertainty. Therefore, an in-depth understanding of the variability is essential for uncertainty analysis of stormwater quality model outputs. This paper presents the outcomes of a research study which investigated the variability of pollutants build-up characteristics on road surfaces in residential, commercial and industrial land uses. It was found that build-up characteristics vary highly even within the same land use. Additionally, industrial land use showed relatively higher variability of maximum build-up, build-up rate and particle size distribution, whilst the commercial land use displayed a relatively higher variability of pollutant-solid ratio. Among the various build-up parameters analysed, D50 (volume-median-diameter) displayed the relatively highest variability for all three land uses.

Network protocols and predictive control strategies for distributed real-time control applications

A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

Variable structure control for power systems stabilization

The application of variable structure control (VSC) for power systems stabilization is studied in this paper. It is the application, aspects and constraints of VSC which are of particular interest. A variable structure control methodology has been proposed for power systems stabilization. The method is implemented using thyristor controlled series compensators. A three machine power system is stabilized using a switching line control for large disturbances which becomes a sliding control as the disturbance becomes smaller. The results demonstrate the effectiveness of the methodology proposed as an useful tool to suppress the oscillations in power systems.

Influence of parameters on the heterogeneous photocatalytic degradation of pesticides and phenolic contaminants in wastewater : a short review

In recent years, the application of heterogeneous photocatalytic water purification process has gained wide attention due to its effectiveness in degrading and mineralizing the recalcitrant organic compounds as well as the possibility of utilizing the solar UV and visible light spectrum. This paper aims to review and summarize the recently published works on the titanium dioxide (TiO2) photocatalytic oxidation of pesticides and phenolic compounds, predominant in storm and waste water effluents. The effect of various operating parameters on the photocatalytic degradation of pesticides and phenols are discussed. Results reported here suggested that the photocatalytic degradation of organic compounds depends on the type of photocatalyst and composition, light intensity, initial substrate concentration, amount of catalyst, pH of the reaction medium, ionic components in water, solvent types, oxidizing agents/electron acceptors, catalyst application mode, and calcinations temperature in water environment. A substantial amount of research has focused on the enhancement of TiO2 photocatalysis by modification with metal, non-metal and ion doping. Recent developments in TiO2 photocatalysis for the degradation of various pesticides and phenols are also highlighted in this review. It is evident from the literature survey that photocatalysis has shown good potential for the removal of various organic pollutants. However, still there is a need to find out the practical utility of this technique on commercial scale.