Energy efficient, fully-connected mesh networks for high speed applications

Fully-connected mesh networks that can potentially be employed in a range of applications, are inherently associated with major deficiencies in interference management and network capacity improvement. The tree-connected (routing based) mesh networks used in today’s applications have major deficiencies in routing delays and reconfiguration delays in the implementation stage. This paper introduces a CDMA based fully-connected mesh network, which controls the transmission powers of the nodes in order to ensure that the communication channels remain interference-free and minimizes the energy consumption. Moreover, the bounds for the number of nodes and the spatial configuration are provided to ensures that the communication link satisfies the QoS (Quality of Service) requirements at all times.

3D virtual haptic cone for intuitive vehicle motion control

Haptic human-machine interfaces and interaction techniques have been shown to offer advantages over conventional approaches. This work introduces the 3D virtual haptic cone with the aim of improving human remote control of a vehicle's motion. The 3D cone introduces a third dimension to the haptic control surface over existing approaches. This approach improves upon existing methods by providing the human operator with an intuitive method for issuing vehicle motion commands whilst simultaneously receiving real-time haptic information from the remote system. The presented approach offers potential across many applications, and as a case study, this work considers the approach in the context of mobile robot motion control. The performance of the approach in providing the operator with improved motion controllability is evaluated and the performance improvement determined.

A low-cost intelligent gas sensing device for military applications

The field of electronic noses and gas sensing has been developing rapidly since the introduction of the silicon based sensors. There are numerous systems that can detect and indicate the level of a specific gas. We introduce here a system that is low power, small and cheap enough to be used in mobile robotic platforms while still being accurate and reliable enough for confident use. The design is based around a small circuit board mounted in a plastic case with holes to allow the sensors to protrude through the top and allow the natural flow of gas evenly across them. The main control board consists of a microcontroller PCB with surface mount components for low cost and power consumption. The firmware of the device is based on an algorithm that uses an Artificial Neural Network (ANN) which receives input from an array of gas sensors. The various sensors feeding the ANN allow the microcontroller to determine the gas type and quantity. The Testing of the device involves the training of the ANN with a number of different target gases to determine the weightings for the ANN. Accuracy and reliability of the ANN is validated through testing in a specific gas filled environment.

Fuzzy neural networks for control of dynamic systems

This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.

Use of phosphite as a control for Phytophthora cinnamomi in southeastern Victorian vegetation communities

One of the major aims of the research presented in this thesis was to assist managers of native vegetation communities in southeastern Australia in understanding the dynamics of P. cinnamomi with an important ecological species, Xanthorrhoea australis. It trialed the use of phosphite in large-scale field applications to establish the usefulness of this management option for the first time on Victorian flora. This thesis describes the process of disease development within mature X. Australia plants. For the first time it was shown that within X. australis plants, secondary disease symptoms are related to the percentage of stem that has been infested by the disease. It was evident that after initial invasion the pathogen moves via root xylem and throughout the plant within vascular to the stem, especially within the desmium. The research shows that the pathogen could not be isolated consistently even though it was considered to be responsible for disease symptoms. Trials of a control fungicide (Foli-R-fos 200) shows that protection occurs in many susceptible plants when 2 and 6g a.i./L phosphite is applied. Phytotoxicity occurred in native plants at Anglesea and within controlled environment trials when using ≥ 6g a.i./L. It will be shown that 2g a.i./L phosphite controls disease in sprayed plots within heathlands at Anglesea and a recently burnt coastal woodland community at Wilson’s Promontory. The proportion of healthy X. australis plants treated with phosphite was significantly higher than the proportion in control plots without phosphite. The research shows that phosphite was recovered from leaves of three species treated with Foli-R-fos 200 in the field. For the first time it has been shown that seed germination was reduced in two species when high concentrations of phosphite were applied. The first documentation of the effect that phosphite has on soil properties showed that nitrogen and oxidised organic carbon were the only parameters to alter significantly. This thesis provides answers to some important questions, answers that can now be used by managers in formulating better policies and actions at an operational level. There has been a dire need in Victoria to address many issues regarding P. cinnamomi and this thesis provides relevant and informative approaches to disease control, and a better understanding of the disease progress.

Investigation into and control of microwave induced thermal run-away

Analyses the mechanisms that cause thermal run-away in some materials. A control strategy was devised to provide effective temperature control independent of material characteristics. The set of control criteria derived from mathematical models allowed the control limits of a microwave processing system to calculated.

The computer modelling of development proposals : a routine part of development control

This paper describes and discusses the aims and practicalities involed in the computer modelling of contentious development applications becoming accepted as a routine part of the processes of development control.  It uses three case studies frawn from the University of Adelaide's work with the City of Adelaide in Australia to delineate the role of 3D computer models of proposed new buildings and their immediate surroundings in the public understanding of the streetscape, neighbourhood context, overshadowing and overlooking implications of the proposals.

A simulation-based control interface layer for a high-fidelity anthropomorphic training simulator

Deakin University’s futuristic Universal Motion simulator will overcome the limitations of current motion simulator platforms by employing an anthropomorphic robot arm to provide the motion fidelity necessary to exploit the potential of modern simulation environments. Full motion simulators frequently utilize Stewart platforms to mimic the movement of vehicles during simulation. However, due to the limited motion range and dexterity of such systems, and their inability to convey realistic accelerations, they are unable to represent accurate motion characteristics. The Universal Motion Simulation aims to close the gap between the limitations of the current motion technology and real world, by introducing a flexible, modular, high-fidelity motion system that can be used for a variety of immersive training applications. The modular nature of the design allows interchangeable and configurable simulation pods to be attached to the end effectors.

Simultaneous control of spectroscopic and electrochemical properties in functionalised electrochemiluminescent tris(2,2'-bipyridine)ruthenium(II) complexes

Using a combination of electrochemical, spectroscopic and computational techniques, we have explored the fundamental properties of a series of ruthenium diimine complexes designed for coupling with other molecules or surfaces for electrochemiluminescence (ECL) sensing applications. With appropriate choice of ligand functionality, it is possible to manipulate emission wavelengths while keeping the redox ability of the complex relatively constant. DFT calculations show that in the case of electron withdrawing substituents such as ester or amide, the excited state is located on the substituted bipyridine ligand whereas in the case of alkyl functionality it is localised on a bipyridine. The factors that dictate annihilation ECL efficiency are interrelated. For example, the same factors that determine ΔG for the annihilation reaction (i.e. the relative energies of the HOMO and LUMO) have a corresponding effect on the energy of the excited state product. As a result, most of the complexes populate the excited state with an efficiency (Φex) of close to 80% despite the relatively wide range of emission maxima. The quantum yield of emission (Φp) and the possibility of competing side reactions are found to be the main determinants of ECL intensity.

Quality control of sensor network data

A wireless sensor network (WSN) is a group of sensors that are geographically distributed and interconnected by wireless networks. Sensors gather information about the state of physical world. Then, after processing forward them to the main destination. To be able to provide this service, there are many aspects of communication techniques that need to be explored. Supporting quality of service (QoS) will be of critical importance for pervasive WSNs that serve as the network infrastructure of diverse applications. To illustrate new research and development interests in this field, this paper examines and discusses the requirements, critical challenges, and open research issues on QoS management in WSNs. A brief overview of recent progress is given.

Nanofibers - production, properties and functional applications

With the rapid development of nanoscience and nanotechnology over the last decades, great progress has been made not only in the preparation and characterization of nanomaterials, but also in their functional applications. As an important one-dimensional nanomaterial, nanofibers have extremely high specific surface area because of their small diameters, and nanofiber membranes are highly porous with excellent pore interconnectivity. These unique characteristics plus the functionalities from the materials themselves impart nanofibers with a number of novel properties for applications in areas as various as biomedical engineering, wound healing, drug delivery and release control, catalyst and enzyme carriers, filtration, environment protection, composite reinforcement, sensors, optics, energy harvest and storage , and many others. More and more emphasis has recently been placed on large-scale nanofiber production, the key technology to the wide usages of nanofibers in practice. Tremendous efforts have been made on producing nanofibers from special materials. Concerns have been raised to the safety issue of nanofibrous materials. This book is a compilation of contributions made by experts who specialize in their chosen field. It is grouped into three sections composed of twenty-one chapters, providing an up-to-date coverage of nanofiber preparation, properties and functional applications. I am deeply appreciative of all the authors and have no doubt that their contribution will be a useful resource of anyone associated with the discipline of nanofibers.

Enzyme-assisted self-assembly under thermodynamic control

The production of functional molecular architectures through self-assembly is commonplace in biology, but despite advances^{1, 2, 3}, it is still a major challenge to achieve similar complexity in the laboratory. Self-assembled structures that are reproducible and virtually defect free are of interest for applications in three-dimensional cell culture^{4, 5}, templating⁶, biosensing⁷ and supramolecular electronics⁸. Here, we report the use of reversible enzyme-catalysed reactions to drive self-assembly. In this approach, the self-assembly of aromatic short peptide derivatives^{9, 10} provides a driving force that enables a protease enzyme to produce building blocks in a reversible and spatially confined manner. We demonstrate that this system combines three features: (i) self-correction—fully reversible self-assembly under thermodynamic control; (ii) component-selection—the ability to amplify the most stable molecular self-assembly structures in dynamic combinatorial libraries^{11, 12, 13}; and (iii) spatiotemporal confinement of nucleation and structure growth. Enzyme-assisted self-assembly therefore provides control in bottom-up fabrication of nanomaterials that could ultimately lead to functional nanostructures with enhanced complexities and fewer defects.

Novel applications and research problems for sensor-clouds

Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we foresee novel applications being created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrents of data as a result of social interactions. The data generated appear in different formats such as photographs, videos, or short texts, etc. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices like smart phones, tablets or laptops. Further, they do not generate data at a constant rate or format like other sensors do. Instead, data from social sensors are spurious and varied, often in response to social events, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses three such applications utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.

On monotonic sufficient conditions of fuzzy inference systems and their applications

An important and difficult issue in designing a Fuzzy Inference System (FIS) is the specification of fuzzy sets and fuzzy rules. In this paper, two useful qualitative properties of the FIS model, i.e., the monotonicity and sub-additivity properties, are studied. The monotonic sufficient conditions of the FIS model with Gaussian membership functions are further analyzed. The aim is to incorporate the sufficient conditions into the FIS modeling process, which serves as a simple (which can be easily understood by domain users), easy-to-use (which can be easily applied to or can be a part of the FIS model), and yet reliable (which has a sound mathematical foundation) method to preserve the monotonicity property of the FIS model. Another aim of this paper is to demonstrate how these additional qualitative information can be exploited and extended to be part of the FIS designing procedure (i.e., for fuzzy sets and fuzzy rules design) via the sufficient conditions (which act as a set of useful governing equations for designing the FIS model). The proposed approach is able to avoid the "trial and error" procedure in obtaining a monotonic FIS model. To assess the applicability of the proposed approach, two practical problems are examined. The first is an FIS-based model for water level control, while the second is an FIS-based Risk Priority Number (RPN) model in Failure Mode and Effect Analysis (FMEA). To further illustrate the importance of the sufficient conditions as the governing equations, an analysis on the consequences of violating the sufficient conditions of the FIS-based RPN model is presented.

Sensor-cloud computing : novel applications and research problems

Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we are seeing novel applications been created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrent of data as a result of social interactions and social events. The data generated appear in different formats such as photographs, videos and short text messages. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices such as a phone or a laptop. And unlike other sensors that generate data at a constant rate or format, social sensors generate data that are spurious and varied, often in response to events as individual as a dinner outing, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses such applications as a result of utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.