Controlling a submerged rigid body : a geometric analysis

In this paper we analyze the equations of motion of a submerged rigid body. Our motivation is based on recent developments done in trajectory design for this problem. Our goal is to relate some properties of singular extremals to the existence of decoupling vector fields. The ideas displayed in this paper can be viewed as a starting point to a geometric formulation of the trajectory design problem for mechanical systems with potential and external forces.

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*.

A qualitative investigation of socio-cultural factors influencing binge-drinking : a multi-country study

Despite substantial investment by governments in social marketing campaigns and the introduction of various legislative and supply controls on alcohol, the binge drinking phenomenon amongst young people continues unabated in many countries and appears to be spreading to others. This paper examines drinking behaviour amongst university students from 50 countries across Europe, North America and the Asia Pacific region and argues that more needs to be done in understanding socio-cultural factors. To date, little is known of the specific socio-cultural factors that are common in countries that have high drinking behaviour compared to countries that have moderate bingedrinking behaviour. Using a marketing systems approach, this exploratory study identifies two key themes that distinguish these countries, namely family influences and peer influences.

Human-body shadowing effects on indoor MIMO-OFDM channels at 5.2 GHz

Pedestrian movement is known to cause significant effects on indoor MIMO channels. In this paper, a statistical characterization of the indoor MIMO-OFDM channel subject ot pedestrian movement is reported. The experiment used 4 sending and 4 receiving antennas and 114 sub-carriers at 5.2 GHz. Measurement scenarios varied from zero to ten pedestrians walking randomly between transmitter (tx) and receiver (Rx) arrays. The empirical cumulative distribution function (CDF) of the received fading envelope fits the Ricean distribution with K factors ranging from 7dB to 15 dB, for the 10 pedestrians and vacant scenarios respectively. In general, as the number of pedestrians increase, the CDF slope tends to decrease proportionally. Furthermore, as the number of pedestrians increase, increasing multipath contribution, the dynamic range of channel capacity increases proportionally. These results are consistent with measurement results obtained in controlled scenarios for a fixed narrowband Single-Input Single-Output (SISO) link at 5.2 GHz in previous work. The described empirical characterization provides an insight into the prediction of human-body shadowing effects for indoor MIMO-OFDM channels at 5.2 GHz.

Asset renewal decision modelling with application to the water utility industry

Reliable infrastructure assets impact significantly on quality of life and provide a stable foundation for economic growth and competitiveness. Decisions about the way assets are managed are of utmost importance in achieving this. Timely renewal of infrastructure assets supports reliability and maximum utilisation of infrastructure and enables business and community to grow and prosper. This research initially examined a framework for asset management decisions and then focused on asset renewal optimisation and renewal engineering optimisation in depth. This study had four primary objectives. The first was to develop a new Asset Management Decision Framework (AMDF) for identifying and classifying asset management decisions. The AMDF was developed by applying multi-criteria decision theory, classical management theory and life cycle management. The AMDF is an original and innovative contribution to asset management in that: · it is the first framework to provide guidance for developing asset management decision criteria based on fundamental business objectives; · it is the first framework to provide a decision context identification and analysis process for asset management decisions; and · it is the only comprehensive listing of asset management decision types developed from first principles. The second objective of this research was to develop a novel multi-attribute Asset Renewal Decision Model (ARDM) that takes account of financial, customer service, health and safety, environmental and socio-economic objectives. The unique feature of this ARDM is that it is the only model to optimise timing of asset renewal with respect to fundamental business objectives. The third objective of this research was to develop a novel Renewal Engineering Decision Model (REDM) that uses multiple criteria to determine the optimal timing for renewal engineering. The unique features of this model are that: · it is a novel extension to existing real options valuation models in that it uses overall utility rather than present value of cash flows to model engineering value; and · it is the only REDM that optimises timing of renewal engineering with respect to fundamental business objectives; The final objective was to develop and validate an Asset Renewal Engineering Philosophy (AREP) consisting of three principles of asset renewal engineering. The principles were validated using a novel application of real options theory. The AREP is the only renewal engineering philosophy in existence. The original contributions of this research are expected to enrich the body of knowledge in asset management through effectively addressing the need for an asset management decision framework, asset renewal and renewal engineering optimisation based on fundamental business objectives and a novel renewal engineering philosophy.

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modelling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modelling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modelling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

Interpreting regional frequencies from synchronized phasor measurement in multi-area power systems

In this paper a new approach is proposed for interpreting of regional frequencies in multi machine power systems. The method uses generator aggregation and system reduction based on coherent generators in each area. The reduced system structure is able to be identified and a kalman estimator is designed for the reduced system to estimate the inter-area modes using the synchronized phasor measurement data. The proposed method is tested on a six machine, three area test system and the obtained results show the estimation of inter-area oscillations in the system with a high accuracy.

Test and evaluation system for multi-protocol sampled value protection schemes

Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

Addressing sustainable living using a collaborative approach and multi-disciplinary techniques

In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

Strategy in developing cell based therapy for large bone

Regeneration of osseous defects by tissue-engineering approach provides a novel means of treatment utilizing cell biology, materials science, and molecular biology. The concept of in vitro cultured osteoblasts having an ability to induce new bone formation has been demonstrated in the critical size defects using small animal models. The bone derived cells can be incorporated into bioengineered scaffolds and synthesize bone matrix, which on implantation can induce new bone formation. In search of optimal cell delivery materials, the extracellular matrix as cell carriers for the repair and regeneration of tissues is receiving increased attention. We have investigated extracellular matrix formed by osteoblasts in vitro as a scaffold for osteoblasts transplantation and found a mineralized matrix, formed by human osteoblasts in vitro, can initiate bone formation by activating endogenous mesenchymal cells. To repair the large bone defects, osteogenic or stem cells need to be prefabricated in a large three dimensional scaffold usually made of synthetic biomaterials, which have inadequate interaction with cells and lead to in vivo foreign body reactions. The interstitial extracellular matrix has been applied to modify biomaterials surface and identified vitronectin, which binds the heparin domain and RGD (Arg-Gly-Asp) sequence can modulate cell spreading, migration and matrix formation on biomaterials. We also synthesized a tri-block copolymer, methoxy-terminated poly(ethylene glycol)(MPEG)-polyL-lactide(PLLA)-polylysine(PLL) for human osteoblasts delivery. We identified osteogenic activity can be regulated by the molecular weight and composition of the triblock copolymers. Due to the sequential loss of lineage differentiation potential during the culture of bone marrow stromal cells that hinderers their potential clinical application, we have developed a clonal culture system and established several stem cell clones with fast growing and multi-differentiation properties. Using proteomics and subtractive immunization, several differential proteins have been identified and verified their potential application in stem cell characterization and tissue regeneration

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

The expanding roles of the ghrelin-gene derived peptide obestatin in health and disease

Obestatin is a 23 amino acid, ghrelin gene-derived peptide hormone produced in the stomach and a range of other tissues throughout the body. While it was initially reported that obestatin opposed the actions of ghrelin with regards to appetite and food intake, it is now clear that obestatin is not an endogenous ghrelin antagonist of ghrelin, but it is a multi-functional peptide hormone in its own right. In this review we will discuss the controversies associated with the discovery of obestatin and explore emerging central and peripheral roles of obestatin, roles in adipogenesis, pancreatic homeostasis and cancer.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.