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This thesis examines a novel induction-based framework for logic programming. Limiting programs are logic programs distinguished by two features, in general they contain an infinite data stream over which induction will be performed, and in general it is not possible for a system to know when a solution for any program is correct. These facts are characteristic of some problems involving induction in artificial intelligence, and several problems in knowledge representation and logic programming have exactly these properties. This thesis presents a specification language for problems with an inductive nature, limiting programs, and a resolution based system, limiting resolution, for solving these problems. This framework has properties which guarantee that the system will converge upon a particular answer in the limit. Solutions to problems which have such an inductive property by nature can be implemented using the language, and solved with the solver. For instance, many classification problems are inductive by nature. Some generalized planning problems also have the inductive property. For a class of generalized planning problems, we show that identifying a collection of domains where a plan reaches a goal is equivalent to producing a plan. This thesis gives examples of both. Limiting resolution works by a generate-and-test strategy, creating a potential solution and iteratively looking for a contradiction with the growing stream of data provided. Limiting resolution can be implemented by modifying conventional PROLOG technology. The generateand- test strategy has some inherent inefficiencies. Two improvements have arisen from this work; the first is a tabling strategy which records previously failed attempts to produce a solution and thereby avoids redundant test steps. The second is based on the heuristic observation that for some problems the size of the test step is proportional to the closeness of the generated potential-solution to the real solution, in a suitable metric. The observation can be used to improve the performance of limiting resolution. Thus this thesis describes, from theoretical foundations to implementation, a coherent methodology for incorporating induction into existing general A.I. programming techniques, along with examples of how to perform such tasks.

Hydroxyapatite ( HA ) coatings are widely used on metal implant devices to improve biocompatibility, enhance bonding strength and to shorten bonding aging between the implant and natural bones. Current coating methods share a common drawback : coatings produced by these processes are not crystalline and further heat treatment must be performed at high temperature ( 700 ° C ). Unfortunately, this treatment often reduces the bonding strength between the coating layer and the metal substrates and may cause chemical degradation of the HA. Recently, a biomimetic coating method has been developed. The strategy adopted in this method is to induce formation of the HA layer by coating implant surfaces with biologically inspired functional groups. This attempts to simulate the natural mineralization process occurring in the human body and it is hoped that the low crystallinity problem may be overcome. Unfortunately, industrial - scale production is not attractive due to the slow growth rate of the crystalline layer. Several weeks are required to produce a detectable thickness of HA and the deposited layer ' s in - vivo performance has not been quantified. As a consequence, further studies elucidating the key factors influencing formation of the HA layers and its in - vivo performance are desirable. In this study, self - assembled monolayers ( SAM layers ) with different functional groups were produced on titanium substrates and characterized. The titanium substrates were immersed in simulated body fluid ( SBF ) to synthesize HA coatings. After measuring the chemical compositions, crystallinity, morphology and growth rates of those coatings, the optimal SAM for HA formation was determined. In addition, the influences of key variables such as temperature, pH, ionic concentrations and functional groups on HA formation were investigated. The goal of this work was to accelerate the growth of the HA coatings for industrial scale production. Finally, human bone cells behaviors on HA coated titanium were observed to confirm an improvement in the biocompatibility and bioconductivity. It was found that SAMs significantly enhanced the formation of HA coatings on titanium surface. The optimum functional group for the SAM was - COOH. This functional group produced the fastest rate of formation and a HA coating with morphological attributes and crystallinity most like natural bone. Significant factors affecting HA formation on - COOH SAM were temperature, calcium concentration and Ca / P ratio in SBF. Significantly, it was discovered that higher temperatures and calcium concentration in SBF substantially increased rate of growth of the HA coating whilst appearing not to adversely affect crystallinity. This could reduce time for producing SAM induced HA coatings on titanium implants from a month to a week. Finally, the HA coating formed at 37 ° C on - COOH SAM substantially enhanced the growth of human bone cells on the titanium surface. / Thesis (M.Eng.Sc.)--School of Chemical Engineering, 2005.

Heart disease is the principal cause of death in most industrialised countries. In the U.S.A. for example, 2.3 million individuals suffer from chronic heart failure, with an annual increase in numbers of 17%. It is estimated that 17,000 to 35,000 of them per year will die from this disease if they are not given either a heart transplant or an artificial heart. Unfortunately, the numbers of heart donors cannot meet the demand for transplantation, and, at present, the artificial heart is a prohibitively expensive alternative. The total artificial heart (TAH) intended for the total replacement of the natural heart is still some years away from realisation. However, the ventricular assist device (VAD) which is used temporarily to maintain an ailing heart is available now, although only in restricted numbers due to difficulties in processing the biocompatible materials used during manufacture. Consequently, such devices are expensive, costing anywhere from AUS$30,000 for the pump head to AUS$200,000 for a complete system. In this study, the Australian designed $quot;Spiral Vortex$quot; VAD was used to investigate fabrication techniques for use in the eventual cost-effective manufacture of a pump head costing approximately AUS$4,000. A second VAD originally designed at the Kolff Laboratory, University of Utah, U.S.A. was also used for comparative evaluation. The hard-shell Spiral Vortex VAD is intended to be used outside the body, while the soft-shell Kolff VAD has the advantage of being implantable for long-term use. They were cast from epoxy resin and vacuum formed from polyurethane, respectively. Several units of each were fabricated, including 60 of the Kolff VAD, for use in vitro and in vivo experiments. From these experiments it was found that both the Spiral Vortex and Kolff VADs could be fabricated to quality controllable standards. The Kolff VAD was used exclusively in chronic animal experiments, and was able to sustain sheep and goats for periods of up to five weeks. Furthermore, it became evident that techniques used in fabrication of the Kolff VAD could be adopted for use in the mass production of the Spiral Vortex VAD. The two other areas investigated in this study were the prosthetic heart valves and drive systems used for an artificial heart. A high percentage of the cost of an artificial heart is accounted for by the inflow/outflow valves. The trileaflet valve used in the Kolff VAD, which mimics the natural heart valve, was fabricated using inexpensive vacuum-forming techniques. Quality control was found to be adequate, with good flow characteristics which could be maintained for several weeks in animal experiments. Both the Spiral Vortex and Kolff VADs are pulsation pumps which require a pneumatic driver unit. This driver is the single most expensive component in a VAD system, costing upwards of AUS$150,000. The theoretical efficiency of a compact hydromechanical drive unit was investigated using a test rig to simulate an original design based primarily on proprietary components. Results obtained so far indicate that the proposed driver can operate only under limited conditions as a result of its severe reduction in size. By adopting mass production techniques wherever possible in the fabrication of the VAD (pump head) and valves, and by reducing the cost and size of the driver unit, it may therefore be possible to produce a cost effective ventricular assist device system.

<p>Initially we pursue a minimal model of a cognitive system. This in turn form the basis for the development of amethodological and theoretical framework. Two methodological requirements of the model are that explanation be from the perspective of the phenomena, and that we have structural determination. The minimal model is derived from the explanatory side of a biologically based cognitive science. Fransisco Varela is our principal source for this part. The model defines the relationship between a formally defined autonomous system and an environment, in such a way as to generate the world of the system, its actual environment. The minimal model is a modular explanation in that we find it on different levels in bio-cognitive systems, from the cell to small social groups. For the latter and for the role played by artefactual systems we bring in Edwin Hutchins' observational study of a cognitive system in action. This necessitates the introduction of a complementary form of explanation. A key aspect of Hutchins' findings is the social domain as environment for humans. Aspects of human cognitive abilities usually attributed to the person are more properly attributed to the social system, including artefactual systems.</p><p>Developing the methodological and theoretical framework means making a transition from the bio-cognitive to the computational. The two complementary forms of explanation are important for the ability to develop a methodology that supports the construction of actual systems. This has to be able to handle the transition from external determination of a system in design to internal determination (autonomy) in operation.</p><p>Once developed, the combined framework is evaluated in an application area. This is done by comparing the standard conception of the Semantic Web with how this notion looks from the perspective of the framework. This includes the development of the methodological framework as a metalevel external knowledge representation. A key difference between the two approaches is the directness by which the semantic is approached. Our perspective puts the focus on interaction and the structural regularities this engenders in the external representation. Regularities which in turn form the basis for machine processing. In this regard we see the relationship between representation and inference as analogous to the relationship between environment and system. Accordingly we have the social domain as environment for artefactual agents. For human level cognitive abilities the social domain as environment is important. We argue that a reasonable shortcut to systems we can relate to, about that very domain, is for artefactual agents to have an external representation of the social domain as environment.</p>

Since Robotics is the field concerned with the connection of perception to action, Artificial Intelligence must have a central role in Robotics if the connection is to be intelligent. Artificial Intelligence addresses the crucial questions of: what knowledge is required in any aspect of thinking; how that knowledge should be represented; and how that knowledge should be used. Robotics challenges AI by forcing it to deal with real objects in the real world. Techniques and representations developed for purely cognitive problems, often in toy domains, do not necessarily extend to meet the challenge. Robots combine mechanical effectors, sensors, and computers. AI has made significant contributions to each component. We review AI contributions to perception and object oriented reasoning. Object-oriented reasoning includes reasoning about space, path-planning, uncertainty, and compliance. We conclude with three examples that illustrate the kinds of reasoning or problem solving abilities we would like to endow robots with and that we believe are worthy goals of both Robotics and Artificial Intelligence, being within reach of both.