Mind change complexity of learning logic programs

The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.

Learning to win process-control games watching game-masters

The present paper focuses on some interesting classes of process-control games, where winning essentially means successfully controlling the process. A master for one of these games is an agent who plays a winning strategy. In this paper we investigate situations in which even a complete model (given by a program) of a particular game does not provide enough information to synthesize—even incrementally—a winning strategy. However, if in addition to getting a program, a machine may also watch masters play winning strategies, then the machine is able to incrementally learn a winning strategy for the given game. Studied are successful learning from arbitrary masters and from pedagogically useful selected masters. It is shown that selected masters are strictly more helpful for learning than are arbitrary masters. Both for learning from arbitrary masters and for learning from selected masters, though, there are cases where one can learn programs for winning strategies from masters but not if one is required to learn a program for the master's strategy itself. Both for learning from arbitrary masters and for learning from selected masters, one can learn strictly more by watching m+1 masters than one can learn by watching only m. Last, a simulation result is presented where the presence of a selected master reduces the complexity from infinitely many semantic mind changes to finitely many syntactic ones.

Knowledge infrastructure : managing the assets of creative urban regions

Urban infrastructure along the hard forms such as roads, electricity, water and sewers also includes the soft forms such as research, training, innovation and technology. Knowledge and creativity are keys to soft infrastructure and socioeconomic development. Many city administrations around the world adjust their endogenous development strategies increasingly by investing in soft infrastructure and aiming for a knowledge-based development. At this point, the mapping and management of knowledge asset of cities has become a critical issue for promoting creative urban regions. The chapter scrutinizes the relations between knowledge assets and urban infrastructures and examines the management model to improve soft infrastructure provision.

Research project for managing skid resistance is on the road

In December 2006, the Engineering and Technology Group of Queensland’s Department of Main Roads entered into a three-year skid resistance management research project with QUT Faculty of Built Environment and Engineering researchers and the QUT-based CRC for Integrated Engineering Asset Management (CIEAM). CIEAM undertakes a broad range of asset management research in the areas of defence, utilities, transportation and industrial processes. “The research project is an important activity of Main Roads’ Skid Resistance Management Plan published in June 2006.” said Main Roads project leader Mr Justin Weligamage. “The intended project output is a decision-support model for use by Road Asset Managers throughout a road network. The research objective is to enable road asset managers to better manage the surfacing condition of the road asset with specific focus on skid resistance,” said QUT project leader Professor Arun Kumar. The research project will review existing skid resistance investigatory levels, develop a risk-based method to establish skid resistance investigatory levels and improve the decision support methodology in order to minimise crashes. The new risk-based approach will be used to identify locations on the Queensland state-controlled road network that may have inadequate skid resistance. Once a high risk site is identified, the appropriate remedial action will be decided on. This approach will allow road asset managers to target optimal remedial actions, reducing the incidence and severity of crashes where inadequate skid resistance is a contributing cause.

Overloading truck traffic study and strategy to minimise it

Overloaded truck traffic is a significant problem on highways around the world. Developing countries in particular, overloaded truck traffic causes large amounts of unexpected expenditure in terms of road maintenance because of premature pavement damage. Overloaded truck traffic is a common phenomenon in developing countries, because of inefficient road management and monitoring systems. According to the available literature, many developing countries are facing the same problem, which is economic loss caused by the existence of overloaded trucks in the traffic stream. This paper summarizes the available literature, news reports, journal articles and traffic research regarding overloaded traffic. It examines the issue of overloading and the strategies and legislation used in developed countries.

Identifying relationship between skid resistance, road characteristics and crashes using probability-based risk approach

Road accidents are of great concerns for road and transport departments around world, which cause tremendous loss and dangers for public. Reducing accident rates and crash severity are imperative goals that governments, road and transport authorities, and researchers are aimed to achieve. In Australia, road crash trauma costs the nation A$ 15 billion annually. Five people are killed, and 550 are injured every day. Each fatality costs the taxpayer A$1.7 million. Serious injury cases can cost the taxpayer many times the cost of a fatality. Crashes are in general uncontrolled events and are dependent on a number of interrelated factors such as driver behaviour, traffic conditions, travel speed, road geometry and condition, and vehicle characteristics (e.g. tyre type pressure and condition, and suspension type and condition). Skid resistance is considered one of the most important surface characteristics as it has a direct impact on traffic safety. Attempts have been made worldwide to study the relationship between skid resistance and road crashes. Most of these studies used the statistical regression and correlation methods in analysing the relationships between skid resistance and road crashes. The outcomes from these studies provided mix results and not conclusive. The objective of this paper is to present a probability-based method of an ongoing study in identifying the relationship between skid resistance and road crashes. Historical skid resistance and crash data of a road network located in the tropical east coast of Queensland were analysed using the probability-based method. Analysis methodology and results of the relationships between skid resistance, road characteristics and crashes are presented.

On the data consumption benefits of accepting increased uncertainty

In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.

On a Syntactic Characterization of Classification with a Mind Change Bound

Most learning paradigms impose a particular syntax on the class of concepts to be learned; the chosen syntax can dramatically affect whether the class is learnable or not. For classification paradigms, where the task is to determine whether the underlying world does or does not have a particular property, how that property is represented has no implication on the power of a classifier that just outputs 1’s or 0’s. But is it possible to give a canonical syntactic representation of the class of concepts that are classifiable according to the particular criteria of a given paradigm? We provide a positive answer to this question for classification in the limit paradigms in a logical setting, with ordinal mind change bounds as a measure of complexity. The syntactic characterization that emerges enables to derive that if a possibly noncomputable classifier can perform the task assigned to it by the paradigm, then a computable classifier can also perform the same task. The syntactic characterization is strongly related to the difference hierarchy over the class of open sets of some topological space; this space is naturally defined from the class of possible worlds and possible data of the learning paradigm.

An object oriented road asset information model

Preservation and enhancement of transportation infrastructure is critical to continuous economic development in Australia. Of particular importance are the road assets infrastructure, due to their high costs of setting up and their social and economic impact on the national economy. Continuous availability of road assets, however, is contingent upon their effective design, condition monitoring, maintenance, and renovation and upgrading. However, in order to achieve this data exchange, integration, and interoperability is required across municipal boundaries. On the other hand, there are no agreed reference frameworks that consistently describe road infrastructure assets. As a consequence, specifications and technical solutions being chosen to manage road assets do not provide adequate detail and quality of information to support asset lifecycle management processes and decisions taken are based on perception not reality. This paper presents a road asset information model, which works as reference framework to, link other kinds of information with asset information; integrate different data suppliers; and provide a foundation for service driven integrated information framework for community infrastructure and asset management.

Sustainable infrastructure operations : a review of assessment schemes and decision support

Infrastructure forms a vital component in supporting today’s way of life and has a significant role or impact on economic, environmental and social outcomes of the region around it. The design, construction and operation of such assets are a multi-billion dollar industry in Australia alone. Another issue that will play a major role in our way life is that of climate change and the greater concept of sustainability. With limited resources and a changing natural world it is necessary for infrastructure to be developed and maintained in a manner that is sustainable. In order to achieve infrastructure sustainability in operations it is necessary for there to be: a sustainability assessment scheme that provides a scientifically sound and realistic approach to measuring an assets level of sustainability; and, systems and tools to support the making of decisions that result in sustainable outcomes by providing feedback in a timely manner. Having these in place will then help drive the consideration of sustainability during the decision making process for infrastructure operations and maintenance. In this paper we provide two main contributions; a comparison and review of sustainability assessment schemes for infrastructure and their suitability for use in the operations phase; and, a review of decision support systems/tools in the area of infrastructure sustainability in operations. For this paper, sustainability covers not just the environment, but also finance/economic and societal/community aspects as well. This is often referred to as the Triple Bottom Line and forms one of the three dimensions of corporate sustainability [Stapledon, 2004].

Introducing sustainability assessment to civil infrastructure projects & assets

Civil infrastructure plays a key role in supporting and improving current way of life. However, the assets can have a large impact on the region around them, which are both positive (usually for the purpose they are built) and negative (consequences and unintended effects). There is an increasing trend for society to place an importance on the role of sustainability to ensure that there is a world suitable for future generations. In order to ensure that the world for future generations is in the best possible condition it is increasingly important to look at integrating sustainability outcomes into the way industry operates, including the infrastructure industry. It is therefore important to undertake sustainability assessment of civil infrastructure projects. By having organisations take on sustainability assessments of civil infrastructure assets both during construction and in operation, the industry can assist to drive outcomes and results that will benefit society and future generations and make their own operations more efficient.

Sustainability in post disaster road infrastructure recovery projects in Queensland, Australia

between mid 2010 and early 2011, Queensland road related infrastructures were devastated by flood and cyclone related natural disasters. Responding to these recent events and in preparing for more regular and intense climate-change induced events in future, the Queensland Government is now reviewing how post-disaster road infrastructure recovery projects are planned and delivered. In particular, there is awareness that rebuilding such infrastructure need sustainable strategies across economic, environmental and social dimensions. A comprehensive sustainability assessment framework for pre and post disaster situations can minimize negative impact on our communities, economy and environment. This research is underway to develop a comprehensive sustainability element frame work for post disaster management in road infrastructures in Queensland, Australia. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of natural disasters. This research can contribute to strategic planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes in Queensland. Within this context, this paper provides an overview of the qualitative mixed-method research approach involving literature reviews and case studies to explore and evaluate a number of sustainability elements with a view to develop operational strategies for disaster recovery road projects.

Learning environments – Laboratories at the cross roads

Laboratories and technical hands on learning have always been a part of Engineering and Science based university courses. They provide the interface where theory meets practice and students may develop professional skills through interacting with real objects in an environment that models appropriate standards and systems. Laboratories in many countries are facing challenges to their sustainable operation and effectiveness. In some countries such as Australia, significantly reduced funding and staff reduction is eroding a once strong base of technical infrastructure. Other countries such as Thailand are seeking to develop their laboratory infrastructure and are in need of staff skill development, management and staff structure in technical areas. In this paper the authors will address the need for technical development with reference to work undertaken in Thailand and Australia. The authors identify the roads which their respective university sectors are on and point out problems and opportunities. It is hoped that the cross roads where we meet will result in better directions for both.

Sustainability in post disaster road infrastructure recovery projects in Queensland, Australia

Between mid 2010 and early 2013, Queensland road related infrastructures were devastated by flood and cyclone related natural disasters. Responding to these recent events and in preparing for more regular and intense climate-change induced events in future, the Queensland Government is now reviewing how post-disaster road infrastructure recovery projects are planned and delivered. In particular, there is awareness that rebuilding such infrastructure need sustainable strategies across economic, environmental and social dimensions. A comprehensive sustainability assessment framework for pre and post disaster situations can minimize negative impact on our communities, economy and environment. This research is underway to develop a comprehensive sustainability element frame work for post disaster management in road infrastructures in Queensland, Australia. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of natural disasters. This research can contribute to strategic planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes in Queensland. Within this context, this paper provides an overview of the qualitative mixed-method research approach involving literature reviews and case studies to explore and evaluate a number of sustainability elements with a view to develop operational strategies for disaster recovery road projects.

Endothelin-1 is a novel prognostic factor in non-small cell lung cancer

Endothelin-1 (ET-1) is a potent vasoactive peptide and a hypoxia-inducible angiogenic growth factor associated with the development and growth of solid tumours. This study evaluated the expression of big endothelin-1 (big ET-1), a stable precursor of ET-1, and ET-1 in non-small cell lung cancer (NSCLC). Big ET-1 expression was evaluated in paraffin-embedded tissue sections from 10 NSCLC tumours using immunohistochemistry and in situ hybridisation. The production of big ET-1 and ET-1 was studied in six established NSCLC cell lines. The plasma concentrations of big ET-1 were measured in 30 patients with proven NSCLC prior to chemotherapy by means of a sandwich enzyme-linked immunoassay and compared to levels in 20 normal controls. Big ET-1 immunostaining was detected in the cancer cells of all tumours studied. Using in situ hybridisation, tumour cell big ET-1 mRNA expression was demonstrated in all samples. All six NSCLC cell lines expressed ET-1, with big ET-1 being detected in three. The median big ET-1 plasma level in patients with NSCLC was 5.4 pg/mL (range 0-22.7 pg/mL) and was significantly elevated compared to median big ET-1 plasma levels in controls, 2.1 pg/mL (1.2-13.4 pg/mL) (p=0.0001). Furthermore, patients with plasma big ET-1 levels above the normal range (upper tertile) had a worse outcome (p=0.01). In conclusion, big ET-1/ET-1 is expressed by resected NSCLC specimens and tumour cell lines. Plasma big ET-1 levels are elevated in NSCLC patients compared to controls with levels >7.8 pg/mL being associated with a worse outcome. The development of selective ET-1 antagonists such as Atrasentan indicates that ET-1 may be a therapeutic target in NSCLC. © 2004 Wichtig Editore.