Strategic project evaluation for open pit mining ventures using real options and allied econometric techniques

Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

Using cost-effective multimedia to create engaging learning experiences in law and other disciplines

This is the final report of an Australian Learning and Teaching Council Teaching Fellowship which addressed the needs of two separate groups of learners: (1) final year law students studying ethics and (2) law academics and other interested educators in higher education wishing to use information and communication technologies (ICT) to create engaging learning environments for their students but lacking the capacity to do so. The Fellowship resulted in final year law students being infused with an improved appreciation of ethical practice than they receive from traditional lecture/tutorial means by the development of an integrated program of blended learning including an online program entitled "Entry into Valhalla". This "ethics capstone‟ utilises multimedia produced using cost effective resources (including the "Second Life" virtual environment) to create engaging, contextualised learning experiences. The Fellowship also constructed the knowledge of producing cost-effective multimedia projects in other law academics and other educators in higher education by staff development activities comprising workshops, conference presentations and an interactive website using the "Entry into Valhalla" program as a case study exemplar.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

Developing a transition pedagogy : intentional curriculum design in first and final year law programs

This chapter will first consider the rationale for a transition pedagogy for first and final year law students. It then discusses the elements of a transition pedagogy for both years, noting the synergies and differences between programs designed to assist transition into and out of a law degree. In doing so, the authors attempt to explore the extent to which the first year curriculum principles identified by Sally Kift under an Australian Learning and Teaching Council (ALTC) Senior Fellowship may also be applied to the final year university experience. During the course of the discussion, examples are drawn from universities and Law Schools in Australia and internationally which seek to address these imperatives...

The capstone experience in law

An effective capstone experience provides closure through: Supporting students to synthesise their learning in the program by building upon the knowledge, skills and capability development that has taken place over the entirety of the curriculum; Providing enhanced opportunities for students to reflect on their personal and professional development over the course of their legal education experience and how that prepares them for their future professional and personal lives; Assisting students to attain an understanding of what it means to be a graduate of the discipline and begin to develop a professional identity.

Optimum utilisation of rolling stocks for iron ore mining industries

In this paper, a generic and flexible optimisation methodology is developed to represent, model, solve and analyse the iron ore supply chain system by integrating of iron ore shipment, stockpiles and railing within a whole system. As a result, an integrated train-stockpile-ship timetable is created and optimised for improving efficiency of overall supply chain system. The proposed methodology provides better decision making on how to significantly improve rolling stock utilisation with the best cost-effectiveness ratio. Based on extensive computational experiments and analysis, insightful and quantitative advices are suggested for iron ore mine industry practitioners. The proposed methodology contributes to the sustainability of the environment by reducing pollution due to better utilisation of transportation resources and fuel.

Operations research for mining : a classification and literature review

In this paper, we describe the main processes and operations in mining industries and present a comprehensive survey of operations research methodologies that have been applied over the last several decades. The literature review is classified into four main categories: mine design; mine production; mine transportation; and mine evaluation. Mining design models are further separated according to two main mining methods: open-pit and underground. Moreover, mine production models are subcategorised into two groups: ore mining and coal mining. Mine transportation models are further partitioned in accordance with fleet management, truck haulage and train scheduling. Mine evaluation models are further subdivided into four clusters in terms of mining method selection, quality control, financial risks and environmental protection. The main characteristics of four Australian commercial mining software are addressed and compared. This paper bridges the gaps in the literature and motivates researchers to develop more applicable, realistic and comprehensive operations research models and solution techniques that are directly linked with mining industries.

A fragment of the LG3 peptide of endorepellin is present in the urine of physically active mining workers : a potential marker of physical activity

Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

Physical effect in patent law

This thesis addresses one of the fundamental issues that remains unresolved in patent law today. It is a question that strikes at the heart of what a patent is and what it is supposed to protect. That question is whether an invention must produce a physical effect or cause a physical transformation of matter to be patentable, or whether it is sufficient that an invention involves a specific practical application of an idea or principle to achieve a useful result. In short, the question is whether patent law contains a physicality requirement. Resolving this issue will determine whether only traditional mechanical, industrial and manufacturing processes are patent eligible, or whether patent eligibility extends to include purely intangible, or non-physical, products and processes. To this end, this thesis seeks to identify where the dividing line lies between patentable subject matter and the recognised categories of excluded matter, namely, fundamental principles of nature, physical phenomena, and abstract ideas. It involves determining which technological advances are worth the inconvenience monopoly protection causes the public at large, and which should remain free for all to use without restriction. This is an issue that has important ramifications for innovation in the ‘knowledge economy’ of the Information Age. Determining whether patent law contains a physicality requirement is integral to deciding whether much of the valuable innovation we are likely to witness, in what are likely to be the emerging areas of technology in the near future, will receive the same encouragement as industrial and manufacturing advances of previous times.

Group law computations on Jacobians of hyperelliptic Curves

We derive an explicit method of computing the composition step in Cantor’s algorithm for group operations on Jacobians of hyperelliptic curves. Our technique is inspired by the geometric description of the group law and applies to hyperelliptic curves of arbitrary genus. While Cantor’s general composition involves arithmetic in the polynomial ring F_q[x], the algorithm we propose solves a linear system over the base field which can be written down directly from the Mumford coordinates of the group elements. We apply this method to give more efficient formulas for group operations in both affine and projective coordinates for cryptographic systems based on Jacobians of genus 2 hyperelliptic curves in general form.

The role of law in responding to climate change : emerging regulatory, liability and market approaches

Climate change presents as the archetypal environmental problem with short-term economic self-interest operating to the detriment of the long-term sustainability of our society. The scientific reports of the Intergovernmental Panel on Climate Change strongly assert that the stabilisation of emissions in the atmosphere, to avoid the adverse impacts of climate change, requires significant and rapid reductions in ‘business as usual’ global greenhouse gas emissions. The sheer magnitude of emissions reductions required, within this urgent timeframe, will necessitate an unprecedented level of international, multi-national and intra-national cooperation and will challenge conventional approaches to the creation and implementation of international and domestic legal regimes. To meet this challenge, existing international, national and local legal systems must harmoniously implement a strong international climate change regime through a portfolio of traditional and innovative legal mechanisms that swiftly transform current behavioural practices in emitting greenhouse gases. These include the imposition of strict duties to reduce emissions through the establishment of strong command and control regulation (the regulatory approach); mechanisms for the creation and distribution of liabilities for greenhouse gas emissions and climaterelated harm (the liability approach) and the use of innovative regulatory tools in the form of the carbon trading scheme (the market approach). The legal relations between these various regulatory, liability and market approaches must be managed to achieve a consistent, compatible and optimally effective legal regime to respond to the threat of climate change. The purpose of this thesis is to analyse and evaluate the emerging legal rules and frameworks, both international and Australian, required for the effective regulation of greenhouse gas emissions to address climate change in the context of the urgent and deep emissions reductions required to minimise the adverse impacts of climate change. In doing so, this thesis will examine critically the existing and potential role of law in effectively responding to climate change and will provide recommendations on the necessary reforms to achieve a more effective legal response to this global phenomenon in the future.

Murray-Darling basin governance : the focus of the law

The legal arrangements for the management of the Murray-Darling Basin in Australia have changed significantly over the years. The Constitution of the Commonwealth has led to the legal arrangements for the management of the Murray-Darling Basin. The Water Act 2000 of Queensland aimed at advancing sustainable management and efficient use of water and other resources by establishing a system for the planning, allocation and use of water. The Water Management Act 2000 of New South Wales ensures the sustainable and integrated management of the water resources of the state benefiting the present and future generations. The Natural Resources Management Act 2004 of South Australia applies to water resources and to other natural resources. The Act aimed at assisting the achievement of ecologically sustainable development in the state.

A requirements and capability discussion : UAS for SAR and law enforcement

This presentation explores the requirements and capabilities of Unmanned Aircraft Systems (UAS) for applications in Law Enforcement and Search and Rescue.

Text mining and probabilistic language modeling for online review spam detecting

In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.