Dragline automation - a decade of development : shared autonomy for improving mining equipment productivity

Draglines are massive machines commonly used in surface mining to strip overburden, revealing the targeted minerals for extraction. Automating some or all of the phases of operation of these machines offers the potential for significant productivity and maintenance benefits. The mining industry has a history of slow uptake of automation systems due to the challenges contained in the harsh, complex, three-dimensional (3D), dynamically changing mine operating environment. Robotics as a discipline is finally starting to gain acceptance as a technology with the potential to assist mining operations. This article examines the evolution of robotic technologies applied to draglines in the form of machine embedded intelligent systems. Results from this work include a production trial in which 250,000 tons of material was moved autonomously, experiments demonstrating steps towards full autonomy, and teleexcavation experiments in which a dragline in Australia was tasked by an operator in the United States.

The role of the health surveillance program in the Queensland coal mining industry

The Queensland Coal Industry Employees Health Scheme was implemented in 1993 to provide health surveillance for all Queensland coal industry workers. Tt1e government, mining employers and mining unions agreed that the scheme should operate for seven years. At the expiry of the scheme, an assessment of the contribution of health surveillance to meet coal industry needs would be an essential part of determining a future health surveillance program. This research project has analysed the data made available between 1993 and 1998. All current coal industry employees have had at least one health assessment. The project examined how the centralised nature of the Health Scheme benefits industry by identi~)jng key health issues and exploring their dimensions on a scale not possible by corporate based health surveillance programs. There is a body of evidence that indicates that health awareness - on the scale of the individual, the work group and the industry is not a part of the mining industry culture. There is also growing evidence that there is a need for this culture to change and that some change is in progress. One element of this changing culture is a growth in the interest by the individual and the community in information on health status and benchmarks that are reasonably attainable. This interest opens the way for health education which contains personal, community and occupational elements. An important element of such education is the data on mine site health status. This project examined the role of health surveillance in the coal mining industry as a tool for generating the necessary information to promote an interest in health awareness. The Health Scheme Database provides the material for the bulk of the analysis of this project. After a preliminary scan of the data set, more detailed analysis was undertaken on key health and related safety issues that include respiratory disorders, hearing loss and high blood pressure. The data set facilitates control for confounding factors such as age and smoking status. Mines can be benchmarked to identify those mines with effective health management and those with particular challenges. While the study has confirmed the very low prevalence of restrictive airway disease such as pneu"moconiosis, it has demonstrated a need to examine in detail the emergence of obstructive airway disease such as bronchitis and emphysema which may be a consequence of the increasing use of high dust longwall technology. The power of the Health Database's electronic data management is demonstrated by linking the health data to other data sets such as injury data that is collected by the Department of l\1mes and Energy. The analysis examines serious strain -sprain injuries and has identified a marked difference between the underground and open cut sectors of the industry. The analysis also considers productivity and OHS data to examine the extent to which there is correlation between any pairs ofJpese and previously analysed health parameters. This project has demonstrated that the current structure of the Coal Industry Employees Health Scheme has largely delivered to mines and effective health screening process. At the same time, the centralised nature of data collection and analysis has provided to the mines, the unions and the government substantial statistical cross-sectional data upon which strategies to more effectively manage health and relates safety issues can be based.

Development and synthesis of innovative approaches to the surgical assessment of articular cartilage degeneration

This research has established, through ultrasound, near infrared spectroscopy and biomechanics experiments, parameters and parametric relationships that can form the framework for quantifying the integrity of the articular cartilage-on-bone laminate, and objectively distinguish between normal/healthy and abnormal/degenerated joint tissue, with a focus on articular cartilage. This has been achieved by: 1. using traditional experimental methods to produce new parameters for cartilage assessment; 2. using novel methodologies to develop new parameters; and 3. investigating the interrelationships between mechanical, structural and molec- ular properties to identify and select those parameters and methodologies that can be used in a future arthroscopic probe based on points 1 and 2. By combining the molecular, micro- and macro-structural characteristics of the tissue with its mechanical properties, we arrive at a set of critical benchmarking parameters for viable and early-stage non-viable cartilage. The interrelationships between these characteristics, examined using a multivariate analysis based on principal components analysis, multiple linear regression and general linear modeling, could then to deter- mine those parameters and relationships which have the potential to be developed into a future clinical device. Specifically, this research has found that the ultrasound and near infrared techniques can subsume the mechanical parameters and combine to characterise the tissue at the molecular, structural and mechanical levels over the full depth of the cartilage matrix. It is the opinion in this thesis that by enabling the determination of the precise area of in uence of a focal defect or disease in the joint, demarcating the boundaries of articular cartilage with dierent levels of degeneration around a focal defect, better surgical decisions that will advance the processes of joint management and treatment will be achieved. Providing the basis for a surgical tool, this research will contribute to the enhancement and quanti�cation of arthroscopic procedures, extending to post- treatment monitoring and as a research tool, will enable a robust method for evaluating developing (particularly focalised) treatments.

Candidate metastasis suppressor genes uncovered by array comparative genomic hybridization in a mouse allograft model of prostate cancer.

Background The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors. Results This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors. Conclusion This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.

Raman spectroscopic study of the mineral thorikosite Pb3(OH)(SbO3,AsO3)Cl2 : a mineral of archaeological significance

The mineral thorikosite Pb3(OH)(SbO3,AsO3)Cl2 is named after the ancient city of Thorikos, in the region of Attica, where the ancient mine sites dating back to the bronze ages are found. Raman spectra of the antimonate bearing mineral thorikosite Pb3(OH)(SbO3,AsO3)Cl2 were studied, and related to the structure of the mineral. Two intense Raman peaks are observed at 596 and 730 cm-1 and are assigned to the Sb3+O3 and As3+O3 stretching vibrations. A peak at 1085 cm-1 is assigned to the Sb3+OH deformation mode. Raman band at 325 cm-1 is assigned to an OAsO bending vibration of the As3+O3 units and the bands at 269 and 275 cm-1 are attributed to the OSbO bending modes of the Sb3+O3 units. The intense Raman bands at 112 and 133 cm-1 are associated with PbCl stretching modes. Minerals such as nealite and thorikosite are minerals of archaeological significance. Yet no spectroscopic studies of these minerals have been undertaken.

The mineral nealite Pb4Fe2+(AsO3)2Cl4•2H2O : a Raman spectroscopic study

The mineral nealite Pb4Fe2+(AsO3)2Cl4•2H2O is of archaeological significance as it is man made mineral formed through the dumping of mine wastes in the sea. The mineral has been studied by Raman spectroscopy. Raman spectroscopy identifies intense Raman bands at 708 and 732 cm-1 assigned to AsO33- stretching vibrations. In addition low intensity bands are observed at 604 and 632 cm-1 which are attributed to As2O42- symmetric and antisymmetric stretching modes. Low intensity Raman band is observed at 831 cm-1 and is assigned to the AsO44- stretching vibration. Intense Raman bands at 149 and 183 cm-1 are attributed to M-Cl stretching vibrations. Raman spectroscopy identifies arsenic anions in different oxidation states in the mineral. The molecular structure of the mineral nealite, as indicated by Raman spectroscopy, is more complex than has been reported by previous studies.

Suppressed democracy in China : theoretical rationalisation using a cosmopolitan methodology

The intention of this work is to explain theoretically that democracy logically exists in China, despite the statements to the contrary by China’s ruling party. We will have to look at several recent developments in social and political theory to fully understand my point. The first involves recent findings in the historical analysis of democracy from thinkers like Keane (2009), Isakhan and Stockwell (2011). The second deals with cosmopolitan theory and 2nd modernity, or from the works of David Held (2003), Ulrich Beck and Edgar Grande (2010) respectively. Finally, the third is a recent work of mine titled “Democratic Theory and Theoretical Physics” (2010).

Optimal fluid injection strategies for in situ mineral leaching in two-dimensions

This paper examines the ground-water flow problem associated with the injection and recovery of certain corrosive fluids into mineral bearing rock. The aim is to dissolve the minerals in situ, and then recover them in solution. In general, it is not possible to recover all the injected fluid, which is of concern economically and environmentally. However, a new strategy is proposed here, that allows all the leaching fluid to be recovered. A mathematical model of the situation is solved approximately using an asymptotic solution, and exactly using a boundary integral approach. Solutions are shown for two-dimensional flow, which is of some practical interest as it is achievable in old mine tunnels, for example.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.

Discovering characteristics of stochastic collections of process models

Process models in organizational collections are typically modeled by the same team and using the same conventions. As such, these models share many characteristic features like size range, type and frequency of errors. In most cases merely small samples of these collections are available due to e.g. the sensitive information they contain. Because of their sizes, these samples may not provide an accurate representation of the characteristics of the originating collection. This paper deals with the problem of constructing collections of process models, in the form of Petri nets, from small samples of a collection for accurate estimations of the characteristics of this collection. Given a small sample of process models drawn from a real-life collection, we mine a set of generation parameters that we use to generate arbitrary-large collections that feature the same characteristics of the original collection. In this way we can estimate the characteristics of the original collection on the generated collections.We extensively evaluate the quality of our technique on various sample datasets drawn from both research and industry.

Mining users’ opinions based on item folksonomy and taxonomy for personalized recommender systems

Item folksonomy or tag information is a kind of typical and prevalent web 2.0 information. Item folksonmy contains rich opinion information of users on item classifications and descriptions. It can be used as another important information source to conduct opinion mining. On the other hand, each item is associated with taxonomy information that reflects the viewpoints of experts. In this paper, we propose to mine for users’ opinions on items based on item taxonomy developed by experts and folksonomy contributed by users. In addition, we explore how to make personalized item recommendations based on users’ opinions. The experiments conducted on real word datasets collected from Amazon.com and CiteULike demonstrated the effectiveness of the proposed approaches.

Real-time volume estimation of a dragline payload

This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.