972 resultados para mining machine industry


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This Toolkit was developed for the Australian dairy processing industry on behalf of Dairy Australia. At the conclusion of the project, industry participants gained exclusive access to a comprehensive Eco-Efficiency Manual, which outlined many of the opportunities available to the industry. Summary fact sheets were also prepared as publicly available resources and these are available for download below

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This manual has been developed to help the Australian dairy processing industry increase its competitiveness through increased awareness and uptake of eco-efficiency. The manual seeks to consolidate and build on existing knowledge, accumulated through projects and initiatives that the industry has previously undertaken to improve its use of raw materials and resources and reduce the generation of wastes. Where there is an existing comprehensive report or publication, the manual refers to this for further information. Eco-efficiency is about improving environmental performance to become more efficient and profitable. It is about producing more with less. It involves applying strategies that will not only ensure efficient use of resources and reduction in waste, but will also reduce costs. This chapter outlines the environmental challenges faced by Australian dairy processors. The manual explores opportunities for reducing environmental impacts in relation to water, energy, product yield, solid and liquid waste reduction and chemical use.

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Australia struggles to achieve economic competitiveness, prevent expansion of the trade deficit and develop value-added production despite applications of policy strategies from protectionism to trade liberalisation. This article argues that these problems were emerging at the turn of the century, and that an investigation of music technology manufacturing in the first two decades of this century reveals fundamental problems in the conduct of relevant policy analysis. Analysis has focused on the trade or technology gap which is only symptomatic of an underlying knowledge gap. The article calls for a knowledge policy approach which can allow protection without the negative effects of isolation from global markets and without having to resort to unworkable utopian free-trade dogma. A shift of focus from a 'goods traded' view to a knowledge transaction (or diffusion) perspective is advocated.

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Community awareness of the sustainable use of land, water and vegetation resources is increasing. The sustainable use of these resources is pivotal to sustainable farming systems. However, techniques for monitoring the sustainable management of these resources are poorly understood and untested. We propose a framework to benchmark and monitor resources in the grains industry. Eight steps are listed below to achieve these objectives: (i) define industry issues; (ii) identify the issues through growers, stakeholder and community consultation; (iii) identify indicators (measurable attributes, properties or characteristics) of sustainability through consultation with growers, stakeholders, experts and community members, relating to: crop productivity; resource maintenance/enhancement; biodiversity; economic viability; community viability; and institutional structure; (iv) develop and use selection criteria to select indicators that consider: responsiveness to change; ease of capture; community acceptance and involvement; interpretation; measurement error; stability, frequency and cost of measurement; spatial scale issues; and mapping capability in space and through time. The appropriateness of indicators can be evaluated using a decision making system such as a multiobjective decision support system (MO-DSS, a method to assist in decision making from multiple and conflicting objectives); (v) involve stakeholders and the community in the definition of goals and setting benchmarking and monitoring targets for sustainable farming; (vi) take preventive and corrective/remedial action; (vii) evaluate effectiveness of actions taken; and (viii) revise indicators as part of a continual improvement principle designed to achieve best management practice for sustainable farming systems. The major recommendations are to: (i) implement the framework for resources (land, water and vegetation, economic, community and institution) benchmarking and monitoring, and integrate this process with current activities so that awareness, implementation and evolution of sustainable resource management practices become normal practice in the grains industry; (ii) empower the grains industry to take the lead by using relevant sustainability indicators to benchmark and monitor resources; (iii) adopt a collaborative approach by involving various industry, community, catchment management and government agency groups to minimise implementation time. Monitoring programs such as Waterwatch, Soilcheck, Grasscheck and Topcrop should be utilised; (iv) encourage the adoption of a decision making system by growers and industry representatives as a participatory decision and evaluation process. Widespread use of sustainability indicators would assist in validating and refining these indicators and evaluating sustainable farming systems. The indicators could also assist in evaluating best management practices for the grains industry.

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Recent structural studies of proteins mediating membrane fusion reveal intriguing similarities between diverse viral and mammalian systems. Particularly striking is the close similarity between the transmembrane envelope glycoproteins from the retrovirus HTLV-1 and the filovirus Ebola. These similarities suggest similar mechanisms of membrane fusion. The model that fits most currently available data suggests fusion activation in viral systems is driven by a symmetrical conformational change triggered by an activation event such as receptor binding or a pH change. The mammalian vesicle fusion mediated by the SNARE protein complex most likely occurs by a similar mechanism but without symmetry constraints.

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The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

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This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.

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The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

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To attend and obtain the systems and. internal controls mechanisms proposed by Sarbanes-Oxley certifications is actually a big challenge,for most of the multinational companies registered in SEC (US Securities and Exchange Commission). This work has the objective of contributing to the analysis of this methodology, not only to attend the law but to reduce cost and generate value through the strengthen of the internal control systems, turning them into animating value generation process mechanisms. So, the idea is to identify the main gaps in the theory through the literature revision and a case study in order to put a question to the main deficiencies, strong points or contributions through the evaluation of the noticed practices. Finally, we can say that a a result of the research and the analyses made in. this case, the vast majority of executives and other employees recognize the benefit that Sarbanes-Oxley Act has brought to the company searched. Also recognize that, although there is still necessity for systemic adequacy and infrastructure, it helps and reinforce reducing and controlling the risks. the system of internal controls in all areas of expertise. They approach and understand that there is the need for a change in the other employees` culture to be inserted in the day-today routine as internal controls, attention to Sarbanes-Oxley and Corporate Governance, making the control cost smaller when compared to the benefits generated.

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The fabrication of heavy-duty printer heads involves a great deal of grinding work. Previously in the printer manufacturing industry, four grinding procedures were manually conducted in four grinding machines, respectively. The productivity of the whole grinding process was low due to the long loading time. Also, the machine floor space occupation was large because of the four separate grinding machines. The manual operation also caused inconsistent quality. This paper reports the system and process development of a highly integrated and automated high-speed grinding system for printer heads. The developed system, which is believed to be the first of its kind, not only produces printer heads of consistently good quality, but also significantly reduces the cycle time and machine floor space occupation.

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There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

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The large number of wetlands treating mining wastewaters around the world have mostly been constructed in temperate environments. Wetlands have yet to be proven in low rainfall, high evaporation environments and such conditions are common in many parts of Australia. BHP Australia Coal is researching whether wetlands have potential in central Queensland to treat coal mining wastewaters. In this region, mean annual rainfall is < 650 mm and evaporation > 2 000 mm. A pilot-scale wetland system has been constructed at an open-cut coal mine. The system comprises six treatment cells, each 125 m long and 10 m wide. The system is described in the paper and some initial results presented. Results over the first fourteen months of operation have shown that although pH has not increased enough to enable reuse or release of the water, sulfate reduction has been observed in parts of the system, as shown by the characteristic black precipitate and smell of hydrogen sulfide emanating from the wetlands. These encouraging signs have led to experiments aimed at identifying the factors limiting sulfate reduction. The first experiment, described herein, included four treatments where straw was overlain by soil and the water level varied, being either at the top of the straw, at the top of the soil, or about 5 cm above the soil. The effect of inoculating with sulfate-reducing bacteria was investigated. Two controls were included, one covered and one open, to enable the effect of evaporation to be determined. The final treatment consisted of combined straw/cattle manure overlain with soil. Results showed that sulfate reduction did occur, as demonstrated by pH increases and lowering of sulfate levels. Mean pH of the water was significantly higher after 19 days; in the controls, pH was < 3.3, whereas in the treatments, pH ranged from 5.4 to 6.7. The best improvement in sulfate levels occurred in the straw/cattle manure treatment. (C) 1997 IAWQ. Published by Elsevier Science Ltd.

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Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.