24 datasets found
  1. s

    Online Feature Selection and Its Applications

    • researchdata.smu.edu.sg
    Updated May 31, 2023
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    HOI Steven; Jialei WANG; Peilin ZHAO; Rong JIN (2023). Online Feature Selection and Its Applications [Dataset]. http://doi.org/10.25440/smu.12062733.v1
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    Dataset updated
    May 31, 2023
    Dataset provided by
    SMU Research Data Repository (RDR)
    Authors
    HOI Steven; Jialei WANG; Peilin ZHAO; Rong JIN
    License

    https://www.gnu.org/licenses/gpl-3.0.htmlhttps://www.gnu.org/licenses/gpl-3.0.html

    Description

    Feature selection is an important technique for data mining before a machine learning algorithm is applied. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. This is in contrast to the classical setup of online learning where all the features can be used for prediction. We attempt to tackle this challenge by studying sparsity regularization and truncation techniques. Specifically, this article addresses two different tasks of online feature selection: (1) learning with full input where an learner is allowed to access all the features to decide the subset of active features, and (2) learning with partial input where only a limited number of features is allowed to be accessed for each instance by the learner. We present novel algorithms to solve each of the two problems and give their performance analysis. We evaluate the performance of the proposed algorithms for online feature selection on several public datasets, and demonstrate their applications to real-world problems including image classification in computer vision and microarray gene expression analysis in bioinformatics. The encouraging results of our experiments validate the efficacy and efficiency of the proposed techniques.Related Publication: Hoi, S. C., Wang, J., Zhao, P., & Jin, R. (2012). Online feature selection for mining big data. In Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (pp. 93-100). ACM. http://dx.doi.org/10.1145/2351316.2351329 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2402/ Wang, J., Zhao, P., Hoi, S. C., & Jin, R. (2014). Online feature selection and its applications. IEEE Transactions on Knowledge and Data Engineering, 26(3), 698-710. http://dx.doi.org/10.1109/TKDE.2013.32 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2277/

  2. D

    Electric Mining Equipment Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Electric Mining Equipment Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/electric-mining-equipment-market
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    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Electric Mining Equipment Market Outlook



    The global market size for electric mining equipment is projected to grow from USD 9.8 billion in 2023 to approximately USD 21.5 billion by 2032, reflecting a robust Compound Annual Growth Rate (CAGR) of 9.2%. The primary growth factors driving this market include rising environmental concerns, regulatory pressures for reducing carbon emissions, and the increasing focus on sustainable mining practices. The adoption of electric mining equipment is accelerated by advancements in battery technologies and the growing demand for energy-efficient and cost-effective mining solutions.



    One of the significant growth factors for the electric mining equipment market is the stringent environmental regulations imposed by governments worldwide. As concerns over climate change and environmental degradation intensify, regulatory bodies have set ambitious targets for carbon emission reductions. This has compelled mining companies to adopt cleaner and greener technologies, thereby increasing the demand for electric mining equipment. Furthermore, the ability of electric equipment to reduce particulate emissions and noise pollution is another appealing factor, promoting its adoption in environmentally sensitive mining areas.



    Technological advancements in battery and electric powertrain technologies are also playing a pivotal role in the market's growth. Innovations such as longer-lasting batteries, faster charging capabilities, and improvements in power density have made electric mining equipment more viable and attractive for mining operations. These advancements not only improve operational efficiency but also reduce the total cost of ownership, making electric equipment a more economically feasible option. Additionally, the integration of IoT and AI technologies in electric mining equipment is enhancing performance monitoring and predictive maintenance, further driving market growth.



    Economic factors are also contributing to the expanding market for electric mining equipment. Fluctuating fuel prices and the rising costs of diesel fuel have made the operational expenses of traditional mining equipment increasingly unsustainable. In contrast, electric mining equipment offers lower operating costs and reduced maintenance expenses. These economic benefits, coupled with improved efficiencies and longer equipment life, make electric mining equipment a more attractive investment for mining companies looking to optimize their operations and reduce overall costs.



    The introduction of the Mining Electric Locomotive is revolutionizing the way materials are transported within mining operations. These locomotives are specifically designed to operate efficiently in the challenging environments of mines, where traditional diesel-powered locomotives may struggle due to emissions and maintenance issues. By utilizing electric power, these locomotives significantly reduce the carbon footprint of mining operations, aligning with global sustainability goals. Furthermore, the Mining Electric Locomotive offers enhanced safety features and improved energy efficiency, making it a preferred choice for modern mining companies. As the mining industry continues to evolve, the adoption of such innovative solutions is expected to grow, driven by the need for cleaner and more efficient transportation methods within mines.



    From a regional perspective, the Asia Pacific region is expected to dominate the electric mining equipment market due to its substantial mining activities and the presence of prominent mining companies. The region is also experiencing significant investments in mining infrastructure and technology, particularly in countries such as China, India, and Australia. North America and Europe are also anticipated to witness substantial growth, driven by stringent environmental regulations and strong commitments to reducing carbon footprints. Conversely, regions like Latin America and the Middle East & Africa are gradually embracing electric mining solutions, primarily driven by increasing mining activities and growing awareness about sustainable practices.



    Product Type Analysis



    The electric mining equipment market by product type includes various segments such as electric loaders, electric excavators, electric drills, electric haul trucks, and others. Electric loaders are gaining significant traction due to their efficiency in material handling and reduced operational costs. These machines are particularly beneficial for undergroun

  3. r

    A predictive model for opal exploration in Australia from a data mining...

    • researchdata.edu.au
    Updated May 1, 2015
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    Thomas Landgrebe; Thomas Landgrebe; Adriana Dutkiewicz; Dietmar Muller (2015). A predictive model for opal exploration in Australia from a data mining approach [Dataset]. http://doi.org/10.4227/11/5587A86C0FDF1
    Explore at:
    Dataset updated
    May 1, 2015
    Dataset provided by
    The University of Sydney
    Authors
    Thomas Landgrebe; Thomas Landgrebe; Adriana Dutkiewicz; Dietmar Muller
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    Dataset funded by
    Australian Research Council
    Description

    This data collection is associated with the publications: Merdith, A. S., Landgrebe, T. C. W., Dutkiewicz, A., & Müller, R. D. (2013). Towards a predictive model for opal exploration using a spatio-temporal data mining approach. Australian Journal of Earth Sciences, 60(2), 217-229. doi: 10.1080/08120099.2012.754793

    and

    Landgrebe, T. C. W., Merdith, A., Dutkiewicz, A., & Müller, R. D. (2013). Relationships between palaeogeography and opal occurrence in Australia: A data-mining approach. Computers & Geosciences, 56(0), 76-82. doi: 10.1016/j.cageo.2013.02.002

    Publication Abstract - Merdith et al. (2013)

    Opal is Australia's national gemstone, however most significant opal discoveries were made in the early 1900's - more than 100 years ago - until recently. Currently there is no formal exploration model for opal, meaning there are no widely accepted concepts or methodologies available to suggest where new opal fields may be found. As a consequence opal mining in Australia is a cottage industry with the majority of opal exploration focused around old opal fields. The EarthByte Group has developed a new opal exploration methodology for the Great Artesian Basin. The work is based on the concept of applying “big data mining” approaches to data sets relevant for identifying regions that are prospective for opal. The group combined a multitude of geological and geophysical data sets that were jointly analysed to establish associations between particular features in the data with known opal mining sites. A “training set” of known opal localities (1036 opal mines) was assembled, using those localities, which were featured in published reports and on maps. The data used include rock types, soil type, regolith type, topography, radiometric data and a stack of digital palaeogeographic maps. The different data layers were analysed via spatio-temporal data mining combining the GPlates PaleoGIS software (www.gplates.org) with the Orange data mining software (orange.biolab.si) to produce the first opal prospectivity map for the Great Artesian Basin. One of the main results of the study is that the geological conditions favourable for opal were found to be related to a particular sequence of surface environments over geological time. These conditions involved alternating shallow seas and river systems followed by uplift and erosion. The approach reduces the entire area of the Great Artesian Basin to a mere 6% that is deemed to be prospective for opal exploration. The work is described in two companion papers in the Australian Journal of Earth Sciences and Computers and Geosciences.

    Publication Abstract - Landgrebe et al. (2013)

    Age-coded multi-layered geological datasets are becoming increasingly prevalent with the surge in open-access geodata, yet there are few methodologies for extracting geological information and knowledge from these data. We present a novel methodology, based on the open-source GPlates software in which age-coded digital palaeogeographic maps are used to “data-mine” spatio-temporal patterns related to the occurrence of Australian opal. Our aim is to test the concept that only a particular sequence of depositional/erosional environments may lead to conditions suitable for the formation of gem quality sedimentary opal. Time-varying geographic environment properties are extracted from a digital palaeogeographic dataset of the eastern Australian Great Artesian Basin (GAB) at 1036 opal localities. We obtain a total of 52 independent ordinal sequences sampling 19 time slices from the Early Cretaceous to the present-day. We find that 95% of the known opal deposits are tied to only 27 sequences all comprising fluvial and shallow marine depositional sequences followed by a prolonged phase of erosion. We then map the total area of the GAB that matches these 27 opal-specific sequences, resulting in an opal-prospective region of only about 10% of the total area of the basin. The key patterns underlying this association involve only a small number of key environmental transitions. We demonstrate that these key associations are generally absent at arbitrary locations in the basin. This new methodology allows for the simplification of a complex time-varying geological dataset into a single map view, enabling straightforward application for opal exploration and for future co-assessment with other datasets/geological criteria. This approach may help unravel the poorly understood opal formation process using an empirical spatio-temporal data-mining methodology and readily available datasets to aid hypothesis testing.

    Authors and Institutions

    Andrew Merdith - EarthByte Research Group, School of Geosciences, The University of Sydney, Australia. ORCID: 0000-0002-7564-8149

    Thomas Landgrebe - EarthByte Research Group, School of Geosciences, The University of Sydney, Australia

    Adriana Dutkiewicz - EarthByte Research Group, School of Geosciences, The University of Sydney, Australia

    R. Dietmar Müller - EarthByte Research Group, School of Geosciences, The University of Sydney, Australia. ORCID: 0000-0002-3334-5764

    Overview of Resources Contained

    This collection contains geological data from Australia used for data mining in the publications Merdith et al. (2013) and Landgrebe et al. (2013). The resulting maps of opal prospectivity are also included.

    List of Resources

    Note: For details on the files included in this data collection, see “Description_of_Resources.txt”.

    Note: For information on file formats and what programs to use to interact with various file formats, see “File_Formats_and_Recommended_Programs.txt”.

    • Map of Barfield region, Australia (.jpg, 270 KB)
    • Map overviewing the Great Artesian basins and main opal mining camps (.png, 82 KB)
    • Maps showing opal prospectivity data mining results for different geological datasets (.tif, 23.1 MB)
    • Map of opal prospectivity from palaeogeography data mining (.pdf, 2.6 MB)
    • Raster of palaeogeography target regions for viewing in Google Earth (.jpg, 418 KB)
    • Opal mine locations (.gpml, .txt, .kmz, .shp, total 15.6 MB)
    • Map of opal prospectivity from all data mining results as a Google Earth overlay (.kmz, 12 KB)
    • Map of probability of opal occurrence in prospective regions from all data mining results (.tif, 5.9 MB)
    • Paleogeography of Australia (.gpml, .txt, .shp, total 114.2 MB)
    • Radiometric data showing potassium concentration contrasts (.tif, .kmz, total 311.3 MB)
    • Regolith data (.gpml, .txt, .kml, .shp, total 7.1 MB)
    • Soil type data (.gpml, .txt, .kml, .shp, total 7.1 MB)

    For more information on this data collection, and links to other datasets from the EarthByte Research Group please visit EarthByte

    For more information about using GPlates, including tutorials and a user manual please visit GPlates or EarthByte

  4. d

    Data from: Mining the Mammalian Genome for Artiodactyl Systematics

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Apr 3, 2025
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    Conrad A. Matthee; Jay D. Burzlaff; Jeremy F. Taylor; Scott K. Davis (2025). Mining the Mammalian Genome for Artiodactyl Systematics [Dataset]. http://doi.org/10.5061/dryad.653
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Conrad A. Matthee; Jay D. Burzlaff; Jeremy F. Taylor; Scott K. Davis
    Time period covered
    Jan 1, 2009
    Description

    A total of 7806 nucleotide positions derived from one mitochondrial and eight nuclear DNA segments were used to provide a robust phylogeny for members of the order Artiodactyla. Twenty-four artiodactyl and two cetacean species were included and the horse, order Perissodactyla, was used as the outgroup. Limited rate heterogeneity was observed among the nuclear genes. The partition homogeneity tests indicated no conflicting signal among the nuclear gene fragments and the sequence data were analyzed together and as separate loci. Analyses based on the individual nuclear DNA fragments, and 34 unique indels, all produced phylogenies largely congruent with the topology from the combined data set. In sharp contrast to the nuclear DNA data, the mtDNA cytochrome b sequence data showed high levels of homoplasy, failed to produce a robust phylogeny, and were remarkably sensitive to taxon sampling. The nuclear DNA data clearly support the paraphyletic nature of the Artiodactyla. Additionally, the f...

  5. D

    Mine Refuge Chambers Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 5, 2024
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    Dataintelo (2024). Mine Refuge Chambers Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/mine-refuge-chambers-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Oct 5, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Mine Refuge Chambers Market Outlook



    The global mine refuge chambers market size was valued at approximately $XX billion in 2023 and is projected to reach $XX billion by 2032, growing at a compound annual growth rate (CAGR) of X.X% during the forecast period. The significant growth factor driving this market is the increasing focus on mine safety regulations across various countries, aiming to enhance the safety and security of mine workers.



    One of the pivotal growth factors for the mine refuge chambers market is the stringent regulatory environment set by governments and international organizations, emphasizing miners' safety. Multiple incidents of mine collapses and other hazards in the past have led to heightened awareness and increased stringent regulations. As a result, mining companies are investing significantly in advanced safety equipment, including refuge chambers, to ensure compliance and safeguard their workers. The technological advancements in mine refuge chambers, such as improved materials, better life-support systems, and enhanced communication capabilities, have also contributed to the growing adoption of these systems.



    Furthermore, the rise in mining activities worldwide, driven by the increasing demand for minerals and metals, plays a crucial role in market growth. The expanding use of electronic devices, renewable energy sources, and the construction industry has led to a surge in demand for various mined materials. Consequently, mining activities have intensified, leading to an increased focus on safety measures to protect miners. Investment in mine refuge chambers is seen as a necessary expenditure to maintain operational continuity and worker safety, thereby driving market expansion.



    In addition, the increasing implementation of automation and smart mining technologies is another significant driver for market growth. Modern mining operations are integrating sophisticated technologies to monitor and manage mine safety more efficiently. Mine refuge chambers are becoming more advanced with real-time monitoring systems, automated alerts, and better integration with overall mine safety systems. This technological progression not only enhances the functionality of refuge chambers but also drives their adoption in mines globally.



    Regionally, the market dynamics and growth trends vary significantly. For instance, in regions with a high density of mining activities like Asia Pacific, North America, and Latin America, the demand for mine refuge chambers is higher due to the stringent safety regulations and the larger number of operating mines. In contrast, regions with fewer mining activities may witness slower adoption rates. However, the overall global trend indicates a positive growth trajectory due to the universal emphasis on mining safety and the increasing implementation of advanced mining technologies.



    Product Type Analysis



    In terms of product types, the mine refuge chambers market is segmented into portable refuge chambers and stationary refuge chambers. Portable refuge chambers are designed to be easily moved and relocated within the mine, providing flexibility and adaptability to changing work environments. They are particularly beneficial in mines with dynamic operational zones where mobility is crucial. The growth of portable refuge chambers is driven by their versatility and ease of deployment, making them a preferred choice in both coal and metal mining operations. Additionally, advancements in lightweight materials and compact designs have enhanced the portability and functionality of these chambers.



    On the other hand, stationary refuge chambers are typically installed in fixed locations within a mine, offering a more permanent solution for miner safety. These chambers are often equipped with more extensive life-support systems, including oxygen supplies, food, water, and communication tools, to sustain miners for extended periods. Stationary refuge chambers are commonly used in large-scale mining operations where specific areas are designated as safe zones. The demand for stationary refuge chambers is driven by their robustness and comprehensive safety features, making them essential in deeper and more hazardous mining environments.



    The choice between portable and stationary refuge chambers depends largely on the specific mining operation's needs and the mine's layout. Some mining companies may opt for a combination of both types to ensure comprehensive coverage and optimal safety for their workers. The market for both types is expected to grow, driven by the overall increase in

  6. c

    Data from: Geochemical and mineralogical analyses of uranium ores from the...

    • s.cnmilf.com
    • data.usgs.gov
    • +2more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Geochemical and mineralogical analyses of uranium ores from the Hack II and Pigeon deposits, solution-collapse breccia pipes, Grand Canyon region, Mohave and Coconino Counties, Arizona, USA [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/geochemical-and-mineralogical-analyses-of-uranium-ores-from-the-hack-ii-and-pigeon-deposit
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States, Mohave County, Coconino County, Arizona
    Description

    This data release compiles the whole-rock geochemistry, X-ray diffraction, and electron microscopy analyses of samples collected from the uranium ore bodies of two mined-out deposits in the Grand Canyon region of northwestern Arizona - the Hack II and Pigeon deposits. The samples are grab samples of ore collected underground at each mine by the U.S. Geological Survey (USGS) during the mid-1980s, while each mine was active. The Hack II and Pigeon mines were remediated after their closure, so these data, analyses of samples in the archives of the USGS, are provided as surviving, although limited representations of these ore bodies. The Hack II and Pigeon deposits are similar to numerous other uranium deposits hosted by solution-collapse breccia pipes in the Grand Canyon region of northwest Arizona. The uranium-copper deposits occur within matrix-supported columns of breccia (a "breccia pipe") that formed by solution and collapse of sedimentary strata (Wenrich, 1985; Alpine, 2010). The regions north and south of the Grand Canyon host hundreds of solution-collapse breccia pipes (Van Gosen and others, 2016). Breccia refers to the broken rock that fills these features, and pipe refers to their vertical, pipe-like shape. The breccia pipes average about 300 ft (90 m) in diameter and can extend vertically for as much as 3,000 ft (900 m), from their base in the Mississippian Redwall Limestone to as stratigraphically high as the Triassic Chinle Formation. The breccia fragments are blocks and pieces of rock units that have fallen downward, now resting below their original stratigraphic level. In contrast to many other types of breccia pipes, there are no igneous rocks associated with the northwestern Arizona breccia pipes, nor have igneous processes contributed to their formation. Many of these breccia pipes contain concentrated deposits of uranium, copper, arsenic, barium, cobalt, lead, molybdenum, nickel, antimony, strontium, vanadium, and zinc minerals (Wenrich, 1985), which is reflected in this data set. The Hack II and Pigeon mines were two of thirteen breccia pipe deposits in the Grand Canyon region mined for uranium from the 1950s to present (2020) (Alpine, 2010; Van Gosen and others, 2016). While hundreds of breccia pipes in the region have been identified (Van Gosen and others, 2016), six decades of exploration across the region has found that most are not mineralized or substantially mineralized, and only a small percentage of the breccia pipes contain economic uranium deposits. The most recent mining operation in a breccia pipe deposit in the region is the Canyon mine, located about 6.1 miles (10 km) south-southeast of Tusayan, Arizona. In 2018, Energy Fuels completed a mine shaft and other mining facilities at the Canyon deposit, a copper- uranium-bearing breccia pipe (Van Gosen and others, 2020); however, this mining operation is currently (2020) inactive, awaiting higher market prices for uranium oxide. The Hack II deposit is one of four breccia pipes mined in Hack Canyon near its intersection with Robinson Canyon (Chenoweth, 1988; Otton and Van Gosen, 2010), approximately 30 miles (48 km) southwest of Fredonia and 9 miles (14.5 km) north-northwest of Kanab Creek. Hack Canyon incised and exposed part of the "Hacks" (or "Hack Canyon") breccia pipe, which was discovered and mined as a surface mine in the early 1900s for copper and silver. The original Hacks mine and adjacent Hack I deposit were later mined underground for uranium from 1950 to 1954 (Chenoweth, 1988). The Hack II deposit was discovered in the late 1970s along Hack Canyon about 1 mile (1.6 km) upstream of the Hacks and Hack I mines. The Hack II mine is located at latitude 36.58219 north, longitude -112.81059 west (datum of WGS84). Mining began at Hack II in 1981 and ended in May 1987. The USGS collected the ore samples reported in this data release in 1984 from underground exposures in the Hack II mine while it was in operation. Reclamation of the four mines in the area (Hacks, Hack I, Hack II, and Hack III) was planned and completed from March 1987 to April 1988, including infilling of the shafts and adits. Total production from the Hack II mine was reported as 7.00 million pounds (3.2 million kilograms) of uranium oxide from ore that had an average grade of 0.70 percent uranium oxide. This represents the largest uranium production from a breccia pipe deposit in the Grand Canyon region thus far (Otton and Van Gosen, 2010). The Pigeon mine was discovered along Kanab Creek in 1980. The site was prepared and developed from 1982 to 1984, and mining began in December 1984. The pipe was mined out in late 1989 and reclamation begun shortly thereafter. The former mine site is located at latitude 36.7239 north, longitude -112.5275 south (datum of WGS84). The Pigeon mine reportedly produced 5.7 million pounds (2.6 million kilograms) of ore that had an average grade of 0.65 percent uranium oxide. The five Pigeon deposit samples reported in this data release were collected by the USGS from underground exposures in the Pigeon mine in 1985, while the mine was in operation. Fourteen samples of Hack II ore and two samples of Pigeon ore were analyzed for major and trace elements by a laboratory contracted by the USGS. Concentrations for 59 elements were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Additionally, carbonate carbon (inorganic carbon), total carbon, total sulfur, iron oxide, and mercury concentrations were determined using other element-specific analytical techniques. These 16 samples and an additional four Hack II ore samples and three Pigeon ore samples were analyzed by X-ray diffraction (XRD) to determine their mineralogy. Polished thin sections cut from six of the Hack II ore samples were examined using a scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS) to identify the ore minerals and observe their relationships at high magnification. The EDS vendor's auto identification algorithm was used for peak assignments; the user did not attempt to verify every peak identification. The spectra for each EDS measurement are provided in separate documents in Portable Data Format (pdf), one document for each of the six samples that were examined by SEM-EDS. The interpreted mineral phase(s), which is based solely on the judgement of the user, is given below each spectrum. References cited above: Alpine, A.E., ed., 2010, Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, 353 p., 1 plate, scale 1:375,000. Available at http://pubs.usgs.gov/sir/2010/5025/ Chenoweth, W.L., 1988, The production history and geology of the Hacks, Ridenour, Riverview and Chapel breccia pipes, northwestern Arizona: U.S. Geological Survey Open-File Report 88-648, 60 p. Available at https://pubs.usgs.gov/of/1988/0648/report.pdf Otton, J.K., and Van Gosen, B.S., 2010, Uranium resource availability in breccia pipes in northern Arizona, in Alpine, A.E., ed., Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, p. 23-41. Available at http://pubs.usgs.gov/sir/2010/5025/ Van Gosen, B.S., Johnson, M.R., and Goldman, M.A., 2016, Three GIS datasets defining areas permissive for the occurrence of uranium-bearing, solution-collapse breccia pipes in northern Arizona and southeast Utah: U.S. Geological Survey data release, https://doi.org/10.5066/F76D5R3Z Van Gosen, B.S., Benzel, W.M., and Campbell, K.M., 2020, Geochemical and X-ray diffraction analyses of drill core samples from the Canyon uranium-copper deposit, a solution-collapse breccia pipe, Grand Canyon area, Coconino County, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9UUILQI Wenrich, K.J., 1985, Mineralization of breccia pipes in northern Arizona: Economic Geology, v. 80, no. 6, p. 1722-1735, https://doi.org/10.2113/gsecongeo.80.6.1722

  7. Portuguese Comparative Sentences: A Collection of Labeled Sentences on...

    • zenodo.org
    • live.european-language-grid.eu
    • +1more
    csv, json
    Updated Apr 19, 2021
    + more versions
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    Daniel Kansaon; Daniel Kansaon; Michele A. Brandão; Michele A. Brandão; Julio C. S. Reis; Julio C. S. Reis; Matheus Barbosa; Breno Matos; Fabrício Benevenuto; Fabrício Benevenuto; Matheus Barbosa; Breno Matos (2021). Portuguese Comparative Sentences: A Collection of Labeled Sentences on Twitter and Buscapé [Dataset]. http://doi.org/10.5281/zenodo.4124410
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    json, csvAvailable download formats
    Dataset updated
    Apr 19, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Daniel Kansaon; Daniel Kansaon; Michele A. Brandão; Michele A. Brandão; Julio C. S. Reis; Julio C. S. Reis; Matheus Barbosa; Breno Matos; Fabrício Benevenuto; Fabrício Benevenuto; Matheus Barbosa; Breno Matos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    More and more customers demand online reviews of products and comments on the Web to make decisions about buying a product over another. In this context, sentiment analysis techniques constitute the traditional way to summarize a user’s opinions that criticizes or highlights the positive aspects of a product. Sentiment analysis of reviews usually relies on extracting positive and negative aspects of products, neglecting comparative opinions. Such opinions do not directly express a positive or negative view but contrast aspects of products from different competitors.

    Here, we present the first effort to study comparative opinions in Portuguese, creating two new Portuguese datasets with comparative sentences marked by three humans. This repository consists of three important files: (1) lexicon that contains words frequently used to make a comparison in Portuguese; (2) Twitter dataset with labeled comparative sentences; and (3) Buscapé dataset with labeled comparative sentences.

    The lexicon is a set of 176 words frequently used to express a comparative opinion in the Portuguese language. In these contexts, the lexicon is aggregated in a filter and used to build two sets of data with comparative sentences from two important contexts: (1) Social Network Online; and (2) Product reviews.

    For Twitter, we collected all Portuguese tweets published in Brazil on 2018/01/10 and filtered all tweets that contained at least one keyword present in the lexicon, obtaining 130,459 tweets. Our work is based on the sentence level. Thus, all sentences were extracted and a sample with 2,053 sentences was created, which was labeled for three human manuals, reaching an 83.2% agreement with Fleiss' Kappa coefficient. For Buscapé, a Brazilian website (https://www.buscape.com.br/) used to compare product prices on the web, the same methodology was conducted by creating a set of 2,754 labeled sentences, obtained from comments made in 2013. This dataset was labeled by three humans, reaching an agreement of 83.46% with the Fleiss Kappa coefficient.

    The Twitter dataset has 2,053 labeled sentences, of which 918 are comparative. The Buscapé dataset has 2,754 labeled sentences, of which 1,282 are comparative.

    The datasets contain these labeled properties:

    • text: the sentence extracted from the review comment.

    • entity_s1: the first entity compared in the sentence.

    • entity_s2: the second entity compared in the sentence.

    • keyword: the comparative keyword used in the sentence to express comparison.

    • preferred_entity: the preferred entity.

    • id_start: the keyword's initial position in the sentence.

    • id_end: the keyword's final position in the sentence.

    • type: the sentence label, which specifies whether the phrase is a comparison.

    Additional Information:

    1 - The sentences were separated using a sentence tokenizer.

    2 - If the compared entity is not specified, the field will receive a value: "_".

    3 - The property "type" can contain five values, they are:

    • 0: Non-comparative (Não Comparativa).

    • 1: Non-Equal-Gradable (Gradativa com Predileção).

    • 2: Equative (Equitativa).

    • 3: Superlative (Superlativa).

    • 4: Non-Equal-Gradable (Não Gradativa).

    If you use this data, please cite our paper as follows:

    "Daniel Kansaon, Michele A. Brandão, Julio C. S. Reis, Matheus Barbosa,Breno Matos, and Fabrício Benevenuto. 2020. Mining Portuguese Comparative Sentences in Online Reviews. In Brazilian Symposium on Multimedia and the Web (WebMedia ’20), November 30-December 4, 2020, São Luís, Brazil. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3428658.3431081"

    --------------

    Plus Information:

    We make the raw sentences available in the dataset to allow future work to test different pre-processing steps. Then, if you want to obtain the exact sentences used in the paper above, you must reproduce the pre-processing step described in the paper (Figure 2).

    For each sentence with more than one keyword in the dataset:

    • You need to extract three words before and three words after the comparative keyword, creating a new sentence that will receive the existing value in the “type” field as a label;
    • The original sentence will be divided into n new sentences. (n) is the number of keywords in the sentence;
    • The stopwords should not be accounted for as part of this range (3 words);

    Note that: the final processed sentence can have more than six words because the stopwords are not counted as part of the range.

  8. D

    Cloud Mining Service Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Cloud Mining Service Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-cloud-mining-service-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Cloud Mining Service Market Outlook




    The global cloud mining service market size was valued at approximately USD 2.5 billion in 2023 and is expected to reach around USD 6.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% from 2024 to 2032. The market is primarily driven by the increasing adoption of cryptocurrencies and the growing need for decentralized financial systems. A significant growth factor is the rising inclination of individuals and enterprises toward digital currencies as an alternative investment, fueling the demand for cloud mining services.




    Advancements in blockchain technology and the burgeoning popularity of cryptocurrencies such as Bitcoin, Ethereum, and Litecoin have created a robust foundation for the cloud mining service industry. The ease of access to mining operations through cloud-based services has significantly lowered the entry barriers for many new miners. This is particularly appealing for those who may lack the requisite technical knowledge or resources to set up and maintain their own mining hardware. Additionally, the allure of potential high returns on investment in a relatively short period further propels market growth.




    Moreover, the global shift towards green and sustainable energy solutions is another driving factor for the cloud mining service market. Traditional mining operations are often criticized for their high energy consumption and carbon footprint. In contrast, many cloud mining service providers are now partnering with renewable energy firms or establishing data centers in regions with surplus renewable energy. This not only helps in reducing operational costs but also attracts a more environmentally conscious clientele, contributing to the overall market expansion.




    The increasing regulatory acceptance and government interest in blockchain technologies and cryptocurrencies are also fueling market growth. Governments across various regions are exploring and implementing regulatory frameworks that support the growth of cryptocurrencies, thereby legitimizing the mining industry. This regulatory clarity encourages new investments and innovations in the cloud mining service sector, providing a stable and secure environment for growth.




    Regionally, North America and Asia Pacific are expected to dominate the cloud mining service market. North America, particularly the United States, has seen substantial investments in blockchain and cryptocurrency technologies. Meanwhile, Asia Pacific, led by China and Japan, is witnessing rapid adoption of cryptocurrencies and significant technological advancements in blockchain infrastructure. Europe is also showing promising growth, driven by increased regulatory support and large-scale adoption of digital currencies. Latin America and the Middle East & Africa, though relatively nascent markets, are also projected to experience growth due to increasing awareness and investments in cryptocurrency mining.



    The role of Mining Servers Sales in this market cannot be understated. As the demand for cloud mining services grows, so does the need for efficient and powerful mining servers. These servers are the backbone of mining operations, providing the necessary computational power to solve complex algorithms and validate transactions on the blockchain. With advancements in server technology, companies are able to offer more efficient and cost-effective solutions, which in turn drives down the cost of cloud mining services. This has made mining more accessible to a wider audience, from individual hobbyists to large enterprises, further fueling the growth of the market.



    Service Type Analysis



    Hashrate Leasing




    Hashrate leasing is among the most popular types of cloud mining services. This model allows users to lease a portion of the computational power from a mining farm for a predetermined period. It offers both individual and enterprise clients the flexibility to scale their mining operations without the need for significant upfront investment in hardware. The ease of use and the relatively lower risk associated with leasing as compared to purchasing dedicated hardware have made hashrate leasing a preferred option among many market participants.




    The availability of various contract lengths and the ability t

  9. Mining RNA–Seq Data for Infections and Contaminations

    • plos.figshare.com
    pdf
    Updated Jun 1, 2023
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    Thomas Bonfert; Gergely Csaba; Ralf Zimmer; Caroline C. Friedel (2023). Mining RNA–Seq Data for Infections and Contaminations [Dataset]. http://doi.org/10.1371/journal.pone.0073071
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Thomas Bonfert; Gergely Csaba; Ralf Zimmer; Caroline C. Friedel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    RNA sequencing (RNA–seq) provides novel opportunities for transcriptomic studies at nucleotide resolution, including transcriptomics of viruses or microbes infecting a cell. However, standard approaches for mapping the resulting sequencing reads generally ignore alternative sources of expression other than the host cell and are little equipped to address the problems arising from redundancies and gaps among sequenced microbe and virus genomes. We show that screening of sequencing reads for contaminations and infections can be performed easily using ContextMap, our recently developed mapping software. Based on mapping–derived statistics, mapping confidence, similarities and misidentifications (e.g. due to missing genome sequences) of species/strains can be assessed. Performance of our approach is evaluated on three real–life sequencing data sets and compared to state–of–the–art metagenomics tools. In particular, ContextMap vastly outperformed GASiC and GRAMMy in terms of runtime. In contrast to MEGAN4, it was capable of providing individual read mappings to species and resolving non–unique mappings, thus allowing the identification of misalignments caused by sequence similarities between genomes and missing genome sequences. Our study illustrates the importance and potentials of routinely mining RNA–seq experiments for infections or contaminations by microbes and viruses. By using ContextMap, gene expression of infecting agents can be analyzed and novel insights in infection processes and tumorigenesis can be obtained.

  10. Mining Conveyor Belt Splicing Adhesive Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jul 14, 2025
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    Growth Market Reports (2025). Mining Conveyor Belt Splicing Adhesive Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/mining-conveyor-belt-splicing-adhesive-market
    Explore at:
    pptx, csv, pdfAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Mining Conveyor Belt Splicing Adhesive Market Outlook



    According to our latest research and analysis, the global Mining Conveyor Belt Splicing Adhesive Market size in 2024 stands at USD 543.6 million, with a robust year-on-year growth trajectory. The industry is forecasted to expand at a CAGR of 6.2% from 2025 to 2033, reaching an estimated USD 935.4 million by the end of the forecast period. This growth is being propelled by the increasing demand for efficient and durable conveyor systems in mining operations, coupled with advancements in adhesive technologies that enhance belt longevity and minimize downtime.




    The primary growth driver of the Mining Conveyor Belt Splicing Adhesive Market is the surge in mining activities globally, especially in emerging economies where infrastructure development and resource extraction are experiencing unprecedented growth. The expansion of mining operations necessitates the deployment of robust conveyor systems, which in turn fuels the demand for high-performance splicing adhesives. Additionally, the growing emphasis on operational efficiency and safety in mining environments has led to the adoption of advanced splicing solutions that ensure minimal interruptions and extended belt life. This shift towards high-quality adhesives is further supported by stringent regulatory standards mandating the use of reliable and environmentally compliant materials in mining processes.




    Another significant factor contributing to the market’s expansion is the continuous technological innovation in adhesive formulations. Manufacturers are investing heavily in research and development to create products that offer superior bonding strength, faster curing times, and enhanced resistance to harsh mining conditions such as extreme temperatures, moisture, and abrasion. The introduction of cold and hot vulcanizing adhesives with improved performance characteristics has revolutionized conveyor belt maintenance, enabling mining companies to achieve greater productivity and cost savings. Furthermore, the integration of eco-friendly and low-VOC adhesives aligns with the global sustainability trend, encouraging wider adoption across the mining sector.




    The market is also benefiting from the increasing automation and digitalization of mining operations. The adoption of smart conveyor systems, equipped with sensors and real-time monitoring capabilities, necessitates the use of reliable splicing adhesives that can withstand high operational loads and provide long-term stability. As mining companies strive to reduce downtime and maintenance costs, the demand for innovative splicing solutions that offer quick application and superior durability is expected to rise. These technological advancements, combined with the expansion of mining activities in untapped regions, are set to drive the market forward over the next decade.




    From a regional perspective, Asia Pacific dominates the Mining Conveyor Belt Splicing Adhesive Market, accounting for over 38% of the global market share in 2024. This is primarily due to the extensive mining operations in countries like China, India, and Australia, where the demand for coal, metals, and minerals remains high. North America and Europe follow closely, with substantial investments in mining infrastructure and a strong focus on technological innovation. In contrast, Latin America and the Middle East & Africa are emerging as lucrative markets, driven by increasing exploration activities and favorable government policies promoting mining sector growth. The regional outlook suggests a balanced growth pattern, with each region contributing significantly to the overall market expansion.





    Product Type Analysis



    The Product Type segment of the Mining Conveyor Belt Splicing Adhesive Market encompasses cold vulcanizing adhesive, hot vulcanizing adhesive, and other specialized adhesive solutions. Cold vulcanizing adhesives have gained substantial traction due to their ease of application, rapid c

  11. D

    Landfill Mining Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Landfill Mining Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-landfill-mining-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Dec 3, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Landfill Mining Market Outlook



    The global landfill mining market size is set to experience significant growth, with an estimated valuation of USD 3.5 billion in 2023 and is projected to reach approximately USD 6.7 billion by 2032, reflecting a robust CAGR of 7.3% over the forecast period. This growth is primarily driven by the increasing awareness regarding sustainable waste management and the potential resource recovery inherent in landfill sites. With the depletion of natural resources and the increasing cost of raw materials, landfill mining offers a strategic advantage by extracting valuable materials, thereby promoting a circular economy. Moreover, technological advancements in excavation and separation technologies are further enhancing the feasibility and efficiency of landfill mining operations.



    The rising global population and urbanization have led to an exponential increase in waste generation, thereby escalating the demand for effective waste management solutions. Landfills, which historically have been the primary method of waste disposal, are now being revisited not only as waste disposal sites but as potential mines for valuable resources. This shift is bolstered by the growing realization of the economic benefits of recovering metals, plastics, and other materials from landfills. Simultaneously, the global emphasis on reducing the carbon footprint and achieving net-zero targets is encouraging the development of landfill mining projects, as they contribute to reduced environmental impact by minimizing the need for new landfills and promoting recycling and material recovery.



    Government policies and regulatory frameworks are playing a significant role in the growth of the landfill mining market. Many nations are implementing stringent regulations on waste management and recycling to mitigate the adverse environmental impact of traditional landfill systems. Incentives and subsidies for landfill mining projects are being provided to encourage private sector participation and investment. Additionally, international organizations are advocating for sustainable waste management practices, further catalyzing the adoption of landfill mining. These regulatory and policy frameworks are expected to provide a conducive environment for the landfill mining market, facilitating its expansion over the coming years.



    Technological advancements are another critical factor driving the growth of the landfill mining market. Innovations in excavation, screening, and separation technologies have made it possible to efficiently extract and process valuable materials from landfills. New methods that combine artificial intelligence and machine learning are being developed to accurately identify and separate recyclable materials, enhancing the recovery rates and economic viability of landfill mining operations. Moreover, the integration of renewable energy sources into landfill mining processes is improving the sustainability and reducing the overall carbon footprint of these projects. As technology continues to evolve, it will further unlock the potential of landfill mining, driving market growth.



    Regionally, the landfill mining market exhibits varied dynamics. Developed regions such as North America and Europe, with their stringent environmental regulations and advanced waste management infrastructures, are leading the charge in landfill mining initiatives. In contrast, emerging economies in Asia Pacific and Latin America are increasingly exploring landfill mining as a viable solution to their burgeoning waste management challenges. These regions are witnessing significant investments in waste management infrastructure, driven by rapid urbanization and industrialization. The Middle East & Africa region, with its vast deserts and limited landfill space, is also gradually recognizing the potential of landfill mining, though at a relatively slower pace compared to other regions.



    Technology Analysis



    The technology segment of the landfill mining market is comprised of various methods that facilitate the extraction of valuable materials from landfill sites. Excavation is the foundational technology that initiates the process of landfill mining. It involves digging up the waste material, which can then be subjected to further processing. The effectiveness of excavation technologies is paramount as it sets the stage for subsequent processes. Companies are investing in the development of advanced excavation machinery that can efficiently and safely remove waste material without causing significant disturbance to the surrounding environment. These innovations are focused on increasing the speed and reducing the cost of exca

  12. s

    RB 79/00029 Managing mineral exploration and mining. - Document - SARIG...

    • pid.sarig.sa.gov.au
    Updated Nov 6, 2024
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    (2024). RB 79/00029 Managing mineral exploration and mining. - Document - SARIG catalogue [Dataset]. https://pid.sarig.sa.gov.au/dataset/rb7900029
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    Dataset updated
    Nov 6, 2024
    Description

    It is appropriate for a paper on exploration and mining to be included in a conference concerned with conservation because mineral and energy resources have similar unique properties to the other natural and cultural features listed in this... It is appropriate for a paper on exploration and mining to be included in a conference concerned with conservation because mineral and energy resources have similar unique properties to the other natural and cultural features listed in this programme. However, the inherent potential of mineral extraction to create visual impact and to disturb or destroy other valuable natural resources contrasts sharply with many of the objectives of the conservation movement. Society is faced with finding a solution to the dilemma of the need to maintain a continuing supply of essential mineral and energy products and the equally necessary task of protecting those other natural features who value lies in their remaining in an undisturbed state. How can we resolve the conflicting needs of the mining industry to supply the mineral consuming public, with the aims and expectations of the conservation movement? Resolution of this problem depends initially on an understanding of the technical limitations that influence the manner in which mineral exploration and production are conducted. The authors have become aware that many concerned conservationists are not fully acquainted with these limitations or of the techniques used by modern explorers in the search for concealed orebodies. This paper, and the illustrations presented in the appendix, sets out to establish the technical and legal framework within which the mineral industry fulfils its vital role of maintaining an uninterrupted supply of essential mineral products.

  13. D

    ASIC Bitcoin Mining Hardware Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). ASIC Bitcoin Mining Hardware Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-asic-bitcoin-mining-hardware-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    ASIC Bitcoin Mining Hardware Market Outlook



    The ASIC Bitcoin Mining Hardware market is set to witness significant growth, with the market size projected to expand from USD 1.5 billion in 2023 to approximately USD 2.9 billion by 2032, at a compound annual growth rate (CAGR) of around 7.5%. This growth is driven by the increasing demand for efficient and effective mining solutions in the cryptocurrency sector, as ASICs (Application-Specific Integrated Circuits) offer higher performance and energy efficiency compared to traditional mining hardware. The growth of the cryptocurrency market and the increasing recognition of digital currencies as a legitimate investment avenue are pivotal factors contributing to this market's expansion. Additionally, technological advancements in ASIC design and manufacturing are propelling the market forward as they enable miners to achieve higher hash rates while minimizing power consumption.



    One of the primary growth drivers in the ASIC Bitcoin Mining Hardware market is the rising value and acceptance of Bitcoin and other cryptocurrencies. As cryptocurrencies become more mainstream, the profitability of mining operations has increased, encouraging both individuals and enterprises to invest in advanced mining hardware. Furthermore, as Bitcoin's price continues to rise, the competition among miners grows, necessitating more efficient hardware to maintain profitability. This has led to an increased demand for ASICs, which are more efficient and effective than traditional mining methods. The increasing number of transactions and the necessity for blockchain validation continue to fuel the expansion of the ASIC mining hardware market.



    Another significant factor bolstering the market is the continuous innovation and technological advancements in ASIC hardware manufacturing. Manufacturers are focusing on enhancing the efficiency of these circuits, allowing for higher hash rates and reduced power consumption. This not only improves the overall efficiency of mining operations but also reduces the environmental impact, addressing growing concerns over the energy-intensive nature of cryptocurrency mining. Moreover, the integration of advanced cooling systems and improved chip designs has significantly increased the lifespan and performance reliability of ASIC miners, attracting more investments from enterprises looking to optimize their mining operations.



    Furthermore, the regulatory landscape surrounding cryptocurrency mining is evolving, with several countries recognizing the potential economic benefits of fostering a healthy mining ecosystem. Governments in regions such as North America and parts of Europe are implementing favorable regulations and offering incentives for mining operations that utilize energy-efficient technology. This supportive regulatory environment is expected to boost the demand for ASIC Bitcoin Mining Hardware, as enterprises aim to align with sustainable and compliant mining practices. As regulatory frameworks continue to mature, they are likely to provide more clarity and stability, encouraging further investments in this market.



    In the evolving landscape of cryptocurrency mining, the concept of a Bitcoin Pooling Platform has emerged as a significant innovation. These platforms allow individual miners to combine their computational resources, enhancing their chances of successfully mining a block and receiving rewards. By pooling resources, miners can achieve more consistent earnings, as the rewards are distributed among participants based on their contributed hash power. This collaborative approach not only democratizes access to mining rewards but also helps smaller miners compete with larger operations. As the mining difficulty continues to increase, Bitcoin Pooling Platforms are becoming an essential tool for miners seeking to optimize their operations and ensure profitability in a competitive market.



    The regional outlook for the ASIC Bitcoin Mining Hardware market indicates that Asia Pacific is currently the dominant region, driven by the presence of major ASIC manufacturers in China and increased mining activities across the region. North America is also witnessing rapid growth, particularly in the United States, where favorable regulations and abundant renewable energy sources are attracting significant investments in mining infrastructure. Europe, while trailing behind, is expected to experience steady growth due to increasing acceptance of cryptocurrencies and supportive government policies. In contrast, Latin America and the Middle East & Africa are i

  14. Bauxite Mining in Australia - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Sep 26, 2023
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    IBISWorld (2023). Bauxite Mining in Australia - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/au/industry/bauxite-mining/66/
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    Dataset updated
    Sep 26, 2023
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2013 - 2028
    Area covered
    Australia
    Description

    Australia is the world's largest bauxite producer, accounting for approximately 30% of global output, ahead of China, Guinea and Brazil. For over a decade up until 2019-20, bauxite production in Australia had been growing steadily, peaking at 107.2 million tonnes in the 2019-20 financial year. Expansion projects at several bauxite mines contributed to this strong growth in production, increasing mine output to meet higher demand. However, a combination of weakened global demand, falling prices and slowed expansion activity have contributed to production volumes contracting in recent years, totalling 99.8 million tonnes in 2022-23. Production volumes and prices are anticipated to improve in 2023-24 as demand from China recovers. Overall, industry-wide revenue is expected to fall at an annualised 5.9% over the five years through 2023-24 to $3.2 billion, including an estimated 7.1% jump in 2023-24. Weaker demand and lower revenue have also squeezed industry profit margins. While most bauxite mined in Australia is locally processed into alumina, exports account for a high and increasing share of industry revenue. In contrast, competing bauxite imports are negligible. A small number of firms operate or develop bauxite mines in Australia. Rio Tinto, Alcoa and South32 are major multinational companies that use a high proportion of bauxite for their own alumina-refining operations. On the other hand, Metro Mining exports all of its bauxite to refineries in China. While some small bauxite exploration and development companies are exploring new mining sites, only a couple have started mining operations, with the others still in the development stage. The performance of the Bauxite Mining industry is on track to improve over the coming years. The gradual recovery of the Chinese economy from the COVID-19 pandemic will support rebounding demand for bauxite. Bauxite prices are set to increase thanks to climbing global demand. However, global production growth and a strengthening Australian dollar in US dollar terms will constrain bauxite price growth for Australian bauxite miners. Industry revenue is forecast to grow at an annualised 3.5% over the five years through 2028-29 to total $3.8 billion.

  15. f

    Data from: Prediction of Photochromism of Salicylideneaniline Crystals Using...

    • acs.figshare.com
    zip
    Updated Dec 23, 2023
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    Shodai Hasebe; Kan Hatakeyama-Sato; Kenichi Oyaizu; Toru Asahi; Hideko Koshima (2023). Prediction of Photochromism of Salicylideneaniline Crystals Using a Data Mining Approach [Dataset]. http://doi.org/10.1021/acsomega.3c07859.s002
    Explore at:
    zipAvailable download formats
    Dataset updated
    Dec 23, 2023
    Dataset provided by
    ACS Publications
    Authors
    Shodai Hasebe; Kan Hatakeyama-Sato; Kenichi Oyaizu; Toru Asahi; Hideko Koshima
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    Salicylideneanilines (SAs) are photochromic compounds that undergo enol–keto photoisomerization in the solid state. Research over the past 60 years has revealed empirically that SAs with steric and planar conformations tend to be photochromic and nonphotochromic, respectively. However, increasing counterexamples in the recent literature raise questions about the nature of the relationship between structure and photochromism in SA crystals and whether the photochromism of SA crystals is predictable. This study is the first to construct a data set on SA crystals and conduct a comprehensive analysis to investigate the relationship between molecular and crystal structures and photochromism. A data mining approach revealed that the dihedral angle is the most dominant structural parameter for photochromism, followed by the Hirshfeld surface volume. SAs with neutral bulky hydrocarbon groups, such as the tert-butyl group, tend to be photochromic because such SAs have steric conformation and a loosely packed structure. In contrast, SAs with fluorine, pyridine, and pyrazine are less likely to be photochromic due to their planar conformation and densely packed structures. The photochromism of the SA crystals in our data set was predicted with high accuracy (>85%) using machine learning. The results of this study provide a useful reference for designing SA crystals with desired photochromic properties.

  16. D

    Nickel Mining Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 4, 2024
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    Dataintelo (2024). Nickel Mining Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-nickel-mining-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Dec 4, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Nickel Mining Market Outlook



    As of 2023, the global nickel mining market size has been estimated to be approximately USD 38 billion, with a forecasted surge to around USD 51 billion by 2032, reflecting a compound annual growth rate (CAGR) of 3.3%. This market expansion is primarily driven by the burgeoning demand for nickel in various industrial applications, most notably in stainless steel production and electric vehicle (EV) batteries. The growth of this market is underpinned by the increasing emphasis on sustainable and renewable energy sources, alongside technological advancements in mining techniques that have improved efficiency and reduced operational costs. As industries worldwide pivot towards greener alternatives, nickel, known for its durability and corrosion resistance, plays a pivotal role in the transition towards sustainable development.



    One of the key growth factors for the nickel mining market is the exponential rise in the production and sales of electric vehicles. Nickel is an essential component of lithium-ion batteries, which are extensively used in electric vehicles. With governments worldwide implementing stringent regulations to curb carbon emissions and promote electric mobility, the demand for nickel is expected to witness substantial growth. The automotive industry, in particular, is undergoing a significant transformation as manufacturers innovate to produce more efficient, longer-lasting batteries, where nickel's high energy density makes it an invaluable resource. This shift towards electrification not only propels the demand for nickel but also encourages investments in mining operations to ensure the steady supply of this critical metal.



    Additionally, the stainless steel industry continues to be a major consumer of nickel, accounting for a considerable share of the market demand. Nickel is integral to stainless steel production, imparting strength, luster, and corrosion resistance to the metal. The construction and infrastructure sectors are substantial drivers of stainless steel demand, given the material's application in building frameworks, facades, and other structural components. As global urbanization trends persist, particularly in emerging economies, the construction industry's growth is expected to contribute significantly to the continuous demand for nickel. Furthermore, the ongoing recovery and expansion of industrial activities post the COVID-19 pandemic have rejuvenated the demand for stainless steel, thereby bolstering the nickel mining market.



    Furthermore, technological advancements in mining techniques have played a crucial role in the growth of the nickel mining market. Improved technologies in exploration and extraction processes have enhanced the efficiency and reduced the environmental impact of mining operations. Innovations such as automated drilling, remote sensors, and real-time data analytics allow for more precise and efficient mining, minimizing waste and optimizing resource extraction. These technological strides not only make mining operations more sustainable but also economically viable, attracting further investments into the sector. Additionally, the development of more environmentally-friendly methods, such as bioleaching, which uses microorganisms to extract nickel, represents a significant leap towards sustainable mining practices.



    Regionally, Asia Pacific stands out as a major hub for nickel mining activities, driven by rapid industrialization and economic growth in countries like China and Indonesia. These nations are not only leading producers of nickel but also major consumers, especially in the stainless steel and battery manufacturing industries. North America and Europe also represent significant markets, with a focus on sustainable mining practices and technological innovation. In contrast, Latin America and the Middle East & Africa are emerging regions with untapped reserves and increasing foreign investments in mining projects, showcasing potential for future growth.



    Mining Technique Analysis



    The nickel mining market is predominantly divided into two major mining techniques: underground mining and open-pit mining. Each technique has its own set of advantages and challenges, influencing the choice of method based on several factors such as ore depth, environmental impact, and cost-effectiveness. Underground mining involves extracting nickel ores located deep beneath the earth's surface. This technique is preferred when ore bodies are located at considerable depths or in areas where surface mining is not feasible. Underground mining is characterized by its ability to access deeper deposits with minimal surf

  17. D

    Mine Design Software Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Mine Design Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-mine-design-software-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Mine Design Software Market Outlook



    The global mine design software market size is projected to witness a significant expansion, with an estimated value of USD 1.3 billion in 2023 to a forecasted USD 2.5 billion by 2032, reflecting a robust CAGR of 7.5%. This growth is propelled by the increasing demand for efficient and cost-effective mining operations worldwide. As the industry strives to enhance productivity, reduce operational costs, and ensure safety, the adoption of advanced software solutions that facilitate better planning and management of mining activities becomes critical. The integration of modern technologies such as AI, IoT, and big data analytics into these software solutions is also driving the market forward, enabling more dynamic and precise mining operations.



    One of the primary growth factors fueling the mine design software market is the escalating need for resource optimization and waste reduction in mining operations. Mining companies are under constant pressure to maximize resource extraction while minimizing environmental impact, thus necessitating the use of sophisticated software solutions. These tools help in detailed mapping, planning, and simulation of mining operations, ensuring optimal resource use and adherence to environmental regulations. Furthermore, the growing number of mining exploration activities in untapped regions is creating a demand for advanced software that can handle complex geological data and assist in efficient mine design.



    Technological advancements in the mining industry are another significant factor contributing to the growth of the mine design software market. The integration of cutting-edge technologies such as machine learning, artificial intelligence, and digital twin technology into mine design software is revolutionizing the way mining operations are conducted. These technologies enable predictive analysis, real-time monitoring, and automation, which not only enhance operational efficiency but also improve safety standards. The rise in digital transformation initiatives across the mining sector is further pushing the adoption of advanced software solutions, thereby driving market growth.



    The increasing focus on sustainability and safety is also playing a crucial role in the expansion of the mine design software market. There is a growing emphasis on ensuring safety and reducing the human workforce's exposure to hazardous mining environments. Mine design software allows for precise planning and simulation, which helps in identifying potential risks and planning mitigation strategies effectively. Additionally, the software supports compliance with stringent safety regulations and standards, which are becoming increasingly vital as the mining industry shifts towards more sustainable practices.



    Process Mining Software is becoming increasingly relevant in the mining industry as companies seek to optimize their operations and improve efficiency. This type of software allows mining companies to analyze their processes in real-time, identifying bottlenecks and inefficiencies that can be addressed to enhance productivity. By leveraging process mining software, companies can gain valuable insights into their operational workflows, enabling them to make data-driven decisions that lead to improved resource management and cost savings. As the industry continues to embrace digital transformation, the integration of process mining software is set to play a pivotal role in driving operational excellence and achieving sustainable growth.



    Regionally, the Asia Pacific region is expected to dominate the mine design software market during the forecast period, driven by the rapid industrialization and urbanization in countries such as China and India. The abundance of mineral resources and the growing investments in mining sector infrastructure are further fueling market growth in this region. Meanwhile, North America and Europe are anticipated to witness steady growth due to the presence of established mining companies and the increasing adoption of advanced technologies. In contrast, regions like Latin America and the Middle East & Africa are emerging as key markets due to the rising exploration activities and investments in mining projects.



    Component Analysis



    When examining the mine design software market by component, the software segment is poised to hold a substantial share. This segment primarily includes advanced software solutions designed for modeling, designing, and managing mini

  18. D

    Off Highway Dump Truck Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Oct 16, 2024
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    Dataintelo (2024). Off Highway Dump Truck Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/off-highway-dump-truck-market
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    pptx, csv, pdfAvailable download formats
    Dataset updated
    Oct 16, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Off Highway Dump Truck Market Outlook



    The global off-highway dump truck market size was valued at approximately USD 12.5 billion in 2023 and is projected to reach USD 18.6 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 4.5% during the forecast period. This market's growth is driven by the increasing demand in construction and mining industries, innovations in engine technologies, and the rising focus on infrastructure development worldwide.



    The growth of the off-highway dump truck market is majorly propelled by the surge in construction activities across the globe. Rapid urbanization and industrialization, especially in emerging economies, have led to a significant rise in infrastructure projects. This boom in construction has subsequently increased the demand for efficient, high-capacity dump trucks that can handle large volumes of construction materials. Governments' initiatives on infrastructural development further contribute to this rising demand, with several large-scale projects set to commence or complete within the forecast period.



    Another crucial factor driving the off-highway dump truck market is the robust growth witnessed in the mining sector. As global demand for minerals and metals continues to rise, mining operations are expanding, necessitating the use of durable and high-performance dump trucks. These vehicles are essential for transporting materials in harsh and uneven terrains, making them indispensable in mining operations. Technological advancements in the manufacturing of these trucks, such as improved engine performance and enhanced fuel efficiency, also play a significant role in supporting market growth.



    The agriculture sector, although a smaller segment compared to construction and mining, also contributes to the market's expansion. Off-highway dump trucks are used for various agricultural activities, including the transportation of harvested crops and other materials. With the increasing trend of mechanization in agriculture to improve productivity and efficiency, the demand for specialized heavy-duty vehicles like dump trucks is likely to grow. Additionally, the adoption of electric and hybrid dump trucks in agriculture can reduce operational costs, providing a further boost to market growth.



    Regionally, the Asia Pacific region dominates the off-highway dump truck market owing to rapid industrialization and urbanization in countries such as China and India. These countries are witnessing substantial investments in infrastructure, mining, and industrial projects, which in turn drive the demand for off-highway dump trucks. North America and Europe are also significant markets due to high investments in mining and construction activities. In contrast, the market in the Middle East & Africa is poised for growth due to increasing infrastructural development and mining activities in the region, supported by governmental investments and international collaborations.



    Engine Type Analysis



    When examining the off-highway dump truck market by engine type, it is clear that diesel-powered trucks have traditionally dominated the market. Diesel engines are preferred due to their high torque and power, which are critical for handling the heavy loads and challenging terrains commonly encountered in construction and mining activities. These engines offer durability and reliability, making them suitable for long-term operations in harsh conditions. However, despite their advantages, diesel engines face growing scrutiny due to environmental concerns and stringent emission regulations being enforced globally.



    Electric dump trucks have emerged as a promising segment within the off-highway dump truck market. The adoption of electric trucks is driven by the need for sustainability and reduction in carbon emissions. Electric engines offer the advantage of lower operational costs, reduced noise pollution, and compliance with stringent emission norms. Technological advancements in battery technology are making electric dump trucks more viable for heavy-duty applications. Companies are increasingly investing in electric truck models to cater to the rising demand for environmentally friendly alternatives, signaling a shift towards greener solutions in the market.



    Hybrid dump trucks represent a middle ground between traditional diesel engines and electric powertrains. These trucks combine the benefits of both engine types, offering improved fuel efficiency and reduced emissions without compromising on power and performance. Hybrid dump trucks are gaining traction in the market as they

  19. D

    Plow Bolts Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Plow Bolts Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-plow-bolts-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Dec 3, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Plow Bolts Market Outlook



    The global plow bolts market size was estimated at USD 550 million in 2023 and is anticipated to reach USD 870 million by 2032, growing at a CAGR of 5.1% during the forecast period. The steady growth in this market can be attributed to the burgeoning demand from the agriculture, construction, and mining sectors, which require durable and reliable fastening solutions. Plow bolts, known for their unparalleled strength and resistance to harsh environmental conditions, have become indispensable in these industries. As technological advancements continue to enhance the functionality and application of plow bolts, market growth is further propelled by the rising investment in infrastructure projects and the modernization of agricultural practices globally.



    A significant growth factor for the plow bolts market is the increased mechanization and automation in the agriculture sector. The global population is expected to reach nearly 9 billion by 2050, pushing the demand for efficient agricultural practices to ensure food security. As a result, the adoption of advanced farming machinery that relies on robust components like plow bolts is witnessing a significant uptick. Additionally, with governments in developing countries prioritizing agricultural productivity through subsidies and technological integration, the demand for high-strength bolts to support heavy machinery is set to rise. The shift toward sustainable agriculture, which incorporates advanced machinery, further validates the essential role of plow bolts in this evolving landscape.



    Another vital growth driver in the plow bolts market is the construction industry, which is experiencing exponential growth due to rapid urbanization and industrialization. According to the Global Construction 2030 report, the volume of construction output is projected to grow by 85% to USD 15.5 trillion worldwide by 2030. This growth necessitates high-performance components such as plow bolts for the assembly of construction machinery and equipment. The increasing demand for infrastructure development in emerging economies, coupled with the renovation and maintenance of existing structures in developed regions, significantly augments the market demand for plow bolts. Moreover, advancements in construction technologies that demand high-precision components further elevate the need for superior quality fastening solutions.



    In the mining sector, the necessity for durable and resilient components is paramount due to the challenging operating environments. Plow bolts are crucial in mining equipment, such as earthmovers and excavators, due to their ability to withstand immense stress and abrasion. The global mining industry, estimated to grow at a CAGR of 6% from 2024 to 2032, continues to expand driven by increasing demand for minerals and resources. This expansion directly correlates with the demand for high-strength fastening solutions capable of ensuring the longevity and efficiency of mining equipment. The ongoing exploration of untapped mineral reserves and increased investment in mining operations in regions such as Africa and Latin America further contribute to the robust demand for plow bolts.



    Regionally, the Asia Pacific is expected to dominate the plow bolts market, driven by massive investments in infrastructure and the expansion of agricultural operations. North America and Europe are also significant markets due to their advanced agricultural practices and robust construction activities. In contrast, the growing mining sector in regions such as Latin America and Africa presents lucrative opportunities for market expansion. As these regions continue to receive foreign investments aimed at mining exploration and infrastructure development, the demand for high-grade plow bolts is anticipated to witness strong growth.



    Product Type Analysis



    The plow bolts market is segmented by product type into flat head, dome head, countersunk head, and others, each serving distinct applications across various industries. Flat head plow bolts, characterized by their simple design and ease of installation, are predominantly used in applications where a flush surface is required. This makes them ideal for agricultural equipment, where minimizing soil disruption is crucial. The construction industry also favors flat head bolts for their structural applications, ensuring stability and strength. The demand for flat head plow bolts is expected to remain strong, thanks to their versatility and widespread applicability across sectors.



    Dome head plow bolts, on the other hand, are valued for their excellent load distribution char

  20. s

    Data release [made at SA Director of Mines' discretion] : Bremer. Progress...

    • pid.sarig.sa.gov.au
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    Data release [made at SA Director of Mines' discretion] : Bremer. Progress reports and annual reports to licence expiry/renewal, for the period 8/3/1991 to 7/3/1995. [ Index Part 1 of 3 ]. [Dataset]. https://pid.sarig.sa.gov.au/dataset/mesac24685
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    Description

    Exploration of an extensive area lying to the north of and surrounding Strathalbyn, 40 km south-east of Adelaide, is targeting possible economic stratiform base and precious metals mineralisation hosted within the Cambrian Kanmantoo Group... Exploration of an extensive area lying to the north of and surrounding Strathalbyn, 40 km south-east of Adelaide, is targeting possible economic stratiform base and precious metals mineralisation hosted within the Cambrian Kanmantoo Group metasediments/metavolcanics. Work commenced with a lengthy review of available geoscientific information for the region, with an emphasis on past stream sediment sampling geochemical data. An inspection and grab sampling of the rocks hosting historic old metals mines in the district identified the abandoned Strathalbyn mine environs as having the best potential for harbouring untested stratiform base metal mineralisation. Geological mapping and rock chip sampling undertaken in this area yielded very encouraging petrological and lead isotope geochemical results. A review and reprocessing of past aeromagnetic data, looking for magnetic stratal trends in the vicinity of known base metal, principally copper sulphide occurrences, reinforced Aberfoyle's evolving exploration concept of seeking to test previously inadequately explored geophysical and geochemical anomalies having what appeared to be thinly bedded quartz-gahnite meta-exhalite and banded iron formation rocks outcropping nearby. The lead isotope ratios of a number of significant Kanmantoo Trough base metal sulphide ore occurrences were shown to be homogeneous, and are consistent with a mid-Cambrian age of crystallization, while the absence of sulphur isotopic fractionation in the chalcopyrite of the region's abundant small copper occurrences was taken as evidence that these copper lodes may occupy footwall hydrothermal feeders to stratiform lead-zinc exhalative mineralisation. When considered together, the above factors seemed to enhance observed geological affinities with the Broken Hill deposit sedex ore genetic model, despite the host sediments' age difference. During December 1991, while surface prospecting for any evidence of southerly extensions to the apparently southwards-plunging Strathalbyn mine Pb-Ag lode, Aberfoyle's chief geologist Stephen Toteff discovered a 30 m wide zone of weakly gossanous garnetite that is exposed in a low cutting on the Callington Road, just east of Strathalbyn township. His further prospecting led to the nearby discovery, along strike, of a 45 m wide zone of float fragments of gossan and ferruginous quartz-gahnite-garnet rocks scattered next to the northern bank of the Strathalbyn Council sewage farm effluent ponds. Sporadic narrow eastwards-dipping outcrops of these rocks were next found, extending northwards for about 200 m before disappearing under Tertiary ferricrete cover. South of the Callington Road exposure, the zinc-mineralised zone is covered by ~10 m thickness of flat-lying Tertiary limestone. It was seen by Toteff to re-emerge in farm paddocks further south as float consisting of banded quartz-gahnite-garnet-tourmaline rocks and limonite-calcite gossans, before it passes beneath the Angas River alluvial plain. When sampled, all exposures along the 700 m strike extent of this weathered mineralised horizon were found to be very anomalous in lead, zinc, silver, gold and mercury, yielding assay value maxima of 8.3% Pb, 1.9% Zn, 12 g/t Ag, 1.8 g/t Au and 0.15 ppm Hg that correspond to the loci of best gossan development. Upon subsequent office-based inspection of the geophysical data for this location, Toteff saw that overall, the subtley-expressed mineralised zone coincides with two aligned aeromagnetic anomalies that define a 2.2 km long trend passing immediately east of Strathalbyn. The magnetic source was thought to be possible disseminated pyrrhotite and/or ilmenite within meta-exhalite or sulphidic beds. A sinistral north-northeast shear zone was later interpreted to separate the Strathalbyn mine lode from the most northerly segments of gossan belonging to this newly named Angas prospect. Examination of previous CRA Exploration regional airborne EM survey data discerned a poorly located INPUT anomaly centred just south of the Strathalbyn mine, which the Aberfoyle team surmised might represent a conductive connection between the buried mine lode and the northern end of the Angas mineralisation, across the shear zone. After formal consents had been obtained from numerous private and corporate landowners to allow unhindered access onto the ground covering the prospective Angas magnetic trend, Aberfoyle set about acquiring detailed information on the prospect's geophysics. A surveyed baseline and exploration grid were created, and several ground magnetic traverses were read to better delineate the subsurface structure. In the northern part of the prospect, an assymetric anomaly of up to 200 nT directly overlies the outcropping quartz-biotite-sericite-gahnite gossan. Magnetic data modelling indicated a steep eastwards-dipping body with depth to top of about 40 m (i.e. close to the base of the oxidation). Heading further south along the prospective zone, the magnetic response loses its assymetric peak character and also becomes progressively more subdued. Detailed geochemical soil sampling was also undertaken along 100 m spaced lines at the northern end of the prospect, between the effluent ponds and the old Victor Harbor railway line, with samples collected at 20 m closing to 10 m intervals right above the inferred mineralised horizon. Pronounced soil anomalies in lead, zinc, silver and gold were recorded over the Angas magnetic anomaly, over a 100-200 m width, with lead and zinc providing the most coherent and contrasting highs against background, while a possible elevated arsenic/gold association was noted, extending into the footwall. These trace metal anomalies narrow further to the south, to 90 m along the southernmost sampling line in Jettner's paddock. Thickening cover of Tertiary gravels and sands at the eastern ends of all of the sampling lines muted the soil Pb-Zn levels, however. A two loop ground TEM survey was carried out over the mainly alluvium-covered southern portion of the Angas prospect, from south of the Jettner residence down to the Milang Road. This survey successfully detected bedrock conductors on all three profile lines. A single good conductor was unambiguously interpreted to lie at 125-150 m depth below the northernmost survey line. This TEM feature lies close to, and almost on strike of, the peak of the magnetic ridge which crosses Jettner's southern paddock containing highly anomalous schist and gossan float. Because of the highly anomalous mercury levels accompanying base metal mineralisation in the Strathalbyn district, Aberfoyle conducted a trial survey of mercury dispersed in soil gas during April 1992. The sampling line was located along the Jettner-Croser properties' boundary fence at the southern end of the Angas prospect. Some high mercury levels, to 15 ng/l cf. background of 0.5 ng/l, were encountered, but wet soil conditions affected reading repeatability.

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HOI Steven; Jialei WANG; Peilin ZHAO; Rong JIN (2023). Online Feature Selection and Its Applications [Dataset]. http://doi.org/10.25440/smu.12062733.v1

Online Feature Selection and Its Applications

Related Article
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Dataset updated
May 31, 2023
Dataset provided by
SMU Research Data Repository (RDR)
Authors
HOI Steven; Jialei WANG; Peilin ZHAO; Rong JIN
License

https://www.gnu.org/licenses/gpl-3.0.htmlhttps://www.gnu.org/licenses/gpl-3.0.html

Description

Feature selection is an important technique for data mining before a machine learning algorithm is applied. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of Online Feature Selection (OFS) in which an online learner is only allowed to maintain a classifier involved only a small and fixed number of features. The key challenge of Online Feature Selection is how to make accurate prediction using a small and fixed number of active features. This is in contrast to the classical setup of online learning where all the features can be used for prediction. We attempt to tackle this challenge by studying sparsity regularization and truncation techniques. Specifically, this article addresses two different tasks of online feature selection: (1) learning with full input where an learner is allowed to access all the features to decide the subset of active features, and (2) learning with partial input where only a limited number of features is allowed to be accessed for each instance by the learner. We present novel algorithms to solve each of the two problems and give their performance analysis. We evaluate the performance of the proposed algorithms for online feature selection on several public datasets, and demonstrate their applications to real-world problems including image classification in computer vision and microarray gene expression analysis in bioinformatics. The encouraging results of our experiments validate the efficacy and efficiency of the proposed techniques.Related Publication: Hoi, S. C., Wang, J., Zhao, P., & Jin, R. (2012). Online feature selection for mining big data. In Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (pp. 93-100). ACM. http://dx.doi.org/10.1145/2351316.2351329 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2402/ Wang, J., Zhao, P., Hoi, S. C., & Jin, R. (2014). Online feature selection and its applications. IEEE Transactions on Knowledge and Data Engineering, 26(3), 698-710. http://dx.doi.org/10.1109/TKDE.2013.32 Full text available in InK: http://ink.library.smu.edu.sg/sis_research/2277/

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