Cd often occurs as a byproduct of Zn ore mining and refining, with levels typically elevated in areas surrounding mining sites (Sadegh Safarzadeh et al., 2007). Pb is associated with various mining operations, including Pb, Zn, and Ag mining, and can persist in the environment for extended periods (Kumar et al., 2020).
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Resource-oriented community is composed of organizational mining (T4), privacy-preserving process mining (T12), process mining visualization (T15), web and cloud services (A7), e-business (A8), machine learning and business intelligence (S1), Business process management and business process redesign (S2), and decision support (S4). This ...
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Search ScienceDirect. International Journal of Mineral Processing. Volume 145, 10 December 2015, Pages 17-22. ... Mining machinery industry transformation is oriented towards highly sophisticated technologies aimed at enhancing the nature of operations carried out. Vibrating screen machine is a major player in the mining processing plants and ...
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Search ScienceDirect. Pharmacology & Therapeutics. Volume 203, November 2019, 107395. ... Herein, we address these critical questions by: i) presenting and discussing current trends in machine learning and data mining methodologies related to drug response (Table 1, Fig. 1, Fig. 2) and ii) ...
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With Data Science, Data Mining and Machine Learning platforms allow the development of decision support systems, capable of establishing patterns between data and …
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Machine learning (ML) is an important research field of artificial intelligence that assists computers in modeling based on experiences and accurately predicting future events. The major ML approaches can be classified into two main categories: supervised learning (Parvin, Alinejad-Rokny, Minaei-Bidgoli, & Parvin, 2013) and unsupervised learning (Minaei-Bidgoli, …
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This technique has been successfully used in various machine-learning-based text mining studies. For instance, Amrit et al. (2017) used text mining to analyze consultation notes from public health institutions to identify …
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Shovels are universally acknowledged as vital machinery in surface mining production systems, and enhancements to this equipment substantially augment operational mine output capacity.
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Search ScienceDirect. Journal of Biomedical Informatics. Volume 128, April 2022, 104026. ... (Prediction OR Prognosis), and techniques (Data mining OR Machine learning OR Classification OR Rule mining OR Sequence mining) were used on the title and abstract for the analysis from each of the databases. A total of 1378 publications were retrieved ...
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Search ScienceDirect. Safety Science. Volume 181, January 2025, 106677. ... Decision support system for the prediction of mine fire levels in underground coal mining using machine learning approaches. Min. Metall. Explor., 39 (2) (2022), pp. 591-601. Crossref View in Scopus Google Scholar.
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Search ScienceDirect. Energy Conversion and Management. Volume 238, 15 June 2021, 114153. Data mining with 12 machine learning algorithms for predict costs and carbon dioxide emission in integrated energy-water optimization model in buildings. Author links open overlay panel Majid Emami Javanmard a b, ...
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Innovative systems have been presented in this area as the integration of a sample collector adapted from surface mining applications into underground drill rigs (International Mining, 2023, Raatikainen et al., 2023). This device called "Autosampler" was designed for top hammer drill rigs, and consists on a rotating cone splitter that ...
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Software fault/defect prediction assists software developers to identify faulty constructs, such as modules or classes, early in the software development life cycle.There are data mining, machine learning, and deep learning techniques used for software fault prediction. We perform analysis of previously published reviews, surveys, and related studies to distill a …
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The 6th International Conference on Mining Science & Technology Study on design of operating mechanism of auger mining machine Du Chang-long*, Liu Song-yong, Cui Xin-xia, Gu Jiu-lin College of Mecnanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China Abstract To raise the cutting efficiency and percentage of …
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Previous work has been done in the overlapping fields of medical data mining, medical NLP or BioNLP and medical text mining (Chapman, Cohen, 2009, Van Der Spoel, Van Keulen, Amrit, 2012). Relevant to this research are studies that focus on data mining or text mining in the (semi-) medical context. Closest to this research are applications of
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In the article it is presented the comparison of two methods of experimental determination of the center of gravity of machines used in opencast mining: measurement …
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Machine-learning-based modeling plays a key role in tackling the complexities of urban mining, enabling the development of predictive models for efficient postconsumption product and …
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Prediction of allogeneic hematopoietic stem-cell transplantation mortality 100 days after transplantation using a machine learning algorithm: a European Group for Blood and Marrow Transplantation Acute Leukemia Working Party retrospective data mining study
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Three Open Problems in the Context of E2E Web Testing and a Vision: NEONATE. Filippo Ricca, ... Andrea Stocco, in Advances in Computers, 2019. 3.1.1 Robust Data Extraction. In the context of information retrieval and web data mining, researchers have proposed techniques for the robust extraction of information from evolving structured documents (e.g., XML documents).
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Currently, digital twin systems in mining are employed to create virtual models that simulate and optimize various mining processes. These models can represent mine sites, …
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It has been defined by researchers as one of the key data mining techniques. Standard data mining techniques are used to extract logical patterns from structured data, while text mining is a process of knowledge discovery and a technique for identifying logical patterns from unstructured data (Kano et al., 2009).
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Search ScienceDirect. Journal of Environmental Management. Volume 352, 14 February 2024, 120107. Research article. Remote sensing-based prediction of organic carbon in agricultural and natural soils influenced by salt and sand mining using machine learning. Author links open overlay panel Tianqi Zhang, Ye Li, Mingyou Wang. Show more. Add to ...
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The total area of high risk and very high risk in Tunlan mine was 4. 596 %, and the areas of high risk and very high risk in Xiqu mine, Zhenchengdi mine, and Baijiazhuang mine accounted for 3. 855 %, 3.625 %, and 3. 188 % respectively. Among them, the Xiqu mine had the largest area of extremely high risk, which accounted for 1.373 %.
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Due to technological innovations and the mining of social media data, it has been argued that Natural Language Processing (NLP) and Machine Learning (ML) can assist researchers in these fields and ultimately impact the health of individuals and the general population (Conway & O'Connor, 2016).
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© 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing. Keywords: condition-based maintenance; data analytics; data mining; machine learning; failure event * Corresponding author.
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mining was used to scour the internet for relevant articles and extract data for the study. This approach is widespread in scholarly works concentrating on text mining for web content (Singh & Singh, 2010). Conceptually, web mining represents the process of using data mining methods to extract useful information from the web.
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Since the coal mining areas accounted for only 3.6% of the total study area, a low contribution of coal mining to ecosystem health was observed. However, in coal mining areas, the mining intensity was the dominant contributing factor affecting EH (Fig. 5). The distance to the mining areas contributed about 10% to the EH during the study period.
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Big data, AI, machine learning, autonomous vehicles enable sustainable mining and high production efficiency. Digitization addresses mining's environmental impact and …
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Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity – A review Author links open overlay panel Ana M. Jiménez-Carvelo, Antonio González-Casado, M. Gracia Bagur-González, Luis Cuadros-Rodríguez
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Due to the priority exercised by MIM, the experience with this machine has rapidly evolved the Mobile Miner concept as a potentially viable mining system. It is not too difficult to …
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