Academic literature on the topic 'Mining engineering'

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Journal articles on the topic "Mining engineering"

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Smith, Arthur E. "Mining Engineering Periodicals." Rocks & Minerals 67, no. 3 (June 1992): 183–86. http://dx.doi.org/10.1080/00357529.1992.9926479.

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Kratzsch, Ing H. "Mining subsidence engineering." Environmental Geology and Water Sciences 8, no. 3 (September 1986): 133–36. http://dx.doi.org/10.1007/bf02509900.

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Harit Priyadarshi, Nasim, B. N. Dubey, Meenali Modi. "Green Mining: Environmental Ethics in Mining Engineering." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (October 28, 2023): 3099–104. http://dx.doi.org/10.52783/tjjpt.v44.i3.1286.

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Green mining, an evolving paradigm within mining engineering, is driven by a commitment to environmental ethics and sustainability. This article explores the principles, benefits, and challenges associated with green mining, presenting a comprehensive view of its potential transformation of the mining industry. Traditional mining practices have historically resulted in habitat destruction, air and water pollution, and other environmental challenges. However, green mining principles emphasize resource efficiency, minimal environmental disturbance, responsible waste management, and social responsibility. The adoption of these principles promises numerous advantages, including environmental conservation, reduced carbon footprint, economic efficiency, and long-term sustainability. Despite various challenges, such as economic pressures and regulatory hurdles, the transition to green mining is gaining momentum. This shift embodies an ethical imperative and a practical approach to ensuring responsible resource extraction while preserving the planet's delicate ecosystems and the well-being of local communities.
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Mahamud-López, Manuel María, and Juan Mariá Menéndez-Aguado. "Environmental engineering in mining engineering education." European Journal of Engineering Education 30, no. 3 (September 2005): 329–39. http://dx.doi.org/10.1080/03043790500114490.

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Komissarov, Anatoly P., Yuliya A. Lagunova, Rustem Sh Nabiullin, and Olga A. Lukashuk. "DIGITALIZATION IN MINING ENGINEERING." Mining Equipment and Electromechanics, no. 5 (December 23, 2020): 34–38. http://dx.doi.org/10.26730/1816-4528-2020-5-34-38.

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Chen, Zhongqiang, Lang Liu, Xueyuan Qi, and Junjun Geng. "Digital Mining Technology-Based Teaching Mode for Mining Engineering." International Journal of Emerging Technologies in Learning (iJET) 11, no. 10 (October 27, 2016): 47. http://dx.doi.org/10.3991/ijet.v11i10.6271.

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In this paper, the main problem in present mining engineering teaching was analyzed. Based on the analysis, the study of bringing digital mining technology into mining engineering teaching was presented. Furthermore, a new mining engineering teaching mode that includes mining knowledge demonstration, mining expertise building, mining environment modeling, and creative mining thought was also presented. In the teaching mode, 3D digital mining technology was used to model the mining environment. The modeled environment facilitated a systematic mining teaching system that helped students understand both mining concepts and mining operations. Thus, the instructor, student, and mining workers were essential to the teaching mode. The use of digital mining technology and relevant multimedia made mining teaching vivid and easy to be understood. Digitized primary data in mining engineering were readily and visually understood by students. Simulated 3D mining scenario generated with the data helped students understand theory and practice. Meanwhile, application of distant information technology helped mining workers in the abovementioned mining engineering teaching mode to be involved, thereby providing first-hand experience for classroom mining teaching. Hence, the digital mining based mining engineering teaching mode shows considerable promise in raising teaching effectiveness and efficiency.
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Li, Fabiana. "Engineering responsibility." Focaal 2011, no. 60 (June 1, 2011): 61–73. http://dx.doi.org/10.3167/fcl.2011.600106.

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Focusing on a controversial gold mining project in Chile, this article examines how engineers and other mining professionals perceive and help shape Corporate Social Responsibility initiatives. Compensation agreements, environmental management, and community relations programs rest on what I call a logic of equivalence that makes the environmental consequences of mining activity commensurate with the mining companies’ mitigation plans. For example, legal codes enable engineers to measure, compare, and reconcile the costs and benefits of a project. However, the law is neither fixed nor uncontestable, and companies must respond to increased public scrutiny and the growing demands of communities, governments, and international actors. In Chile, campaigns against mining focused on the presence of glaciers at the mine site and the project’s possible effects on water availability. By introducing new moral dimensions to debates over corporate responsibility, these campaigns challenged established strategies of commensuration and existing ethical guideposts.
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Barai, Sudhir Kumar. "DATA MINING APPLICATIONS IN TRANSPORTATION ENGINEERING." TRANSPORT 18, no. 5 (October 31, 2003): 216–23. http://dx.doi.org/10.3846/16483840.2003.10414100.

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Data mining is the extraction of implicit, previously unknown and potentially useful information from data. In recent time, data mining studies have been carried out in many engineering disciplines. In this paper the background of data mining and tools is introduced. Further applications of data mining to transportation engineering problems are reviewed. The application of data mining for typical example of ‘Vehicle Crash Study’ is demonstrated using commercially available data mining tool. The paper highlights the potential of data mining tool application in transportation engineering sector.
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Shen, Hai Ying, Shu Ming Wen, and Ti Zhuan Wang. "Mining Engineering Professionals Motivated to Improve their Proficiency in English." Applied Mechanics and Materials 525 (February 2014): 765–69. http://dx.doi.org/10.4028/www.scientific.net/amm.525.765.

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The industrialization is progressing on the unparalleled scale, bringing an ever greater impetus to the growth of mining industry. China has had its unique pattern of developing its mining engineerin: firstly importing technologies, then studying and absorbing them, and finally achieving some innovation. Until now, China has been honored with some of mining theories taking the lead in the international mining world. As the disseminators of human civilization including advanced mining technologies, the Chinese professionals concerned are duty-bound to introduce abroad Chinas new progresses in mining engineering; that they are skillfully equipped with the four kinds of English abilities in reading, writing, listening and speaking, which is prerequisite for them to work well in foreign cooperation, has become an urgent matter to for them as well as for the authorities concerned.
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Yue, Xiao Guang, Guang Zhang, Qing Guo Ren, Wen Cheng Liao, Jing Xi Chen, Zi Qiang Zhao, and Xiao Lan Xie. "Research on Sustainable Mining Engineering." Applied Mechanics and Materials 340 (July 2013): 126–30. http://dx.doi.org/10.4028/www.scientific.net/amm.340.126.

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The concepts of Chinese information processing and natural language processing (NLP) and their development tendency are summarized. There are different comprehension of Chinese information processing and natural language processing in China and the other countries. But the work appears to emerge in the study of key point of languages processing. Mining engineering is very important for our country. Though the final task of languages processing is difficult, Chinese information processing has contributed substantially to our scientific research and social economy and it will play an important part for mining engineering in our future.
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Dissertations / Theses on the topic "Mining engineering"

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Mitchell, Trent Russell. "Normalization of Deviance in Mining Engineering." Thesis, The University of Utah, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10603711.

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Normalization of deviance has been thoroughly studied and proven to have a dramatic impact on the medical industry, particularly in the field of anesthesiology, and for the National Aeronautics and Space Administration (NASA). Few such studies have been conducted in the mining industry. This research was designed to show whether normalization of deviance is occurring within the subculture of mining engineers.

This research project was based on a cross-sectional surveillance of a group of mining engineers and consultants belonging to the Society for Mining, Metallurgy and Exploration (SME).

There were three hypotheses for this research: 1) there is a correlation between ethics, compensation, risk tolerance, and normalization of deviance; 2) there are either positive or negative associations between each of the independent variables—ethics, compensation, and risk tolerance—to the dependent variable—normalization of deviance; 3) the data would make it possible to predict normalization of deviance among mining engineers. All three hypotheses were proven true in this study.

This research is important because it shows that normalization of deviance exists among mining engineers.

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Kang, U. "Mining Tera-Scale Graphs: Theory, Engineering and Discoveries." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/160.

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How do we find patterns and anomalies, on graphs with billions of nodes and edges, which do not fit in memory? How to use parallelism for such Tera- or Peta-scale graphs? In this thesis, we propose PEGASUS, a large scale graph mining system implemented on the top of the HADOOP platform, the open source version of MAPREDUCE. PEGASUS includes algorithms which help us spot patterns and anomalous behaviors in large graphs. PEGASUS enables the structure analysis on large graphs. We unify many different structure analysis algorithms, including the analysis on connected components, PageRank, and radius/diameter, into a general primitive called GIM-V. GIM-V is highly optimized, achieving good scale-up on the number of edges and available machines. We discover surprising patterns using GIM-V, including the 7-degrees of separation in one of the largest publicly available Web graphs, with 7 billion edges. PEGASUS also enables the inference and the spectral analysis on large graphs. We design an efficient distributed belief propagation algorithm which infer the states of unlabeled nodes given a set of labeled nodes. We also develop an eigensolver for computing top k eigenvalues and eigenvectors of the adjacency matrices of very large graphs. We use the eigensolver to discover anomalous adult advertisers in the who-follows-whom Twitter graph with 3 billion edges. In addition, we develop an efficient tensor decomposition algorithm and use it to analyze a large knowledge base tensor. Finally, PEGASUS allows the management of large graphs. We propose efficient graph storage and indexing methods to answer graph mining queries quickly. We also develop an edge layout algorithm for better compressing graphs.
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Xiao, G. C. "Rock engineering investigations for North Selby shaft insets." Thesis, University of Newcastle Upon Tyne, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.376322.

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Li, Wenyan Kusiak Andrew. "Predictive engineering in wind energy a data-mining approach /." [Iowa City, Iowa] : University of Iowa, 2009. http://ir.uiowa.edu/etd/399.

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Damoni, Arben. "Multimodal segmentation for data mining applications in multimedia engineering." Thesis, London South Bank University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631732.

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This project describes a novel approach to the development of a multimodal video segmentation system for the analysis of multimedia data. The current practices of multimedia data analysis rely either solely on one of the video and audio components or on the presence of both together. The proposed approach makes use of both the video and audio inputs in parallel, complementing each other during the video processing stage, towards optimising both the accuracy and speed of the method. Unlike in the other commonly established methods, the video analysis here is carried out using both the luminance and the chrominance values of the colour images, instead of relying on either of them. The approach considered in the proposed method of video cut detection primarily uses a modified luminance based histogram analysis algorithm, supported by the additional sub-sampling and median filtering options. They improve the efficiency of the method through enhancing its speed and the accuracy of detection respectively. The algorithm mentioned above uses a progressively varying threshold for indicating a significant variation in the measurement of successive histograms for a window length of 2 image frames. The method worked successfully for the videos with varying rates and sizes of the frames that have been under investigation. Because of the degrading effect of chrominance histogram analysis on the processing speed its use is kept to a minimum. This is restricted only to verify the existence of possible cuts, failed to be identified by the luminance analysis. The indication of such cuts could be obtained through audio classification analysis.
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Li, Wenyan. "Predictive engineering in wind energy: a data-mining approach." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/399.

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The large-scale wind energy industry is relatively new and is rapidly expanding. The ability of a wind turbine to extract power from the wind is a function of three main factors: the measured wind speed, the power curve of the turbine, and the ability of the machine to handle wind fluctuations. The key parameter determining wind turbine performance is wind speed and it is normally measured with an anemometer placed at the nacelle of a turbine. The dynamic nature of wind speed, however, is a barrier for applying predictive engineering in wind energy. Traditional approaches based on physical science and mathematical modelings have limitations on wind power prediction models. Conventional approach based on dynamic modeling has disadvantage of power generation process modeling due to time-shift nature of the process. Data mining is a promising approach for modeling wind energy, e.g., power prediction and optimization, wind speed forecasting, power curve monitoring and fault diagnosis. It involves a number of steps including data pre-processing, data sampling, feature selection, dimension reduction and, etc. This thesis focus on applying data mining to predictive engineering in wind industry, and ultimately builds wind speed prediction and wind farm power prediction models, develops turbine dynamic control and power optimization strategy, explores methodology for system level fault diagnosis. However the philosophy, methods and frameworks discussed in this research can also be applied to other industrial processes. This thesis proposes a series of predictive models under the framework of data mining. Chapter 2 introduces a methodology for short term wind speed prediction based on wind farm layout information. Chapter 3 and Chapter 4 present prediction models for wind turbine parameters. Chapter 5 proposes strategies for dynamic control of wind turbines. Chapter 6 explores the fault diagnosis and prediction using SCADA data.
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Shinde, Jagdish. "Acquisition modelling for heavy engineering assets in mining industry." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/54637/1/Jagdish_Shinde_Thesis.pdf.

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Each year, organizations in Australian mining industry (asset intensive industry) spend substantial amount of capital (A$86 billion in 2009-10) (Statistics, 2011) in acquiring engineering assets. Engineering assets are put to use in operations to generate value. Different functions (departments) of an organization have different expectations and requirements from each of the engineering asset e.g. return on investment, reliability, efficiency, maintainability, low cost of running the asset, low or nil environmental impact and easy of disposal, potential salvage value etc. Assets are acquired from suppliers or built by service providers and or internally. The process of acquiring assets is supported by procurement function. One of the most costly mistakes that organizations can make is acquiring the inappropriate or non-conforming assets that do not fit the purpose. The root cause of acquiring non confirming assets belongs to incorrect acquisition decision and the process of making decisions. It is very important that an asset acquisition decision is based on inputs and multi-criteria of each function within the organization which has direct or indirect impact on the acquisition, utilization, maintenance and disposal of the asset. Literature review shows that currently there is no comprehensive process framework and tool available to evaluate the inclusiveness and breadth of asset acquisition decisions that are taken in the Mining Organizations. This thesis discusses various such criteria and inputs that need to be considered and evaluated from various functions within the organization while making the asset acquisition decision. Criteria from functions such as finance, production, maintenance, logistics, procurement, asset management, environment health and safety, material management, training and development etc. need to be considered to make an effective and coherent asset acquisition decision. The thesis also discusses a tool that is developed to be used in the multi-criteria and cross functional acquisition decision making. The development of multi-criteria and cross functional inputs based decision framework and tool which utilizes that framework to formulate cross functional and integrated asset acquisition decisions are the contribution of this research.
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Mottola, Laura. "Systems analysis for robotic mining." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23751.

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Mining automation has incrementally progressed from line-of-sight remote operation to teleoperation and automatic control of mobile machines, mainly due to significant advances in underground communication systems. The present trend points towards a robotic mining environment where mobile machinery and stationary equipment will be fully integrated with a mine-wide information system overseeing all aspects of mining via a communication network. The successful design and implementation of the software and hardware components necessary to realize this vision depends on the level of seamless integration achieved. The complexity involved in terms of systems functionality and coherence necessitates systems analysis and computer-aided software engineering tools to actively support this integration effort.
Hence, the primary objective of this thesis is to introduce and relate systems analysis concepts and tools to the business of mining. This investigation begins by setting the industrial context of this work with respect to past initiatives and future trends. It discusses different approaches to the design and implementation of mining information systems. It reviews the fundamentals of software and information engineering as well as structured and object-oriented analysis and design. It presents a survey of computerized tools for systems analysis. It then applies systems analysis concepts and tools to a high-level top-down analysis of a Mine Information System and examines a specific mining process in detail. Finally, it compares the applicability of structured versus object-oriented analysis and design methodologies to the complex problem of mining.
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De, Tomi Giorgio. "Software engineering for the design of integrated mining computer systems." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338651.

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Belin, Siderov Mitkov. "AUTONOMOUS MINING VEHICLE." Thesis, KTH, Industriell produktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215965.

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Books on the topic "Mining engineering"

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Mining, Petroleum, and Metallurgy Conference (4th 1994 Asyūṭ, Egypt). Mining engineering. [Asyūṭ]: Faculty of Engineering, Assiut University, 1994.

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Mining, Geological, and Metallurgical Institute of India., ed. Mining engineering. Calcutta: Mining, Geological and Metallurgical Institute of India, 1998.

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Bise, Christopher J. Mining engineering analysis. 2nd ed. Littleton, Colo: Society for Mining, Metallurgy, and Exploration, 2003.

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Hartman, Howard L. Introductory mining engineering. New York: Wiley, 1987.

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M, Mutmansky Jan, ed. Introductory mining engineering. 2nd ed. Hoboken, N.J: J. Wiley, 2002.

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Darling, Peter. SME mining engineering handbook. 3rd ed. [Englewood, Colo.]: Society for Mining, Metallurgy, and Exploration, 2011.

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L, Hartman Howard, Seeley W. Mudd Memorial Fund of AIME, and Society for Mining, Metallurgy, and Exploration (U.S.), eds. SME mining engineering handbook. 2nd ed. Littleton, CO: Society for Mining, Metallurgy, and Exploration, 1992.

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L, Hartman Howard, Seeley W. Mudd Memorial Fund of AIME., and Society for Mining, Metallurgy, and Exploration (U.S.), eds. SME mining engineering handbook. 2nd ed. Littleton, Colo: Society for Mining, Metallurgy, and Exploration, 1992.

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Soofastaei, Ali, ed. Advanced Analytics in Mining Engineering. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-91589-6.

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Spaccapietra, Stefano, and Fred Maryanski, eds. Data Mining and Reverse Engineering. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35300-5.

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Book chapters on the topic "Mining engineering"

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Yao, Yuan, Xing Su, and Hanghang Tong. "Feature Engineering." In Mobile Data Mining, 17–23. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02101-6_3.

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Sierra, Carlos, and Emilio Andrea. "Introduction to Reliability Engineering." In Mining Maintenance, 15–50. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59450-2_2.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 348–50. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0393-0_29.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 274–75. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-5969-6_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 307. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3412-9_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 341–44. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3474-7_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 339–41. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0599-6_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 325–31. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-5197-9_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 284–86. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2832-6_30.

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Shafer, Wade H. "Mining and Metallurgical Engineering." In Masters Theses in the Pure and Applied Sciences, 230–32. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-5782-8_30.

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Conference papers on the topic "Mining engineering"

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"Automation in Mining Engineering." In 2019 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2019. http://dx.doi.org/10.1109/icit.2019.8755080.

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Xie, Tao, Jian Pei, and Ahmed E. Hassan. "Mining Software Engineering Data." In 29th International Conference on Software Engineering (ICSE'07 Companion). IEEE, 2007. http://dx.doi.org/10.1109/icsecompanion.2007.50.

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Hassan, Ahmed E., and Tao Xie. "Mining software engineering data." In the 32nd ACM/IEEE International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1810295.1810451.

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Kluge, Paul, and Arthur Neale. "A Mining Engineering Approach to Mining Lunar Regolith." In 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-358.

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Ko, Andrew J. "Mining the mind, minding the mine." In ICSE '18: 40th International Conference on Software Engineering. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196398.3196477.

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Ko, Andrew J. "Mining the mind, minding the mine." In ICSE '18: 40th International Conference on Software Engineering. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196321.3196324.

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Qiao, Weiguo, V. V. Pershin, E. G. Kassikhina, and N. O. Butrim. "Engineering and process design solutions for the vertical shaft completion." In Taishan Academic Forum - Project on Mine Disaster Prevention and Control. Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/mining-14.2014.2.

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Pershin, Vladimir Viktorovich, and Dmitriy Ivanovich Nazarov. "Safety of Mining Engineering Buildings and Facilities Under Fem Analysis and Catastrophe Theory." In Taishan Academic Forum - Project on Mine Disaster Prevention and Control. Paris, France: Atlantis Press, 2014. http://dx.doi.org/10.2991/mining-14.2014.64.

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Hayes, Jane Huffman, Alex Dekhtyar, and Senthil Sundaram. "Text mining for software engineering." In the 2005 international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1083142.1083153.

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Kasravi, Kas. "Improving the Engineering Processes With Text Mining." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57790.

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The engineering process relies on extensive sources of knowledge in textual form, such as books, conference papers, product catalogs, and web pages. Leveraging the full value of the knowledge in textual data is difficult due to the length of time required to read and comprehend the documents. Text mining untaps the vast amounts of information buried in textual data. Text mining can process the content of large numbers of documents, semantically analyze and organize the content, and extract the useful information for downstream applications. Once analyzed, the informational content of documents can be indexed and accessed in multiple formats, such as summaries, key concepts, events, relationships, and visual representations. Applications of text mining in engineering are diverse and include predictive warranty analysis, quality improvements, patent analysis, competitive assessments, FMEA, and product searches.
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Reports on the topic "Mining engineering"

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Morkun, Volodymyr S., Сергій Олексійович Семеріков, Svitlana M. Hryshchenko, and Kateryna I. Slovak. Environmental Geo-information Technologies as a Tool of Pre-service Mining Engineer’s Training for Sustainable Development of Mining Industry. CEUR Workshop Proceedings, 2017. http://dx.doi.org/10.31812/0564/730.

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The article highlights peculiarities of geoinformation technologies’ application in course of pre-service engineers’ training for sustainable development, their functionalities, geoinformation system’s role and position in environmental protection acts. Concepts of geoinformation technologies, geoinformation system have been disclosed. The pedagogical experiment was done concerning introduction of the developed method of using geoinformation technologies as means of forming environmental competence profile mining engineers predicted an experemental studying on course «Environmental Geoinformatics». The results of the expert assessment of rational using geoinformation technologies there were given to create an ecological competence of future mining engineering profile.
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Foley, William. New Mexico Institute of Mining and Technology Environmental Engineering Seminar PFAs Overview. Office of Scientific and Technical Information (OSTI), October 2022. http://dx.doi.org/10.2172/1891807.

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Ступнік, М. І., В. С. Моркун, and З. П. Бакум. Information and Communication Technologies in the Process of Mining Engineer Training. Криворізький державний педагогічний університет, 2013. http://dx.doi.org/10.31812/0564/405.

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Based on scientific analysis the authors of the article argued the necessity of solving priority tasks – the development of new educational technologies aimed at supporting the training of engineers in terms of the mining engineering as high-tech industry. The features of mining computer technologies are determined. There was worked out the project of the adaptive system of a mining engineer individual training "Electronic manual" aimed at the development of future professionals. The essence of individual preparation of future mining engineer ICT is defined. It is proved that the efficiency of the designing and planning of mining operations through the introduction of ICT at present is the real way to influence the quality of mining products that will promote individual learning orientation. For the first time pedagogical foundations for introducing adaptive training of mining engineers are clarified.
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4

Бакум, З. П., and В. В. Ткачук. Mining Engineers Training in Context of Innovative System of Ukraine. Криворізький державний педагогічний університет, 2014. http://dx.doi.org/10.31812/0564/425.

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The paper clarifies the process of a mining engineer training in terms of the innovation system of Ukraine. The authors analyze a number of normative documents concerning innovative activity in Ukraine in general and mining business in particular. In the process of implementation of innovations into mining industrial complex urgent problems are defined. The methodology of information and communication technologies (electronic, distance and mobile studies) usage in engineers training within the conditions of university education is offered. It is marked that the worked out methodology finds its practical introduction: e-learning involves creation of the portal "Electronic mentor"; distance learning is presented in the study of professional disciplines as an example of the course "Сomputer Technologies in Mining"; mobile learning is considered as an example of discipline "Computer Science and Engineering".
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Stevens, D. S. P. Engineering - geologic map of the Eagle A-1 Quadrangle, Fortymile mining district, Alaska. Alaska Division of Geological & Geophysical Surveys, October 2012. http://dx.doi.org/10.14509/24544.

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6

Pinney, D. S. Engineering - geologic map of the Eagle A-2 Quadrangle, Fortymile mining district, Alaska. Alaska Division of Geological & Geophysical Surveys, 2001. http://dx.doi.org/10.14509/2672.

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7

Morkun, Vladimir S., Serhiy O. Semerikov, Nataliya V. Morkun, Svitlana M. Hryshchenko, and Arnold E. Kiv. Defining the Structure of Environmental Competence of Future Mining Engineers: ICT Approach. [б. в.], November 2018. http://dx.doi.org/10.31812/123456789/2650.

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The object is to the reasonable selection of the ICT tools for formation of ecological competence. Pressing task is constructive and research approach to preparation of future engineers to performance of professional duties in order to make them capable to develop engineering projects independently and exercise control competently. Subject of research: the theoretical justification of competence system of future mining engineers. Methods: source analysis on the problem of ecological competence formation. Results: defining the structure of environmental competence of future mining engineers. Conclusion: the relevance of the material covered in the article, due to the need to ensure the effectiveness of the educational process in the preparation of the future mining engineers.
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Grossman, R. The High Performance and Wide Area Analysis and Mining of Scientific & Engineering Data. Office of Scientific and Technical Information (OSTI), December 2002. http://dx.doi.org/10.2172/836590.

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Foley, William. New Mexico Institute of Mining and Technology Civil/Environmental Engineering Seminar Storm Water Conveyance Pipe - Support Failure. Office of Scientific and Technical Information (OSTI), October 2021. http://dx.doi.org/10.2172/1825379.

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Foley, William. New Mexico Institute of Mining and Technology Civil/Environmental Engineering Seminar Storm Water Conveyance Pipe - Support Failure. Office of Scientific and Technical Information (OSTI), October 2022. http://dx.doi.org/10.2172/1890962.

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