- منطقة بودونغ الجديدة ، شنغهاي ، الصين .
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• Data mining can solve complex "needle in haystack" problems. • Data mining can eliminate bad (like fraud), highlight good (such as new opportunities), and streamline decision processes. • Data mining can now be used for qualitative data, as in text mining (see case study below).
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Creating a gender-inclusive mining industry: Uncovering the challenges of mining stakeholders ... The low enrollment in mining related university programs led the University of Mines and Technology (UMaT) to institute the Gender Mainstreaming program. ... Analysis of the quantitative data was performed using pivot …
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Our data set contains 798 wells with resistivity and gamma ray well log data in the gas hydrate stability zone - 788 wells from the petroleum industry and 10 wells with data collected for the purposes of scientific drilling.
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Overall, this study provides valuable insights into the environmental costs of mining activities, which can inform decision-making in the mining industry and contribute to sustainable mining practices. CRediT author statement. Naser Badakhshan: Conceptualization, Data Collection, Methodology, Results, Writing.
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This study reviewed the existing literature on the application of semi-quantitative methods to assess the risk of occupational accidents. The main goal was to identify and describe the methods used in practical applications. PRISMA methodology was applied in this...
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This paper introduces a semi-quantitative coal burst risk classification system, namely, BurstRisk. Based on back-analysis of case histories from Australia, China and the United States, BurstRisk classifies the coal burst risk into …
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Therefore, in order to realize the quantitative or semi-quantitative analysis of disaster causes and consequences, a new semi-quantitative HAZOP method takes HAZOP as the main line to integrate LOPA, F&EI (fire and explosion index) for quantitatively calculating the reduction factors, probability on failure demand (PFD) of general protection ...
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Among the methods that have been applied for impact assessment of mining activities on SD indexes, semi-quantitative ones provide a good solution for this problem regarding the conceptual nature of many issues related to SD, especially social issues.
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Exponential improvements in computational processing speed and data storage are fostering the development of data mining models and algorithms. This, in combination with quicker pathways to publication, led to a large landscape of tools and methods for data mining and extraction.
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The evaluation of data breaches and cybersecurity risks has not yet been formally addressed in modern business systems. There has been a tremendous increase in the generation, usage and consumption of industrial and business data as a result of smart and computational intensive software systems. This has resulted in an increase in the …
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We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes.
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Semi-quantitative methods allow some relative numerical risk comparisons, but are equally unable to provide complete and detailed ... Despite its size, the mining industry lacks such data, which in part has limited the application of QRA methods in the industry.
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In this study, for the first time, a holistic hybrid semi-quantitative 2D assessment matrix and MCDM techniques are developed to evaluate the impacts of both positive and negative impacts of mining activities individually as well as simultaneously …
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Data mining is defined as a set of rules, processes, algorithms that are designed to generate actionable insights, extract patterns, and identify relationships from large datasets (Morabito, 2016). Data mining incorporates automated data extraction, processing, and modeling by means of a range of methods and techniques.
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Semi-Quantitative measurements of transcripts attempt to measure something indirectly related to their concentration, which, while not producing a number, concentration or amount, gives some value related to these that can be used for comparison with other mRNA transcripts.
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Semi-quantitative environmental impact assessment and sustainability level determination of coal mining using a mathematical model ... Mining operations and mineral-related industries are closely and directly related with the environment. The negative impacts of mining industry on the environment, known as environmental risks, must be ...
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The mining industry plays a significant role in economic growth and development. ... a qualitative evaluation and a semi-quantitative evaluation of some data series are used. For the entire research approach, the objectives of sustainable development and its principles are used. ... Kecojevic, V.; Komljenovic, D.; Groves, W. Risk assessment for ...
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Industry 4.0 concepts with related extensive digitalization of industrial processes ... In terms of the latter, various quantitative and qualitative analytic techniques are used (e.g., value-added analysis, why-why method, flow analysis, ... Data mining is the exploration and analysis of large data sets to discover meaningful, previously ...
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