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9 results for “mining industry”
Data and Python script for article "A text mining analysis of the climate change literature in industrial ecology'
<p>The data and Python script are part of the forum article "A text mining analysis of the climate change literature in industrial ecology" authored by Dayeen, F.R., Sharma, A.S., and Derrible, S., and published in the <em>Journal of Industrial Ecology</em> in 2020.</p> <p>The Python script and instructions are included in the LiTCoF_v1.00-py.zip file. The original data is available in two formats: .csv and .pkl.</p> <p>Updates of the script will be posted at https://github.com/csunlab/LiTCoF and at https://csun.uic.edu/codes/LiTCoF.html. The data is also available at https://csun.uic.edu/datasets.html#AbstractsIE.</p> <p>Feel free to contact any of the authors for information and questions about the data and code.</p>
MAED template Reconstruction Base Year - Agriculture, Construction, Mining (Industry Sector)
<p>MAED template Reconstruction Base Year - Agriculture, Construction, Mining (Industry Sector) for Hands-on 5 of the Open Learn Create Course on MAED. </p>
Change in gender roles as a factor in gender participation and empowerment in the oil mining industry: A case of Lokichar, Turkana county, Kenya
<p><span>This paper analyses a study done by the authors of this paper on changes on gender role as a factor in <em>gender participation and empowerment in the oil mining industry; a case of Lokichar in Turkana County</em>. The paper centres on three null hypothesis tested.</span> <span>The studies target group was the active </span>labour<span> force aged between 15 to 64 years. Those who retired from work were also targeted. The data was collected from a sample of three hundred (300) respondents selected through systematic random and purposive sampling methods. Focus Group Discussions (FGD) and in-depth interviews were conducted to supplement the questionnaires given to the sampled respondents. Chi-square was used to test the hypotheses. Major findings indicate that there is a relationship between</span> equal hiring and equal opportunity for men <span>and women to work in mining activities; </span>there is relationship between involvement in oil mining activities and change in livelihood and there is no relationship between involvement in oil mining activities and equal opportunity for men and women to work in mining activities<span>. Key recommendation include gender mainstreaming in legal frameworks, policies, Bills and programs.</span></p>
FIGURE. Sampling sites in Province Sud (New Caledonia) and major mining Ni sites (* i.e.: Thio, Goro, La Tontouta), and major industrial Ni site (circle: Doniambo). in Marine Achnanthales (Bacillariophyceae) from New Caledonia (Melanesia): assemblage specificities, ultramafic environment
FIGURE. Sampling sites in Province Sud (New Caledonia) and major mining Ni sites (* i.e.: Thio, Goro, La Tontouta), and major industrial Ni site (circle: Doniambo).
Change in gender roles as a factor in gender participation and empowerment in the oil mining industry: A case of Lokichar, Turkana county, Kenya
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Implicit aspect-based opinion mining and analysis of airline industry based on user generated reviews
<p>Mining opinions from reviews has been a field of ever-growing research. These include mining opinions on document level, sentence-level, and even aspect level of a review. While explicitly mentioned aspects in a review have been widely researched, very little work has been done in gathering opinions on aspects that are <em><strong>implied </strong></em>and not explicitly mentioned. E.g. “<strong><em>the flight was spacious and there was plenty of legroom</em></strong>”. This gives an opinion on the <em><strong>entities </strong></em>of the <em><strong>cabin </strong></em>and <em><strong>seat </strong></em>of an airline. Words like “<strong><em>spacious</em></strong>” and phrases like “<strong><em>plenty of legroom</em></strong>” help identify these <em><strong>implied entities</strong></em> and the <strong><em>opinions </em></strong>attached to them. Not much research has been done for gathering such implicit aspects and opinions for airline reviews. The present dataset is a <em><strong>manually annotated domain-specific aspect-based corpus </strong></em>that helps a study to extract and analyze opinions about such implied aspects and entities of airlines.</p>
Self-regulation in the peruvian mining industry: tackling the challenge of sustainable water management
<p>Ponencia - IV Congreso Latinoamericano de Marketing Social</p>
Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining
<p>The Supplementary Material of the paper "Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining" includes: <br> 1) APPENDIX 1: SQL Statements for data extraction. Appendix 2: Interview for operating Staff.<br> 2) The DataSet of the normalized data to define the predictive model.</p>
Regression tables and data for "CEO letters: social license to operate and community involvement in the mining industry. Business Ethics: A Eur Rev. 2018"
<p>This file presents the data obtained in the regression analysis for Table 10 included in the paper: </p> <p>"CEO letters: social license to operate and community involvement in the mining industry. Business Ethics: A Eur Rev. 2018;00:1–20".</p> <p>The file also includes the data used in the analyses for each variable and code, and also count of codes used in the analyses. Data included are for both years (2011 and 2015).</p> <p>Please, cite the tables with the paper reference: de‐Miguel‐Molina B, Chirivella‐González V, García‐Ortega B. CEO letters: social license to operate and community involvement in the mining industry. Business Ethics: A Eur Rev. 2018;00:1–20. ht tps://doi.org/10.1111/beer.12205</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.