Text Mining in Biomedical Domain with Emphasis on Document Clustering

PubMed Central

2017-01-01

Objectives With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. Methods This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Results Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Conclusions Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise. PMID:28875048

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Decision support methods for the environmental assessment of contamination at mining sites.

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a 'holistic' approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.

Process mining in oncology using the MIMIC-III dataset

NASA Astrophysics Data System (ADS)

Prima Kurniati, Angelina; Hall, Geoff; Hogg, David; Johnson, Owen

2018-03-01

Process mining is a data analytics approach to discover and analyse process models based on the real activities captured in information systems. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncology with a regular complaint being the limited availability and accessibility of datasets with suitable information for process mining. Publicly available datasets are one option and this paper describes the potential to use MIMIC-III, for process mining in oncology. MIMIC-III is a large open access dataset of de-identified patient records. There are 134 publications listed as using the MIMIC dataset, but none of them have used process mining. The MIMIC-III dataset has 16 event tables which are potentially useful for process mining and this paper demonstrates the opportunities to use MIMIC-III for process mining in oncology. Our research applied the L* lifecycle method to provide a worked example showing how process mining can be used to analyse cancer pathways. The results and data quality limitations are discussed along with opportunities for further work and reflection on the value of MIMIC-III for reproducible process mining research.

Open-source tools for data mining.

PubMed

Zupan, Blaz; Demsar, Janez

2008-03-01

With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. In this article, we discuss the evolution of open-source toolboxes that data mining researchers and enthusiasts have developed over the span of a few decades and review several currently available open-source data mining suites. The approaches we review are diverse in data mining methods and user interfaces and also demonstrate that the field and its tools are ready to be fully exploited in biomedical research.

Optimization research of structural parameters in non-pillar sublevel caving method with large structural parameters

NASA Astrophysics Data System (ADS)

Han, Wencheng; Zhou, Renjie; Liu, Xianfeng; Sun, Dongdong

2018-03-01

The non-pillar sublevel caving method with large structural parameters used in Mao Gong Iron Mine is of high rate of dilution and loss, and the ore recovery rate is less than 50%. Aiming at this problem, this paper analyzes the influence mechanism of the caving step on the mining index by means of the matching relationship between the shape of caved ore body and the drawn-out ore body, then through the physical simulation experiment in laboratory, the mining index such as the volume of pure ore drawing, ore recovery ratio and rock mixing ratio are studied under different caving step. The results show that the mining index under caving step of two row of blast hole is better than that under caving step of one row of blast hole. The research has guided significance for production of the mine.

Chapter 16: text mining for translational bioinformatics.

PubMed

Cohen, K Bretonnel; Hunter, Lawrence E

2013-04-01

Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

Iowa State Mining and Mineral Resources Research Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1990-08-01

This final report describes the activities of the Iowa State Mining and Mineral Resources Research Institute (ISMMRRI) at Iowa State University for the period July 1, 1989, to June 30, 1990. Activities include research in mining- and mineral-related areas, education and training of scientists and engineers in these fields, administration of the Institute, and cooperative interactions with industry, government agencies, and other research centers. During this period, ISMMRRI has supported research efforts to: (1) Investigate methods of leaching zinc from sphalerite-containing ores. (2) Study the geochemistry and geology of an Archean gold deposit and of a gold-telluride deposit. (3) Enchancemore » how-quality aggregates for use in construction. (4) Pre-clean coal by triboelectric charging in a fluidized-bed. (5) Characterize the crystal/grain alignment during processing of yttrium-barium-copper-perovskite (1-2-3) superconductors. (5) Study the fluid inclusion properties of a fluorite district. (6) Study the impacts of surface mining on community planning. (7) Assess the hydrophobicity of coal and pyrite for beneficiation. (8) Investigate the use of photoacoustic absorption spectroscopy for monitoring unburnt carbon in the exhaust gas from coal-fired boilers. The education and training program continued within the interdepartmental graduate minor in mineral resources includes courses in such areas as mining methods, mineral processing, industrial minerals, extractive metallurgy, coal science and technology, and reclamation of mined land. In addition, ISMMRRI hosted the 3rd International Conference on Processing and Utilization of High-Sulfur Coals in Ames, Iowa. The Institute continues to interact with industry in order to foster increased cooperation between academia and the mining and mineral community.« less

Empirical Models of Zones Protecting Against Coal Dust Explosion

NASA Astrophysics Data System (ADS)

Prostański, Dariusz

2017-09-01

The paper presents predicted use of research' results to specify relations between volume of dust deposition and changes of its concentration in air. These were used to shape zones protecting against coal dust explosion. Methodology of research was presented, including methods of measurement of dust concentration as well as deposition. Measurements were taken in the Brzeszcze Mine within framework of MEZAP, co-financed by The National Centre for Research and Development (NCBR) and performed by the Institute of Mining Technology KOMAG, the Central Mining Institute (GIG) and the Coal Company PLC. The project enables performing of research related to measurements of volume of dust deposition as well as its concentration in air in protective zones in a number of mine workings in the Brzeszcze Mine. Developed model may be supportive tool in form of system located directly in protective zones or as operator tool warning about increasing hazard of coal dust explosion.

Indirect Measures of Learning Transfer between Real and Virtual Environments

ERIC Educational Resources Information Center

Garrett, Michael; McMahon, Mark

2013-01-01

This paper reports on research undertaken to determine the effectiveness of a 3D simulation environment used to train mining personnel in emergency evacuation procedures, designated the Fires in Underground Mines Evacuation Simulator (FUMES). Owing to the operational constraints of the mining facility, methods for measuring learning transfer were…

Population Validity for Educational Data Mining Models: A Case Study in Affect Detection

ERIC Educational Resources Information Center

Ocumpaugh, Jaclyn; Baker, Ryan; Gowda, Sujith; Heffernan, Neil; Heffernan, Cristina

2014-01-01

Information and communication technology (ICT)-enhanced research methods such as educational data mining (EDM) have allowed researchers to effectively model a broad range of constructs pertaining to the student, moving from traditional assessments of knowledge to assessment of engagement, meta-cognition, strategy and affect. The automated…

Reestablishing natural succession on acidic mine spoils at high elevations: long-term ecological restoration

Treesearch

Ray W. Brown; Michael C. Amacher; Walter F. Mueggler; Janice Kotuby-Amacher

2003-01-01

Methods for restoring native plant communities on acidic mine spoils at high elevations were evaluated in a "demonstration area" in the New World Mining District of southern Montana. Research plots installed in 1976 were assessed for 22 years and compared with adjacent native reference plant communities. A 1.5-acre (0.61-ha) area of mine spoils was shaped and...

Data Mining Research with the LSST

NASA Astrophysics Data System (ADS)

Borne, Kirk D.; Strauss, M. A.; Tyson, J. A.

2007-12-01

The LSST catalog database will exceed 10 petabytes, comprising several hundred attributes for 5 billion galaxies, 10 billion stars, and over 1 billion variable sources (optical variables, transients, or moving objects), extracted from over 20,000 square degrees of deep imaging in 5 passbands with thorough time domain coverage: 1000 visits over the 10-year LSST survey lifetime. The opportunities are enormous for novel scientific discoveries within this rich time-domain ultra-deep multi-band survey database. Data Mining, Machine Learning, and Knowledge Discovery research opportunities with the LSST are now under study, with a potential for new collaborations to develop to contribute to these investigations. We will describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. We also give some illustrative examples of current scientific data mining research in astronomy, and point out where new research is needed. In particular, the data mining research community will need to address several issues in the coming years as we prepare for the LSST data deluge. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night); multi-resolution methods for exploration of petascale databases; visual data mining algorithms for visual exploration of the data; indexing of multi-attribute multi-dimensional astronomical databases (beyond RA-Dec spatial indexing) for rapid querying of petabyte databases; and more. Finally, we will identify opportunities for synergistic collaboration between the data mining research group and the LSST Data Management and Science Collaboration teams.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

OVERBURDEN MINERALOGY AS RELATED TO GROUND-WATER CHEMICAL CHANGES IN COAL STRIP MINING

EPA Science Inventory

A research program was initiated to define and develop an inclusive, effective, and economical method for predicting potential ground-water quality changes resulting from the strip mining of coal in the Western United States. To utilize the predictive method, it is necessary to s...

Chapter 2: The forestry reclamation approach

Treesearch

Jim Burger; Don Graves; Patrick Angel; Vic Davis; Carl Zipper

2017-01-01

The Forestry Reclamation Approach (FRA) is a method for reclaiming coal-mined land to forest under the federal Surface Mining Control and Reclamation Act of 1977 (SMCRA). The FRA is based on knowledge gained from both scientific research and experience (Fig. 2-1). The FRA can achieve cost-effective regulatory compliance for mine operators while creating productive...

Comparison of different static methods for assessment of AMD generation potential in mining waste dumps in the Muteh Gold Mines, Iran.

PubMed

Mohammadi, Zohreh; Modabberi, Soroush; Jafari, Mohammad Reza; Ajayebi, Kimia Sadat

2015-06-01

Acid mine drainage (AMD) gives rise to several problems in sulfide-bearing mineral deposits whether in an ore body or in the mining wastes and tailings. Hence, several methods and parameters have been proposed to evaluate the acid-producing and acid-neutralizing potential of a material. This research compares common static methods for evaluation of acid-production potential of mining wastes in the Muteh gold mines by using 62 samples taken from six waste dumps around Senjedeh and Chah-Khatoun mines. According to a detailed mineralogical study, the waste materials are composed of mica-schist and quartz veins with a high amount of pyrite and are supposed to be susceptible to acid production, and upon a rainfall, they release acid drainage. All parameters introduced in different methods were calculated and compared in this research in order to predict the acid-generating and neutralization potential, including APP, NNP, MPA, NPR, and NAGpH. Based on the analytical results and calculation of different parameters, all methods are in a general consensus that DWS-02 and DWS-03 waste dumps are acid-forming which is clearly attributed to high content of pyrite in samples. DWS-04 is considered as non-acid forming in all methods except method 8 which is uncertain about its acid-forming potential and method 7 which considers a low potential for it. DWC-01 is acid-forming based on all methods except 8, 9, 10, and 11 which are also uncertain about its potential. The methods used are not reached to a compromise on DWS-01 and DWC-02 waste dumps. It is supposed that method 7 gives the conservationist results in all cases. Method 8 is unable to decide on some cases. It is recommended to use and rely on results provided by methods 1, 2, 3, and 12 for taking decisions for further studies. Therefore, according to the static tests used, the aforementioned criteria in selected methods can be used with much confidence as a rule of thumb estimation.

Identification of ex-sand mining area using optical and SAR imagery

NASA Astrophysics Data System (ADS)

Indriasari, Novie; Kusratmoko, Eko; Indra, Tito Latif; Julzarika, Atriyon

2018-05-01

Open mining activities in Sumedang Regency has been operated since 1984 impacted to degradation of environment due to large area of ex-mining. Therefore, identification of ex-mining area which generally been used for sand mining is crucial and important to detect and monitor recent environmental degradation impacted from the ex-mining activities. In this research, identification ex-sand mining area using optical and SAR data in Sumedang Regency will be discussed. We use Landsat 5 TM acquisition date August 01, 2009 and Landsat 8 OLI acquired on June 24, 2016 to identify location of sand mining area, processed using Tasselled Cap Trasformation (TCT), while the landform deformation approached using ALOS PALSAR in 2009 and ALOS PALSAR 2 in 2016 processed using SAR interferometry (InSAR) method. The results show that TCT and InSAR method can can be used to identify the areas of ex-sand mining clearly. In 2016 the total area of ex-mining were 352.92 Ha. The land deformation show that during 7 years period since 2009 has impacted to the deformation at 7 meters.

A study of unstable rock failures using finite difference and discrete element methods

NASA Astrophysics Data System (ADS)

Garvey, Ryan J.

Case histories in mining have long described pillars or faces of rock failing violently with an accompanying rapid ejection of debris and broken material into the working areas of the mine. These unstable failures have resulted in large losses of life and collapses of entire mine panels. Modern mining operations take significant steps to reduce the likelihood of unstable failure, however eliminating their occurrence is difficult in practice. Researchers over several decades have supplemented studies of unstable failures through the application of various numerical methods. The direction of the current research is to extend these methods and to develop improved numerical tools with which to study unstable failures in underground mining layouts. An extensive study is first conducted on the expression of unstable failure in discrete element and finite difference methods. Simulated uniaxial compressive strength tests are run on brittle rock specimens. Stable or unstable loading conditions are applied onto the brittle specimens by a pair of elastic platens with ranging stiffnesses. Determinations of instability are established through stress and strain histories taken for the specimen and the system. Additional numerical tools are then developed for the finite difference method to analyze unstable failure in larger mine models. Instability identifiers are established for assessing the locations and relative magnitudes of unstable failure through measures of rapid dynamic motion. An energy balance is developed which calculates the excess energy released as a result of unstable equilibria in rock systems. These tools are validated through uniaxial and triaxial compressive strength tests and are extended to models of coal pillars and a simplified mining layout. The results of the finite difference simulations reveal that the instability identifiers and excess energy calculations provide a generalized methodology for assessing unstable failures within potentially complex mine models. These combined numerical tools may be applied in future studies to design primary and secondary supports in bump-prone conditions, evaluate retreat mining cut sequences, asses pillar de-stressing techniques, or perform backanalyses on unstable failures in select mining layouts.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chironis, N.P.

This book contains a wealth of valuable information carefully selected and compiled from recent issues of Coal Age magazine. Much of the source material has been gathered by Coal Age Editors during their visits to coal mines, research establishments, universities and technical symposiums. Equally important are the articles and data contributed by over 50 top experts, many of whom are well known to the mining industry. Specifically, this easy-to-use handbook is divided into eleven key areas of underground mining. Here you will find the latest information on continuous mining techniques, longwall and shortwall methods and equipment, specialized mining and boringmore » systems, continuous haulage techniques, improved roof control and ventilation methods, mine communications and instrumentation, power systems, fire control methods, and new mining regulations. There is also a section on engineering and management considerations, including the modern use of computer terminals, practical techniques for picking leaders and for encouraging more safety consciousness in employees, factors affecting absenteeism, and some highly important financial considerations. All of this valuable information has been thoroughly indexed to provide immediate access to the specific data needed by the reader.« less

Mining of Business-Oriented Conversations at a Call Center

NASA Astrophysics Data System (ADS)

Takeuchi, Hironori; Nasukawa, Tetsuya; Watanabe, Hideo

Recently it has become feasible to transcribe textual records from telephone conversations at call centers by using automatic speech recognition. In this research, we extended a text mining system for call summary records and constructed a conversation mining system for the business-oriented conversations at the call center. To acquire useful business insights from the conversational data through the text mining system, it is critical to identify appropriate textual segments and expressions as the viewpoints to focus on. In the analysis of call summary data using a text mining system, some experts defined the viewpoints for the analysis by looking at some sample records and by preparing the dictionaries based on frequent keywords in the sample dataset. However with conversations it is difficult to identify such viewpoints manually and in advance because the target data consists of complete transcripts that are often lengthy and redundant. In this research, we defined a model of the business-oriented conversations and proposed a mining method to identify segments that have impacts on the outcomes of the conversations and can then extract useful expressions in each of these identified segments. In the experiment, we processed the real datasets from a car rental service center and constructed a mining system. With this system, we show the effectiveness of the method based on the defined conversation model.

Data mining in pharma sector: benefits.

PubMed

Ranjan, Jayanthi

2009-01-01

The amount of data getting generated in any sector at present is enormous. The information flow in the pharma industry is huge. Pharma firms are progressing into increased technology-enabled products and services. Data mining, which is knowledge discovery from large sets of data, helps pharma firms to discover patterns in improving the quality of drug discovery and delivery methods. The paper aims to present how data mining is useful in the pharma industry, how its techniques can yield good results in pharma sector, and to show how data mining can really enhance in making decisions using pharmaceutical data. This conceptual paper is written based on secondary study, research and observations from magazines, reports and notes. The author has listed the types of patterns that can be discovered using data mining in pharma data. The paper shows how data mining is useful in the pharma industry and how its techniques can yield good results in pharma sector. Although much work can be produced for discovering knowledge in pharma data using data mining, the paper is limited to conceptualizing the ideas and view points at this stage; future work may include applying data mining techniques to pharma data based on primary research using the available, famous significant data mining tools. Research papers and conceptual papers related to data mining in Pharma industry are rare; this is the motivation for the paper.

Reuse and Securing of Mining Waste : Need of the hour

NASA Astrophysics Data System (ADS)

Mehta, Neha; Dino, Giovanna; Ajmone-Marsan, Franco; De Luca, Domenico Antonio

2016-04-01

With recent advancements in technology and rising standards of living the demand for minerals has increased drastically. Increased reliance on mining industry has led to unmanageable challenges of Mining waste generated out of Mining and Quarrying activities. According to Statistics from EuroStat Mining and Quarrying generated 734 million Tons in Europe in 2012 which accounted for 29.19 % of the total waste, becoming second most important sector in terms of waste generation after Construction Industry. Mining waste can be voluminous and/ or chemically active and can cause environmental threats like groundwater pollution due to leaching of pollutants, surface water pollution due to runoffs during rainy season, river and ocean pollution due to intentional dumping of tailings by mining companies. Most of the big mining companies have not adopted policies against dumping of tailings in rivers and oceans. Deep Sea Tailings Placement (DSTP) is creating havoc in remote and pristine environment of deep-sea beds e.g. Bismarck Sea. Furthermore, mining waste is contaminating soil in nearby areas by disturbing soil microbial activity and other physio-chemical and biological properties of soil (e.g. Barruecopardo village - Spain). Mining waste stored in heaps and dams has led to many accidents and on an average, worldwide, there is one major accident in a year involving tailings dams (e.g. Myanmar, Brazil, 2015). Pollution due to tailings is causing local residents to relocate and become 'ecological migrants'. The above issues linked to mining waste makes reuse and securing of mining waste one of the urgent challenge to deal with. The studies done previously on mining show that most of the researches linked with mining waste reuse and securing are very site specific. For instance, the type of recovery method should not only provide environmental clean-up but also economic benefits to promise sustainability of the method. Environmental risk assessment of using mining waste as agricultural soils can depend on Bio-accumulation factor, Translocation factor of heavy metals, species of plant grown and type of the natural biota of the surroundings and effect of different exposure routes. This also leads to the fact that more research is required in this area. Accordingly the same problem statement was chosen as part of a PhD research Project. The PhD research is part of REMEDIATE project (A Marie Sklodowska-Curie Action Initial Training Network for Improved decision making in contaminated land site investigation and risk assessment, Grant Agreement No. 643087). In this project the researcher will select a mining site in Italy to find possible solutions to the environmental impact of mining waste collected there. The project will focus on 1) physical and chemical characterization of waste 2)environmental risk assessment study of the mining waste 3) impact of mining waste on water bodies and soil 4) to discover possible routes of reuse and recovery of minerals from the waste. Thus project focuses on environmental sustainability of mining waste reuse and clean up. Keywords : Mining waste ; environmental risk assessment ;reuse and recovery.

Clinical diabetes research using data mining: a Canadian perspective.

PubMed

Shah, Baiju R; Lipscombe, Lorraine L

2015-06-01

With the advent of the digitization of large amounts of information and the computer power capable of analyzing this volume of information, data mining is increasingly being applied to medical research. Datasets created for administration of the healthcare system provide a wealth of information from different healthcare sectors, and Canadian provinces' single-payer universal healthcare systems mean that data are more comprehensive and complete in this country than in many other jurisdictions. The increasing ability to also link clinical information, such as electronic medical records, laboratory test results and disease registries, has broadened the types of data available for analysis. Data-mining methods have been used in many different areas of diabetes clinical research, including classic epidemiology, effectiveness research, population health and health services research. Although methodologic challenges and privacy concerns remain important barriers to using these techniques, data mining remains a powerful tool for clinical research. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Soil preparation methods promoting ectomycorrhizal colonization and American chestnut Castanea dentata establishment in coal mine restoration

Treesearch

Jenise M. Bauman; Carolyn H. Keiffer; Shiv Hiremath; Brian C. McCarthy

2013-01-01

The objective of this research was to evaluate soil subsurface methods that may aid in seedling establishment and encourage root colonization from a diverse group of ectomycorrhizal (ECM) fungi during restoration projects. American chestnut Castanea dentata Marsh. Borkh. and backcrossed chestnuts seedlings were planted on a reclaimed coal mine site...

A Study on Environmental Research Trends Using Text-Mining Method - Focus on Spatial information and ICT -

NASA Astrophysics Data System (ADS)

Lee, M. J.; Oh, K. Y.; Joung-ho, L.

2016-12-01

Recently there are many research about analysing the interaction between entities by text-mining analysis in various fields. In this paper, we aimed to quantitatively analyse research-trends in the area of environmental research relating either spatial information or ICT (Information and Communications Technology) by Text-mining analysis. To do this, we applied low-dimensional embedding method, clustering analysis, and association rule to find meaningful associative patterns of key words frequently appeared in the articles. As the authors suppose that KCI (Korea Citation Index) articles reflect academic demands, total 1228 KCI articles that have been published from 1996 to 2015 were reviewed and analysed by Text-mining method. First, we derived KCI articles from NDSL(National Discovery for Science Leaders) site. And then we pre-processed their key-words elected from abstract and then classified those in separable sectors. We investigated the appearance rates and association rule of key-words for articles in the two fields: spatial-information and ICT. In order to detect historic trends, analysis was conducted separately for the four periods: 1996-2000, 2001-2005, 2006-2010, 2011-2015. These analysis were conducted with the usage of R-software. As a result, we conformed that environmental research relating spatial information mainly focused upon such fields as `GIS(35%)', `Remote-Sensing(25%)', `environmental theme map(15.7%)'. Next, `ICT technology(23.6%)', `ICT service(5.4%)', `mobile(24%)', `big data(10%)', `AI(7%)' are primarily emerging from environmental research relating ICT. Thus, from the analysis results, this paper asserts that research trends and academic progresses are well-structured to review recent spatial information and ICT technology and the outcomes of the analysis can be an adequate guidelines to establish environment policies and strategies. KEY WORDS: Big data, Test-mining, Environmental research, Spatial-information, ICT Acknowledgements: The authors appreciate the support that this study has received from `Building application frame of environmental issues, to respond to the latest ICT trends'.

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

Weighted mining of massive collections of [Formula: see text]-values by convex optimization.

PubMed

Dobriban, Edgar

2018-06-01

Researchers in data-rich disciplines-think of computational genomics and observational cosmology-often wish to mine large bodies of [Formula: see text]-values looking for significant effects, while controlling the false discovery rate or family-wise error rate. Increasingly, researchers also wish to prioritize certain hypotheses, for example, those thought to have larger effect sizes, by upweighting, and to impose constraints on the underlying mining, such as monotonicity along a certain sequence. We introduce Princessp , a principled method for performing weighted multiple testing by constrained convex optimization. Our method elegantly allows one to prioritize certain hypotheses through upweighting and to discount others through downweighting, while constraining the underlying weights involved in the mining process. When the [Formula: see text]-values derive from monotone likelihood ratio families such as the Gaussian means model, the new method allows exact solution of an important optimal weighting problem previously thought to be non-convex and computationally infeasible. Our method scales to massive data set sizes. We illustrate the applications of Princessp on a series of standard genomics data sets and offer comparisons with several previous 'standard' methods. Princessp offers both ease of operation and the ability to scale to extremely large problem sizes. The method is available as open-source software from github.com/dobriban/pvalue_weighting_matlab (accessed 11 October 2017).

Technologies for Decreasing Mining Losses

NASA Astrophysics Data System (ADS)

Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin

2013-12-01

In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.

Geographical Information System Model for Potential Mines Data Management Presentation in Kabupaten Gorontalo

NASA Astrophysics Data System (ADS)

Roviana, D.; Tajuddin, A.; Edi, S.

2017-03-01

Mining potential in Indonesian is very abundant, ranging from Sabang to Marauke. Kabupaten Gorontalo is one of many places in Indonesia that have different types of minerals and natural resources that can be found in every district. The abundant of mining potential must be balanced with good management and ease of getting information by investors. The current issue is, (1) ways of presenting data/information about potential mines area is still manually (the maps that already capture from satellite image, then printed and attached to information board in the office) it caused the difficulties of getting information; (2) the high cost of maps printing; (3) the difficulties of regency leader (bupati) to obtain information for strategic decision making about mining potential. The goal of this research is to build a model of Geographical Information System that could provide data management of potential mines, so that the investors could easily get information according to their needs. To achieve that goal Research and Development method is used. The result of this research, is a model of Geographical Information System that implemented in an application to presenting data management of mines.

A novel approach to generating CER hypotheses based on mining clinical data.

PubMed

Zhang, Shuo; Li, Lin; Yu, Yiqin; Sun, Xingzhi; Xu, Linhao; Zhao, Wei; Teng, Xiaofei; Pan, Yue

2013-01-01

Comparative effectiveness research (CER) is a scientific method of investigating the effectiveness of alternative intervention methods. In a CER study, clinical researchers typically start with a CER hypothesis, and aim to evaluate it by applying a series of medical statistical methods. Traditionally, the CER hypotheses are defined manually by clinical researchers. This makes the task of hypothesis generation very time-consuming and the quality of hypothesis heavily dependent on the researchers' skills. Recently, with more electronic medical data being collected, it is highly promising to apply the computerized method for discovering CER hypotheses from clinical data sets. In this poster, we proposes a novel approach to automatically generating CER hypotheses based on mining clinical data, and presents a case study showing that the approach can facilitate clinical researchers to identify potentially valuable hypotheses and eventually define high quality CER studies.

Adaptive semantic tag mining from heterogeneous clinical research texts.

PubMed

Hao, T; Weng, C

2015-01-01

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

Research of land resources comprehensive utilization of coal mining in plain area based on GIS: case of Panyi Coal Mine of Huainan Mining Group Corp.

NASA Astrophysics Data System (ADS)

Dai, Chunxiao; Wang, Songhui; Sun, Dian; Chen, Dong

2007-06-01

The result of land use in coalfield is important to sustainable development in resourceful city. For surface morphology being changed by subsidence, the mining subsidence becomes the main problem to land use with the negative influence of ecological environment, production and steadily develop in coal mining areas. Taking Panyi Coal Mine of Huainan Mining Group Corp as an example, this paper predicted and simulated the mining subsidence in Matlab environment on the basis of the probability integral method. The change of land use types of early term, medium term and long term was analyzed in accordance with the results of mining subsidence prediction with GIS as a spatial data management and spatial analysis tool. The result of analysis showed that 80% area in Panyi Coal Mine be affected by mining subsidence and 52km2 perennial waterlogged area was gradually formed. The farmland ecosystem was gradually turned into wetland ecosystem in most study area. According to the economic and social development and natural conditions of mining area, calculating the ecological environment, production and people's livelihood, this paper supplied the plan for comprehensive utilization of land resource. In this plan, intervention measures be taken during the coal mining and the mining subsidence formation and development, and this method can solve the problems of Land use at the relative low cost.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

Knowledge mining from clinical datasets using rough sets and backpropagation neural network.

PubMed

Nahato, Kindie Biredagn; Harichandran, Khanna Nehemiah; Arputharaj, Kannan

2015-01-01

The availability of clinical datasets and knowledge mining methodologies encourages the researchers to pursue research in extracting knowledge from clinical datasets. Different data mining techniques have been used for mining rules, and mathematical models have been developed to assist the clinician in decision making. The objective of this research is to build a classifier that will predict the presence or absence of a disease by learning from the minimal set of attributes that has been extracted from the clinical dataset. In this work rough set indiscernibility relation method with backpropagation neural network (RS-BPNN) is used. This work has two stages. The first stage is handling of missing values to obtain a smooth data set and selection of appropriate attributes from the clinical dataset by indiscernibility relation method. The second stage is classification using backpropagation neural network on the selected reducts of the dataset. The classifier has been tested with hepatitis, Wisconsin breast cancer, and Statlog heart disease datasets obtained from the University of California at Irvine (UCI) machine learning repository. The accuracy obtained from the proposed method is 97.3%, 98.6%, and 90.4% for hepatitis, breast cancer, and heart disease, respectively. The proposed system provides an effective classification model for clinical datasets.

Text mining a self-report back-translation.

PubMed

Blanch, Angel; Aluja, Anton

2016-06-01

There are several recommendations about the routine to undertake when back translating self-report instruments in cross-cultural research. However, text mining methods have been generally ignored within this field. This work describes a text mining innovative application useful to adapt a personality questionnaire to 12 different languages. The method is divided in 3 different stages, a descriptive analysis of the available back-translated instrument versions, a dissimilarity assessment between the source language instrument and the 12 back-translations, and an item assessment of item meaning equivalence. The suggested method contributes to improve the back-translation process of self-report instruments for cross-cultural research in 2 significant intertwined ways. First, it defines a systematic approach to the back translation issue, allowing for a more orderly and informed evaluation concerning the equivalence of different versions of the same instrument in different languages. Second, it provides more accurate instrument back-translations, which has direct implications for the reliability and validity of the instrument's test scores when used in different cultures/languages. In addition, this procedure can be extended to the back-translation of self-reports measuring psychological constructs in clinical assessment. Future research works could refine the suggested methodology and use additional available text mining tools. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Supporting Solar Physics Research via Data Mining

NASA Astrophysics Data System (ADS)

Angryk, Rafal; Banda, J.; Schuh, M.; Ganesan Pillai, K.; Tosun, H.; Martens, P.

2012-05-01

In this talk we will briefly introduce three pillars of data mining (i.e. frequent patterns discovery, classification, and clustering), and discuss some possible applications of known data mining techniques which can directly benefit solar physics research. In particular, we plan to demonstrate applicability of frequent patterns discovery methods for the verification of hypotheses about co-occurrence (in space and time) of filaments and sigmoids. We will also show how classification/machine learning algorithms can be utilized to verify human-created software modules to discover individual types of solar phenomena. Finally, we will discuss applicability of clustering techniques to image data processing.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Chapter 3: Selecting materials for mine soil construction when establishing forests on Appalachian mined lands

Treesearch

Jeff Skousen; Carl Zipper; Jim Burger; Christopher Barton; Patrick. Angel

2017-01-01

The Forestry Reclamation Approach (FRA), a method for reclaiming coal-mined land to forest (Chapter 2, this volume), is based on research, knowledge, and experience of forest soil scientists and reclamation practitioners. Step 1 of the FRA is to create a suitable rooting medium for good tree growth that is no less than 4 feet deep and consists of topsoil, weathered...

Geotechnical approach for occupational safety risk analysis of critical slope in open pit mining as implication for earthquake hazard

NASA Astrophysics Data System (ADS)

Munirwansyah; Irsyam, Masyhur; Munirwan, Reza P.; Yunita, Halida; Zulfan Usrina, M.

2018-05-01

Occupational safety and health (OSH) is a planned effort to prevent accidents and diseases caused by work. In conducting mining activities often occur work accidents caused by unsafe field conditions. In open mine area, there is often a slump due to unstable slopes, which can disrupt the activities and productivity of mining companies. Based on research on stability of open pit slopes conducted by Febrianti [8], the Meureubo coal mine located in Aceh Barat district, on the slope of mine was indicated unsafe slope conditions, it will be continued research on OSH for landslide which is to understand the stability of the excavation slope and the shape of the slope collapse. Plaxis software was used for this research. After analyzing the slope stability and the effect of landslide on OSH with Job Safety Analysis (JSA) method, to identify the hazard to work safety, risk management analysis will be conducted to classified hazard level and its handling technique. This research aim is to know the level of risk of work accident at the company and its prevention effort. The result of risk analysis research is very high-risk value that is > 350 then the activity must be stopped until the risk can be reduced to reach the risk value limit < 20 which is allowed or accepted.

ABC for AIDS prevention in Guinea: migrant gold mining communities address their risks.

PubMed

Kis, Adam Daniel

2010-04-01

Contrary to expectation when compared with other migrant mining zones of sub-Saharan Africa, the nation of Guinea has a comparatively low and stable HIV rate. In addition, the regions with the largest gold, diamond, and bauxite mining operations report the lowest HIV rates within the country. This research set out to explain practices and beliefs within gold mining communities near Siguiri, Guinea--the highest-producing gold mining zone in the country--that may contribute to this phenomenon, particularly as they relate to the Abstinence, Be faithful, use a Condom approach to AIDS prevention. Structured interviews on a randomly selected sample of 460 adults and regular visitation to 16 pharmacies and health clinics within the mining zone yielded data showing that abstinence and condom use are minimally practiced for AIDS prevention. Instead, faithfulness to partners was overwhelmingly reported as the method of choice for AIDS avoidance. In addition, this research explored ways in which local conceptions of fidelity differed from those generally understood in other contexts, including engagement in short-term marriages at the gold mining sites.

Automated Text Data Mining Analysis of Five Decades of Educational Leadership Research Literature: Probabilistic Topic Modeling of "EAQ" Articles From 1965 to 2014

ERIC Educational Resources Information Center

Wang, Yinying; Bowers, Alex J.; Fikis, David J.

2017-01-01

Purpose: The purpose of this study is to describe the underlying topics and the topic evolution in the 50-year history of educational leadership research literature. Method: We used automated text data mining with probabilistic latent topic models to examine the full text of the entire publication history of all 1,539 articles published in…

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

Research on position and orientation measurement method for roadheader based on vision/INS

NASA Astrophysics Data System (ADS)

Yang, Jinyong; Zhang, Guanqin; Huang, Zhe; Ye, Yaozhong; Ma, Bowen; Wang, Yizhong

2018-01-01

Roadheader which is a kind of special equipment for large tunnel excavation has been widely used in Coal Mine. It is one of the main mechanical-electrical equipment for mine production and also has been regarded as the core equipment for underground tunnel driving construction. With the deep application of the rapid driving system, underground tunnel driving methods with higher automation level are required. In this respect, the real-time position and orientation measurement technique for roadheader is one of the most important research contents. For solving the problem of position and orientation measurement automatically in real time for roadheaders, this paper analyses and compares the features of several existing measuring methods. Then a new method based on the combination of monocular vision and strap down inertial navigation system (SINS) would be proposed. By realizing five degree-of-freedom (DOF) measurement of real-time position and orientation of roadheader, this method has been verified by the rapid excavation equipment in Daliuta coal mine. Experiment results show that the accuracy of orientation measurement is better than 0.1°, the standard deviation of static drift is better than 0.25° and the accuracy of position measurement is better than 1cm. It is proved that this method can be used in real-time position and orientation measurement application for roadheader which has a broad prospect in coal mine engineering.

Investigating MOOCs through Blog Mining

ERIC Educational Resources Information Center

Chen, Yong

2014-01-01

MOOCs (massive open online course) is a disruptive innovation and a current buzzword in higher education. However, the discussion of MOOCs is disparate, fragmented, and distributed among different outlets. Systematic, extensively published research on MOOCs is unavailable. This paper adopts a novel method called blog mining to analyze MOOCs. The…

Guidelines for geophysical investigations of mines under highways : mine research project - GUE 70 - 14.10 - PID No. 18459 : [report].

DOT National Transportation Integrated Search

2003-06-01

This document discusses the results of geophysical investigation methods conducted along : Interstate Route 70 (IR-70) under a contract with the Ohio Department of Transportation : (ODOT). The specific site conditions, as determined by the investigat...

Web mining in soft computing framework: relevance, state of the art and future directions.

PubMed

Pal, S K; Talwar, V; Mitra, P

2002-01-01

The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state of the art. The reason for considering Web mining, a separate field from data mining, is explained. The limitations of some of the existing Web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) are highlighted. A survey of the existing literature on "soft Web mining" is provided along with the commercially available systems. The prospective areas of Web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft Web mining" systems is explained. An extensive bibliography is also provided.

Status and Prospects for Developing Electromagnetic Methods and Facilities for Engineer Reconnaissance in Russia

NASA Astrophysics Data System (ADS)

Potekaev, A. I.; Donchenko, V. A.; Zambalov, S. D.; Parvatov, G. N.; Smirnov, I. M.; Svetlichnyi, V. A.; Yakubov, V. P.; Yakovlev, I. A.

2018-03-01

An analysis of the most effective methods, techniques and scientific-research developments of induction mine detectors is performed, their comparative tactical-technical characteristics are reported, and priority avenues for further research are outlined.

Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques.

PubMed

Ghaibeh, A Ammar; Kasem, Asem; Ng, Xun Jin; Nair, Hema Latha Krishna; Hirose, Jun; Thiruchelvam, Vinesh

2018-01-01

The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.

Effective integrated frameworks for assessing mining sustainability.

PubMed

Virgone, K M; Ramirez-Andreotta, M; Mainhagu, J; Brusseau, M L

2018-05-28

The objectives of this research are to review existing methods used for assessing mining sustainability, analyze the limited prior research that has evaluated the methods, and identify key characteristics that would constitute an enhanced sustainability framework that would serve to improve sustainability reporting in the mining industry. Five of the most relevant frameworks were selected for comparison in this analysis, and the results show that there are many commonalities among the five, as well as some disparities. In addition, relevant components are missing from all five. An enhanced evaluation system and framework were created to provide a more holistic, comprehensive method for sustainability assessment and reporting. The proposed framework has five components that build from and encompass the twelve evaluation characteristics used in the analysis. The components include Foundation, Focus, Breadth, Quality Assurance, and Relevance. The enhanced framework promotes a comprehensive, location-specific reporting approach with a concise set of well-defined indicators. Built into the framework is quality assurance, as well as a defined method to use information from sustainability reports to inform decisions. The framework incorporates human health and socioeconomic aspects via initiatives such as community-engaged research, economic valuations, and community-initiated environmental monitoring.

Review of Studies of Mechanoelectrical Transformations in Rocks in Russia and Abroad

NASA Astrophysics Data System (ADS)

Pomishin, E.; Yavorovich, L.

2016-06-01

The problem of monitoring and forecast of dynamic manifestations of rock masses becomes immediate in the mining industry because of the growth of mining work intensity and changeover to the mining operations in deeper levels. The article presents a short review of the scientific works of foreign researchers for more complete and in-depth study of geophysical methods of control of the stress-strain state and bump hazard of rock masses.

Optical method for continuous monitoring of dust deposition in mine's entry / Optyczna metoda ciągłego pomiaru intensywności osiadania pyłu węglowego w wyrobisku górniczym

NASA Astrophysics Data System (ADS)

2012-12-01

The paper presents factors determining dust explosion hazards occurring in underground hard coal mines. The authors described the mechanism of transport and deposition of dust in mines entries and previous research on this topic. The paper presents a method of determination of depositing dust distribution during mining and presents the way to use it to assess coal dust explosion risk. The presented method of calculating the intensity of coal dust deposition is based on continuous monitoring of coal dust concentrations with use of optical sensors. Mathematical model of the distribution of the average coal dust concentration was created. Presented method allows to calculate the intensity of coal dust deposition in a continuous manner. Additionally, the authors presented the PŁ-2 stationary optical dust sampler, used in the study, connected to the monitoring system in the mine. The article features the results of studies conducted in the return air courses of the active longwalls, and the results of calculations of dust deposition intensity carried out with the use of the presented method.

Web Mining: Machine Learning for Web Applications.

ERIC Educational Resources Information Center

Chen, Hsinchun; Chau, Michael

2004-01-01

Presents an overview of machine learning research and reviews methods used for evaluating machine learning systems. Ways that machine-learning algorithms were used in traditional information retrieval systems in the "pre-Web" era are described, and the field of Web mining and how machine learning has been used in different Web mining…

Use of electrical resistivity to detect underground mine voids in Ohio : research implementation plan.

DOT National Transportation Integrated Search

2005-09-01

This project was a natural extension of the 1996-1997 void detection work completed by the USGS for : ODOT. This earlier project was entitled Detection of Underground Mine Voids in Ohio by Use of : Geophysical Methods and was published as U. S....

Using data mining to segment healthcare markets from patients' preference perspectives.

PubMed

Liu, Sandra S; Chen, Jie

2009-01-01

This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics. Data were derived from a number of individuals who received in-patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables. Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles. The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters. Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.

AstroML: Python-powered Machine Learning for Astronomy

NASA Astrophysics Data System (ADS)

Vander Plas, Jake; Connolly, A. J.; Ivezic, Z.

2014-01-01

As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.org) provides a common repository for practical examples of the data mining and machine learning tools used and developed by astronomical researchers, written in Python. The astroML module contains a host of general-purpose data analysis and machine learning routines, loaders for openly-available astronomical datasets, and fast implementations of specific computational methods often used in astronomy and astrophysics. The associated website features hundreds of examples of these routines being used for analysis of real astronomical datasets, while the associated textbook provides a curriculum resource for graduate-level courses focusing on practical statistics, machine learning, and data mining approaches within Astronomical research. This poster will highlight several of the more powerful and unique examples of analysis performed with astroML, all of which can be reproduced in their entirety on any computer with the proper packages installed.

An evaluation of processing InSAR Sentinel-1A/B data for correlation of mining subsidence with mining induced tremors in the Upper Silesian Coal Basin (Poland)

NASA Astrophysics Data System (ADS)

Krawczyk, Artur; Grzybek, Radosław

2018-01-01

The Satellite Radar Interferometry is one of the common methods that allow to measure the land subsidence caused by the underground black coal excavation. The interferometry images processed from the repeat-pass Synthetic Aperture Radar (SAR) systems give the spatial image of the terrain subjected to the surface subsidence over mining areas. Until now, the InSAR methods using data from the SAR Systems like ERS-1/ERS-2 and Envisat-1 were limited to a repeat-pass cycle of 35-day only. Recently, the ESA launched Sentinel-1A and 1B, and together they can provide the InSAR coverage in a 6-day repeat cycle. The studied area was the Upper Silesian Coal Basin in Poland, where the underground coal mining causes continuous subsidence of terrain surface and mining tremors (mine-induced seismicity). The main problem was with overlapping the subsidence caused by the mining exploitation with the epicentre tremors. Based on the Sentinel SAR images, research was done in regard to the correlation between the short term ground subsidence range border and the mine-induced seismicity epicentres localisation.

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

According to the problem that traditional chemical methods to the mine water source identification takes a long time, put forward a method for rapid source identification system of mine water inrush based on the technology of laser induced fluorescence (LIF). Emphatically analyzes the basic principle of LIF technology. The hardware composition of LIF system are analyzed and the related modules were selected. Through the fluorescence experiment with the water samples of coal mine in the LIF system, fluorescence spectra of water samples are got. Traditional water source identification mainly according to the ion concentration representative of the water, but it is hard to analysis the ion concentration of the water from the fluorescence spectra. This paper proposes a simple and practical method of rapid identification of water by fluorescence spectrum, which measure the space distance between unknown water samples and standard samples, and then based on the clustering analysis, the category of the unknown water sample can be get. Water source identification for unknown samples verified the reliability of the LIF system, and solve the problem that the current coal mine can't have a better real-time and online monitoring on water inrush, which is of great significance for coal mine safety in production.

Mining and beneficiation: A review of possible lunar applications

NASA Technical Reports Server (NTRS)

Chamberlain, Peter G.

1991-01-01

Successful exploration of Mars and outer space may require base stations strategically located on the Moon. Such bases must develop a certain self-sufficiency, particularly in the critical life support materials, fuel components, and construction materials. Technology is reviewed for the first steps in lunar resource recovery-mining and beneficiation. The topic is covered in three main categories: site selection; mining; and beneficiation. It will also include (in less detail) in-situ processes. The text described mining technology ranging from simple diggings and hauling vehicles (the strawman) to more specialized technology including underground excavation methods. The section of beneficiation emphasizes dry separation techniques and methods of sorting the ore by particle size. In-situ processes, chemical and thermal, are identified to stimulate further thinking by future researchers.

TCGA4U: A Web-Based Genomic Analysis Platform To Explore And Mine TCGA Genomic Data For Translational Research.

PubMed

Huang, Zhenzhen; Duan, Huilong; Li, Haomin

2015-01-01

Large-scale human cancer genomics projects, such as TCGA, generated large genomics data for further study. Exploring and mining these data to obtain meaningful analysis results can help researchers find potential genomics alterations that intervene the development and metastasis of tumors. We developed a web-based gene analysis platform, named TCGA4U, which used statistics methods and models to help translational investigators explore, mine and visualize human cancer genomic characteristic information from the TCGA datasets. Furthermore, through Gene Ontology (GO) annotation and clinical data integration, the genomic data were transformed into biological process, molecular function, cellular component and survival curves to help researchers identify potential driver genes. Clinical researchers without expertise in data analysis will benefit from such a user-friendly genomic analysis platform.

Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

NASA Astrophysics Data System (ADS)

Ayuningrum, Theresia Vika; Purnaweni, Hartuti

2018-02-01

Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

Recent developments in the reclamation of surface mined lands

USGS Publications Warehouse

Sharma, K.D.; Gough, L.P.; Kumar, S.; Sharma, B.K.; Saxena, S.K.

1997-01-01

A broad review of mine land reclamation problems and challenges in arid lands is presented with special emphasis on work recently completed in India. The economics of mining in the Indian Desert is second only to agriculture in importance. Lands disturbed by mining, however, have only recently been the focus of reclamation attempts. Studies were made and results compiled of problems associated with germplasm selection, soil, plant and overburden characterization and manipulation, plant establishment methods utilized, soil amendment needs, use and conservation of available water and the evaluation of ecosystem sustainability. Emphasis is made of the need for multi-disciplinary approaches to mine land reclamation research and for the long-term monitoring of reclamation success.

Target-Based Maintenance of Privacy Preserving Association Rules

ERIC Educational Resources Information Center

Ahluwalia, Madhu V.

2011-01-01

In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association rules. This research fills this gap by describing a method based on discrete wavelet transform (DWT) to protect input data privacy while preserving…

[Research of bleeding volume and method in blood-letting acupuncture therapy based on data mining].

PubMed

Liu, Xin; Jia, Chun-Sheng; Wang, Jian-Ling; Du, Yu-Zhu; Zhang, Xiao-Xu; Shi, Jing; Li, Xiao-Feng; Sun, Yan-Hui; Zhang, Shen; Zhang, Xuan-Ping; Gang, Wei-Juan

2014-03-01

Through computer-based technology and data mining method, with treatment in cases of bloodletting acupuncture therapy in collected literature as sample data, the association rule in data mining was applied. According to self-built database platform, the data was input, arranged and summarized, and eventually required data was acquired to perform the data mining of bleeding volume and method in blood-letting acupuncture therapy, which summarized its application rules and clinical values to provide better guide for clinical practice. There were 9 kinds of blood-letting tools in the literature, in which the frequency of three-edge needle was the highest, accounting for 84.4% (1239/1468). The bleeding volume was classified into six levels, in which less volume (less than 0.1 mL) had the highest frequency (401 times). According to the results of the data mining, blood-letting acupuncture therapy was widely applied in clinical practice of acupuncture, in which use of three-edge needle and less volume (less than 0.1 mL) of blood were the most common, however, there was no central tendency in general.

Field Assessment of Enclosed Cab Filtration System Performance Using Particle Counting Measurements

PubMed Central

Organiscak, John A.; Cecala, Andrew B.; Noll, James D.

2015-01-01

Enclosed cab filtration systems are typically used on mobile mining equipment to reduce miners’ exposure to airborne dust generated during mining operations. The National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) has recently worked with a mining equipment manufacturer to examine a new cab filtration system design for underground industrial minerals equipment. This cab filtration system uses a combination of three particulate filters to reduce equipment operators’ exposure to dust and diesel particulates present in underground industrial mineral mines. NIOSH initially examined this cab filtration system using a two-instrument particle counting method at the equipment company’s manufacturing shop facility to assess several alternative filters. This cab filtration system design was further studied on several pieces of equipment during a two- to seven-month period at two underground limestone mines. The two-instrument particle counting method was used outside the underground mine at the end of the production shifts to regularly test the cabs’ long-term protection factor performance with particulates present in the ambient air. This particle counting method showed that three of the four cabs achieved protection factors greater than 1,000 during the field studies. The fourth cab did not perform at this level because it had a damaged filter in the system. The particle counting measurements of submicron particles present in the ambient air were shown to be a timely and useful quantification method in assessing cab performance during these field studies. PMID:23915268

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Occupational respiratory diseases in the South African mining industry

PubMed Central

Nelson, Gill

2013-01-01

Background Crystalline silica and asbestos are common minerals that occur throughout South Africa, exposure to either causes respiratory disease. Most studies on silicosis in South Africa have been cross-sectional and long-term trends have not been reported. Although much research has been conducted on the health effects of silica dust and asbestos fibre in the gold-mining and asbestos-mining sectors, little is known about their health effects in other mining sectors. Objective The aims of this thesis were to describe silicosis trends in gold miners over three decades, and to explore the potential for diamond mine workers to develop asbestos-related diseases and platinum mine workers to develop silicosis. Methods Mine workers for the three sub-studies were identified from a mine worker autopsy database at the National Institute for Occupational Health. Results From 1975 to 2007, the proportions of white and black gold mine workers with silicosis increased from 18 to 22% and from 3 to 32% respectively. Cases of diamond and platinum mine workers with asbestos-related diseases and silicosis, respectively, were also identified. Conclusion The trends in silicosis in gold miners at autopsy clearly demonstrate the failure of the gold mines to adequately control dust and prevent occupational respiratory disease. The two case series of diamond and platinum mine workers contribute to the evidence for the risk of asbestos-related diseases in diamond mine workers and silicosis in platinum mine workers, respectively. The absence of reliable environmental dust measurements and incomplete work history records impedes occupational health research in South Africa because it is difficult to identify and/or validate sources of dust exposure that may be associated with occupational respiratory disease. PMID:23364097

Applying operational research and data mining to performance based medical personnel motivation system.

PubMed

Niaksu, Olegas; Zaptorius, Jonas

2014-01-01

This paper presents the methodology suitable for creation of a performance related remuneration system in healthcare sector, which would meet requirements for efficiency and sustainable quality of healthcare services. Methodology for performance indicators selection, ranking and a posteriori evaluation has been proposed and discussed. Priority Distribution Method is applied for unbiased performance criteria weighting. Data mining methods are proposed to monitor and evaluate the results of motivation system.We developed a method for healthcare specific criteria selection consisting of 8 steps; proposed and demonstrated application of Priority Distribution Method for the selected criteria weighting. Moreover, a set of data mining methods for evaluation of the motivational system outcomes was proposed. The described methodology for calculating performance related payment needs practical approbation. We plan to develop semi-automated tools for institutional and personal performance indicators monitoring. The final step would be approbation of the methodology in a healthcare facility.

Deformation Failure Characteristics of Coal Body and Mining Induced Stress Evolution Law

PubMed Central

Wen, Zhijie; Wen, Jinhao; Shi, Yongkui; Jia, Chuanyang

2014-01-01

The results of the interaction between coal failure and mining pressure field evolution during mining are presented. Not only the mechanical model of stope and its relative structure division, but also the failure and behavior characteristic of coal body under different mining stages are built and demonstrated. Namely, the breaking arch and stress arch which influence the mining area are quantified calculated. A systematic method of stress field distribution is worked out. All this indicates that the pore distribution of coal body with different compressed volume has fractal character; it appears to be the linear relationship between propagation range of internal stress field and compressed volume of coal body and nonlinear relationship between the range of outburst coal mass and the number of pores which is influenced by mining pressure. The results provide theory reference for the research on the range of mining-induced stress and broken coal wall. PMID:24967438

Knowledge based word-concept model estimation and refinement for biomedical text mining.

PubMed

Jimeno Yepes, Antonio; Berlanga, Rafael

2015-02-01

Text mining of scientific literature has been essential for setting up large public biomedical databases, which are being widely used by the research community. In the biomedical domain, the existence of a large number of terminological resources and knowledge bases (KB) has enabled a myriad of machine learning methods for different text mining related tasks. Unfortunately, KBs have not been devised for text mining tasks but for human interpretation, thus performance of KB-based methods is usually lower when compared to supervised machine learning methods. The disadvantage of supervised methods though is they require labeled training data and therefore not useful for large scale biomedical text mining systems. KB-based methods do not have this limitation. In this paper, we describe a novel method to generate word-concept probabilities from a KB, which can serve as a basis for several text mining tasks. This method not only takes into account the underlying patterns within the descriptions contained in the KB but also those in texts available from large unlabeled corpora such as MEDLINE. The parameters of the model have been estimated without training data. Patterns from MEDLINE have been built using MetaMap for entity recognition and related using co-occurrences. The word-concept probabilities were evaluated on the task of word sense disambiguation (WSD). The results showed that our method obtained a higher degree of accuracy than other state-of-the-art approaches when evaluated on the MSH WSD data set. We also evaluated our method on the task of document ranking using MEDLINE citations. These results also showed an increase in performance over existing baseline retrieval approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Data mining: Potential applications in research on nutrition and health.

PubMed

Batterham, Marijka; Neale, Elizabeth; Martin, Allison; Tapsell, Linda

2017-02-01

Data mining enables further insights from nutrition-related research, but caution is required. The aim of this analysis was to demonstrate and compare the utility of data mining methods in classifying a categorical outcome derived from a nutrition-related intervention. Baseline data (23 variables, 8 categorical) on participants (n = 295) in an intervention trial were used to classify participants in terms of meeting the criteria of achieving 10 000 steps per day. Results from classification and regression trees (CARTs), random forests, adaptive boosting, logistic regression, support vector machines and neural networks were compared using area under the curve (AUC) and error assessments. The CART produced the best model when considering the AUC (0.703), overall error (18%) and within class error (28%). Logistic regression also performed reasonably well compared to the other models (AUC 0.675, overall error 23%, within class error 36%). All the methods gave different rankings of variables' importance. CART found that body fat, quality of life using the SF-12 Physical Component Summary (PCS) and the cholesterol: HDL ratio were the most important predictors of meeting the 10 000 steps criteria, while logistic regression showed the SF-12PCS, glucose levels and level of education to be the most significant predictors (P ≤ 0.01). Differing outcomes suggest caution is required with a single data mining method, particularly in a dataset with nonlinear relationships and outliers and when exploring relationships that were not the primary outcomes of the research. © 2017 Dietitians Association of Australia.

Development of a Workbench to Address the Educational Data Mining Bottleneck

ERIC Educational Resources Information Center

Rodrigo, Ma. Mercedes T.; Baker, Ryan S. J. d.; McLaren, Bruce M.; Jayme, Alejandra; Dy, Thomas T.

2012-01-01

In recent years, machine-learning software packages have made it easier for educational data mining researchers to create real-time detectors of cognitive skill as well as of metacognitive and motivational behavior that can be used to improve student learning. However, there remain challenges to overcome for these methods to become available to…

Close-range photogrammetry in underground mining ground control

NASA Astrophysics Data System (ADS)

Benton, Donovan J.; Chambers, Amy J.; Raffaldi, Michael J.; Finley, Seth A.; Powers, Mark J.

2016-09-01

Monitoring underground mine deformation and support conditions has traditionally involved visual inspection and geotechnical instrumentation. Monitoring displacements with conventional instrumentation can be expensive and time-consuming, and the number of locations that can be effectively monitored is generally limited. Moreover, conventional methods typically produce vector rather than tensor descriptions of geometry changes. Tensor descriptions can provide greater insight into hazardous ground movements, particularly in recently excavated openings and in older workings that have been negatively impacted by high stress concentrations, time-dependent deformation, or corrosion of ground support elements. To address these issues, researchers with the National Institute for Occupational Safety and Health, Spokane Mining Research Division are developing and evaluating photogrammetric systems for ground control monitoring applications in underground mines. This research has demonstrated that photogrammetric systems can produce millimeter-level measurements that are comparable to conventional displacement-measuring instruments. This paper provides an overview of the beneficial use of close-range photogrammetry for the following three ground control applications in underground mines: monitoring the deformation of surface support, monitoring rock mass movement, and monitoring the corrosion of surface support. Preliminary field analyses, case studies, limitations, and best practices for these applications are also discussed.

Overview of bureau research directed towards surface powered haulage safety

DOE Office of Scientific and Technical Information (OSTI.GOV)

May, J.P.; Aldinger, J.A.

1995-12-31

Surface mining operations, including mills and preparation plants, employ over 260,000 people. This represents a significant contribution to our nation`s economy and an important source of skilled and well-paying jobs. As mine production has shifted from underground to surface, and with continuing advances in underground mine safety, surface mining has unfortunately become the leader in mine fatalities. In 1994 surface mining accidents accounted for 49% of all mine fatalities, followed by underground mining with 37% and mills and preparation plants with 14%. The U.S. Bureau of Mines (USBM) has targeted surface mining as an important research priority to reduce themore » social and economic costs associated with fatalities and lost-work-time injuries. USBM safety research focuses on the development of technologies that can enhance productivity and reduce mining costs through a reduction in the number and severity of mining accidents. This report summarizes a number of completed and ongoing research programs directed towards surface powered haulage--the single largest category of fatalities in surface mining and a major cause of lost workdays. Research products designed for industry are highlighted and future USBM surface mining safety research is discussed.« less

Development and application of the Safe Performance Index as a risk-based methodology for identifying major hazard-related safety issues in underground coal mines

NASA Astrophysics Data System (ADS)

Kinilakodi, Harisha

The underground coal mining industry has been under constant watch due to the high risk involved in its activities, and scrutiny increased because of the disasters that occurred in 2006-07. In the aftermath of the incidents, the U.S. Congress passed the Mine Improvement and New Emergency Response Act of 2006 (MINER Act), which strengthened the existing regulations and mandated new laws to address the various issues related to a safe working environment in the mines. Risk analysis in any form should be done on a regular basis to tackle the possibility of unwanted major hazard-related events such as explosions, outbursts, airbursts, inundations, spontaneous combustion, and roof fall instabilities. One of the responses by the Mine Safety and Health Administration (MSHA) in 2007 involved a new pattern of violations (POV) process to target mines with a poor safety performance, specifically to improve their safety. However, the 2010 disaster (worst in 40 years) gave an impression that the collective effort of the industry, federal/state agencies, and researchers to achieve the goal of zero fatalities and serious injuries has gone awry. The Safe Performance Index (SPI) methodology developed in this research is a straight-forward, effective, transparent, and reproducible approach that can help in identifying and addressing some of the existing issues while targeting (poor safety performance) mines which need help. It combines three injury and three citation measures that are scaled to have an equal mean (5.0) in a balanced way with proportionate weighting factors (0.05, 0.15, 0.30) and overall normalizing factor (15) into a mine safety performance evaluation tool. It can be used to assess the relative safety-related risk of mines, including by mine-size category. Using 2008 and 2009 data, comparisons were made of SPI-associated, normalized safety performance measures across mine-size categories, with emphasis on small-mine safety performance as compared to large- and medium-sized mines. The accident rates (NDL IR, NFDL IR, SM/100) of very small and small mines in 2008 and 2009 were less than those of medium and large mines. The data indicates a heavy occurrence of very severe injuries in a number of very small and small mines. In another application which is a part of this research, the six normalized safety measures and the SPI are used to evaluate the risk that existed at mines in the two years preceding the occurrence of a fatality. This mine safety performance tracking method could have been helpful to the companies, state agency, or MSHA in recognizing and addressing emerging problems with actions that may have been able to prevent high-risk conditions, the fatality, and/or other serious injuries. The approach would have given scrutiny to the risk of mines that encompassed 74% of the fatalities during 2007-2010. In order to assess the SPI as a comparable risk measurement tool, a traditional risk approach is also developed using data embracing frequency and severity in the final equation to analyze the relative risk for all underground coal mines for the years 2007--2010. Then, the SPI is compared with this traditional risk analysis method to demonstrate that the results attained by either method provide the relative safety-related risk of underground coal mines regarding injuries and citations for violations of regulations. The comparison reveals that the SPI does emulate a traditional approach to risk analysis. A correlation coefficient of --0.89 or more was observed between the results of these two methodologies and either can be used to assist companies, the Mine Safety and Health Administration (MSHA), or state agencies in target-ing mines with high risk for serious injuries and elevated citations for remediation of their injury and/or violation experience. The SPI, however, provides a more understandable approach for mine operators to apply using measures compatible with MSHA's enforcement tools. These methodologies form an all-encompassing approach that can be used to assist companies, the MSHA, or state agencies in targeting mines with high risk for serious injuries and elevated citations. Once targeted as high risk, mines can then pursue appropriate intervention to remediate their violation and/or injury experience. This research may help in plugging the gap in the safety system and better pursue the goal of zero fatalities and serious injuries in the underground coal mines.

Effect of ground control mesh on dust sampling and explosion mitigation.

PubMed

Alexander, D W; Chasko, L L

2015-07-01

Researchers from the National Institute for Occupational Safety and Health's Office of Mine Safety and Health Research conducted an assessment of the effects that ground control mesh might have on rock and float coal dust distribution in a coal mine. The increased use of mesh to control roof and rib spall introduces additional elevated surfaces on which rock or coal dust can collect. It is possible to increase the potential for dust explosion propagation if any float coal dust is not adequately inerted. In addition, the mesh may interfere with the collection of representative dust samples when using the pan-and-brush sampling method developed by the U.S. Bureau of Mines and used by the Mine Safety and Health Administration for band sampling. This study estimates the additional coal or rock dust that could accumulate on mesh and develops a means to collect representative dust samples from meshed entries.

Effect of ground control mesh on dust sampling and explosion mitigation

PubMed Central

Alexander, D.W.; Chasko, L.L.

2017-01-01

Researchers from the National Institute for Occupational Safety and Health’s Office of Mine Safety and Health Research conducted an assessment of the effects that ground control mesh might have on rock and float coal dust distribution in a coal mine. The increased use of mesh to control roof and rib spall introduces additional elevated surfaces on which rock or coal dust can collect. It is possible to increase the potential for dust explosion propagation if any float coal dust is not adequately inerted. In addition, the mesh may interfere with the collection of representative dust samples when using the pan-and-brush sampling method developed by the U.S. Bureau of Mines and used by the Mine Safety and Health Administration for band sampling. This study estimates the additional coal or rock dust that could accumulate on mesh and develops a means to collect representative dust samples from meshed entries. PMID:28936000

The Research on the Impact of Management Level's Charismatic Leadership Style on Miners' Unsafe Behavior.

PubMed

Li, Hongxia; Di, Hongxi; Tian, Shuicheng; Li, Jian

2015-01-01

The aim of this study is research the impact of management level's charismatic leadership style on miners' unsafe behavior by using the questionnaires on charismatic leadership style, safety attitude and the miners' unsafe behavior measurement to investigate 200 employees in Shen Dong Company. The research results suggest that management level's charismatic leadership style have very important influence on miners' unsafe behavior and the influence is affected by the safety attitude which is the intermediary function. In the end, this study propose advice on how to improve the coal mine enterprise managers charismatic leadership style in the coal mine enterprise's safety management work, including attach great importance to a variety of incentive methods, set up safety moral models, practice of inductive leadership concept, create a good atmosphere of safety, etc for reference for coal mining enterprises.

Research on target tracking in coal mine based on optical flow method

NASA Astrophysics Data System (ADS)

Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

Research on Customer Value Based on Extension Data Mining

NASA Astrophysics Data System (ADS)

Chun-Yan, Yang; Wei-Hua, Li

Extenics is a new discipline for dealing with contradiction problems with formulize model. Extension data mining (EDM) is a product combining Extenics with data mining. It explores to acquire the knowledge based on extension transformations, which is called extension knowledge (EK), taking advantage of extension methods and data mining technology. EK includes extensible classification knowledge, conductive knowledge and so on. Extension data mining technology (EDMT) is a new data mining technology that mining EK in databases or data warehouse. Customer value (CV) can weigh the essentiality of customer relationship for an enterprise according to an enterprise as a subject of tasting value and customers as objects of tasting value at the same time. CV varies continually. Mining the changing knowledge of CV in databases using EDMT, including quantitative change knowledge and qualitative change knowledge, can provide a foundation for that an enterprise decides the strategy of customer relationship management (CRM). It can also provide a new idea for studying CV.

Mining reflective continuing medical education data for family physician learning needs.

PubMed

Lewis, Denice Colleen; Pluye, Pierre; Rodriguez, Charo; Grad, Roland

2016-04-06

A mixed methods research (sequential explanatory design) studied the potential of mining the data from the consumers of continuing medical education (CME) programs, for the developers of CME programs. The quantitative data generated by family physicians, through applying the information assessment method to CME content, was presented to key informants from the CME planning community through a qualitative description study.The data were revealed to have many potential applications including supporting the creation of CME content, CME program planning and personal learning portfolios.

The Hazards of Data Mining in Healthcare.

PubMed

Househ, Mowafa; Aldosari, Bakheet

2017-01-01

From the mid-1990s, data mining methods have been used to explore and find patterns and relationships in healthcare data. During the 1990s and early 2000's, data mining was a topic of great interest to healthcare researchers, as data mining showed some promise in the use of its predictive techniques to help model the healthcare system and improve the delivery of healthcare services. However, it was soon discovered that mining healthcare data had many challenges relating to the veracity of healthcare data and limitations around predictive modelling leading to failures of data mining projects. As the Big Data movement has gained momentum over the past few years, there has been a reemergence of interest in the use of data mining techniques and methods to analyze healthcare generated Big Data. Much has been written on the positive impacts of data mining on healthcare practice relating to issues of best practice, fraud detection, chronic disease management, and general healthcare decision making. Little has been written about the limitations and challenges of data mining use in healthcare. In this review paper, we explore some of the limitations and challenges in the use of data mining techniques in healthcare. Our results show that the limitations of data mining in healthcare include reliability of medical data, data sharing between healthcare organizations, inappropriate modelling leading to inaccurate predictions. We conclude that there are many pitfalls in the use of data mining in healthcare and more work is needed to show evidence of its utility in facilitating healthcare decision-making for healthcare providers, managers, and policy makers and more evidence is needed on data mining's overall impact on healthcare services and patient care.

SparkText: Biomedical Text Mining on Big Data Framework.

PubMed

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

SparkText: Biomedical Text Mining on Big Data Framework

PubMed Central

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

Model for the prediction of subsurface strata movement due to underground mining

NASA Astrophysics Data System (ADS)

Cheng, Jianwei; Liu, Fangyuan; Li, Siyuan

2017-12-01

The problem of ground control stability due to large underground mining operations is often associated with large movements and deformations of strata. It is a complicated problem, and can induce severe safety or environmental hazards either at the surface or in strata. Hence, knowing the subsurface strata movement characteristics, and making any subsidence predictions in advance, are desirable for mining engineers to estimate any damage likely to affect the ground surface or subsurface strata. Based on previous research findings, this paper broadly applies a surface subsidence prediction model based on the influence function method to subsurface strata, in order to predict subsurface stratum movement. A step-wise prediction model is proposed, to investigate the movement of underground strata. The model involves a dynamic iteration calculation process to derive the movements and deformations for each stratum layer; modifications to the influence method function are also made for more precise calculations. The critical subsidence parameters, incorporating stratum mechanical properties and the spatial relationship of interest at the mining level, are thoroughly considered, with the purpose of improving the reliability of input parameters. Such research efforts can be very helpful to mining engineers’ understanding of the moving behavior of all strata over underground excavations, and assist in making any damage mitigation plan. In order to check the reliability of the model, two methods are carried out and cross-validation applied. One is to use a borehole TV monitor recording to identify the progress of subsurface stratum bedding and caving in a coal mine, the other is to conduct physical modelling of the subsidence in underground strata. The results of these two methods are used to compare with theoretical results calculated by the proposed mathematical model. The testing results agree well with each other, and the acceptable accuracy and reliability of the proposed prediction model are thus validated.

Knowledge-guided mutation in classification rules for autism treatment efficacy.

PubMed

Engle, Kelley; Rada, Roy

2017-03-01

Data mining methods in biomedical research might benefit by combining genetic algorithms with domain-specific knowledge. The objective of this research is to show how the evolution of treatment rules for autism might be guided. The semantic distance between two concepts in the taxonomy is measured by the number of relationships separating the concepts in the taxonomy. The hypothesis is that replacing a concept in a treatment rule will change the accuracy of the rule in direct proportion to the semantic distance between the concepts. The method uses a patient database and autism taxonomies. Treatment rules are developed with an algorithm that exploits the taxonomies. The results support the hypothesis. This research should both advance the understanding of autism data mining in particular and of knowledge-guided evolutionary search in biomedicine in general.

The systematic assessment of traditional evidence from the premodern Chinese medical literature: a text-mining approach.

PubMed

May, Brian H; Zhang, Anthony; Lu, Yubo; Lu, Chuanjian; Xue, Charlie C L

2014-12-01

This project aimed to develop an approach to evaluating information contained in the premodern Traditional Chinese Medicine (TCM) literature that was (1) comprehensive, systematic, and replicable and (2) able to produce quantifiable output that could be used to answer specific research questions in order to identify natural products for clinical and experimental research. The project involved two stages. In stage 1, 14 TCM collections and compendia were evaluated for suitability as sources for searching; 8 of these were compared in detail. The results were published in the Journal of Alternative and Complementary Medicine. Stage 2 developed a text-mining approach for two of these sources. The text-mining approach was developed for Zhong Hua Yi Dian; Encyclopaedia of Traditional Chinese Medicine, 4th edition) and Zhong Yi Fang Ji Da Ci Dian; Great Compendium of Chinese Medical Formulae). This approach developed procedures for search term selection; methods for screening, classifying, and scoring data; procedures for systematic searching and data extraction; data checking procedures; and approaches for analyzing results. Examples are provided for studies of memory impairment and diabetic nephropathy, and issues relating to data interpretation are discussed. This approach to the analysis of large collections of the premodern TCM literature uses widely available sources and provides a text-mining approach that is systematic, replicable, and adaptable to the requirements of the particular project. Researchers can use these methods to explore changes in the names and conceptions of a disease over time, to identify which therapeutic methods have been more or less frequently used in different eras for particular disorders, and to assist in the selection of natural products for research efforts.

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

PubMed Central

2012-01-01

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials.

PubMed

Korkontzelos, Ioannis; Mu, Tingting; Ananiadou, Sophia

2012-04-30

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.

Magnetic sensor technology for detecting mines, UXO, and other concealed security threats

NASA Astrophysics Data System (ADS)

Czipott, Peter V.; Iwanowski, Mark D.

1997-01-01

Magnetic sensors have been the sensor of choice in the detection and classification of buried mines and unexploded ordnance (UXO), both on land and underwater, Quantum Magnetics (QM), together with its research partner IBM, have developed a variety of advanced, very high sensitivity superconducting and room temperature magnetic sensors to meet military needs. This work has led to the development and utilization of a three-sensor gradiometer (TSG) patented by IBM, which cannot only detect, but also localize mines and ordnance. QM is also working with IBM and the U.S. Navy to develop an advanced superconducting gradiometer for buried underwater mine detection. The ability to both detect and classify buried non-metallic mines is virtually impossible with existing magnetic sensors. To solve this problem, Quantum Magnetics, building on work of the Naval Research Laboratory (NRL), is pioneering work in the development of quadrupole resonance (QR) methods which can be used to detect the explosive material directly. Based on recent laboratory work done at QM and previous work done in the U.S., Russia and the United Kingdom, we are confident that QR can be effectively applied to the non-metallic mine identification problem.

Evaluation and selection of decision-making methods to assess landfill mining projects.

PubMed

Hermann, Robert; Baumgartner, Rupert J; Vorbach, Stefan; Ragossnig, Arne; Pomberger, Roland

2015-09-01

For the first time in Austria, fundamental technological and economic studies on recovering secondary raw materials from large landfills have been carried out, based on the 'LAMIS - Landfill Mining Austria' pilot project. A main focus of the research - and the subject of this article - was to develop an assessment or decision-making procedure that allows landfill owners to thoroughly examine the feasibility of a landfill mining project in advance. Currently there are no standard procedures that would sufficiently cover all the multiple-criteria requirements. The basic structure of the multiple attribute decision making process was used to narrow down on selection, conceptual design and assessment of suitable procedures. Along with a breakdown into preliminary and main assessment, the entire foundation required was created, such as definitions of requirements to an assessment method, selection and accurate description of the various assessment criteria and classification of the target system for the present 'landfill mining' vs. 'retaining the landfill in after-care' decision-making problem. Based on these studies, cost-utility analysis and the analytical-hierarchy process were selected from the range of multiple attribute decision-making procedures and examined in detail. Overall, both methods have their pros and cons with regard to their use for assessing landfill mining projects. Merging these methods or connecting them with single-criteria decision-making methods (like the net present value method) may turn out to be reasonable and constitute an appropriate assessment method. © The Author(s) 2015.

Spatial variability of sediment erosion processes using GIS analysis within watersheds in a historically mined region, Patagonia Mountains, Arizona

USGS Publications Warehouse

Brady, Laura M.; Gray, Floyd; Wissler, Craig A.; Guertin, D. Phillip

2001-01-01

In this study, a geographic information system (GIS) is used to integrate and accurately map field studies, information from remotely sensed data, watershed models, and the dispersion of potentially toxic mine waste and tailings. The purpose of this study is to identify erosion rates and net sediment delivery of soil and mine waste/tailings to the drainage channel within several watershed regions to determine source areas of sediment delivery as a method of quantifying geo-environmental analysis of transport mechanisms in abandoned mine lands in arid climate conditions. Users of this study are the researchers interested in exploration of approaches to depicting historical activity in an area which has no baseline data records for environmental analysis of heavily mined terrain.

A Framework for Text Mining in Scientometric Study: A Case Study in Biomedicine Publications

NASA Astrophysics Data System (ADS)

Silalahi, V. M. M.; Hardiyati, R.; Nadhiroh, I. M.; Handayani, T.; Rahmaida, R.; Amelia, M.

2018-04-01

The data of Indonesians research publications in the domain of biomedicine has been collected to be text mined for the purpose of a scientometric study. The goal is to build a predictive model that provides a classification of research publications on the potency for downstreaming. The model is based on the drug development processes adapted from the literatures. An effort is described to build the conceptual model and the development of a corpus on the research publications in the domain of Indonesian biomedicine. Then an investigation is conducted relating to the problems associated with building a corpus and validating the model. Based on our experience, a framework is proposed to manage the scientometric study based on text mining. Our method shows the effectiveness of conducting a scientometric study based on text mining in order to get a valid classification model. This valid model is mainly supported by the iterative and close interactions with the domain experts starting from identifying the issues, building a conceptual model, to the labelling, validation and results interpretation.

Fuzzy linear model for production optimization of mining systems with multiple entities

NASA Astrophysics Data System (ADS)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

A data mining based approach to predict spatiotemporal changes in satellite images

NASA Astrophysics Data System (ADS)

Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

2011-06-01

The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

Characterization of airborne float coal dust emitted during continuous mining, longwall mining and belt transport.

PubMed

Shahan, M R; Seaman, C E; Beck, T W; Colinet, J F; Mischler, S E

2017-09-01

Float coal dust is produced by various mining methods, carried by ventilating air and deposited on the floor, roof and ribs of mine airways. If deposited, float dust is re-entrained during a methane explosion. Without sufficient inert rock dust quantities, this float coal dust can propagate an explosion throughout mining entries. Consequently, controlling float coal dust is of critical interest to mining operations. Rock dusting, which is the adding of inert material to airway surfaces, is the main control technique currently used by the coal mining industry to reduce the float coal dust explosion hazard. To assist the industry in reducing this hazard, the Pittsburgh Mining Research Division of the U.S. National Institute for Occupational Safety and Health initiated a project to investigate methods and technologies to reduce float coal dust in underground coal mines through prevention, capture and suppression prior to deposition. Field characterization studies were performed to determine quantitatively the sources, types and amounts of dust produced during various coal mining processes. The operations chosen for study were a continuous miner section, a longwall section and a coal-handling facility. For each of these operations, the primary dust sources were confirmed to be the continuous mining machine, longwall shearer and conveyor belt transfer points, respectively. Respirable and total airborne float dust samples were collected and analyzed for each operation, and the ratio of total airborne float coal dust to respirable dust was calculated. During the continuous mining process, the ratio of total airborne float coal dust to respirable dust ranged from 10.3 to 13.8. The ratios measured on the longwall face were between 18.5 and 21.5. The total airborne float coal dust to respirable dust ratio observed during belt transport ranged between 7.5 and 21.8.

Limitations in small artisanal gold mining addressed by educational components paired with alternative mining methods.

PubMed

Zolnikov, Tara R

2012-03-01

Current solutions continue to be inadequate in addressing the longstanding, worldwide problem of mercury emissions from small artisanal gold mining. Mercury, an inexpensive and easily accessible heavy metal, is used in the process of extracting gold from ore. Mercury emissions disperse, affecting human populations by causing adverse health effects and environmental and social ramifications. Many developing nations have sizable gold ore deposits, making small artisanal gold mining a major source of employment in the world. Poverty drives vulnerable, rural populations into gold mining because of social and economic instabilities. Educational programs responding to this environmental hazard have been implemented in the past, but have had low positive results due to lack of governmental support and little economic incentive. Educational and enforced intervention programs must be developed in conjunction with governmental agencies in order to successfully eliminate this ongoing problem. Industry leaders offered hopeful suggestions, but revealed limitations when trying to develop encompassing solutions to halt mercury emissions. This research highlights potential options that have been attempted in the past and suggests alternative solutions to improve upon these methods. Some methods include buyer impact recognition, risk assessment proposals exposing a cost-benefit analysis and toxicokinetic modeling, public health awareness campaigns, and the education of miners, healthcare workers, and locals within hazardous areas of mercury exposure. These methods, paired with the implementation of alternative mining techniques, propose a substantial reduction of mercury emissions. Copyright © 2011 Elsevier B.V. All rights reserved.

The Weather Forecast Using Data Mining Research Based on Cloud Computing.

NASA Astrophysics Data System (ADS)

Wang, ZhanJie; Mazharul Mujib, A. B. M.

2017-10-01

Weather forecasting has been an important application in meteorology and one of the most scientifically and technologically challenging problem around the world. In my study, we have analyzed the use of data mining techniques in forecasting weather. This paper proposes a modern method to develop a service oriented architecture for the weather information systems which forecast weather using these data mining techniques. This can be carried out by using Artificial Neural Network and Decision tree Algorithms and meteorological data collected in Specific time. Algorithm has presented the best results to generate classification rules for the mean weather variables. The results showed that these data mining techniques can be enough for weather forecasting.

Control of water erosion and sediment in open cut coal mines in tropical areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueda, T.; Nugraha, C.; Matsui, K.

2005-07-01

The purpose is to reduce the environmental impacts from open cut mining in tropical areas, such as Indonesia and Vietnam. Research conducted on methods for the control of water erosion and sediment from open cut coal mines is described. Data were collected on climate and weathering in tropical areas, mechanism of water erosion and sedimentation, characteristics of rocks in coal measures under wet conditions, water management at pits and haul roads and ramps, and construction of waste dumps and water management. The results will be applied to the optimum control and management of erosion and sediments in open cut mining.more » 6 refs., 8 figs.« less

The application of data mining to explore association rules between metabolic syndrome and lifestyles.

PubMed

Huang, Yi Chao

This study used an efficient data mining algorithm, called DCIP (the data cutting and inner product method), to explore association rules between the lifestyles of factory workers in Taiwan and the metabolic syndrome. A total of 1,216 workers in four companies completed a lifestyle questionnaire. Results of the questionnaire survey were integrated into the workers' health examination reports to form an attribute database of the metabolic syndrome. Among the association rules derived by DCIP, 80% of those on the list of the top 15 highest support counts are corroborated by medical literature or by healthcare professionals. These findings prove that data mining is a valid and effective research method, and that larger sample sizes will likely produce more accurate associations connecting the metabolic syndrome to specific lifestyles. The rules already verified can serve as a reference guide for the health management of factory workers. The remaining 20%, while still lacking hard evidence, provide fertile ground for future research.

Leaching characteristics, ecotoxicity, and risk assessment based management of mine wastes

NASA Astrophysics Data System (ADS)

Kim, J.; Ju, W. J.; Jho, E. H.; Nam, K.; Hong, J. K.

2016-12-01

Mine wastes generated during mining activities in metal mines generally contain high concentrations of metals that may impose toxic effects to surrounding environment. Thus, it is necessary to properly assess the mining-impacted landscapes for management. The study investigated leaching characteristics, potential environmental effects, and human health risk of mine wastes from three different metal mines in South Korea (molybdenum mine, lead-zinc mine, and magnetite mine). The heavy metal concentrations in the leachates obtained by using the Korean Standard Test Method for Solid Wastes (STM), Toxicity Characteristics Leaching Procedure (TCLP), and Synthetic Precipitation Leaching Procedure (SPLP) met the Korea Waste Control Act and the USEPA region 3 regulatory levels accordingly, even though the mine wastes contained high concentrations of metals. Assuming that the leachates may get into nearby water sources, the leachate toxicity was tested using Daphnia Magna. The toxic unit (TU) values after 24 h and 48 h exposure of all the mine wastes tested met the Korea Allowable Effluent Water Quality Standards (TU<1). The column leaching test showed that the lead-zinc mine waste may have long-term toxic effects (TU>1 for the eluent at L/S of 30) implying that the long-term effect of mine wastes left in mining areas need to be assessed. Considering reuse of mine wastes as a way of managing mine wastes, the human health risk assessment of reusing the lead-zinc mine waste in industrial areas was carried out using the bioavailable fraction of the heavy metals contained in the mine wastes, which was determined by using the Solubility/Bioavailability Research Consortium method. There may be potential carcinogenic risk (9.7E-05) and non-carcinogenic risk (HI, Hazard Index of 1.0E+00) as CR≧1.0E-05 has carcinogenic risk and HI≧1.0E+00 has non-carcinogenic risk. Overall, this study shows that not only the concentration-based assessment but ecological toxic effect and human health risk based assessments can be utilized for mining-impacted landscapes management.

The Research on the Impact of Management Level’s Charismatic Leadership Style on Miners' Unsafe Behavior

PubMed Central

Li, Hongxia; Di, Hongxi; Tian, Shuicheng; Li, Jian

2015-01-01

The aim of this study is research the impact of management level’s charismatic leadership style on miners' unsafe behavior by using the questionnaires on charismatic leadership style, safety attitude and the miners' unsafe behavior measurement to investigate 200 employees in Shen Dong Company. The research results suggest that management level’s charismatic leadership style have very important influence on miners' unsafe behavior and the influence is affected by the safety attitude which is the intermediary function. In the end, this study propose advice on how to improve the coal mine enterprise managers charismatic leadership style in the coal mine enterprise's safety management work, including attach great importance to a variety of incentive methods, set up safety moral models, practice of inductive leadership concept, create a good atmosphere of safety, etc for reference for coal mining enterprises. PMID:26628936

Confidentiality issues for medical data miners.

PubMed

Berman, Jules J

2002-01-01

The first task in any medical data mining effort is ensuring patient confidentiality. In the past, most data mining efforts ensured confidentiality by the dubious policy of withholding their raw data from colleagues and the public. A cursory review of medical informatics literature in the past decade reveals that much of what we have "learned" consists of assertions derived from confidential datasets unavailable for anyone's review. Without access to the original data, it is impossible to validate or improve upon a researcher's conclusions. Without access to research data, we are asked to accept findings as an act of faith, rather than as a scientific conclusion. This special issue of Artificial Intelligence in Medicine is devoted to medical data mining. The medical data miner has an obligation to conduct valid research in a way that protects human subjects. Today, data miners have the technical tools to merge large data collections and to distribute queries over disparate databases. In order to include patient-related data in shared databases, data miners will need methods to anonymize and deidentify data. This article reviews the human subject risks associated with medical data mining. This article also describes some of the innovative computational remedies that will permit researchers to conduct research AND share their data without risk to patient or institution.

Astroinformatics, data mining and the future of astronomical research

NASA Astrophysics Data System (ADS)

Brescia, Massimo; Longo, Giuseppe

2013-08-01

Astronomy, as many other scientific disciplines, is facing a true data deluge which is bound to change both the praxis and the methodology of every day research work. The emerging field of astroinformatics, while on the one end appears crucial to face the technological challenges, on the other is opening new exciting perspectives for new astronomical discoveries through the implementation of advanced data mining procedures. The complexity of astronomical data and the variety of scientific problems, however, call for innovative algorithms and methods as well as for an extreme usage of ICT technologies.

caTIES: a grid based system for coding and retrieval of surgical pathology reports and tissue specimens in support of translational research.

PubMed

Crowley, Rebecca S; Castine, Melissa; Mitchell, Kevin; Chavan, Girish; McSherry, Tara; Feldman, Michael

2010-01-01

The authors report on the development of the Cancer Tissue Information Extraction System (caTIES)--an application that supports collaborative tissue banking and text mining by leveraging existing natural language processing methods and algorithms, grid communication and security frameworks, and query visualization methods. The system fills an important need for text-derived clinical data in translational research such as tissue-banking and clinical trials. The design of caTIES addresses three critical issues for informatics support of translational research: (1) federation of research data sources derived from clinical systems; (2) expressive graphical interfaces for concept-based text mining; and (3) regulatory and security model for supporting multi-center collaborative research. Implementation of the system at several Cancer Centers across the country is creating a potential network of caTIES repositories that could provide millions of de-identified clinical reports to users. The system provides an end-to-end application of medical natural language processing to support multi-institutional translational research programs.

Detecting Underground Mine Voids Using Complex Geophysical Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaminski, V. F.; Harbert, W. P.; Hammack, R. W.

2006-12-01

In July 2006, the National Energy Technology Laboratory in collaboration with Department of Geology and Planetary Science, University of Pittsburgh conducted complex ground geophysical surveys of an area known to be underlain by shallow coal mines. Geophysical methods including electromagnetic induction, DC resistivity and seismic reflection were conducted. The purpose of these surveys was to: 1) verify underground mine voids based on a century-old mine map that showed subsurface mine workings georeferenced to match with present location of geophysical test-site located on the territory of Bruceton research center in Pittsburgh, PA, 2) deliniate mine workings that may be potentially filledmore » with electrically conductive water filtrate emerging from adjacent groundwater collectors and 3) establish an equipment calibration site for geophysical instruments. Data from electromagnetic and resistivity surveys were further processed and inverted using EM1DFM, EMIGMA or Earthimager 2D capablilities in order to generate conductivity/depth images. Anomaly maps were generated, that revealed the locations of potential mine openings.« less

Assessment and evaluation of noise controls on roof bolting equipment and a method for predicting sound pressure levels in underground coal mining

NASA Astrophysics Data System (ADS)

Matetic, Rudy J.

Over-exposure to noise remains a widespread and serious health hazard in the U.S. mining industries despite 25 years of regulation. Every day, 80% of the nation's miners go to work in an environment where the time weighted average (TWA) noise level exceeds 85 dBA and more than 25% of the miners are exposed to a TWA noise level that exceeds 90 dBA, the permissible exposure limit (PEL). Additionally, MSHA coal noise sample data collected from 2000 to 2002 show that 65% of the equipment whose operators exceeded 100% noise dosage comprise only seven different types of machines; auger miners, bulldozers, continuous miners, front end loaders, roof bolters, shuttle cars (electric), and trucks. In addition, the MSHA data indicate that the roof bolter is third among all the equipment and second among equipment in underground coal whose operators exceed 100% dosage. A research program was implemented to: (1) determine, characterize and to measure sound power levels radiated by a roof bolting machine during differing drilling configurations (thrust, rotational speed, penetration rate, etc.) and utilizing differing types of drilling methods in high compressive strength rock media (>20,000 psi). The research approach characterized the sound power level results from laboratory testing and provided the mining industry with empirical data relative to utilizing differing noise control technologies (drilling configurations and types of drilling methods) in reducing sound power level emissions on a roof bolting machine; (2) distinguish and correlate the empirical data into one, statistically valid, equation, in which, provided the mining industry with a tool to predict overall sound power levels of a roof bolting machine given any type of drilling configuration and drilling method utilized in industry; (3) provided the mining industry with several approaches to predict or determine sound pressure levels in an underground coal mine utilizing laboratory test results from a roof bolting machine and (4) described a method for determining an operators' noise dosage of a roof bolting machine utilizing predicted or determined sound pressure levels.

The Functional Genomics Network in the evolution of biological text mining over the past decade.

PubMed

Blaschke, Christian; Valencia, Alfonso

2013-03-25

Different programs of The European Science Foundation (ESF) have contributed significantly to connect researchers in Europe and beyond through several initiatives. This support was particularly relevant for the development of the areas related with extracting information from papers (text-mining) because it supported the field in its early phases long before it was recognized by the community. We review the historical development of text mining research and how it was introduced in bioinformatics. Specific applications in (functional) genomics are described like it's integration in genome annotation pipelines and the support to the analysis of high-throughput genomics experimental data, and we highlight the activities of evaluation of methods and benchmarking for which the ESF programme support was instrumental. Copyright © 2013 Elsevier B.V. All rights reserved.

Monitoring of Soil Remediation Process in the Metal Mining Area

NASA Astrophysics Data System (ADS)

Kim, Kyoung-Woong; Ko, Myoung-Soo; Han, Hyeop-jo; Lee, Sang-Ho; Na, So-Young

2016-04-01

Stabilization using proper additives is an effective soil remediation technique to reduce As mobility in soil. Several researches have reported that Fe-containing materials such as amorphous Fe-oxides, goethite and hematite were effective in As immobilization and therefore acid mine drainage sludge (AMDS) may be potential material for As immobilization. The AMDS is the by-product from electrochemical treatment of acid mine drainage and mainly contains Fe-oxide. The Chungyang area in Korea is located in the vicinity of the huge abandoned Au-Ag Gubong mine which was closed in the 1970s. Large amounts of mine tailings have been remained without proper treatment and the mobilization of mine tailings can be manly occurred during the summer heavy rainfall season. Soil contamination from this mobilization may become an urgent issue because it can cause the contamination of groundwater and crop plants in sequence. In order to reduce the mobilization of the mine tailings, the pilot scale study of in-situ stabilization using AMDS was applied after the batch and column experiments in the lab. For the monitoring of stabilization process, we used to determine the As concentration in crop plants grown on the field site but it is not easily applicable because of time and cost. Therefore, we may need simple monitoring technique to measure the mobility or leachability which can be comparable with As concentration in crop plants. We compared several extraction methods to suggest the representative single extraction method for the monitoring of soil stabilization efficiency. Several selected extraction methods were examined and Mehlich 3 extraction method using the mixture of NH4F, EDTA, NH4NO3, CH3COOH and HNO3 was selected as the best predictor of the leachability or mobility of As in the soil remediation process.

Citation Mining: Integrating Text Mining and Bibliometrics for Research User Profiling.

ERIC Educational Resources Information Center

Kostoff, Ronald N.; del Rio, J. Antonio; Humenik, James A.; Garcia, Esther Ofilia; Ramirez, Ana Maria

2001-01-01

Discusses the importance of identifying the users and impact of research, and describes an approach for identifying the pathways through which research can impact other research, technology development, and applications. Describes a study that used citation mining, an integration of citation bibliometrics and text mining, on articles from the…

The Potentials of Educational Data Mining for Researching Metacognition, Motivation and Self-Regulated Learning

ERIC Educational Resources Information Center

Winne, Philip H.; Baker, Ryan S. J. D.

2013-01-01

Our article introduces the "Journal of Educational Data Mining's" Special Issue on Educational Data Mining on Motivation, Metacognition, and Self-Regulated Learning. We outline general research challenges for data mining researchers who conduct investigations in these areas, the potential of EDM to advance research in this area, and…

Determining the area of influence of depression cone in the vicinity of lignite mine by means of triangle method and LANDSAT TM/ETM+ satellite images.

PubMed

Zawadzki, Jarosław; Przeździecki, Karol; Miatkowski, Zygmunt

2016-01-15

Problems with lowering of water table are common all over the world. Intensive pumping of water from aquifers for consumption, irrigation, industrial or mining purposes often causes groundwater depletion and results in the formation of cone of depression. This can severely decrease water pressure, even over vast areas, and can create severe problems such as degradation of agriculture or natural environment sometimes depriving people and animals of water supply. In this paper, the authors present a method for determining the area of influence of a groundwater depression cone resulting from prolonged drainage, by means of satellite images in optical, near infrared and thermal infrared bands from TM sensor (Thematic Mapper) and ETM+ sensor (Enhanced Thematic Mapper +) placed on Landsat 5 and Landsat 7 satellites. The research area was Szczercowska Valley (Pol. Kotlina Szczercowska), Central Poland, located within a range of influence of a groundwater drainage system of the lignite coal mine in Belchatow. It is the biggest lignite coal mine in Poland and one of the largest in Europe exerting an enormous impact on the environment. The main method of satellite data analysis for determining soil moisture, was the so-called triangle method. This method, based on TVDI (Temperature Vegetation Dryness Index) was supported by additional spatial analysis including ordinary kriging used in order to combine fragmentary information obtained from areas covered by meadows. The results obtained are encouraging and confirm the usefulness of the triangle method not only for soil moisture determination but also for assessment of the temporal and spatial changes in the area influenced by the groundwater depression cone. The range of impact of the groundwater depression cone determined by means of above-described remote sensing analysis shows good agreement with that determined by ground measurements. The developed satellite method is much faster and cheaper than in-situ measurements, and allows for systematic monitoring of the vast area in the vicinity of Belchatow lignite mine. Besides, this method could be useful as a helper in in-situ measurement allowing a significant reduction of the number of in-situ measurements by performing them only within problematic areas. Hence, the triangle method can be used as an effective supplement to field measurements. Although the research area is located in Poland, in the vicinity of lignite mine, the method of observation of depression cones provided in this study is universal and effective, and therefore could also be useful to an international audience. Copyright © 2015 Elsevier Ltd. All rights reserved.

Phylogeny-guided (meta)genome mining approach for the targeted discovery of new microbial natural products.

PubMed

Kang, Hahk-Soo

2017-02-01

Genomics-based methods are now commonplace in natural products research. A phylogeny-guided mining approach provides a means to quickly screen a large number of microbial genomes or metagenomes in search of new biosynthetic gene clusters of interest. In this approach, biosynthetic genes serve as molecular markers, and phylogenetic trees built with known and unknown marker gene sequences are used to quickly prioritize biosynthetic gene clusters for their metabolites characterization. An increase in the use of this approach has been observed for the last couple of years along with the emergence of low cost sequencing technologies. The aim of this review is to discuss the basic concept of a phylogeny-guided mining approach, and also to provide examples in which this approach was successfully applied to discover new natural products from microbial genomes and metagenomes. I believe that the phylogeny-guided mining approach will continue to play an important role in genomics-based natural products research.

A Method of Measuring the Costs and Benefits of Applied Research.

ERIC Educational Resources Information Center

Sprague, John W.

The Bureau of Mines studied the application of the concepts and methods of cost-benefit analysis to the problem of ranking alternative applied research projects. Procedures for measuring the different classes of project costs and benefits, both private and public, are outlined, and cost-benefit calculations are presented, based on the criteria of…

A Visualization Tool for Integrating Research Results at an Underground Mine

NASA Astrophysics Data System (ADS)

Boltz, S.; Macdonald, B. D.; Orr, T.; Johnson, W.; Benton, D. J.

2016-12-01

Researchers with the National Institute for Occupational Safety and Health are conducting research at a deep, underground metal mine in Idaho to develop improvements in ground control technologies that reduce the effects of dynamic loading on mine workings, thereby decreasing the risk to miners. This research is multifaceted and includes: photogrammetry, microseismic monitoring, geotechnical instrumentation, and numerical modeling. When managing research involving such a wide range of data, understanding how the data relate to each other and to the mining activity quickly becomes a daunting task. In an effort to combine this diverse research data into a single, easy-to-use system, a three-dimensional visualization tool was developed. The tool was created using the Unity3d video gaming engine and includes the mine development entries, production stopes, important geologic structures, and user-input research data. The tool provides the user with a first-person, interactive experience where they are able to walk through the mine as well as navigate the rock mass surrounding the mine to view and interpret the imported data in the context of the mine and as a function of time. The tool was developed using data from a single mine; however, it is intended to be a generic tool that can be easily extended to other mines. For example, a similar visualization tool is being developed for an underground coal mine in Colorado. The ultimate goal is for NIOSH researchers and mine personnel to be able to use the visualization tool to identify trends that may not otherwise be apparent when viewing the data separately. This presentation highlights the features and capabilities of the mine visualization tool and explains how it may be used to more effectively interpret data and reduce the risk of ground fall hazards to underground miners.

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

A review of contrast pattern based data mining

NASA Astrophysics Data System (ADS)

Zhu, Shiwei; Ju, Meilong; Yu, Junfeng; Cai, Binlei; Wang, Aiping

2015-07-01

Contrast pattern based data mining is concerned with the mining of patterns and models that contrast two or more datasets. Contrast patterns can describe similarities or differences between the datasets. They represent strong contrast knowledge and have been shown to be very successful for constructing accurate and robust clusters and classifiers. The increasing use of contrast pattern data mining has initiated a great deal of research and development attempts in the field of data mining. A comprehensive revision on the existing contrast pattern based data mining research is given in this paper. They are generally categorized into background and representation, definitions and mining algorithms, contrast pattern based classification, clustering, and other applications, the research trends in future. The primary of this paper is to server as a glossary for interested researchers to have an overall picture on the current contrast based data mining development and identify their potential research direction to future investigation.

Investigation of the Mechanism of Roof Caving in the Jinchuan Nickel Mine, China

NASA Astrophysics Data System (ADS)

Ding, Kuo; Ma, Fengshan; Guo, Jie; Zhao, Haijun; Lu, Rong; Liu, Feng

2018-04-01

On 13 March 2016, a sudden, violent roof caving event with a collapse area of nearly 11,000 m2 occurred in the Jinchuan Nickel Mine and accompanied by air blasts, loud noises and ground vibrations. This collapse event coincided with related, conspicuous surface subsidence across an area of nearly 19,000 m2. This article aims to analyse this collapse event. In previous studies, various mining-induced collapses have been studied, but collapse accidents associated with the filling mining method are very rare and have not been thoroughly studied. The filling method has been regarded as a safe mining method for a long time, so research on associated collapse mechanisms is of considerable significance. In this study, a detailed field investigation of roadway damage was performed, and GPS monitoring results were used to analyse the surface failure. In addition, a numerical model was constructed based on the geometry of the ore body and a major fault. The analysis of the model revealed three failure mechanisms acting during different stages of destruction: double-sided embedded beam deformation, fault activation, and cantilever-articulated rock beam failure. The fault activation and the specific filling method are the key factors of this collapse event. To gain a better understanding of these factors, the shear stress and normal stress along the fault plane were monitored to determine the variation in stress at different failure stages. Discrete element models were established to study two filling methods and to analyse the stability of different filling structures.

Strip mine reclamation: criteria and methods for measurement of revegetation success. Progress report, April 1, 1980-March 31, 1981

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carrel, J.E.; Kucera, C.L.; Johannsen, C.J.

1980-12-01

During this contract period research was continued at finding suitable methods and criteria for determining the success of revegetation in Midwestern prime ag lands strip mined for coal. Particularly important to the experimental design was the concept of reference areas, which were nearby fields from which the performance standards for reclaimed areas were derived. Direct and remote sensing techniques for measuring plant ground cover, production, and species composition were tested. 15 mine sites were worked in which were permitted under interim permanent surface mine regulations and in 4 adjoining reference sites. Studies at 9 prelaw sites were continued. All sitesmore » were either in Missouri or Illinois. Data gathered in the 1980 growing season showed that 13 unmanaged or young mineland pastures generally had lower average ground cover and production than 2 reference pastures. In contrast, yields at approximately 40% of 11 recently reclaimed mine sites planted with winter wheat, soybeans, or milo were statistically similar to 3 reference values. Digital computer image analysis of color infrared aerial photographs, when compared to ground level measurements, was a fast, accurate, and inexpensive way to determine plant ground cover and areas. But the remote sensing approach was inferior to standard surface methods for detailing plant species abundance and composition.« less

Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

NASA Astrophysics Data System (ADS)

Wang, Chenggen; Zhou, Qian; Han, Mingzhe; Lv, Zhan’ao; Hou, Xiao; Zhao, Haoran; Bu, Jing

2018-04-01

Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.

77 FR 42314 - Proposed Data Collections Submitted for Public Comment and Recommendations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-18

... Act of 1970) has the responsibility to conduct research relating to innovative methods, techniques, and approaches dealing with occupational safety and health problems. This research relates to... recruited to diversify the research sample. Data will be collected one time at each mine; this is not a...

Impact of Coal Mining on Self-Rated Health among Appalachian Residents

PubMed Central

Woolley, Shannon M.; Bear, Todd M.; Balmert, Lauren C.; Talbott, Evelyn O.; Buchanich, Jeanine M.

2015-01-01

Objective. To determine the impact of coal mining, measured as the number of coal mining-related facilities nearby one's residence or employment in an occupation directly related to coal mining, on self-rated health in Appalachia. Methods. Unadjusted and adjusted ordinal logistic regression models calculated odds ratio estimates and associated 95% confidence intervals for the probability of having an excellent self-rated health response versus another response. Covariates considered in the analyses included number of coal mining-related facilities nearby one's residence and employment in an occupation directly related to coal mining, as well as potential confounders age, sex, BMI, smoking status, income, and education. Results. The number of coal mining facilities near the respondent's residence was not a statistically significant predictor of self-rated health. Employment in a coal-related occupation was a statistically significant predictor of self-rated health univariably; however, after adjusting for potential confounders, it was no longer a significant predictor. Conclusions. Self-rated health does not seem to be associated with residential proximity to coal mining facilities or employment in the coal industry. Future research should consider additional measures for the impact of coal mining. PMID:26240577

Knowledge Discovery and Data Mining in Iran's Climatic Researches

NASA Astrophysics Data System (ADS)

Karimi, Mostafa

2013-04-01

Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for internal climate studies in data mining and knowledge discovery techniques are used. However, it is necessary to use the KDD Approach and DM techniques in the climatic studies, specific interpreter of climate modeling result.

Model of load distribution for earth observation satellite

NASA Astrophysics Data System (ADS)

Tu, Shumin; Du, Min; Li, Wei

2017-03-01

For the system of multiple types of EOS (Earth Observing Satellites), it is a vital issue to assure that each type of payloads carried by the group of EOS can be used efficiently and reasonably for in astronautics fields. Currently, most of researches on configuration of satellite and payloads focus on the scheduling for launched satellites. However, the assignments of payloads for un-launched satellites are bit researched, which are the same crucial as the scheduling of tasks. Moreover, the current models of satellite resources scheduling lack of more general characteristics. Referring the idea about roles-based access control (RBAC) of information system, this paper brings forward a model based on role-mining of RBAC to improve the generality and foresight of the method of assignments of satellite-payload. By this way, the assignment of satellite-payload can be mapped onto the problem of role-mining. A novel method will be introduced, based on the idea of biclique-combination in graph theory and evolutionary algorithm in intelligence computing, to address the role-mining problem of satellite-payload assignments. The simulation experiments are performed to verify the novel method. Finally, the work of this paper is concluded.

Comparison of Basic and Ensemble Data Mining Methods in Predicting 5-Year Survival of Colorectal Cancer Patients.

PubMed

Pourhoseingholi, Mohamad Amin; Kheirian, Sedigheh; Zali, Mohammad Reza

2017-12-01

Colorectal cancer (CRC) is one of the most common malignancies and cause of cancer mortality worldwide. Given the importance of predicting the survival of CRC patients and the growing use of data mining methods, this study aims to compare the performance of models for predicting 5-year survival of CRC patients using variety of basic and ensemble data mining methods. The CRC dataset from The Shahid Beheshti University of Medical Sciences Research Center for Gastroenterology and Liver Diseases were used for prediction and comparative study of the base and ensemble data mining techniques. Feature selection methods were used to select predictor attributes for classification. The WEKA toolkit and MedCalc software were respectively utilized for creating and comparing the models. The obtained results showed that the predictive performance of developed models was altogether high (all greater than 90%). Overall, the performance of ensemble models was higher than that of basic classifiers and the best result achieved by ensemble voting model in terms of area under the ROC curve (AUC= 0.96). AUC Comparison of models showed that the ensemble voting method significantly outperformed all models except for two methods of Random Forest (RF) and Bayesian Network (BN) considered the overlapping 95% confidence intervals. This result may indicate high predictive power of these two methods along with ensemble voting for predicting 5-year survival of CRC patients.

Environmental Impact of the Helen, Research, and Chicago Mercury Mines on Water, Sediment, and Biota in the Upper Dry Creek Watershed, Lake County, California

USGS Publications Warehouse

Rytuba, James J.; Hothem, Roger L.; May, Jason T.; Kim, Christopher S.; Lawler, David; Goldstein, Daniel; Brussee, Brianne E.

2009-01-01

The Helen, Research, and Chicago mercury (Hg) deposits are among the youngest Hg deposits in the Coast Range Hg mineral belt and are located in the southwestern part of the Clear Lake volcanic field in Lake County, California. The mine workings and tailings are located in the headwaters of Dry Creek. The Helen Hg mine is the largest mine in the watershed having produced about 7,600 flasks of Hg. The Chicago and Research Hg mines produced only a small amount of Hg, less than 30 flasks. Waste rock and tailings have eroded from the mines, and mine drainage from the Helen and Research mines contributes Hg-enriched mine wastes to the headwaters of Dry Creek and contaminate the creek further downstream. The mines are located on federal land managed by the U.S. Bureau of Land Management (USBLM). The USBLM requested that the U.S. Geological Survey (USGS) measure and characterize Hg and geochemical constituents in tailings, sediment, water, and biota at the Helen, Research, and Chicago mines and in Dry Creek. This report is made in response to the USBLM request to conduct a Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA - Removal Site Investigation (RSI). The RSI applies to removal of Hg-contaminated mine waste from the Helen, Research, and Chicago mines as a means of reducing Hg transport to Dry Creek. This report summarizes data obtained from field sampling of mine tailings, waste rock, sediment, and water at the Helen, Research, and Chicago mines on April 19, 2001, during a storm event. Further sampling of water, sediment, and biota at the Helen mine area and the upper part of Dry Creek was completed on July 15, 2003, during low-flow conditions. Our results permit a preliminary assessment of the mining sources of Hg and associated chemical constituents that could elevate levels of monomethyl Hg (MMeHg) in the water, sediment, and biota that are impacted by historic mining.

New efforts using helicopter-borne and ground based electromagnetics for mineral exploration

NASA Astrophysics Data System (ADS)

Meyer, U.; Siemon, B.; Noell, U.; Gutzmer, J.; Spitzer, K.; Becken, M.

2014-12-01

Throughout the last decades mineral resources, especially rare earth elements, gained a steadily growing importance in industry and therefore as well in exploration. New targets for mineral investigations came into focus and known sources have been and will be revisited. Since most of the mining for mineral resources in the past took place in the upper hundred metres below surface new techniques made deeper mining economically feasible. Consequently, mining engineers need the best possible knowledge about the full spatial extent of prospective geological structures, including their maximum depths. Especially in Germany and Europe, politics changed in terms not to rely only on the global mineral trade market but on national resources, if available. BGR and partners therefore started research programs on different levels to evaluate and develop new technologies on environmental friendly, non-invasive spatial exploration using airborne and partly ground-based electromagnetic methods. Mining waste heaps have been explored for valuable residual minerals (research project ROBEHA), a promising tin bearing ore body is being explored by airborne electromagnetics (research project E3) and a new airborne technology is aimed at to be able to reach investigation depths of about 1 km (research project DESMEX). First results of the projects ROBEHA and E3 will be presented and the project layout of DESMEX will be discussed.

Mining influence on underground water resources in arid and semiarid regions

NASA Astrophysics Data System (ADS)

Luo, A. K.; Hou, Y.; Hu, X. Y.

2018-02-01

Coordinated mining of coal and water resources in arid and semiarid regions has traditionally become a focus issue. The research takes Energy and Chemical Base in Northern Shaanxi as an example, and conducts statistical analysis on coal yield and drainage volume from several large-scale mines in the mining area. Meanwhile, research determines average water volume per ton coal, and calculates four typical years’ drainage volume in different mining intensity. Then during mining drainage, with the combination of precipitation observation data in recent two decades and water level data from observation well, the calculation of groundwater table, precipitation infiltration recharge, and evaporation capacity are performed. Moreover, the research analyzes the transforming relationship between surface water, mine water, and groundwater. The result shows that the main reason for reduction of water resources quantity and transforming relationship between surface water, groundwater, and mine water is massive mine drainage, which is caused by large-scale coal mining in the research area.

Biomedical text mining for research rigor and integrity: tasks, challenges, directions.

PubMed

Kilicoglu, Halil

2017-06-13

An estimated quarter of a trillion US dollars is invested in the biomedical research enterprise annually. There is growing alarm that a significant portion of this investment is wasted because of problems in reproducibility of research findings and in the rigor and integrity of research conduct and reporting. Recent years have seen a flurry of activities focusing on standardization and guideline development to enhance the reproducibility and rigor of biomedical research. Research activity is primarily communicated via textual artifacts, ranging from grant applications to journal publications. These artifacts can be both the source and the manifestation of practices leading to research waste. For example, an article may describe a poorly designed experiment, or the authors may reach conclusions not supported by the evidence presented. In this article, we pose the question of whether biomedical text mining techniques can assist the stakeholders in the biomedical research enterprise in doing their part toward enhancing research integrity and rigor. In particular, we identify four key areas in which text mining techniques can make a significant contribution: plagiarism/fraud detection, ensuring adherence to reporting guidelines, managing information overload and accurate citation/enhanced bibliometrics. We review the existing methods and tools for specific tasks, if they exist, or discuss relevant research that can provide guidance for future work. With the exponential increase in biomedical research output and the ability of text mining approaches to perform automatic tasks at large scale, we propose that such approaches can support tools that promote responsible research practices, providing significant benefits for the biomedical research enterprise. Published by Oxford University Press 2017. This work is written by a US Government employee and is in the public domain in the US.

Geological modelling of mineral deposits for prediction in mining

NASA Astrophysics Data System (ADS)

Sides, E. J.

Accurate prediction of the shape, location, size and properties of the solid rock materials to be extracted during mining is essential for reliable technical and financial planning. This is achieved through geological modelling of the three-dimensional (3D) shape and properties of the materials present in mineral deposits, and the presentation of results in a form which is accessible to mine planning engineers. In recent years the application of interactive graphics software, offering 3D database handling, modelling and visualisation, has greatly enhanced the options available for predicting the subsurface limits and characteristics of mineral deposits. A review of conventional 3D geological interpretation methods, and the model struc- tures and modelling methods used in reserve estimation and mine planning software packages, illustrates the importance of such approaches in the modern mining industry. Despite the widespread introduction and acceptance of computer hardware and software in mining applications, in recent years, there has been little fundamental change in the way in which geology is used in orebody modelling for predictive purposes. Selected areas of current research, aimed at tackling issues such as the use of orientation data, quantification of morphological differences, incorporation of geological age relationships, multi-resolution models and the application of virtual reality hardware and software, are discussed.

Machine-related injuries in the US mining industry and priorities for safety research.

PubMed

Ruff, Todd; Coleman, Patrick; Martini, Laura

2011-03-01

Researchers at the National Institute for Occupational Safety and Health studied mining accidents that involved a worker entangled in, struck by, or in contact with machinery or equipment in motion. The motivation for this study came from the large number of severe accidents, i.e. accidents resulting in a fatality or permanent disability, that are occurring despite available interventions. Accident descriptions were taken from an accident database maintained by the United States Department of Labor, Mine Safety and Health Administration, and 562 accidents that occurred during 2000-2007 fit the search criteria. Machine-related accidents accounted for 41% of all severe accidents in the mining industry during this period. Machinery most often involved in these accidents included conveyors, rock bolting machines, milling machines and haulage equipment such as trucks and loaders. The most common activities associated with these accidents were operation of the machine and maintenance and repair. The current methods to safeguard workers near machinery include mechanical guarding around moving components, lockout/tagout of machine power during maintenance and backup alarms for mobile equipment. To decrease accidents further, researchers recommend additional efforts in the development of new control technologies, training materials and dissemination of information on best practices.

VRLane: a desktop virtual safety management program for underground coal mine

NASA Astrophysics Data System (ADS)

Li, Mei; Chen, Jingzhu; Xiong, Wei; Zhang, Pengpeng; Wu, Daozheng

2008-10-01

VR technologies, which generate immersive, interactive, and three-dimensional (3D) environments, are seldom applied to coal mine safety work management. In this paper, a new method that combined the VR technologies with underground mine safety management system was explored. A desktop virtual safety management program for underground coal mine, called VRLane, was developed. The paper mainly concerned about the current research advance in VR, system design, key techniques and system application. Two important techniques were introduced in the paper. Firstly, an algorithm was designed and implemented, with which the 3D laneway models and equipment models can be built on the basis of the latest mine 2D drawings automatically, whereas common VR programs established 3D environment by using 3DS Max or the other 3D modeling software packages with which laneway models were built manually and laboriously. Secondly, VRLane realized system integration with underground industrial automation. VRLane not only described a realistic 3D laneway environment, but also described the status of the coal mining, with functions of displaying the run states and related parameters of equipment, per-alarming the abnormal mining events, and animating mine cars, mine workers, or long-wall shearers. The system, with advantages of cheap, dynamic, easy to maintenance, provided a useful tool for safety production management in coal mine.

Real -time dispatching modelling for trucks with different capacities in open pit mines / Modelowanie w czasie rzeczywistym przewozów ciężarówek o różnej ładowności w kopalni odkrywkowej

NASA Astrophysics Data System (ADS)

Ahangaran, Daryoush Kaveh; Yasrebi, Amir Bijan; Wetherelt, Andy; Foster, Patrick

2012-10-01

Application of fully automated systems for truck dispatching plays a major role in decreasing the transportation costs which often represent the majority of costs spent on open pit mining. Consequently, the application of a truck dispatching system has become fundamentally important in most of the world's open pit mines. Recent experiences indicate that by decreasing a truck's travelling time and the associated waiting time of its associated shovel then due to the application of a truck dispatching system the rate of production will be considerably improved. Computer-based truck dispatching systems using algorithms, advanced and accurate software are examples of these innovations. Developing an algorithm of a computer- based program appropriated to a specific mine's conditions is considered as one of the most important activities in connection with computer-based dispatching in open pit mines. In this paper the changing trend of programming and dispatching control algorithms and automation conditions will be discussed. Furthermore, since the transportation fleet of most mines use trucks with different capacities, innovative methods, operational optimisation techniques and the best possible methods for developing the required algorithm for real-time dispatching are selected by conducting research on mathematical-based planning methods. Finally, a real-time dispatching model compatible with the requirement of trucks with different capacities is developed by using two techniques of flow networks and integer programming.

Simulation of Industrial Wastewater Treatment from the Suspended Impurities into the Flooded Waste Mining Workings

NASA Astrophysics Data System (ADS)

Bondareva, L.; Zakharov, Yu; Goudov, A.

2017-04-01

The paper is dedicated to the mathematical model of slurry wastewater treatment and disposal in a flooded mine working. The goal of the research is to develop and analyze the mathematical model of suspended impurities flow and distribution. Impurity sedimentation model is under consideration. Due to the sediment compaction problem solution domain can be modified. The model allows making a forecast whether volley emission is possible. Numerical simulation results for “Kolchuginskaya” coal mine presented. Impurity concentration diagrams in outflow corresponding to the real full-scale data obtained. Safely operation time mine workings like a wastewater treatment facility are estimated. The carried out calculations demonstrate that the method of industrial wastewater treatment in flooded waste mine workings can be put into practice but it is very important to observe all the processes going on to avoid volley emission of accumulated impurities.

Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

NASA Astrophysics Data System (ADS)

Wahyuni, Sri

2018-03-01

Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

Safety leadership and systems thinking: application and evaluation of a Risk Management Framework in the mining industry.

PubMed

Donovan, Sarah-Louise; Salmon, Paul M; Lenné, Michael G; Horberry, Tim

2017-10-01

Safety leadership is an important factor in supporting safety in high-risk industries. This article contends that applying systems-thinking methods to examine safety leadership can support improved learning from incidents. A case study analysis was undertaken of a large-scale mining landslide incident in which no injuries or fatalities were incurred. A multi-method approach was adopted, in which the Critical Decision Method, Rasmussen's Risk Management Framework and Accimap method were applied to examine the safety leadership decisions and actions which enabled the safe outcome. The approach enabled Rasmussen's predictions regarding safety and performance to be examined in the safety leadership context, with findings demonstrating the distribution of safety leadership across leader and system levels, and the presence of vertical integration as key to supporting the successful safety outcome. In doing so, the findings also demonstrate the usefulness of applying systems-thinking methods to examine and learn from incidents in terms of what 'went right'. The implications, including future research directions, are discussed. Practitioner Summary: This paper presents a case study analysis, in which systems-thinking methods are applied to the examination of safety leadership decisions and actions during a large-scale mining landslide incident. The findings establish safety leadership as a systems phenomenon, and furthermore, demonstrate the usefulness of applying systems-thinking methods to learn from incidents in terms of what 'went right'. Implications, including future research directions, are discussed.

Mining method selection by integrated AHP and PROMETHEE method.

PubMed

Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

2012-03-01

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

Characterization of airborne float coal dust emitted during continuous mining, longwall mining and belt transport

PubMed Central

Shahan, M.R.; Seaman, C.E.; Beck, T.W.; Colinet, J.F.; Mischler, S.E.

2017-01-01

Float coal dust is produced by various mining methods, carried by ventilating air and deposited on the floor, roof and ribs of mine airways. If deposited, float dust is re-entrained during a methane explosion. Without sufficient inert rock dust quantities, this float coal dust can propagate an explosion throughout mining entries. Consequently, controlling float coal dust is of critical interest to mining operations. Rock dusting, which is the adding of inert material to airway surfaces, is the main control technique currently used by the coal mining industry to reduce the float coal dust explosion hazard. To assist the industry in reducing this hazard, the Pittsburgh Mining Research Division of the U.S. National Institute for Occupational Safety and Health initiated a project to investigate methods and technologies to reduce float coal dust in underground coal mines through prevention, capture and suppression prior to deposition. Field characterization studies were performed to determine quantitatively the sources, types and amounts of dust produced during various coal mining processes. The operations chosen for study were a continuous miner section, a longwall section and a coal-handling facility. For each of these operations, the primary dust sources were confirmed to be the continuous mining machine, longwall shearer and conveyor belt transfer points, respectively. Respirable and total airborne float dust samples were collected and analyzed for each operation, and the ratio of total airborne float coal dust to respirable dust was calculated. During the continuous mining process, the ratio of total airborne float coal dust to respirable dust ranged from 10.3 to 13.8. The ratios measured on the longwall face were between 18.5 and 21.5. The total airborne float coal dust to respirable dust ratio observed during belt transport ranged between 7.5 and 21.8. PMID:28936001

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

PubMed Central

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277

Text mining in livestock animal science: introducing the potential of text mining to animal sciences.

PubMed

Sahadevan, S; Hofmann-Apitius, M; Schellander, K; Tesfaye, D; Fluck, J; Friedrich, C M

2012-10-01

In biological research, establishing the prior art by searching and collecting information already present in the domain has equal importance as the experiments done. To obtain a complete overview about the relevant knowledge, researchers mainly rely on 2 major information sources: i) various biological databases and ii) scientific publications in the field. The major difference between the 2 information sources is that information from databases is available, typically well structured and condensed. The information content in scientific literature is vastly unstructured; that is, dispersed among the many different sections of scientific text. The traditional method of information extraction from scientific literature occurs by generating a list of relevant publications in the field of interest and manually scanning these texts for relevant information, which is very time consuming. It is more than likely that in using this "classical" approach the researcher misses some relevant information mentioned in the literature or has to go through biological databases to extract further information. Text mining and named entity recognition methods have already been used in human genomics and related fields as a solution to this problem. These methods can process and extract information from large volumes of scientific text. Text mining is defined as the automatic extraction of previously unknown and potentially useful information from text. Named entity recognition (NER) is defined as the method of identifying named entities (names of real world objects; for example, gene/protein names, drugs, enzymes) in text. In animal sciences, text mining and related methods have been briefly used in murine genomics and associated fields, leaving behind other fields of animal sciences, such as livestock genomics. The aim of this work was to develop an information retrieval platform in the livestock domain focusing on livestock publications and the recognition of relevant data from cattle and pigs. For this purpose, the rather noncomprehensive resources of pig and cattle gene and protein terminologies were enriched with orthologue synonyms, integrated in the NER platform, ProMiner, which is successfully used in human genomics domain. Based on the performance tests done, the present system achieved a fair performance with precision 0.64, recall 0.74, and F(1) measure of 0.69 in a test scenario based on cattle literature.

Opinion mining on book review using CNN-L2-SVM algorithm

NASA Astrophysics Data System (ADS)

Rozi, M. F.; Mukhlash, I.; Soetrisno; Kimura, M.

2018-03-01

Review of a product can represent quality of a product itself. An extraction to that review can be used to know sentiment of that opinion. Process to extract useful information of user review is called Opinion Mining. Review extraction model that is enhancing nowadays is Deep Learning model. This Model has been used by many researchers to obtain excellent performance on Natural Language Processing. In this research, one of deep learning model, Convolutional Neural Network (CNN) is used for feature extraction and L2 Support Vector Machine (SVM) as classifier. These methods are implemented to know the sentiment of book review data. The result of this method shows state-of-the art performance in 83.23% for training phase and 64.6% for testing phase.

Web-video-mining-supported workflow modeling for laparoscopic surgeries.

PubMed

Liu, Rui; Zhang, Xiaoli; Zhang, Hao

2016-11-01

As quality assurance is of strong concern in advanced surgeries, intelligent surgical systems are expected to have knowledge such as the knowledge of the surgical workflow model (SWM) to support their intuitive cooperation with surgeons. For generating a robust and reliable SWM, a large amount of training data is required. However, training data collected by physically recording surgery operations is often limited and data collection is time-consuming and labor-intensive, severely influencing knowledge scalability of the surgical systems. The objective of this research is to solve the knowledge scalability problem in surgical workflow modeling with a low cost and labor efficient way. A novel web-video-mining-supported surgical workflow modeling (webSWM) method is developed. A novel video quality analysis method based on topic analysis and sentiment analysis techniques is developed to select high-quality videos from abundant and noisy web videos. A statistical learning method is then used to build the workflow model based on the selected videos. To test the effectiveness of the webSWM method, 250 web videos were mined to generate a surgical workflow for the robotic cholecystectomy surgery. The generated workflow was evaluated by 4 web-retrieved videos and 4 operation-room-recorded videos, respectively. The evaluation results (video selection consistency n-index ≥0.60; surgical workflow matching degree ≥0.84) proved the effectiveness of the webSWM method in generating robust and reliable SWM knowledge by mining web videos. With the webSWM method, abundant web videos were selected and a reliable SWM was modeled in a short time with low labor cost. Satisfied performances in mining web videos and learning surgery-related knowledge show that the webSWM method is promising in scaling knowledge for intelligent surgical systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

PubMed Central

Huang, Jingshan; Dou, Dejing; Dang, Jiangbo; Pardue, J Harold; Qin, Xiao; Huan, Jun; Gerthoffer, William T; Tan, Ming

2012-01-01

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. PMID:22371823

Joe Robertson | NREL

Science.gov Websites

Joe Robertson Photo of Joe Robertson Joe Robertson Research Engineer Joseph.Robertson@nrel.gov | 303-275-4575 Joe joined NREL in 2012. His research activities include automated building model student from the Colorado School of Mines on projects involving numerical methods applied to uncertainty

Prediction and assessment of the disturbances of the coal mining in Kailuan to karst groundwater system

NASA Astrophysics Data System (ADS)

Sun, Wenjie; Wu, Qiang; Liu, Honglei; Jiao, Jian

Coal resources and water resources play an essential and strategic role in the development of China's social and economic development, being the priority for China's medium and long technological development. As the mining of the coal extraction is increasingly deep, the mine water inrush of high-pressure confined karst water becomes much more a problem. This paper carried out research on the hundred-year old Kailuan coal mine's karst groundwater system. With the help of advanced Visual Modflow software and numerical simulation method, the paper assessed the flow field of karst water area under large-scale exploitation. It also predicted the evolution ofgroundwaterflow field under different mining schemes of Kailuan Corp. The result shows that two cones of depression are formed in the karst flow field of Zhaogezhuang mining area and Tangshan mining area, and the water levels in two cone centers are -270 m and -31 m respectively, and the groundwater generally flows from the northeast to the southwest. Given some potential closed mines in the future, the mine discharge will decrease and the water level of Ordovician limestone will increase slightly. Conversely, given increase of coal yield, the mine drainage will increase, falling depression cone of Ordovician limestone flow field will enlarge. And in Tangshan's urban district, central water level of the depression cone will move slightly towards north due to pumping of a few mines in the north.

Sentiment topic mining based on comment tags

NASA Astrophysics Data System (ADS)

Zhang, Daohai; Liu, Xue; Li, Juan; Fan, Mingyue

2018-03-01

With the development of e-commerce, various comments based on tags are generated, how to extract valuable information from these comment tags has become an important content of business management decisions. This study takes HUAWEI mobile phone tags as an example using the sentiment analysis and topic LDA mining method. The first step is data preprocessing and classification of comment tag topic mining. And then make the sentiment classification for comment tags. Finally, mine the comments again and analyze the emotional theme distribution under different sentiment classification. The results show that HUAWEI mobile phone has a good user experience in terms of fluency, cost performance, appearance, etc. Meanwhile, it should pay more attention to independent research and development, product design and development. In addition, battery and speed performance should be enhanced.

Blasting methods for heterogeneous rocks in hillside open-pit mines with high and steep slopes

NASA Astrophysics Data System (ADS)

Chen, Y. J.; Chang, Z. G.; Chao, X. H.; Zhao, J. F.

2017-06-01

In the arid desert areas in Xinjiang, most limestone quarries are hillside open-pit mines (OPMs) where the limestone is hard, heterogeneous, and fractured, and can be easily broken into large blocks by blasting. This study tried to find effective technical methods for blasting heterogeneous rocks in such quarries based on an investigation into existing problems encountered in actual mining at Hongshun Limestone Quarry in Xinjiang. This study provided blasting schemes for hillside OPMs with different heights and slopes. These schemes involve the use of vertical deep holes, oblique shallow holes, and downslope hole-by-hole sublevel or simultaneous detonation techniques. In each bench, the detonations of holes in a detonation unit occur at intervals of 25-50 milliseconds. The research findings can offer technical guidance on how to blast heterogeneous rocks in hillside limestone quarries.

Text Mining in Organizational Research

PubMed Central

Kobayashi, Vladimer B.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies. PMID:29881248

Text Mining in Organizational Research.

PubMed

Kobayashi, Vladimer B; Mol, Stefan T; Berkers, Hannah A; Kismihók, Gábor; Den Hartog, Deanne N

2018-07-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies.

Optimizing the use of video-tapes of clinical sessions: the data-mining approach for scale construction and theory building for bereaved persons in Hong Kong.

PubMed

Chow, Amy Yin Man

2010-01-01

Video-taping clinical sessions is a common practice among social workers so that the tapes may be used for clinical supervision and reviewed with the individuals or families involved. They are usually underused for research purposes. This article reports on an innovative research method using such tapes as a basis for clinical data mining to explore the bereavement experience of Chinese people in Hong Kong. Using this data, a rich item pool, containing both negative and positive reactions, was generated to allow the development of a culturally relevant measurement tool of grief reactions. The data also facilitated theory building in the area of grief and bereavement. This study extended the use of video-tapes in clinical sessions for research purposes and helped to collect reliable and timely data in a non-intrusive way. It has also advanced the use of quantitative data in the clinical data-mining approach. The study encouraged collaboration between clinicians and researchers to develop knowledge and skills about their special target group of clients.

Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

ERIC Educational Resources Information Center

Yu, Chong Ho; Jannasch-Pennell, Angel; DiGangi, Samuel

2011-01-01

The objective of this article is to illustrate that text mining and qualitative research are epistemologically compatible. First, like many qualitative research approaches, such as grounded theory, text mining encourages open-mindedness and discourages preconceptions. Contrary to the popular belief that text mining is a linear and fully automated…

[Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

PubMed

Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

2015-11-01

Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution level, using stepwise multiple linear regression and cross validation on the dataset which is consisting of 44 groups of copper ion content information in the polluted vegetation leaves from Dexing Copper Mine in Jiangxi Province to build up a statistical model by also incorporating the HJ-1 satellite images. This model was then used to estimate the copper content distribution over the whole research area at Dexing Copper Mine. The result has shown that there is strong statistical significance of the model which revealed the most sensitive waveband to copper ion is located at 516 nm. The distribution map illustrated that the copper ion content is generally in the range of 0-130 mg · kg⁻¹ in the vegetation covering area at Dexing Copper Mine and the most seriously polluted area is located at the South-east corner of Dexing City as well as the mining spots with a higher value between 80 and 100 mg · kg⁻¹. This result is consistent with the ground observation experiment data. The distribution map can certainly provide some important basic data on the copper pollution monitoring and treatment.

Landfill mining: Developing a comprehensive assessment method.

PubMed

Hermann, Robert; Wolfsberger, Tanja; Pomberger, Roland; Sarc, Renato

2016-11-01

In Austria, the first basic technological and economic examinations of mass-waste landfills with the purpose to recover secondary raw materials have been carried out by the 'LAMIS - Landfill Mining Österreich' pilot project. A main focus of its research, and the subject of this article, is the first conceptual design of a comprehensive assessment method for landfill mining plans, including not only monetary factors (like costs and proceeds) but also non-monetary ones, such as the concerns of adjoining owners or the environmental impact. Detailed reviews of references, the identification of influences and system boundaries to be included in planning landfill mining, several expert workshops and talks with landfill operators have been performed followed by a division of the whole assessment method into preliminary and main assessment. Preliminary assessment is carried out with a questionnaire to rate juridical feasibility, the risk and the expenditure of a landfill mining project. The results of this questionnaire are compiled in a portfolio chart that is used to recommend, or not, further assessment. If a detailed main assessment is recommended, defined economic criteria are rated by net present value calculations, while ecological and socio-economic criteria are examined in a utility analysis and then transferred into a utility-net present value chart. If this chart does not support making a definite statement on the feasibility of the project, the results must be further examined in a cost-effectiveness analysis. Here, the benefit of the particular landfill mining project per capital unit (utility-net present value ratio) is determined to make a final distinct statement on the general benefit of a landfill mining project. © The Author(s) 2016.

Comprehensive Fractal Description of Porosity of Coal of Different Ranks

PubMed Central

Ren, Jiangang; Zhang, Guocheng; Song, Zhimin; Liu, Gaofeng; Li, Bing

2014-01-01

We selected, as the objects of our research, lignite from the Beizao Mine, gas coal from the Caiyuan Mine, coking coal from the Xiqu Mine, and anthracite from the Guhanshan Mine. We used the mercury intrusion method and the low-temperature liquid nitrogen adsorption method to analyze the structure and shape of the coal pores and calculated the fractal dimensions of different aperture segments in the coal. The experimental results show that the fractal dimension of the aperture segment of lignite, gas coal, and coking coal with an aperture of greater than or equal to 10 nm, as well as the fractal dimension of the aperture segment of anthracite with an aperture of greater than or equal to 100 nm, can be calculated using the mercury intrusion method; the fractal dimension of the coal pore, with an aperture range between 2.03 nm and 361.14 nm, can be calculated using the liquid nitrogen adsorption method, of which the fractal dimensions bounded by apertures of 10 nm and 100 nm are different. Based on these findings, we defined and calculated the comprehensive fractal dimensions of the coal pores and achieved the unity of fractal dimensions for full apertures of coal pores, thereby facilitating, overall characterization for the heterogeneity of the coal pore structure. PMID:24955407

A baseline lunar mine

NASA Technical Reports Server (NTRS)

Gertsch, Richard E.

1992-01-01

A models lunar mining method is proposed that illustrates the problems to be expected in lunar mining and how they might be solved. While the method is quite feasible, it is, more importantly, a useful baseline system against which to test other, possible better, methods. Our study group proposed the slusher to stimulate discussion of how a lunar mining operation might be successfully accomplished. Critics of the slusher system were invited to propose better methods. The group noted that while nonterrestrial mining has been a vital part of past space manufacturing proposals, no one has proposed a lunar mining system in any real detail. The group considered it essential that the design of actual, workable, and specific lunar mining methods begin immediately. Based on an earlier proposal, the method is a three-drum slusher, also known as a cable-operated drag scraper. Its terrestrial application is quite limited, as it is relatively inefficient and inflexible. The method usually finds use in underwater mining from the shore and in moving small amounts of ore underground. When lunar mining scales up, the lunarized slusher will be replaced by more efficient, high-volume methods. Other aspects of lunar mining are discussed.

Ensemble Data Mining Methods

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.

2004-01-01

Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

Transient states of air parameters after a stoppage and re-start of the main fan / Stany przejściowe parametrów powietrza po postoju i załączeniu wentylatora głównego

NASA Astrophysics Data System (ADS)

Wasilewski, Stanisław

2012-12-01

A stoppage of the main ventilation fan constitutes a disturbance of ventilation conditions of a deepmine and its effects can cause serious hazards by generating transient states of air and gas flow. Main ventilation fans are the basic deep-mine facilities; therefore, under mining regulations it is only allowed to stop them with the consent and under the conditions specified by the mine maintenance manager. The stoppage of the main ventilation fan may be accompanied by transient air parameters, including the air pressure and flow patterns. There is even the likelihood of reversing the direction of air flow, which, in case of methane mines, can pose a major hazard, particularly in sections of the mine with fire fields or large goaf areas. At the same time, stoppages of deep-mine main ventilation fans create interesting research conditions, which if conducted under the supervision of the monitoring systems, can provide much information about the transient processes of pressure, air and gas flow in underground workings. This article is a discussion of air parameter observations in mine workings made as part of such experiments. It also presents the procedure of the experiments, conducted in three mines. They involved the observation of transient processes of mine air parameters, and most interestingly, the recording of pressure and air and gas flow in the workings of the mine ventilation networks by mine monitoring systems and using specialist recording instruments. In mining practice, both in Poland and elsewhere, software tools and computer modelling methods are used to try and reproduce the conditions prior to and during disasters based on the existing network model and monitoring system data. The use of these tools to simulate the alternatives of combating and liquidation of the gas-fire hazard after its occurrence is an important issue. Measurement data collected during the experiments provides interesting research material for the verification and validation of the software tools used for the simulation of processes occurring in deep-mine ventilation systems.

Identification of Social and Environmental Conflicts Resulting from Open-Cast Mining

NASA Astrophysics Data System (ADS)

Górniak-Zimroz, Justyna; Pactwa, Katarzyna

2016-10-01

Open-cast mining is related to interference in the natural environment. It also affects human health and quality of life. This influence is, among others, dependent on the type of extracted materials, size of deposit, methods of mining and mineral processing, as well as, equally important, sensitivity of the environment within which mining is planned. The negative effects of mining include deformations of land surface or contamination of soils, air and water. What is more, in many cases, mining for minerals leads to clearing of housing and transport infrastructures located within the mining area, a decrease in values of the properties in the immediate vicinity of a deposit, and an increase in stress levels in local residents exposed to noise. The awareness of negative consequences of taking up open-cast mining activity leads to conflicts between a mining entrepreneur and self-government authorities, society or nongovernment organisations. The article attempts to identify potential social and environmental conflicts that may occur in relation to a planned mining activity. The results of the analyses were interpreted with respect to the deposits which were or have been mined. That enabled one to determine which facilities exclude mineral mining and which allow it. The research took the non-energy mineral resources into consideration which are included in the group of solid minerals located in one of the districts of Lower Silesian Province (SW Poland). The spatial analyses used the tools available in the geographical information systems

Psychosocial service needs of pediatric transport accident survivors: Using clinical data-mining to establish demographic and service usage characteristics.

PubMed

Manguy, Alys-Marie; Joubert, Lynette; Bansemer, Leah

2016-09-01

The objectives in this article are the exploration of demographic and service usage data gained through clinical data mining audit and suggesting recommendations for social work service delivery model and future research. The method is clinical data-mining audit of 100 sequentially sampled cases gathering quantitative demographic and service usage data. Descriptive analysis of file audit data raised interesting trends with potential to inform service delivery and usage; the key areas of the results included patient demographics, family involvement and impact, and child safety and risk issues. Transport accidents involving children often include other family members. Care planning must take into account psychosocial issues including patient and family emotional responses, availability of primary carers, and other practical needs that may impact on recovery and discharge planning. This study provides evidence to plan for further research and development of more integrated models of care.

Bats, cyanide, and gold mining

USGS Publications Warehouse

Clark, Donald R.

1991-01-01

Although the boom days of prospectors and gold nuggets are long gone, modern technology enables gold to continue to be extracted from ore. Unfortunately, the extraction method has often been disastrous for bats and other wildlife, an issue I first became aware of in early 1989. Phone calls from Drs. Merlin Tuttle and Elizabeth Pierson, a BCI member and bat researcher from Berkeley, California, alerted me that bats were dying from apparent cyanide poisoning at gold mines in the western United States.

[Soil seed bank research of China mining areas: necessity and challenges].

PubMed

Chang, Qing; Zhang, Da-Wei; Li, Xue; Peng, Jian; Guan, Ai-Nong; Liu, Xiao-Si

2011-05-01

Soil seed bank consists of all living seeds existed in soil and its surface litter, especially in topsoil, and can reflect the characteristics of regional biodiversity. As the base of vegetation restoration and potential greening material, topsoil and its seed bank are the limited and non-renewable resources in mining areas. The study of soil seed bank has become one of the hotspots in the research field of vegetation restoration and land reclamation in China mining areas. Owing to the special characteristics of mining industry, the soil seed bank study of mining areas should not only concern with the seed species, quantities, and their relations with ground surface vegetation, but also make use of the research results on the soil seed bank of other fragile habitats. Besides, a breakthrough should be sought in the thinking ways and research approach. This paper analyzed the particularity of mining area's soil seek bank research, summarized the research progress in the soil seed bank of mining areas and other fragile habitats, and put forward the challenges we are facing with. It was expected that this paper could help to reinforce the soil seed bank research of China mining areas, and provide scientific guidelines for taking great advantage of the significant roles of soil seed bank in land reclamation and vegetation restoration in the future.

Continuous Rating for Diggability Assessment in Surface Mines

NASA Astrophysics Data System (ADS)

IPHAR, Melih

2016-10-01

The rocks can be loosened either by drilling-blasting or direct excavation using powerful machines in opencast mining operations. The economics of rock excavation is considered for each method to be applied. If blasting operation is not preferred and also the geological structures and rock mass properties in site are convenient (favourable ground conditions) for ripping or direct excavation method by mining machines, the next step is to determine which machine or excavator should be selected for the excavation purposes. Many researchers have proposed several diggability or excavatability assessment methods for deciding on excavator type to be used in the field. Most of these systems are generally based on assigning a rating for the parameters having importance in rock excavation process. However, the sharp transitions between the two adjacent classes for a given parameter can lead to some uncertainties. In this paper, it has been proposed that varying rating should be assigned for a given parameter called as “continuous rating” instead of giving constant rating for a given class.

An efficient and practical approach to obtain a better optimum solution for structural optimization

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu; Huang, Jyun-Hao

2013-08-01

For many structural optimization problems, it is hard or even impossible to find the global optimum solution owing to unaffordable computational cost. An alternative and practical way of thinking is thus proposed in this research to obtain an optimum design which may not be global but is better than most local optimum solutions that can be found by gradient-based search methods. The way to reach this goal is to find a smaller search space for gradient-based search methods. It is found in this research that data mining can accomplish this goal easily. The activities of classification, association and clustering in data mining are employed to reduce the original design space. For unconstrained optimization problems, the data mining activities are used to find a smaller search region which contains the global or better local solutions. For constrained optimization problems, it is used to find the feasible region or the feasible region with better objective values. Numerical examples show that the optimum solutions found in the reduced design space by sequential quadratic programming (SQP) are indeed much better than those found by SQP in the original design space. The optimum solutions found in a reduced space by SQP sometimes are even better than the solution found using a hybrid global search method with approximate structural analyses.

Research on Occupational Safety, Health Management and Risk Control Technology in Coal Mines.

PubMed

Zhou, Lu-Jie; Cao, Qing-Gui; Yu, Kai; Wang, Lin-Lin; Wang, Hai-Bin

2018-04-26

This paper studies the occupational safety and health management methods as well as risk control technology associated with the coal mining industry, including daily management of occupational safety and health, identification and assessment of risks, early warning and dynamic monitoring of risks, etc.; also, a B/S mode software (Geting Coal Mine, Jining, Shandong, China), i.e., Coal Mine Occupational Safety and Health Management and Risk Control System, is developed to attain the aforementioned objectives, namely promoting the coal mine occupational safety and health management based on early warning and dynamic monitoring of risks. Furthermore, the practical effectiveness and the associated pattern for applying this software package to coal mining is analyzed. The study indicates that the presently developed coal mine occupational safety and health management and risk control technology and the associated software can support the occupational safety and health management efforts in coal mines in a standardized and effective manner. It can also control the accident risks scientifically and effectively; its effective implementation can further improve the coal mine occupational safety and health management mechanism, and further enhance the risk management approaches. Besides, its implementation indicates that the occupational safety and health management and risk control technology has been established based on a benign cycle involving dynamic feedback and scientific development, which can provide a reliable assurance to the safe operation of coal mines.

Research on Occupational Safety, Health Management and Risk Control Technology in Coal Mines

PubMed Central

Zhou, Lu-jie; Cao, Qing-gui; Yu, Kai; Wang, Lin-lin; Wang, Hai-bin

2018-01-01

This paper studies the occupational safety and health management methods as well as risk control technology associated with the coal mining industry, including daily management of occupational safety and health, identification and assessment of risks, early warning and dynamic monitoring of risks, etc.; also, a B/S mode software (Geting Coal Mine, Jining, Shandong, China), i.e., Coal Mine Occupational Safety and Health Management and Risk Control System, is developed to attain the aforementioned objectives, namely promoting the coal mine occupational safety and health management based on early warning and dynamic monitoring of risks. Furthermore, the practical effectiveness and the associated pattern for applying this software package to coal mining is analyzed. The study indicates that the presently developed coal mine occupational safety and health management and risk control technology and the associated software can support the occupational safety and health management efforts in coal mines in a standardized and effective manner. It can also control the accident risks scientifically and effectively; its effective implementation can further improve the coal mine occupational safety and health management mechanism, and further enhance the risk management approaches. Besides, its implementation indicates that the occupational safety and health management and risk control technology has been established based on a benign cycle involving dynamic feedback and scientific development, which can provide a reliable assurance to the safe operation of coal mines. PMID:29701715

Keeping rail on track: preliminary findings on safety culture in Australian rail.

PubMed

Blewett, Verna; Rainbird, Sophia; Dorrian, Jill; Paterson, Jessica; Cattani, Marcus

2012-01-01

'Safety culture' is identified in the literature as a critical element of healthy and safe workplaces. How can rail organizations ensure that consistently effective work health and safety cultures are maintained across the diversity of their operations? This paper reports on research that is currently underway in the Australian rail industry aimed at producing a Model of Best Practice in Safety Culture for the industry. Located in rail organizations dedicated to the mining industry as well as urban rail and national freight operations, the research examines the constructs of organizational culture that impact on the development and maintenance of healthy and safe workplaces. The research uses a multi-method approach incorporating quantitative (survey) and qualitative (focus groups, interviews and document analysis) methods along with a participative process to identify interventions to improve the organization and develop plans for their implementation. The research uses as its analytical framework the 10 Platinum Rules, from the findings of earlier research in the New South Wales (Australia) mining industry, Digging Deeper. Data collection is underway at the time of writing and preliminary findings are presented at this stage. The research method may be adapted for use as a form of organizational review of safety and health in organizational culture.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

PubMed

He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

2014-01-01

Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.

Biomedical text mining and its applications in cancer research.

PubMed

Zhu, Fei; Patumcharoenpol, Preecha; Zhang, Cheng; Yang, Yang; Chan, Jonathan; Meechai, Asawin; Vongsangnak, Wanwipa; Shen, Bairong

2013-04-01

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research. Copyright © 2012 Elsevier Inc. All rights reserved.

[An Introduction to Methods for Evaluating Health Care Technology].

PubMed

Lee, Ting-Ting

2015-06-01

The rapid and continual advance of healthcare technology makes ensuring that this technology is used effectively to achieve its original goals a critical issue. This paper presents three methods that may be applied by healthcare professionals in the evaluation of healthcare technology. These methods include: the perception/experiences of users, user work-pattern changes, and chart review or data mining. The first method includes two categories: using interviews to explore the user experience and using theory-based questionnaire surveys. The second method applies work sampling to observe the work pattern changes of users. The last method conducts chart reviews or data mining to analyze the designated variables. In conclusion, while evaluative feedback may be used to improve the design and development of healthcare technology applications, the informatics competency and informatics literacy of users may be further explored in future research.

Network-Centric Data Mining for Medical Applications

ERIC Educational Resources Information Center

Davis, Darcy A.

2012-01-01

Faced with unsustainable costs and enormous amounts of under-utilized data, health care needs more efficient practices, research, and tools to harness the benefits of data. These methods create a feedback loop where computational tools guide and facilitate research, leading to improved biological knowledge and clinical standards, which will in…

Rapid Evaluation of Radioactive Contamination in Rare Earth Mine Mining

NASA Astrophysics Data System (ADS)

Wang, N.

2017-12-01

In order to estimate the current levels of environmental radioactivity in Bayan Obo rare earth mine and to study the rapid evaluation methods of radioactivity contamination in the rare earth mine, the surveys of the in-situ gamma-ray spectrometry and gamma dose rate measurement were carried out around the mining area and living area. The in-situ gamma-ray spectrometer was composed of a scintillation detector of NaI(Tl) (Φ75mm×75mm) and a multichannel analyzer. Our survey results in Bayan Obo Mine display: (1) Thorium-232 is the radioactive contamination source of this region, and uranium-238 and potassium - 40 is at the background level. (2) The average content of thorium-232 in the slag of the tailings dam in Bayan Obo is as high as 276 mg/kg, which is 37 times as the global average value of thorium content. (3) We found that the thorium-232 content in the soil in the living area near the mining is higher than that in the local soil in Guyang County. The average thorium-232 concentrations in the mining areas of the Bayan Obo Mine and the living areas of the Bayan Obo Town were 18.7±7.5 and 26.2±9.1 mg/kg, respectively. (4) It was observed that thorium-232 was abnormal distributed in the contaminated area near the tailings dam. Our preliminary research results show that the in-situ gamma-ray spectrometry is an effective approach of fast evaluating rare earths radioactive pollution, not only can the scene to determine the types of radioactive contamination source, but also to measure the radioactivity concentration of thorium and uranium in soil. The environmental radioactive evaluation of rare earth ore and tailings dam in open-pit mining is also needed. The research was supported by National Natural Science Foundation of China (No. 41674111).

Geophysical exploration of historical mine dumps for the estimation of valuable residuals

NASA Astrophysics Data System (ADS)

Martin, Tina; Knieß, Rudolf; Noell, Ursula; Hupfer, Sarah; Kuhn, Kerstin; Günther, Thomas

2015-04-01

Within the project ROBEHA, funded by the German Federal Ministry of Education and Research (033R105) the economic potential of different abandoned dump sites for mine waste in the Harz Mountains was investigated. Two different mining dumps were geophysically and mineralogically analysed in order to characterize the mine dump structure and to estimate the volume of the potential recycling material. The geophysical methods comprised geoelectrics, radar, and spectral induced polarization (SIP). One about 100-year old mining dump containing residues from density separated Ag- and Sb-rich Pb (Zn)-gangue ores was investigated in detail. Like most small-scale mining waste disposal sites this investigated dump is very heterogeneously structured. Therefore, 27 geoelectrical profiles, more than 50 radar profiles, and several SIP profiles were measured and analysed. The results from the radar measurements, registered with the GSSI system and a shielded 200 MHz antenna, show the near surface boundary layer (down to 3-4 m beneath surface) of the waste residuals. These results can be used as pre-information for the inversion process of the geoelectrical data. The geoelectrical results reveal the mineral residues as layers with higher resistivities (> 300 Ohm*m) than the surrounding material. The SIP method found low phase signals (< 0.5°) for the residues. To estimate the volume of the potentially reusable material we analysed each geoelectrical profile and interpolated between the single profiles using the BERT algorithm. Taking into account the wooded areas of the mine dump and other parameters we get a first estimate for the volume of the residues but the economical viability and the environmental impact of the reworking of the dump still needs to be evaluated in detail. The results of the second mine dump, an abandoned Cu and Zn-rich slag heap, show that the slag residues are characterized by higher resistivities and higher phases. A localization of the slag residues which are covered by organic material could be realized applying these geophysical methods.

Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data

PubMed Central

Király, András; Abonyi, János

2014-01-01

During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data) and biclustering (applied to gene expression data analysis). The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers. PMID:24616651

Application and research of block caving in Pulang copper mine

NASA Astrophysics Data System (ADS)

Ge, Qifa; Fan, Wenlu; Zhu, Weigen; Chen, Xiaowei

2018-01-01

The application of block caving in mines shows significant advantages in large scale, low cost and high efficiency, thus block caving is worth promoting in the mines that meets the requirement of natural caving. Due to large scale of production and low ore grade in Pulang copper mine in China, comprehensive analysis and research were conducted on rock mechanics, mining sequence, undercutting and stability of bottom structure in terms of raising mine benefit and maximizing the recovery mineral resources. Finally this study summarizes that block caving is completely suitable for Pulang copper mine.

Predicting rock bursts in mines

USGS Publications Warehouse

Spall, H.

1979-01-01

The microseismic method relies on observational data, amply demonstrated in laboratory experiments, that acoustic noise occurs in rocks subjected to high differential stresses. Acoustic emission becomes most pronounced as the breaking strength of the rock is reached. Laboratory studies have shown that the acoustic emission is linked with the release of stored strain energy as the rock mass undergoes small-scale adjustments such as the formation of cracks. Studies in actual mines have shown that acoustic noises often precede failure of rock masses in rock bursts or in coal bumps. Seismologists are, therefore, very interested in whether these results can be applied to large-scale failures; that is, earthquakes. An active research program in predicting rock bursts in mines is being conducted by Brian T. Brady and his colleagues at the U.S Bureau of Mines, Denver Colo.  

Text Mining.

ERIC Educational Resources Information Center

Trybula, Walter J.

1999-01-01

Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

Research of Cemented Paste Backfill in Offshore Environments

NASA Astrophysics Data System (ADS)

Wang, Kun; Yang, Peng; Lyu, Wensheng; Lin, Zhixiang

2018-01-01

To promote comprehensive utilization of mine waste tailings and control ground pressure, filling mine stopes with cement paste backfill (CPB) is becoming the most widely used and applicable method in contemporary underground mining. However, many urgent new problems have arisen during the exploitation in offshore mines owing to the complex geohydrology conditions. A series of rheological, settling and mechanical tests were carried out to study the influences of bittern ions on CPB properties in offshore mining. The results showed that: (1) the bittern ion compositions and concentrations of backfill water sampled in mine filling station were similar to seawater. Backfill water mixed CPB slurry with its higher viscosity coefficient was adverse to pipeline gravity transporting; (2) Bleeding rate of backfill water mixed slurry was lower than that prepared with tap water at each cement-tailings ratio; (3) The UCS values of backfill water mixed samples were higher at early curing ages (3d, 7d) and then became lower after longer curing time at 14d and 28d. Therefore, for mine production practice, the offshore environments can have adverse effects on the pipeline gravity transporting and have positive effects on stope dewatering process and early-age strength growth.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrer, C.W.; Layne, A.W.; Guthrie, H.D.

The U.S. Department of Energy (DOE), at its Morgantown Energy Technology Center, has been involved in natural gas research since the 1970`s. DOE has assessed the potential of gas in coals throughout the U.S. and promoted research and development for recovery and use of methane found in minable and unminable coalbeds. DOE efforts have focused on the use of coal mine methane for regional economic gas self-sufficiency, energy parks, self-help initiatives, and small-power generation. This paper focuses on DOE`s past and present efforts to more effectively and efficiently recover and use this valuable domestic energy source. The Climate Change Actionmore » Plan (CCAP) (1) lists a series of 50 voluntary initiatives designed to reduce greenhouse gas emissions, such as methane from mining operations, to their 1990 levels. Action No. 36 of the CCAP expands the DOE research, development, and demonstration (RD&D) efforts to broaden the range of cost-effective technologies and practices for recovering methane associated with coal mining operations. The major thrust of Action No. 36 is to reduce methane emissions associated with coal mining operations from target year 2000 levels by 1.5 MMT of carbon equivalent. Crosscutting activities in the DOE Natural Gas Program supply the utilization sectors will address RD&D to reduce methane emissions released from various mining operations, focusing on recovery and end use technology systems to effectively drain, capture, and utilize the emitted gas. Pilot projects with industry partners will develop and test the most effective methods and technology systems for economic recovery and utilization of coal mine gas emissions in regions where industry considers efforts to be presently non-economic. These existing RD&D programs focus on near-term gas recovery and gathering systems, gas upgrading, and power generation.« less

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

TOXICITY APPROACHES TO ASSESSING MINING IMPACTS AND MINE WASTE TREATMENT EFFECTIVENESS

EPA Science Inventory

The USEPA Office of Research and Development's National Exposure Research Laboratory and National Risk Management Research Laboratory have been evaluating the impact of mining sites on receiving streams and the effectiveness of waste treatment technologies in removing toxicity fo...

Uncovering text mining: A survey of current work on web-based epidemic intelligence

PubMed Central

Collier, Nigel

2012-01-01

Real world pandemics such as SARS 2002 as well as popular fiction like the movie Contagion graphically depict the health threat of a global pandemic and the key role of epidemic intelligence (EI). While EI relies heavily on established indicator sources a new class of methods based on event alerting from unstructured digital Internet media is rapidly becoming acknowledged within the public health community. At the heart of automated information gathering systems is a technology called text mining. My contribution here is to provide an overview of the role that text mining technology plays in detecting epidemics and to synthesise my existing research on the BioCaster project. PMID:22783909

An assessment of three different fire resistance tests for hydraulic fluids

NASA Astrophysics Data System (ADS)

Loftus, J. J.

1981-10-01

The Center for Fire Research at the National Bureau of Standards at the request of the Mine Safety and Health Administration (MSHA) and the Bureau of Mines made an evaluation or assessment of the three different flammability tests used by MSHA for measuring the fire resistance of hydraulic fluids intended for use in underground coal mining operations. The methods described in the Code of Federal Regulations Schedule 30, Part 35, consist of the following: an Autogenous Ignition Temperature Test, a Temperature-Pressure Spray Ignition Test, and a Test to Determine the Effect of Evaporation on the Flammability of Hydraulic Fluids. Recommendations for improvement of the three test procedures are provided.

75 FR 12554 - Mine Safety and Health Research Advisory Committee, National Institute for Occupational Safety...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-16

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Mine Safety and Health Research Advisory Committee, National Institute for Occupational Safety and Health (MSHRAC, NIOSH... priorities in mine safety and health research, including grants and contracts for such research, 30 U.S.C...

Automated data mining: an innovative and efficient web-based approach to maintaining resident case logs.

PubMed

Bhattacharya, Pratik; Van Stavern, Renee; Madhavan, Ramesh

2010-12-01

Use of resident case logs has been considered by the Residency Review Committee for Neurology of the Accreditation Council for Graduate Medical Education (ACGME). This study explores the effectiveness of a data-mining program for creating resident logs and compares the results to a manual data-entry system. Other potential applications of data mining to enhancing resident education are also explored. Patient notes dictated by residents were extracted from the Hospital Information System and analyzed using an unstructured mining program. History, examination and ICD codes were obtained and compared to the existing manual log. The automated data History, examination, and ICD codes were gathered for a 30-day period and compared to manual case logs. The automated method extracted all resident dictations with the dates of encounter and transcription. The automated data-miner processed information from all 19 residents, while only 4 residents logged manually. The manual method identified only broad categories of diseases; the major categories were stroke or vascular disorder 53 (27.6%), epilepsy 28 (14.7%), and pain syndromes 26 (13.5%). In the automated method, epilepsy 114 (21.1%), cerebral atherosclerosis 114 (21.1%), and headache 105 (19.4%) were the most frequent primary diagnoses, and headache 89 (16.5%), seizures 94 (17.4%), and low back pain 47 (9%) were the most common chief complaints. More detailed patient information such as tobacco use 227 (42%), alcohol use 205 (38%), and drug use 38 (7%) were extracted by the data-mining method. Manual case logs are time-consuming, provide limited information, and may be unpopular with residents. Data mining is a time-effective tool that may aid in the assessment of resident experience or the ACGME core competencies or in resident clinical research. More study of this method in larger numbers of residency programs is needed.

A novel method for estimating methane emissions from underground coal mines: The Yanma coal mine, China

NASA Astrophysics Data System (ADS)

Ji, Zhong-Min; Chen, Zhi-Jian; Pan, Jie-Nan; Niu, Qing-He

2017-12-01

As the world's largest coal producer and consumer, China accounts for a relatively high proportion of methane emissions from coal mines. Several estimation methods had been established for the coal mine methane (CMM) emission. However, with large regional differences, various reservoir formation types of coalbed methane (CBM) and due to the complicated geological conditions in China, these methods may be deficient or unsuitable for all the mining areas (e.g. Jiaozuo mining area). By combing the CMM emission characteristics and considering the actual situation of methane emissions from underground coal mine, we found that the methane pre-drainage is a crucial reason creating inaccurate evaluating results for most estimation methods. What makes it so essential is the extensive pre-drainage quantity and its irrelevance with annual coal production. Accordingly, the methane releases were divided into two categories: methane pre-drainage and methane release during mining. On this basis, a pioneering method for estimating CMM emissions was proposed. Taking the Yanma coal mine in the Jiaozuo mining area as a study case, the evaluation method of the pre-drainage methane quantity was established after the correlation analysis between the pre-drainage rate and time. Thereafter, the mining activity influence factor (MAIF) was first introduced to reflect the methane release from the coal and rock seams around where affected by mining activity, and the buried depth was adopted as the predictor of the estimation for future methane emissions. It was verified in the six coal mines of Jiaozuo coalfield (2011) that the new estimation method has the minimum errors of 12.11%, 9.23%, 5.77%, -5.20%, -8.75% and 4.92% respectively comparing with other methods. This paper gives a further insight and proposes a more accurate evaluation method for the CMM emissions, especially for the coal seams with low permeability and strong tectonic deformation in methane outburst coal mines.

Trends of Educational Technology Research: More than a Decade of International Research in Six SSCI-Indexed Refereed Journals

ERIC Educational Resources Information Center

Hsu, Yu-Chang; Hung, Jui-Long; Ching, Yu-Hui

2013-01-01

This study applied text mining methods to examine the abstracts of 2,997 international research articles published between 2000 and 2010 by six journals included in the Social Science Citation Index in the field of Educational Technology (EDTECH). A total of 19 clusters of research areas were identified, and these clusters were further analyzed in…

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis.

PubMed

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-10-11

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world's largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to "peer through" atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km 2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson's r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

PubMed Central

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-01-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events. PMID:27725748

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

NASA Astrophysics Data System (ADS)

Alonzo, Michael; van den Hoek, Jamon; Ahmed, Nabil

2016-10-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Introduction to Agent Mining Interaction and Integration

NASA Astrophysics Data System (ADS)

Cao, Longbing

In recent years, more and more researchers have been involved in research on both agent technology and data mining. A clear disciplinary effort has been activated toward removing the boundary between them, that is the interaction and integration between agent technology and data mining. We refer this to agent mining as a new area. The marriage of agents and data mining is driven by challenges faced by both communities, and the need of developing more advanced intelligence, information processing and systems. This chapter presents an overall picture of agent mining from the perspective of positioning it as an emerging area. We summarize the main driving forces, complementary essence, disciplinary framework, applications, case studies, and trends and directions, as well as brief observation on agent-driven data mining, data mining-driven agents, and mutual issues in agent mining. Arguably, we draw the following conclusions: (1) agent mining emerges as a new area in the scientific family, (2) both agent technology and data mining can greatly benefit from agent mining, (3) it is very promising to result in additional advancement in intelligent information processing and systems. However, as a new open area, there are many issues waiting for research and development from theoretical, technological and practical perspectives.

Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track

DTIC Science & Technology

2015-11-20

Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track Paul N. Bennett Microsoft Research Redmond, USA pauben...anchor text graph has proven useful in the general realm of query reformulation [2], we sought to quantify the value of extracting key phrases from...anchor text in the broader setting of the task understanding track. Given a query, our approach considers a simple method for identifying a relevant

Acid-base accounting to predict post-mining drainage quality on surface mines.

PubMed

Skousen, J; Simmons, J; McDonald, L M; Ziemkiewicz, P

2002-01-01

Acid-base accounting (ABA) is an analytical procedure that provides values to help assess the acid-producing and acid-neutralizing potential of overburden rocks prior to coal mining and other large-scale excavations. This procedure was developed by West Virginia University scientists during the 1960s. After the passage of laws requiring an assessment of surface mining on water quality, ABA became a preferred method to predict post-mining water quality, and permitting decisions for surface mines are largely based on the values determined by ABA. To predict the post-mining water quality, the amount of acid-producing rock is compared with the amount of acid-neutralizing rock, and a prediction of the water quality at the site (whether acid or alkaline) is obtained. We gathered geologic and geographic data for 56 mined sites in West Virginia, which allowed us to estimate total overburden amounts, and values were determined for maximum potential acidity (MPA), neutralization potential (NP), net neutralization potential (NNP), and NP to MPA ratios for each site based on ABA. These values were correlated to post-mining water quality from springs or seeps on the mined property. Overburden mass was determined by three methods, with the method used by Pennsylvania researchers showing the most accurate results for overburden mass. A poor relationship existed between MPA and post-mining water quality, NP was intermediate, and NNP and the NP to MPA ratio showed the best prediction accuracy. In this study, NNP and the NP to MPA ratio gave identical water quality prediction results. Therefore, with NP to MPA ratios, values were separated into categories: <1 should produce acid drainage, between 1 and 2 can produce either acid or alkaline water conditions, and >2 should produce alkaline water. On our 56 surface mined sites, NP to MPA ratios varied from 0.1 to 31, and six sites (11%) did not fit the expected pattern using this category approach. Two sites with ratios <1 did not produce acid drainage as predicted (the drainage was neutral), and four sites with a ratio >2 produced acid drainage when they should not have. These latter four sites were either mined very slowly, had nonrepresentative ABA data, received water from an adjacent underground mine, or had a surface mining practice that degraded the water. In general, an NP to MPA ratio of <1 produced mostly acid drainage sites, between 1 and 2 produced mostly alkaline drainage sites, while NP to MPA ratios >2 produced alkaline drainage with a few exceptions. Using these values, ABA is a good tool to assess overburden quality before surface mining and to predict post-mining drainage quality after mining. The interpretation from ABA values was correct in 50 out of 52 cases (96%), excluding the four anomalous sites, which had acid water for reasons other than overburden quality.

Method of gas emission control for safe working of flat gassy coal seams

NASA Astrophysics Data System (ADS)

Vinogradov, E. A.; Yaroshenko, V. V.; Kislicyn, M. S.

2017-10-01

The main problems at intensive flat gassy coal seam longwall mining are considered. For example, mine Kotinskaja JSC “SUEK-Kuzbass” shows that when conducting the work on the gassy coal seams, methane emission control by means of ventilation, degassing and insulated drain of methane-air mixture is not effective and stable enough. It is not always possible to remove the coal production restrictions by the gas factor, which leads to financial losses because of incomplete using of longwall equipment and the reduction of the technical and economic indicators of mining. To solve the problems, the authors used a complex method that includes the compilation and analysis of the theory and practice of intensive flat gassy coal seam longwall mining. Based on the results of field and numerical researches, the effect of parameters of technological schemes on efficiency of methane emission control on longwall panels, the non-linear dependence of the permissible according to gas factor longwall productivity on parameters of technological schemes, ventilation and degassing during intensive mining flat gassy coal seams was established. The number of recommendations on the choice of the location and the size of the intermediate section of coal heading to control gassing in the mining extracted area, and guidelines for choosing the parameters of ventilation of extracted area with the help of two air supply entries and removal of isolated methane-air mixture are presented in the paper. The technological scheme, using intermediate entry for fresh air intake, ensuring effective management gassing and allowing one to refuse from drilling wells from the surface to the mined-out space for mining gas-bearing coal seams, was developed.

Geophysical Properties of Hard Rock for Investigation of Stress Fields in Deep Mines

NASA Astrophysics Data System (ADS)

Tibbo, M.; Young, R. P.; Schmitt, D. R.; Milkereit, B.

2014-12-01

A complication in geophysical monitoring of deep mines is the high-stress dependency of the physical properties of hard rocks. In-mine observations show anisotropic variability of the in situ P- and S-wave velocities and resistivity of the hard rocks that are likely related to stress field changes. As part of a comprehensive study in a deep, highly stressed mine located in Sudbury, Ontario, Canada, data from in situ monitoring of the seismicity, conductivity, stress, and stress dependent physical properties has been obtain. In-laboratory experiments are also being performed on borehole cores from the Sudbury mines. These experiments will measure the Norite borehole core's properties including elastic modulus, bulk modulus, P- and S-wave velocities, and density. Hydraulic fracturing has been successfully implemented in industries such as oil and gas and enhanced geothermal systems, and is currently being investigated as a potential method for preconditioning in mining. However, further research is required to quantify how hydraulic fractures propagate through hard, unfractured rock as well as naturally fractured rock typically found in mines. These in laboratory experiments will contribute to a hydraulic fracturing project evaluating the feasibility and effectiveness of hydraulic fracturing as a method of de-stressing hard rock mines. A tri-axial deformation cell equipped with 18 Acoustic Emission (AE) sensors will be used to bring the borehole cores to a tri-axial state of stress. The cores will then be injected with fluid until the the hydraulic fracture has propagated to the edge of the core, while AE waveforms will be digitized continuously at 10 MHz and 12-bit resolution for the duration of each experiment. These laboratory hydraulic fracture experiments will contribute to understanding how parameters including stress ratio, fluid injection rate, and viscosity, affect the fracturing process.

A novel water quality data analysis framework based on time-series data mining.

PubMed

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of C4.5 algorithm-based particle swarm optimization for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Muslim, M. A.; Rukmana, S. H.; Sugiharti, E.; Prasetiyo, B.; Alimah, S.

2018-03-01

Data mining has become a basic methodology for computational applications in the field of medical domains. Data mining can be applied in the health field such as for diagnosis of breast cancer, heart disease, diabetes and others. Breast cancer is most common in women, with more than one million cases and nearly 600,000 deaths occurring worldwide each year. The most effective way to reduce breast cancer deaths was by early diagnosis. This study aims to determine the level of breast cancer diagnosis. This research data uses Wisconsin Breast Cancer dataset (WBC) from UCI machine learning. The method used in this research is the algorithm C4.5 and Particle Swarm Optimization (PSO) as a feature option and to optimize the algorithm. C4.5. Ten-fold cross-validation is used as a validation method and a confusion matrix. The result of this research is C4.5 algorithm. The particle swarm optimization C4.5 algorithm has increased by 0.88%.

Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT.

PubMed

Shouval, R; Bondi, O; Mishan, H; Shimoni, A; Unger, R; Nagler, A

2014-03-01

Data collected from hematopoietic SCT (HSCT) centers are becoming more abundant and complex owing to the formation of organized registries and incorporation of biological data. Typically, conventional statistical methods are used for the development of outcome prediction models and risk scores. However, these analyses carry inherent properties limiting their ability to cope with large data sets with multiple variables and samples. Machine learning (ML), a field stemming from artificial intelligence, is part of a wider approach for data analysis termed data mining (DM). It enables prediction in complex data scenarios, familiar to practitioners and researchers. Technological and commercial applications are all around us, gradually entering clinical research. In the following review, we would like to expose hematologists and stem cell transplanters to the concepts, clinical applications, strengths and limitations of such methods and discuss current research in HSCT. The aim of this review is to encourage utilization of the ML and DM techniques in the field of HSCT, including prediction of transplantation outcome and donor selection.

Predicting future discoveries from current scientific literature.

PubMed

Petrič, Ingrid; Cestnik, Bojan

2014-01-01

Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

GPR monitoring of rock mass stability in selected post-mining region in Poland

NASA Astrophysics Data System (ADS)

Golebiowski, T.

2012-04-01

Mining activity conducted over a period of many years may cause significant changes in the geological medium and in effect leads to strong degradation of the surface in mining and post-mining regions. One of the most dangerous effects of mining activity is appearance of sinkholes on the ground surface. These phenomena are related to the changes of initial stress-strain state of the rock mass as a result of mining works and the creation of fractures which migrate from excavations to the ground surface. The paper presents the results of selected GPR surveys carried out in the area of the coal mine "Siersza" in two sites, i.e. in the town of Siersza and in the village of Mloszowa (Upper Silesia, South Poland). The aim of the GPR research was 3D visualisation of fractured zones distribution generated by the mining activity and an attempt to make prediction where sinkholes would appear. In order to realize this aim the measurements were conducted in 4D mode (i.e. time-space analysis), which allowed to observe the fractured zones migration towards the ground surface. In order to obtain 4D information (x-y-z-t) GPR surveys were conducted for several years, along the same parallel profiles, separated by a constant distance equals 2.5m. The terrain measurements were carried out with RAMAC and PROEX GPR systems using 250, 200, 100 and 50 MHz antennae. Because of the limited length of this paper, only selected results from the 200-250 MHz antennae are presented. The results were presented in the form of the distribution of GPR signals energies calculated from Hilbert transform, applying the technique of energy inversion. In the site of Siersza, on the basis of 4D GPR visualisation, regions threatened with the formation of sinkholes were distinguished. A few years after the research, 2 cavities appeared in this site which proved that the interpretation was correct. Another fractured zone in this site was confirmed by a borehole. In the site of Mloszowa the GPR measurements were carried out in the region of already existing sinkhole (with the diameter of about 15m and the depth of about 10m) in order to detect the distribution of dangerous fractures around this sinkhole. As the results of GPR research has shown, fractured zones in this site developed quickly as a result of superimposition of fractures induced by mining activity and the processes of suffusion and congelifraction. GPR monitoring of the rock mass stability in mining and post-mining areas is very important because sinkholes threaten the live of people and stability of structures and installations. As it was shown in the paper, the GPR method gives very good results for the prediction of sinkholes creation if it is applied in 4D mode. A limitation of this method is the depth penetration, i.e. a dozen or so meters with resolution which allows to detect fractures and strong attenuation of electromagnetic waves in the clay formations. The research was financed from the funds of National Science Center, on the basis of agreement no. UMO-2011/01/B/ST7/06178 and decision no. DEC-2011/01/B/ST7/06178.

Investigating trends in acoustics research from 1970-1999.

PubMed

Viator, J A; Pestorius, F M

2001-05-01

Text data mining is a burgeoning field in which new information is extracted from existing text databases. Computational methods are used to compare relationships between database elements to yield new information about the existing data. Text data mining software was used to determine research trends in acoustics for the years 1970, 1980, 1990, and 1999. Trends were indicated by the number of published articles in the categories of acoustics using the Journal of the Acoustical Society of America (JASA) as the article source. Research was classified using a method based on the Physics and Astronomy Classification Scheme (PACS). Research was further subdivided into world regions, including North and South America, Eastern and Western Europe, Asia, Africa, Middle East, and Australia/New Zealand. In order to gauge the use of JASA as an indicator of international acoustics research, three subjects, underwater sound, nonlinear acoustics, and bioacoustics, were further tracked in 1999, using all journals in the INSPEC database. Research trends indicated a shift in emphasis of certain areas, notably underwater sound, audition, and speech. JASA also showed steady growth, with increasing participation by non-US authors, from about 20% in 1970 to nearly 50% in 1999.

Using text mining for study identification in systematic reviews: a systematic review of current approaches.

PubMed

O'Mara-Eves, Alison; Thomas, James; McNaught, John; Miwa, Makoto; Ananiadou, Sophia

2015-01-14

The large and growing number of published studies, and their increasing rate of publication, makes the task of identifying relevant studies in an unbiased way for inclusion in systematic reviews both complex and time consuming. Text mining has been offered as a potential solution: through automating some of the screening process, reviewer time can be saved. The evidence base around the use of text mining for screening has not yet been pulled together systematically; this systematic review fills that research gap. Focusing mainly on non-technical issues, the review aims to increase awareness of the potential of these technologies and promote further collaborative research between the computer science and systematic review communities. Five research questions led our review: what is the state of the evidence base; how has workload reduction been evaluated; what are the purposes of semi-automation and how effective are they; how have key contextual problems of applying text mining to the systematic review field been addressed; and what challenges to implementation have emerged? We answered these questions using standard systematic review methods: systematic and exhaustive searching, quality-assured data extraction and a narrative synthesis to synthesise findings. The evidence base is active and diverse; there is almost no replication between studies or collaboration between research teams and, whilst it is difficult to establish any overall conclusions about best approaches, it is clear that efficiencies and reductions in workload are potentially achievable. On the whole, most suggested that a saving in workload of between 30% and 70% might be possible, though sometimes the saving in workload is accompanied by the loss of 5% of relevant studies (i.e. a 95% recall). Using text mining to prioritise the order in which items are screened should be considered safe and ready for use in 'live' reviews. The use of text mining as a 'second screener' may also be used cautiously. The use of text mining to eliminate studies automatically should be considered promising, but not yet fully proven. In highly technical/clinical areas, it may be used with a high degree of confidence; but more developmental and evaluative work is needed in other disciplines.

Text Mining for Neuroscience

NASA Astrophysics Data System (ADS)

Tirupattur, Naveen; Lapish, Christopher C.; Mukhopadhyay, Snehasis

2011-06-01

Text mining, sometimes alternately referred to as text analytics, refers to the process of extracting high-quality knowledge from the analysis of textual data. Text mining has wide variety of applications in areas such as biomedical science, news analysis, and homeland security. In this paper, we describe an approach and some relatively small-scale experiments which apply text mining to neuroscience research literature to find novel associations among a diverse set of entities. Neuroscience is a discipline which encompasses an exceptionally wide range of experimental approaches and rapidly growing interest. This combination results in an overwhelmingly large and often diffuse literature which makes a comprehensive synthesis difficult. Understanding the relations or associations among the entities appearing in the literature not only improves the researchers current understanding of recent advances in their field, but also provides an important computational tool to formulate novel hypotheses and thereby assist in scientific discoveries. We describe a methodology to automatically mine the literature and form novel associations through direct analysis of published texts. The method first retrieves a set of documents from databases such as PubMed using a set of relevant domain terms. In the current study these terms yielded a set of documents ranging from 160,909 to 367,214 documents. Each document is then represented in a numerical vector form from which an Association Graph is computed which represents relationships between all pairs of domain terms, based on co-occurrence. Association graphs can then be subjected to various graph theoretic algorithms such as transitive closure and cycle (circuit) detection to derive additional information, and can also be visually presented to a human researcher for understanding. In this paper, we present three relatively small-scale problem-specific case studies to demonstrate that such an approach is very successful in replicating a neuroscience expert's mental model of object-object associations entirely by means of text mining. These preliminary results provide the confidence that this type of text mining based research approach provides an extremely powerful tool to better understand the literature and drive novel discovery for the neuroscience community.

Terminologies for text-mining; an experiment in the lipoprotein metabolism domain

PubMed Central

Alexopoulou, Dimitra; Wächter, Thomas; Pickersgill, Laura; Eyre, Cecilia; Schroeder, Michael

2008-01-01

Background The engineering of ontologies, especially with a view to a text-mining use, is still a new research field. There does not yet exist a well-defined theory and technology for ontology construction. Many of the ontology design steps remain manual and are based on personal experience and intuition. However, there exist a few efforts on automatic construction of ontologies in the form of extracted lists of terms and relations between them. Results We share experience acquired during the manual development of a lipoprotein metabolism ontology (LMO) to be used for text-mining. We compare the manually created ontology terms with the automatically derived terminology from four different automatic term recognition (ATR) methods. The top 50 predicted terms contain up to 89% relevant terms. For the top 1000 terms the best method still generates 51% relevant terms. In a corpus of 3066 documents 53% of LMO terms are contained and 38% can be generated with one of the methods. Conclusions Given high precision, automatic methods can help decrease development time and provide significant support for the identification of domain-specific vocabulary. The coverage of the domain vocabulary depends strongly on the underlying documents. Ontology development for text mining should be performed in a semi-automatic way; taking ATR results as input and following the guidelines we described. Availability The TFIDF term recognition is available as Web Service, described at PMID:18460175

Mechanism of Rock Burst Occurrence in Specially Thick Coal Seam with Rock Parting

NASA Astrophysics Data System (ADS)

Wang, Jian-chao; Jiang, Fu-xing; Meng, Xiang-jun; Wang, Xu-you; Zhu, Si-tao; Feng, Yu

2016-05-01

Specially thick coal seam with complex construction, such as rock parting and alternative soft and hard coal, is called specially thick coal seam with rock parting (STCSRP), which easily leads to rock burst during mining. Based on the stress distribution of rock parting zone, this study investigated the mechanism, engineering discriminant conditions, prevention methods, and risk evaluation method of rock burst occurrence in STCSRP through setting up a mechanical model. The main conclusions of this study are as follows. (1) When the mining face moves closer to the rock parting zone, the original non-uniform stress of the rock parting zone and the advancing stress of the mining face are combined to intensify gradually the shearing action of coal near the mining face. When the shearing action reaches a certain degree, rock burst easily occurs near the mining face. (2) Rock burst occurrence in STCSRP is positively associated with mining depth, advancing stress concentration factor of the mining face, thickness of rock parting, bursting liability of coal, thickness ratio of rock parting to coal seam, and difference of elastic modulus between rock parting and coal, whereas negatively associated with shear strength. (3) Technologies of large-diameter drilling, coal seam water injection, and deep hole blasting can reduce advancing stress concentration factor, thickness of rock parting, and difference of elastic modulus between rock parting and coal to lower the risk of rock burst in STCSRP. (4) The research result was applied to evaluate and control the risk of rock burst occurrence in STCSRP.

Quantifying the biases in metagenome mining for realistic assessment of microbial ecology of naturally fermented foods.

PubMed

Keisam, Santosh; Romi, Wahengbam; Ahmed, Giasuddin; Jeyaram, Kumaraswamy

2016-09-27

Cultivation-independent investigation of microbial ecology is biased by the DNA extraction methods used. We aimed to quantify those biases by comparative analysis of the metagenome mined from four diverse naturally fermented foods (bamboo shoot, milk, fish, soybean) using eight different DNA extraction methods with different cell lysis principles. Our findings revealed that the enzymatic lysis yielded higher eubacterial and yeast metagenomic DNA from the food matrices compared to the widely used chemical and mechanical lysis principles. Further analysis of the bacterial community structure by Illumina MiSeq amplicon sequencing revealed a high recovery of lactic acid bacteria by the enzymatic lysis in all food types. However, Bacillaceae, Acetobacteraceae, Clostridiaceae and Proteobacteria were more abundantly recovered when mechanical and chemical lysis principles were applied. The biases generated due to the differential recovery of operational taxonomic units (OTUs) by different DNA extraction methods including DNA and PCR amplicons mix from different methods have been quantitatively demonstrated here. The different methods shared only 29.9-52.0% of the total OTUs recovered. Although similar comparative research has been performed on other ecological niches, this is the first in-depth investigation of quantifying the biases in metagenome mining from naturally fermented foods.

Privacy Preserving Sequential Pattern Mining in Data Stream

NASA Astrophysics Data System (ADS)

Huang, Qin-Hua

The privacy preserving data mining technique researches have gained much attention in recent years. For data stream systems, wireless networks and mobile devices, the related stream data mining techniques research is still in its' early stage. In this paper, an data mining algorithm dealing with privacy preserving problem in data stream is presented.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

Using Cluster Analysis for Data Mining in Educational Technology Research

ERIC Educational Resources Information Center

Antonenko, Pavlo D.; Toy, Serkan; Niederhauser, Dale S.

2012-01-01

Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student learning from hyperlinked information resources. In this methodological paper we provide an introduction to cluster analysis for educational technology researchers and illustrate its use through…

Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research

ERIC Educational Resources Information Center

He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne

2018-01-01

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…

78 FR 40743 - Mine Safety and Health Research Advisory Committee, National Institute for Occupational Safety...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-08

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Mine Safety and Health Research Advisory Committee, National Institute for Occupational Safety and Health (MSHRAC, NIOSH... Director, NIOSH, on priorities in mine safety and health research, including grants and contracts for such...

The Role of Economic Uncertainty on the Block Economic Value - a New Valuation Approach / Rola Czynnika Niepewności Przy Obliczaniu Wskaźnika Rentowności - Nowe Podejście

NASA Astrophysics Data System (ADS)

Dehghani, H.; Ataee-Pour, M.

2012-12-01

The block economic value (EV) is one of the most important parameters in mine evaluation. This parameter can affect significant factors such as mining sequence, final pit limit and net present value. Nowadays, the aim of open pit mine planning is to define optimum pit limits and an optimum life of mine production scheduling that maximizes the pit value under some technical and operational constraints. Therefore, it is necessary to calculate the block economic value at the first stage of the mine planning process, correctly. Unrealistic block economic value estimation may cause the mining project managers to make the wrong decision and thus may impose inexpiable losses to the project. The effective parameters such as metal price, operating cost, grade and so forth are always assumed certain in the conventional methods of EV calculation. While, obviously, these parameters have uncertain nature. Therefore, usually, the conventional methods results are far from reality. In order to solve this problem, a new technique is used base on an invented binomial tree which is developed in this research. This method can calculate the EV and project PV under economic uncertainty. In this paper, the EV and project PV were initially determined using Whittle formula based on certain economic parameters and a multivariate binomial tree based on the economic uncertainties such as the metal price and cost uncertainties. Finally the results were compared. It is concluded that applying the metal price and cost uncertainties causes the calculated block economic value and net present value to be more realistic than certain conditions.

A Test Study to Display Buried Anti-Tank Landmines with GPR and Research Soil Characteristics with CRS

NASA Astrophysics Data System (ADS)

Kadioglu, Selma; Kagan Kadioglu, Yusuf

2014-05-01

An anti-tank mine (AT mine) is a type of land mine designed to damage or destroy vehicles including tanks and armored fighting vehicles. Anti-tank mines typically have a much larger explosive charge, and a fuze designed only to be triggered by vehicles or, in some cases, tampering with the mine. There are a lot of AT mine types. In our test study, MK4 and MK5 AT mine types has been used. The Mk 5 was a cylindrical metal cased U.K. anti-tank blast mine that entered service in 1943, during the Second World War. General Specifications of them are 203 mm diameter, 127 mm height, 4.4-5.7 kg weight, 2.05-3.75 kg of TNT explosive content and 350 lbs operating pressure respectively. The aims of the test study were to image anti-tank landmine with GPR method and to analyse the soil characteristics before the mines made explode and after made be exploded and determine changing of the soil characteristics. We realized data measurement on the real 6 unexploded anti-tank landmine buried approximately 15 cm in depth. The mines spaced 3 m were buried in two lines. Space between lines was 1.5 m. We gathered data on the profiles, approximately 7 m, with a Ramac CUII system and 800 MHz shielded antenna. We collected soil samples on the mines, near and around the mines, on the area in village. We collected soil samples before exploding and after exploding mines. We imaged anti-tank landmines on the depth slices of the GPR data and in their interactive transparent 3D subsets successfully. We used polarized microscope and confocal Raman spectroscopy (CRS) to identify soil characteristic before and after exploitation. The results presented that GPR method and its 3D imaging were successful to determine AT mines, and there was no important changing on mineralogical and petrographical characterization of the soil before and after exploding processing. This project has been supported by Ankara University under grant no 11B6055002. The study is a contribution to the EU funded COST action TU1208, "Civil Engineering Applications of Ground penetrating Radar".

First experience with Remote Sensing methods and selected sensors in the monitoring of mining areas - a case study of the Belchatow open cast mine

NASA Astrophysics Data System (ADS)

Wajs, Jaroslaw

2018-01-01

The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.

Industrial wastewater treatment using higher aquatic vegetation in the former mining company of the Far Eastern Federal district

NASA Astrophysics Data System (ADS)

Krupskaya, L. T.; Zvereva, V. P.; Gula, K. E.; Gul', L. P.; Golubev, D. A.; Filatova, M. Yu.

2017-09-01

The article describes the results of studying the problems of industrial wastewater treatment using higher aquatic vegetation (hydrophytes) in the former mining enterprise of the Far Eastern Federal District (FEFD). They are aimed at reducing the negative environment impact of toxic tin ore wastes. The material of research were drainage, mine and slime waters as well as Lemna minor and Common reed grass (Phragmites communis). In the work conventional modern physico-chemical, chemical, biological and mathematical-statistical methods were used, as well as in the process of research the methods of atomic absorption spectrophotometry for AAS and mass spectrometry with inductively coupled plasma on ISP-MS ELASN DRS II PerkinElmer was applied. The data obtained in the course of the experiment (2015-2016), indicate that a degree of wastewater treatment, using Lemna minor, is high. Virtually, all compounds of toxic chemical elements contained in industrial wastewater (zinc, cobalt, nickel, cadmium, iron, manganese, lead, etc.) were fully absorbed by a hydrophyte. Pollutant extraction was almost 95%. The obtained results of the study in laboratory conditions proved the possibility of effective use of the Lemna minor for the purification of drainage and mine waters. A key contribution of this paper is the relationship between possible toxic metals contained in industrial wastewater and a higher degree of absorption by their higher aquatic vegetation. These hydrophytes absorb these possible toxic metals in an aqueous medium and are contaminated with these heavy metals.

The Traversella mining site as Piedmont geosite

NASA Astrophysics Data System (ADS)

Costa, Emanuele; Benna, Piera; Antonella Dino, Giovanna; Rossetti, Piergiorgio

2017-04-01

The multidisciplinary research project PROGEOPiemonte, started in 2012, selected nine strategic geothematic areas that have been and are still investigated as representative of the geodiversity of Piedmont region. The dissemination of the knowledge connected to geological history, climate and environmental changes, natural hazards, soil processes, and georesources, not only of the geosites but also of the museum collections, has been and will be spread, evidencing the mining and quarrying activities, and by means of science exhibits and Nature trails. Among the nine selected geosites, there is the Traversella mining area, object of the present research. Traversella mine is located nearly 50 km north of Torino, and it was (together with the neighbor site of Brosso) one of the most important mining location for iron exploitation. The Traversella orebody was exploited from late medieval age up to the middle XX century. It is a representative contact-metasomatic deposit at the border between granodiorite and preexisting host rocks (micaschists, gneisses and marbles of the Sesia-Lanzo Zone), and the mining district represents the only exploited skarn-type mineralization in the Alps. The iron mineral, exploited from different veins and mass (pertaining to the contact aureola) was primarily magnetite, an iron oxide easy to treat in cast iron even employing the technology locally available before 1900. After the beginning of XX century the extraction involved also pyrite and chalcopyrite (iron and copper-iron sulfide), used mainly for the production of sulfuric acid. The mine, after some interruptions and re-openings, was officially closed in the second half of the XX century, due to the high exploitation costs and the competition of the foreign mine deposits interested by iron extraction. The area still presents several signs of mining and dressing activities (underground pits, explorable under severe restrictions, traces of dressing plant, offices, and miners changing room and canteens, etc..); such signs are the tangible trace of a remarkable industrial activity, which can be considered as cultural heritage of historical industrial activities ("industrial archeology"). To enrich such cultural heritage, a museum for minerals and mining tools exposition is still active. Furthermore, to evidence the importance of Traversella mining site, outstanding mineralogical samples coming from Traversella area are displayed in the most famous museum all over the world. The present research aims at emphasize the extraordinary importance of this mining site both from a scientific and a historical point of view, examining the methods and the amount of production during the last three centuries, and highlighting how these activities contributed to the industrial development of the surrounding area and of the whole Piedmont Region. We also want to illustrate the sociological and environmental impact of mining activities at regional level, highlighting the importance of the site from a geoturistic point of view, thanks to of the cultural exploitation of the mining site remains, the developing and upgrade of the already existing mining museum, and the organization of geoturistic itinerary.

Principles of adoption of the successful environmental practices used in developed countries into mining industry in developing countries.

NASA Astrophysics Data System (ADS)

Masaitis, Alexandra

2013-04-01

The successful implementation of the environmental practices in the mining industry is of a paramount importance, as it not only prevents both local and trans-border pollution but also guarantees clean and healthy environment for the people regardless of their place of habitation. It is especially important to encourage the progress of the environmental practices implementation in developing countries because such countries have resource-oriented economy based on exploitation of nonrenewable resources. Poor environmental practices in developing countries will lead to local environmental crises that could eventually spill into surrounding countries including the most economically advanced. This abstract is a summary of a two-year research project attempted (1) to determine deficiencies of the mining sector ecological practices in developing countries and (2) to suggest substitute practices from developed countries that could be adapted to the developing countries reality. The following research methods were used: 1. The method of the system analysis, where the system is an interaction of the sets of environmental practices with the global mining sector; 2. The comparative method of inquiry, where the comparison was made between environmental protection practices as implemented in the US (developed country) and the developing countries such as RF, Mongolia mining sectors; 3. Quantitative date analysis, where date was collected from "The collection of statistic data", Russian Geographic Society Annual reports, the US EPA open reports, and the USGS Reports; The following results were obtained: Identified the systemic crisis of the ecological environmental policies and practices in the mining sector in developing countries based on the exploitation of nonrenewable resources, absence of the ecological interest by the mining companies that lack mechanisms of environmental and public health protection, the lack of insurance policy, the lack of risk assistance, and in the presence of the audit and monitoring that do not address the local conditions of the mining operations. Based on the above the following concepts were thought of to improve the environmental conditions in mining sector: 1. Was developed the Regional Environmental Management principle based on the local conditions such as physiographic region, local population, and socioeconomic conditions of the area; 2. Devised were criteria for the risk assessment for developing countries. Where the fundamental principals were public health, both near and far from the operation, environmental and biodiversity impact, waste management, long- and short- term rehabilitation plans, compliance with international standards and norms. 3. Developed was the mechanism of the economic motivation to make mining operations "environmentally friendly" that includes defrayal of expenses from both direct and indirect damages. 4. Identified were spheres of possible cooperation between mining companies, government organizations, and the NGOs. These include development of international standards for Good Neighbor Agreement, exchange of environmental information, exchange of successful environmental, health, and safety practices between mining operations from developed and developing countries. The study showed the dire necessity for the mining industry that operates in developing countries to adopt the successful environmental practices used in developed countries. To achieve this goal the Regional Environmental Management principle, the risk assessment criteria, the mechanism of the economic motivation and the principles for international cooperation can play an extremely important role.

Three Interaction Patterns on Asynchronous Online Discussion Behaviours: A Methodological Comparison

ERIC Educational Resources Information Center

Jo, I.; Park, Y.; Lee, H.

2017-01-01

An asynchronous online discussion (AOD) is one format of instructional methods that facilitate student-centered learning. In the wealth of AOD research, this study evaluated how students' behavior on AOD influences their academic outcomes. This case study compared the differential analytic methods including web log mining, social network analysis…

A numerical calculation method of environmental impacts for the deep sea mining industry - a review.

PubMed

Ma, Wenbin; van Rhee, Cees; Schott, Dingena

2018-03-01

Since the gradual decrease of mineral resources on-land, deep sea mining (DSM) is becoming an urgent and important emerging activity in the world. However, until now there has been no commercial scale DSM project in progress. Together with the reasons of technological feasibility and economic profitability, the environmental impact is one of the major parameters hindering its industrialization. Most of the DSM environmental impact research focuses on only one particular aspect ignoring that all the DSM environmental impacts are related to each other. The objective of this work is to propose a framework for the numerical calculation methods of the integrated DSM environmental impacts through a literature review. This paper covers three parts: (i) definition and importance description of different DSM environmental impacts; (ii) description of the existing numerical calculation methods for different environmental impacts; (iii) selection of a numerical calculation method based on the selected criteria. The research conducted in this paper provides a clear numerical calculation framework for DSM environmental impact and could be helpful to speed up the industrialization process of the DSM industry.

Flotation of Mineral and Dyes: A Laboratory Experiment for Separation Method Molecular Hitchhikers

ERIC Educational Resources Information Center

Rappon, Tim; Sylvestre, Jarrett A.; Rappon, Manit

2016-01-01

Flotation as a method of separation is widely researched and is applied in many industries. It has been used to address a wide range of environmental issues including treatment of wastewater, recovery of heavy metals for recycling, extraction of minerals in mining, and so forth. This laboratory attempts to show how such a simple method can be used…

Pressing needs of biomedical text mining in biocuration and beyond: opportunities and challenges

PubMed Central

Singhal, Ayush; Leaman, Robert; Catlett, Natalie; Lemberger, Thomas; McEntyre, Johanna; Polson, Shawn; Xenarios, Ioannis; Arighi, Cecilia; Lu, Zhiyong

2016-01-01

Text mining in the biomedical sciences is rapidly transitioning from small-scale evaluation to large-scale application. In this article, we argue that text-mining technologies have become essential tools in real-world biomedical research. We describe four large scale applications of text mining, as showcased during a recent panel discussion at the BioCreative V Challenge Workshop. We draw on these applications as case studies to characterize common requirements for successfully applying text-mining techniques to practical biocuration needs. We note that system ‘accuracy’ remains a challenge and identify several additional common difficulties and potential research directions including (i) the ‘scalability’ issue due to the increasing need of mining information from millions of full-text articles, (ii) the ‘interoperability’ issue of integrating various text-mining systems into existing curation workflows and (iii) the ‘reusability’ issue on the difficulty of applying trained systems to text genres that are not seen previously during development. We then describe related efforts within the text-mining community, with a special focus on the BioCreative series of challenge workshops. We believe that focusing on the near-term challenges identified in this work will amplify the opportunities afforded by the continued adoption of text-mining tools. Finally, in order to sustain the curation ecosystem and have text-mining systems adopted for practical benefits, we call for increased collaboration between text-mining researchers and various stakeholders, including researchers, publishers and biocurators. PMID:28025348

Pressing needs of biomedical text mining in biocuration and beyond: opportunities and challenges

DOE PAGES

Singhal, Ayush; Leaman, Robert; Catlett, Natalie; ...

2016-12-26

Text mining in the biomedical sciences is rapidly transitioning from small-scale evaluation to large-scale application. In this article, we argue that text-mining technologies have become essential tools in real-world biomedical research. We describe four large scale applications of text mining, as showcased during a recent panel discussion at the BioCreative V Challenge Workshop. We draw on these applications as case studies to characterize common requirements for successfully applying text-mining techniques to practical biocuration needs. We note that system ‘accuracy’ remains a challenge and identify several additional common difficulties and potential research directions including (i) the ‘scalability’ issue due to themore » increasing need of mining information from millions of full-text articles, (ii) the ‘interoperability’ issue of integrating various text-mining systems into existing curation workflows and (iii) the ‘reusability’ issue on the difficulty of applying trained systems to text genres that are not seen previously during development. We then describe related efforts within the text-mining community, with a special focus on the BioCreative series of challenge workshops. We believe that focusing on the near-term challenges identified in this work will amplify the opportunities afforded by the continued adoption of text-mining tools. In conclusion, in order to sustain the curation ecosystem and have text-mining systems adopted for practical benefits, we call for increased collaboration between text-mining researchers and various stakeholders, including researchers, publishers and biocurators.« less

Pressing needs of biomedical text mining in biocuration and beyond: opportunities and challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singhal, Ayush; Leaman, Robert; Catlett, Natalie

Text mining in the biomedical sciences is rapidly transitioning from small-scale evaluation to large-scale application. In this article, we argue that text-mining technologies have become essential tools in real-world biomedical research. We describe four large scale applications of text mining, as showcased during a recent panel discussion at the BioCreative V Challenge Workshop. We draw on these applications as case studies to characterize common requirements for successfully applying text-mining techniques to practical biocuration needs. We note that system ‘accuracy’ remains a challenge and identify several additional common difficulties and potential research directions including (i) the ‘scalability’ issue due to themore » increasing need of mining information from millions of full-text articles, (ii) the ‘interoperability’ issue of integrating various text-mining systems into existing curation workflows and (iii) the ‘reusability’ issue on the difficulty of applying trained systems to text genres that are not seen previously during development. We then describe related efforts within the text-mining community, with a special focus on the BioCreative series of challenge workshops. We believe that focusing on the near-term challenges identified in this work will amplify the opportunities afforded by the continued adoption of text-mining tools. In conclusion, in order to sustain the curation ecosystem and have text-mining systems adopted for practical benefits, we call for increased collaboration between text-mining researchers and various stakeholders, including researchers, publishers and biocurators.« less

Combining complex networks and data mining: Why and how

NASA Astrophysics Data System (ADS)

Zanin, M.; Papo, D.; Sousa, P. A.; Menasalvas, E.; Nicchi, A.; Kubik, E.; Boccaletti, S.

2016-05-01

The increasing power of computer technology does not dispense with the need to extract meaningful information out of data sets of ever growing size, and indeed typically exacerbates the complexity of this task. To tackle this general problem, two methods have emerged, at chronologically different times, that are now commonly used in the scientific community: data mining and complex network theory. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. One may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. The starting point of this review is that this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. An overview of both fields is first provided, some fundamental concepts of which are illustrated. A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. Contexts in which the appropriate integration of complex network metrics can lead to improved classification rates with respect to classical data mining algorithms and, conversely, contexts in which data mining can be used to tackle important issues in complex network theory applications are illustrated. Finally, ways to achieve a tighter integration between complex networks and data mining, and open lines of research are discussed.

Field test of electromagnetic geophysical techniques for locating simulated in situ mining leach solution. Report of investigations/1994

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tweeton, D.R.; Hanson, J.C.; Friedel, M.J.

1994-01-01

The U.S. Bureau of Mines, the University of Arizona, Sandia National Laboratory, and Zonge Engineering and Research, Inc., conducted cooperative field tests of six electromagnetic geophysical methods to compare their effectiveness in locating a brine solution simulating in situ leach solution or a high-conductivity plume of contamination. The brine was approximately 160 meters below the surface. The test site was the University's San Xavier experimental mine near Tucson, Arizona. Geophysical surveys using surface and surface-borehole time-domain electromagnetics (TEM), surface controlled source audio-frequency magnetotellurics (CSAMT), surface-borehole frequency-domain electromagnetics (FEM), crosshole FEM and surface magnetic field ellipticity were conducted before and duringmore » brine injection.« less

Mineral resources management based on GIS and RS: a case study of the Laozhaiwan Gold Mine

NASA Astrophysics Data System (ADS)

Wu, Hao; Hua, Xianghong; Wang, Xinzhou; Ma, Liguang; Yuan, Yanbin

2005-10-01

With the development of digital information technology in mining industry, the concept of DM (Digital Mining) and MGIS (Mining Geographical Information System) are becoming the research focus but not perfect. How to effectively manage the dataset of geological, surveying and mineral products grade is the key point that concerned the sustainable development and standardized management in mining industry. Based on the existing combined GIS and remote sensing technology, we propose a model named DMMIS (Digital Mining Management Information System), which is composed of the database layer, the ActiveX layer and the user interface layer. The system is used in Laozhaiwan Gold Mine, Yunnan Province of China, which is shown to demonstrate the feasibility of the research and development achievement stated in this paper. Finally, some conclusions and constructive advices for future research work are given.

Mining level of control in medical organizations.

PubMed

Çalimli, Olgu; Türkeli, Serkan; Eken, Emir Gökberk; Gönen, Halil Emre

2014-01-01

In literature of strategic management, there are three layers of control defined in organizational structures. These layers are strategic, tactical and operational, in which resides senior, medium level and low level managers respectively. In strategic level, institutional strategies are determined according to senior managers' perceived state of organization. In tactical level, this strategy is processed into methods and activities of a business management plan. Operational level embodies actions and functions to sustain specified business management plan. An acknowledged lead organization in Turkish medical area is examined using case study and data mining method in the scope of this paper. The level of decisions regarded in managerial purposes evaluated through chosen organization's business intelligence event logs report. Hence specification of management level importance of medical organizations is made. Case study, data mining and descriptive statistical method of taken case's reports present that positions of "Chief Executive Officer", "Outpatient Center Manager", "General Manager", monitored and analyzed functions of operational level management more frequently than strategic and tactical level. Absence of strategic management decision level research in medical area distinguishes this paper and consequently substantiates its significant contribution.

TOY SAFETY SURVEILLANCE FROM ONLINE REVIEWS

PubMed Central

Winkler, Matt; Abrahams, Alan S.; Gruss, Richard; Ehsani, Johnathan P.

2016-01-01

Toy-related injuries account for a significant number of childhood injuries and the prevention of these injuries remains a goal for regulatory agencies and manufacturers. Text-mining is an increasingly prevalent method for uncovering the significance of words using big data. This research sets out to determine the effectiveness of text-mining in uncovering potentially dangerous children’s toys. We develop a danger word list, also known as a ‘smoke word’ list, from injury and recall text narratives. We then use the smoke word lists to score over one million Amazon reviews, with the top scores denoting potential safety concerns. We compare the smoke word list to conventional sentiment analysis techniques, in terms of both word overlap and effectiveness. We find that smoke word lists are highly distinct from conventional sentiment dictionaries and provide a statistically significant method for identifying safety concerns in children’s toy reviews. Our findings indicate that text-mining is, in fact, an effective method for the surveillance of safety concerns in children’s toys and could be a gateway to effective prevention of toy-product-related injuries. PMID:27942092

Study of the Rock Mass Failure Process and Mechanisms During the Transformation from Open-Pit to Underground Mining Based on Microseismic Monitoring

NASA Astrophysics Data System (ADS)

Zhao, Yong; Yang, Tianhong; Bohnhoff, Marco; Zhang, Penghai; Yu, Qinglei; Zhou, Jingren; Liu, Feiyue

2018-05-01

To quantitatively understand the failure process and failure mechanism of a rock mass during the transformation from open-pit mining to underground mining, the Shirengou Iron Mine was selected as an engineering project case study. The study area was determined using the rock mass basic quality classification method and the kinematic analysis method. Based on the analysis of the variations in apparent stress and apparent volume over time, the rock mass failure process was analyzed. According to the recent research on the temporal and spatial change of microseismic events in location, energy, apparent stress, and displacement, the migration characteristics of rock mass damage were studied. A hybrid moment tensor inversion method was used to determine the rock mass fracture source mechanisms, the fracture orientations, and fracture scales. The fracture area can be divided into three zones: Zone A, Zone B, and Zone C. A statistical analysis of the orientation information of the fracture planes orientations was carried out, and four dominant fracture planes were obtained. Finally, the slip tendency analysis method was employed, and the unstable fracture planes were obtained. The results show: (1) The microseismic monitoring and hybrid moment tensor analysis can effectively analyze the failure process and failure mechanism of rock mass, (2) during the transformation from open-pit to underground mining, the failure type of rock mass is mainly shear failure and the tensile failure is mostly concentrated in the roof of goafs, and (3) the rock mass of the pit bottom and the upper of goaf No. 18 have the possibility of further damage.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

Treatment of antimony mine drainage: challenges and opportunities with special emphasis on mineral adsorption and sulfate reducing bacteria.

PubMed

Li, Yongchao; Hu, Xiaoxian; Ren, Bozhi

2016-01-01

The present article summarizes antimony mine distribution, antimony mine drainage generation and environmental impacts, and critically analyses the remediation approach with special emphasis on iron oxidizing bacteria and sulfate reducing bacteria. Most recent research focuses on readily available low-cost adsorbents, such as minerals, wastes, and biosorbents. It is found that iron oxides prepared by chemical methods present superior adsorption ability for Sb(III) and Sb(V). However, this process is more costly and iron oxide activity can be inhibited by plenty of sulfate in antimony mine drainage. In the presence of sulfate reducing bacteria, sulfate can be reduced to sulfide and form Sb(2)S(3) precipitates. However, dissolved oxygen and lack of nutrient source in antimony mine drainage inhibit sulfate reducing bacteria activity. Biogenetic iron oxide minerals from iron corrosion by iron-oxidizing bacteria may prove promising for antimony adsorption, while the micro-environment generated from iron corrosion by iron oxidizing bacteria may provide better growth conditions for symbiotic sulfate reducing bacteria. Finally, based on biogenetic iron oxide adsorption and sulfate reducing bacteria followed by precipitation, the paper suggests an alternative treatment for antimony mine drainage that deserves exploration.

The Problem of Multiple Criteria Selection of the Surface Mining Haul Trucks

NASA Astrophysics Data System (ADS)

Bodziony, Przemysław; Kasztelewicz, Zbigniew; Sawicki, Piotr

2016-06-01

Vehicle transport is a dominant type of technological processes in rock mines, and its profit ability is strictly dependent on overall cost of its exploitation, especially on diesel oil consumption. Thus, a rational design of transportation system based on haul trucks should result from thorough analysis of technical and economic issues, including both cost of purchase and its further exploitation, having a crucial impact on the cost of minerals extraction. Moreover, off-highway trucks should be selected with respect to all specific exploitation conditions and even the user's preferences and experience. In this paper a development of universal family of evaluation criteria as well as application of evaluation method for haul truck selection process for a specific exploitation conditions in surface mining have been carried out. The methodology presented in the paper is based on the principles of multiple criteria decision aiding (MCDA) using one of the ranking method, i.e. ELECTRE III. The applied methodology has been allowed for ranking of alternative solution (variants), on the considered set of haul trucks. The result of the research is a universal methodology, and it consequently may be applied in other surface mines with similar exploitation parametres.

KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain

PubMed Central

2013-01-01

Background Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. Results A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. Conclusions The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. PMID:23763826

KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

PubMed

Holzinger, Andreas; Zupan, Mario

2013-06-13

Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

Data Mining and Domain Knowledge: An Exploration of Methods to Advance Medical Research

ERIC Educational Resources Information Center

Engle, Kelley M.

2013-01-01

Researchers in the medical domain consider the double-blind placebo controlled clinical trial the gold standard. The data for these clinical trials are collected for a specifically defined hypothesis and there is very little in the realm of secondary data analyses conducted. The underlying purpose of this work is to demonstrate the value and…

Education Scholars' Evolving Uses of Twitter as a Conference Backchannel and Social Commentary Platform

ERIC Educational Resources Information Center

Kimmons, Royce; Veletsianos, George

2016-01-01

The scholarly community faces a lack of large-scale research examining how students and professors use social media in authentic contexts and how such use changes over time. This study uses data mining methods to better understand academic Twitter use during, around, and between the 2014 and 2015 American Educational Research Association annual…

Text mining for search term development in systematic reviewing: A discussion of some methods and challenges.

PubMed

Stansfield, Claire; O'Mara-Eves, Alison; Thomas, James

2017-09-01

Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (term frequency-inverse document frequency and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews. Copyright © 2017 John Wiley & Sons, Ltd.

Temporal data mining for the quality assessment of hemodialysis services.

PubMed

Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto

2005-05-01

This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

Survey of nine surface mines in North America. [Nine different mines in USA and Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayes, L.G.; Brackett, R.D.; Floyd, F.D.

This report presents the information gathered by three mining engineers in a 1980 survey of nine surface mines in the United States and Canada. The mines visited included seven coal mines, one copper mine, and one tar sands mine selected as representative of present state of the art in open pit, strip, and terrace pit mining. The purpose of the survey was to investigate mining methods, equipment requirements, operating costs, reclamation procedures and costs, and other aspects of current surface mining practices in order to acquire basic data for a study comparing conventional and terrace pit mining methods, particularly inmore » deeper overburdens. The survey was conducted as part of a project under DOE Contract No. DE-AC01-79ET10023 titled The Development of Optimal Terrace Pit Coal Mining Systems.« less

Data Mining: A Hybrid Methodology for Complex and Dynamic Research

ERIC Educational Resources Information Center

Lang, Susan; Baehr, Craig

2012-01-01

This article provides an overview of the ways in which data and text mining have potential as research methodologies in composition studies. It introduces data mining in the context of the field of composition studies and discusses ways in which this methodology can complement and extend our existing research practices by blending the best of what…

Data Mining Research for Information Security

DTIC Science & Technology

2016-01-29

AFRL-AFOSR-JP-TR-2016-0028 Data Mining Research for Information Security Kevin Barton Texas A&M University-San Antonio Final Report 01/29/2016...Final 3.  DATES COVERED (From - To)      20-05-2014 to 19-05-2015 4.  TITLE AND SUBTITLE Data Mining Research for Information Security 5a.  CONTRACT

[Strategy to strengthen health research capabilities in regional public universities: the role of the Mining Canon and the Instituto Nacional de Salud].

PubMed

Romaní, Franco; Cabezas, César; Espinoza, Manuel; Minaya, Gabriela; Huaripata, José; Ureta, Juan Manuel; Yazuda, Myriam; Gastañaga, María del Carmen; Miraval, María Luz; Aparco, Juan Pablo; Anaya, Elizabeth; Castro, José; Esquivel, Silvia

2012-01-01

The development of scientific health research requires a sustained and articulated research system that is consistent with the research priorities, as well as both internal and external funding, and availability of competent human resources. The Mining Canon, a constitutional right, has been partly used to foster applied scientific research in public universities (PU). In addition, the National Health Institute (INSTITUTO NACIONAL DE SALUD - INS) is devoted, among others, to promoting, managing and disseminating health research development at a national level. As part of these activities, a technical team was created to provide technical assistance to PU for research development using Mining Canon funds by making local adjustments to research protocols promoted by the INS and assumed by the professors-researchers at the Universities. This article aims at describing the reality of research at Peruvian public universities that have access to Mining Canon funds, as well as to elaborate on the work the INS is carrying out in order to strengthen research capabilities, starting with the development of research proposals that could potentially be funded by the Mining Canon.

Knowledge Domain and Emerging Trends in Organic Photovoltaic Technology: A Scientometric Review Based on CiteSpace Analysis.

PubMed

Xiao, Fengjun; Li, Chengzhi; Sun, Jiangman; Zhang, Lianjie

2017-01-01

To study the rapid growth of research on organic photovoltaic (OPV) technology, development trends in the relevant research are analyzed based on CiteSpace software of text mining and visualization in scientific literature. By this analytical method, the outputs and cooperation of authors, the hot research topics, the vital references and the development trend of OPV are identified and visualized. Different from the traditional review articles by the experts on OPV, this work provides a new method of visualizing information about the development of the OPV technology research over the past decade quantitatively.

Knowledge Domain and Emerging trends in Organic Photovoltaic Technology: A Scientometric Review Based on CiteSpace Analysis

NASA Astrophysics Data System (ADS)

Xiao, Fengjun; Li, Chengzhi; Sun, Jiangman; Zhang, Lianjie

2017-09-01

To study the rapid growth of research on organic photovoltaic (OPV) technology, development trends in the relevant research are analyzed based on CiteSpace software of text mining and visualization in scientific literature. By this analytical method, the outputs and cooperation of authors, the hot research topics, the vital references and the development trend of OPV are identified and visualized. Different from the traditional review articles by the experts on OPV, this work provides a new method of visualizing information about the development of the OPV technology research over the past decade quantitatively.

Pressing needs of biomedical text mining in biocuration and beyond: opportunities and challenges.

PubMed

Singhal, Ayush; Leaman, Robert; Catlett, Natalie; Lemberger, Thomas; McEntyre, Johanna; Polson, Shawn; Xenarios, Ioannis; Arighi, Cecilia; Lu, Zhiyong

2016-01-01

Text mining in the biomedical sciences is rapidly transitioning from small-scale evaluation to large-scale application. In this article, we argue that text-mining technologies have become essential tools in real-world biomedical research. We describe four large scale applications of text mining, as showcased during a recent panel discussion at the BioCreative V Challenge Workshop. We draw on these applications as case studies to characterize common requirements for successfully applying text-mining techniques to practical biocuration needs. We note that system 'accuracy' remains a challenge and identify several additional common difficulties and potential research directions including (i) the 'scalability' issue due to the increasing need of mining information from millions of full-text articles, (ii) the 'interoperability' issue of integrating various text-mining systems into existing curation workflows and (iii) the 'reusability' issue on the difficulty of applying trained systems to text genres that are not seen previously during development. We then describe related efforts within the text-mining community, with a special focus on the BioCreative series of challenge workshops. We believe that focusing on the near-term challenges identified in this work will amplify the opportunities afforded by the continued adoption of text-mining tools. Finally, in order to sustain the curation ecosystem and have text-mining systems adopted for practical benefits, we call for increased collaboration between text-mining researchers and various stakeholders, including researchers, publishers and biocurators. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

A comprehensive review on privacy preserving data mining.

PubMed

Aldeen, Yousra Abdul Alsahib S; Salleh, Mazleena; Razzaque, Mohammad Abdur

2015-01-01

Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Ever-escalating internet phishing posed severe threat on widespread propagation of sensitive information over the web. Conversely, the dubious feelings and contentions mediated unwillingness of various information providers towards the reliability protection of data from disclosure often results utter rejection in data sharing or incorrect information sharing. This article provides a panoramic overview on new perspective and systematic interpretation of a list published literatures via their meticulous organization in subcategories. The fundamental notions of the existing privacy preserving data mining methods, their merits, and shortcomings are presented. The current privacy preserving data mining techniques are classified based on distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity, where their notable advantages and disadvantages are emphasized. This careful scrutiny reveals the past development, present research challenges, future trends, the gaps and weaknesses. Further significant enhancements for more robust privacy protection and preservation are affirmed to be mandatory.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nurhandoko, Bagus Endar B.; Wely, Woen; Setiadi, Herlan

It is already known that tomography has a great impact for analyzing and mapping unknown objects based on inversion, travel time as well as waveform inversion. Therefore, tomography has used in wide area, not only in medical but also in petroleum as well as mining. Recently, tomography method is being applied in several mining industries. A case study of tomography imaging has been carried out in DOZ ( Deep Ore Zone ) block caving mine, Tembagapura, Papua. Many researchers are undergoing to investigate the properties of DOZ cave not only outside but also inside which is unknown. Tomography takes amore » part for determining this objective.The sources are natural from the seismic events that caused by mining induced seismicity and rocks deformation activity, therefore it is called as passive seismic. These microseismic travel time data are processed by Simultaneous Iterative Reconstruction Technique (SIRT). The result of the inversion can be used for DOZ cave monitoring. These information must be used for identifying weak zone inside the cave. In addition, these results of tomography can be used to determine DOZ and cave information to support mine activity in PT. Freeport Indonesia.« less

Mapping Hydrothermal Alterations in the Muteh Gold Mining Area in Iran by using ASTER satellite Imagery data

NASA Astrophysics Data System (ADS)

Asadi Haroni, Hooshang; Hassan Tabatabaei, Seyed

2016-04-01

Muteh gold mining area is located in 160 km NW of Isfahan town. Gold mineralization is meso-thermal type and associated with silisic, seresitic and carbonate alterations as well as with hematite and goethite. Image processing and interpretation were applied on the ASTER satellite imagery data of about 400 km2 at the Muteh gold mining area to identify hydrothermal alterations and iron oxides associated with gold mineralization. After applying preprocessing methods such as radiometric and geometric corrections, image processing methods of Principal Components Analysis (PCA), Least Square Fit (Ls-Fit) and Spectral Angle Mapper (SAM) were applied on the ASTER data to identify hydrothermal alterations and iron oxides. In this research reference spectra of minerals such as chlorite, hematite, clay minerals and phengite identified from laboratory spectral analysis of collected samples were used to map the hydrothermal alterations. Finally, identified hydrothermal alteration and iron oxides were validated by visiting and sampling some of the mapped hydrothermal alterations.

Intelligent Scheduling for Underground Mobile Mining Equipment.

PubMed

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.

Modern methods of surveyor observations in opencast mining under complex hydrogeological conditions.

NASA Astrophysics Data System (ADS)

Usoltseva, L. A.; Lushpei, V. P.; Mursin, VA

2017-10-01

The article considers the possibility of linking the modern methods of surveying security of open mining works to improve industrial safety in the Primorsky Territory, as well as their use in the educational process. Industrial Safety in the management of Surface Mining depends largely on the applied assessment methods and methods of stability of pit walls and slopes of dumps in the complex mining and hydro-geological conditions.

Comparison of ALE and SPH Methods for Simulating Mine Blast Effects on Structures

DTIC Science & Technology

2010-12-01

Comparison of ALE and SPH methods for simulating mine blast effects on struc- tures Geneviève Toussaint Amal Bouamoul DRDC Valcartier Defence R&D...Canada – Valcartier Technical Report DRDC Valcartier TR 2010-326 December 2010 Comparison of ALE and SPH methods for simulating mine blast...Valcartier TR 2010-326 iii Executive summary Comparison of ALE and SPH methods for simulating mine blast effects on structures

Contamination of houses by workers occupationally exposed in a lead-zinc-copper mine and impact on blood lead concentrations in the families.

PubMed Central

Chiaradia, M; Gulson, B L; MacDonald, K

1997-01-01

OBJECTIVE: To evaluate the pathway of leaded dust from a lead-zinc-copper mine to houses of employees, and the impact on blood lead concentrations (PbB) of children. METHODS: High precision lead isotope and lead concentration data were obtained on venous blood and environmental samples (vacuum cleaner dust, interior dustfall accumulation, water, paint) for eight children of six employees (and the employees) from a lead-zinc-copper mine. These data were compared with results for 11 children from occupationally unexposed control families living in the same city. RESULTS: The median (range) concentrations of lead in vacuum cleaner dust was 470 (21-1300) ppm. In the houses of the mine employees, vacuum cleaner dust contained varying higher proportions of mine lead than did airborne particulate matter measured as dustfall accumulated over a three month period. The median (range) concentrations of lead in soil were 30 (5-407) ppm and these showed no evidence of any mine lead. Lead in blood of the mine employees varied from 7 to 25 micrograms/dl and was generally dominated by mine lead (> 60%). The mean (SD) PbB in the children of the mine employees was 5.7 (1.7) micrograms/dl compared with 4.1 (1.4) micrograms/dl for the control children (P = 0.02). The PbB of all children was always < 10 micrograms/dl, the Australian National Health and Medical Research Council goal for all Australians. Some of the control children had higher PbB than the children of mine employees, probably from exposure to leaded paint as six of the eight houses of the control children were > 50 years old. In five of the eight children of mine employees > 20% of PbB was from the lead mine. However, in the other three cases of children of mine employees, their PbB was from sources other than mine lead (paint, petrol, background sources). CONCLUSIONS: Houses of employees from a lead mine can be contaminated by mine lead even if they are not situated in the same place as the mine. Delineation of the mine to house pathway indicates that lead is probably transported into the houses on the clothes, shoes, hair, skin, and in some cases, motor vehicles of the workers. In one case, dust shaken from clothes of a mine employee contained 3000 ppm lead which was 100% mine lead. The variable contamination of the houses was not expected given the precautions taken by mine employees to minimise transportation of lead into their houses. Although five out of the eight children of mine employees had > 20% mine lead in their blood, in no case did the PbB of a child exceed the Australian National Health and Medical Research Council goal of 10 micrograms/dl. In fact, some children in the control families had higher PbB than children of mine employees. In two cases, this was attributed to a pica habit for paint. The PbB in the children of mine employees and controls was independent of the source of lead. The low PbB in the children of mine employees may reflect the relatively low solubility (bioavailability) of the mine dust in 0.1 M hydrochloric acid (< 40 %), behaviour--for example, limited mouthing activity--or diet. PMID:9072019

Forecasting of Energy Expenditure of Induced Seismicity with Use of Artificial Neural Network

NASA Astrophysics Data System (ADS)

Cichy, Tomasz; Banka, Piotr

2017-12-01

Coal mining in many Polish mines in the Upper Silesian Coal Basin is accompanied by high levels of induced seismicity. In mining plants, the methods of shock monitoring are improved, allowing for more accurate localization of the occurring phenomena and determining their seismic energy. Equally important is the development of ways of forecasting seismic hazards that may occur while implementing mine design projects. These methods, depending on the length of time for which the forecasts are made, can be divided into: longterm, medium-term, short-term and so-called alarm. Long-term forecasts are particularly useful for the design of seam exploitations. The paper presents a method of predicting changes in energy expenditure of shock using a properly trained artificial neural network. This method allows to make long-term forecasts at the stage of the mine’s exploitation design, thus enabling the mining work plans to be reviewed to minimize the potential for tremors. The information given at the input of the neural network is indicative of the specific energy changes of the elastic deformation occurring in the selected, thick, resistant rock layers (tremor-prone layers). Energy changes, taking place in one or more tremor-prone layers are considered. These indicators describe only the specific energy changes of the elastic deformation accumulating in the rock as a consequence of the mining operation, but does not determine the amount of energy released during the destruction of a given volume of rock. In this process, the potential energy of elastic strain transforms into other, non-measurable energy types, including the seismic energy of recorded tremors. In this way, potential energy changes affect the observed induced seismicity. The parameters used are characterized by increases (declines) of specific energy with separation to occur before the hypothetical destruction of the rock and after it. Additional input information is an index characterizing the rate of tectonic faults. This parameter was not included in previous research by authors. At the output of the artificial neural network, the values of the energy density of the mining tremors [J/m3] are obtained. An example of the predicted change in seismicity induced for a highly threatened region is presented. Relatively good predicted and observed energy expenditure of tremors was obtained. The presented method can complement existing methods (analytical and geophysical) forecasting seismic hazard. This method can be used primarily in those areas where the seismic level is determined by the configuration of the edges and residues in the operating seam, as well as in adjacent seams, and to a lesser extent, the geological structure of the rock The method is local, it means that the artificial neural network prediction can only be performed for the region from which the data have been used for its originated learning. The developed method cannot be used in areas where mining is just beginning and it is not possible to predict the level of seismicity induced in areas where no mining tremors have been recorded so far.

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

Summary of Research 1998, Interdisciplinary Academic Groups

DTIC Science & Technology

1999-08-01

Seismic Sonar, Biosonar SEISMO ACOUSTIC DETECTION OF MINES BURIED IN THE SURF ZONE Thomas Muir, Chair of Mine Warfare Undersea Warfare Academic Group...Mine Warfare KEYWORDS: Mining, Mine Countermeasures, Surf Zone, Seismic Sonar, Biosonar PHYSICS OF SEISMIC INTERFACE WAVES IN THE SURF ZONE

OVERVIEW OF THE MINE WASTE TECHNOLOGY PROGRAM; INTERAGENCY COORDINATION MEETING ON MINING

EPA Science Inventory

The Mine Waste Technology Program is a Congressionally-mandated research program jointly administered by the EPA Office of Research and Development (for technical direction) and by the DoE Western Environmental Technology Office (administrative direction). The goal of the resear...

Bias in the reporting of sex and age in biomedical research on mouse models

PubMed Central

Flórez-Vargas, Oscar; Brass, Andy; Karystianis, George; Bramhall, Michael; Stevens, Robert; Cruickshank, Sheena; Nenadic, Goran

2016-01-01

In animal-based biomedical research, both the sex and the age of the animals studied affect disease phenotypes by modifying their susceptibility, presentation and response to treatment. The accurate reporting of experimental methods and materials, including the sex and age of animals, is essential so that other researchers can build on the results of such studies. Here we use text mining to study 15,311 research papers in which mice were the focus of the study. We find that the percentage of papers reporting the sex and age of mice has increased over the past two decades: however, only about 50% of the papers published in 2014 reported these two variables. We also compared the quality of reporting in six preclinical research areas and found evidence for different levels of sex-bias in these areas: the strongest male-bias was observed in cardiovascular disease models and the strongest female-bias was found in infectious disease models. These results demonstrate the ability of text mining to contribute to the ongoing debate about the reproducibility of research, and confirm the need to continue efforts to improve the reporting of experimental methods and materials. DOI: http://dx.doi.org/10.7554/eLife.13615.001 PMID:26939790

Environmental impact assessment of european non-ferro mining industries through life-cycle assessment

NASA Astrophysics Data System (ADS)

Hisan Farjana, Shahjadi; Huda, Nazmul; Parvez Mahmud, M. A.

2018-05-01

European mining industries are the vast industrial sector which contributes largely on their economy which constitutes of ferro and non-ferro metals and minerals industries. The non-ferro metals extraction and processing industries require focus of attention due to sustainability concerns as their manufacturing processes are highly energy intensive and impacts globally on environment. This paper analyses major environmental effects caused by European metal industries based on the life-cycle impact analysis technologies. This research work is the first work in considering the comparative environmental impact analysis of European non-ferro metal industries which will reveal their technological similarities and dissimilarities to assess their environmental loads. The life-cycle inventory datasets are collected from the EcoInvent database while the analysis is done using the CML baseline and ReCipe endpoint method using SimaPro software version 8.4. The CML and ReCipe method are chosen because they are specialized impact assessment methods for European continent. The impact categories outlined for discussion here are human health, global warming and ecotoxicity. The analysis results reveal that the gold industry is vulnerable for the environment due to waste emission and similar result retained by silver mines a little bit. But copper, lead, manganese and zinc mining processes and industries are environment friendly in terms of metal extraction technologies and waste emissions.

Experimental Study on Comprehensive Performance of Full Tailings Paste Filling in Jiaojia Gold Mine.

NASA Astrophysics Data System (ADS)

Zhang, Z. H.; Zou, Q. B.; Wang, P. Z.

2017-11-01

Filling mining method is the main method of modern underground mining. High concentration cementation is carried out using coarse tailing of +37 μm, and the mine has maturely used classified tailings paste filling technology. The gold mine studied on the performance of full tailings paste filling in order to maximize the use of tailings, reduce -37 μm fine tailings discharged into the tailing pond, reduce mining cost and eliminate security risks. The results show that: comprehensive index of full tailings paste filling is higher than that of classified tailings high concentration cementation filling, and the full tailings paste filling of 76% mass concentration has the best comprehensive index of slump, expansibility, yield stress and viscosity to meet the mining method requirements, which can effectively reduce the mining loss rate and dilution rate.

Test operation of a pneumatic vibrating-blade planer in phosphate and coal: a progress report on planer-mining research, 1958--1960

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, W.S.

1962-01-01

Third report in a series describes progress in research with the pneumatic vibrating-blade planer: Tests conducted in the Arickaree phosphate mine in Utah and in the Roslyn No. 9 coal mine in Washington. After the Arickaree mine tests, the bit design was improved, and tests were conducted in the Roslyn No. 9 mine to check the modifications. The redesigned cutting tool was an improvement, and the possibility of planing coal as well as phosphate was proved.

Problems associated with noise measurements in the mining industry

NASA Astrophysics Data System (ADS)

Bauer, Eric R.; Vipperman, Jeffrey S.

2002-05-01

In response to the continuing problem of noise-induced hearing loss (NIHL) among mine workers, the National Institute for Occupational Safety and Health (NIOSH) has been conducting numerous noise- and hearing-loss research efforts in the mining industry. Research is underway to determine worker noise exposure, equipment noise, hearing loss and hearing protection use, and to evaluate engineering controls. Issues that are peculiar to the mining industry have complicated these efforts. A few of the issues that must be overcome to conduct meaningful research include constantly moving equipment, changing work environments, confined space, varying production rates, multiple noise sources, and electronic permissibility of instrumentation. This presentation will address the factors that affect the measurement and analysis of noise in the mining industry and how these factors are managed. In addition, some examples of research results will be included.

OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.

PubMed

García-Pedrajas, Nicolás; Perez-Rodríguez, Javier; de Haro-García, Aida

2013-02-01

In current research, an enormous amount of information is constantly being produced, which poses a challenge for data mining algorithms. Many of the problems in extremely active research areas, such as bioinformatics, security and intrusion detection, or text mining, share the following two features: large data sets and class-imbalanced distribution of samples. Although many methods have been proposed for dealing with class-imbalanced data sets, most of these methods are not scalable to the very large data sets common to those research fields. In this paper, we propose a new approach to dealing with the class-imbalance problem that is scalable to data sets with many millions of instances and hundreds of features. This proposal is based on the divide-and-conquer principle combined with application of the selection process to balanced subsets of the whole data set. This divide-and-conquer principle allows the execution of the algorithm in linear time. Furthermore, the proposed method is easy to implement using a parallel environment and can work without loading the whole data set into memory. Using 40 class-imbalanced medium-sized data sets, we will demonstrate our method's ability to improve the results of state-of-the-art instance selection methods for class-imbalanced data sets. Using three very large data sets, we will show the scalability of our proposal to millions of instances and hundreds of features.

78 FR 48593 - Refuge Alternatives for Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-08

... conduct research and tests concerning the use of refuge chambers in underground coal mines, and to report... of Information MSHA will post all comments and information on the Internet without change, including... actions. NIOSH finalized its Research Report on Refuge Alternatives for Underground Coal Mines (NIOSH...

Machine Learning and Data Mining Methods in Diabetes Research.

PubMed

Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

2017-01-01

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

Filling the gap between biology and computer science

PubMed Central

Aguilar-Ruiz, Jesús S; Moore, Jason H; Ritchie, Marylyn D

2008-01-01

This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biological data. We outline the aims and scope of the journal, introduce the publishing model and describe the open peer review policy, which fosters interaction within the research community. PMID:18822148

Environmental Economics for Watershed Restoration: Valuation for Non-Economists

EPA Science Inventory

EPA economists completed research projects and summarized related valuation methods and case studies, mostly dealing with acid mine drainage. Their recent book (edited by Thurston, et al.) is intended to make stakeholders more comfortable talking about economic jargon and to info...

Applications of machine learning and data mining methods to detect associations of rare and common variants with complex traits.

PubMed

Lu, Ake Tzu-Hui; Austin, Erin; Bonner, Ashley; Huang, Hsin-Hsiung; Cantor, Rita M

2014-09-01

Machine learning methods (MLMs), designed to develop models using high-dimensional predictors, have been used to analyze genome-wide genetic and genomic data to predict risks for complex traits. We summarize the results from six contributions to our Genetic Analysis Workshop 18 working group; these investigators applied MLMs and data mining to analyses of rare and common genetic variants measured in pedigrees. To develop risk profiles, group members analyzed blood pressure traits along with single-nucleotide polymorphisms and rare variant genotypes derived from sequence and imputation analyses in large Mexican American pedigrees. Supervised MLMs included penalized regression with varying penalties, support vector machines, and permanental classification. Unsupervised MLMs included sparse principal components analysis and sparse graphical models. Entropy-based components analyses were also used to mine these data. None of the investigators fully capitalized on the genetic information provided by the complete pedigrees. Their approaches either corrected for the nonindependence of the individuals within the pedigrees or analyzed only those who were independent. Some methods allowed for covariate adjustment, whereas others did not. We evaluated these methods using a variety of metrics. Four contributors conducted primary analyses on the real data, and the other two research groups used the simulated data with and without knowledge of the underlying simulation model. One group used the answers to the simulated data to assess power and type I errors. Although the MLMs applied were substantially different, each research group concluded that MLMs have advantages over standard statistical approaches with these high-dimensional data. © 2014 WILEY PERIODICALS, INC.

Naive Bayes as opinion classifier to evaluate students satisfaction based on student sentiment in Twitter Social Media

NASA Astrophysics Data System (ADS)

Candra Permana, Fahmi; Rosmansyah, Yusep; Setiawan Abdullah, Atje

2017-10-01

Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This research uses text mining and naive Bayes method as opinion classifier, to be used as an alternative methods in the process of evaluating studentss satisfaction for educational institution. Based on test results, this system can determine the opinion classification in Bahasa Indonesia using naive Bayes as opinion classifier with accuracy level of 84% correct, and the comparison between the existing system and the proposed system to evaluate students satisfaction in learning process, there is only a difference of 16.49%.

A novel data-mining approach leveraging social media to monitor consumer opinion of sitagliptin.

PubMed

Akay, Altug; Dragomir, Andrei; Erlandsson, Björn-Erik

2015-01-01

A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of user's clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members. These findings can open new avenues of research into rapid data collection, feedback, and analysis that can enable improved outcomes and solutions for public health and important feedback for the manufacturer.

Sustainable mineral resources management: from regional mineral resources exploration to spatial contamination risk assessment of mining

NASA Astrophysics Data System (ADS)

Jordan, Gyozo

2009-07-01

Wide-spread environmental contamination associated with historic mining in Europe has triggered social responses to improve related environmental legislation, the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background contamination associated with mineral deposits, industrial activities and contamination in the three-dimensional subsurface space, problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites, land use conflicts and abandoned mines. These problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to show how regional mineral resources mapping has developed into the spatial contamination risk assessment of mining and how geological knowledge can be transferred to environmental assessment of mines. The paper provides a state-of-the-art review of the spatial mine inventory, hazard, impact and risk assessment and ranking methods developed by national and international efforts in Europe. It is concluded that geological knowledge on mineral resources exploration is essential and should be used for the environmental contamination assessment of mines. Also, sufficient methodological experience, knowledge and documented results are available, but harmonisation of these methods is still required for the efficient spatial environmental assessment of mine contamination.

Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response

PubMed Central

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy. PMID:25143989

Personalized privacy-preserving frequent itemset mining using randomized response.

PubMed

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy.

The extraction of bitumen from western oil sands. Annual report, July 1991--July 1992

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oblad, A.G.; Bunger, J.W.; Dahlstrom, D.A.

1992-08-01

The University of Utah tar sand research and development program is concerned with research and development on Utah is extensive oil sands deposits. The program has been intended to develop a scientific and technological base required for eventual commercial recovery of the heavy oils from oil sands and processing these oils to produce synthetic crude oil and other products such as asphalt. The overall program is based on mining the oil sand, processing the mined sand to recover the heavy oils and upgrading them to products. Multiple deposits are being investigated since it is believed that a large scale (approximatelymore » 20,000 bbl/day) plant would require the use of resources from more than one deposit. The tasks or projects in the program are organized according to the following classification: Recovery technologies which includes thermal recovery methods, water extraction methods, and solvent extraction methods; upgrading and processing technologies which covers hydrotreating, hydrocracking, and hydropyrolysis; solvent extraction; production of specialty products; and environmental aspects of the production and processing technologies. These tasks are covered in this report.« less

Phase 1 - Test Area Investigation Report : Mine Research Project GUE-70-14.10 : Executive Summary

DOT National Transportation Integrated Search

2001-01-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,200-foot-long section of : Interstate 70 in Guernsey County, Ohio. Portions of the project area pavement were damaged as a : result of mine subsidence. The damaged areas were remediat...

Alexandra Masaitis, UNR NV, USA. PhD Grad St. Principles of Adoption of the Successful Environmental Policies and Practices Used in Developed Countries into the Russian Mining Industry

NASA Astrophysics Data System (ADS)

Masaitis, A.

2012-12-01

The successful implementation of the environmental policies in the mining industry is of a paramount importance, as it not only prevents both local and trans-border pollution but also guarantees a clean and healthy environment for the people regardless of their place of habitation. It is especially important to encourage the progress of the environmental policy implementation in less regulated countries such as the Russia because such countries have resource-oriented economy based on development of nonrenewable resources. Poor environmental practices in such countries will lead to local environmental crises that could eventually spill into surrounding countries including the most economically advanced. This abstract is a summary of a two-year research project attempted (1) to determine deficiencies of the Russian mining sector ecological policies and (2) to suggest substitute policies from developed countries that could be adapted to the Russian reality. The following research methods were used: 1. The method of the system analysis, where the system is an interaction of the sets of environmental policies; 2. The comparative method of inquiry, 3. Quantitative data analysis, where data was collected from "The collection of statistic data", the US EPA open reports, and the USGS Reports; 4. Review of the Norilsk Nickel Company annual reports. The following results were obtained: Identified the systemic crisis of the ecological environmental policies in the Russian mining sector based on the development of nonrenewable resources, in the absence of the ecological interest by the mining companies that lack mechanisms of environmental and public health protection, the lack of insurance policy, the lack of risk assessment, and in the presence of the audit and monitoring that do not address the local conditions. Based on the above, the following concepts were thought of to improve the environmental conditions in the Russian mining sector: 1. Was developed the Regional Environmental Management principle based on the local conditions; 2. Devised were criteria for the risk assessment for mining operations in Russia. Where the fundamental principals were public health, environmental and biodiversity impact, long- and short- term rehabilitation plans, compliance with international standards and norms. Every criterion has grade level of probability that directly affects quarterly fees. 3. Developed was the mechanism of the economic motivation to make mining operations "environmentally friendly" that includes defrayal of expenses from both direct and indirect damages. 4. Identified were spheres of possible cooperation between mining companies, government organizations, and the NGOs. These include development of standards for Good Neighbor Agreement, exchange of environmental information, international exchange of successful environmental, health, and safety practices. The study showed the necessity for the Russian Federation mining industry to adopt the more successful environmental policies and practices used in developed countries. To achieve this goal the Regional Environmental Management principle, the risk assessment criteria, the mechanism of the economic motivation, and the principles for international cooperation can play an extremely important role.

Performance criteria guideline for three explosion protection methods of electrical equipment rated up to 15,000 volts AC

NASA Technical Reports Server (NTRS)

Linley, L. J.; Luper, A. B.; Dunn, J. H.

1982-01-01

The Bureau of Mines, U.S. Department of the Interior, is reviewing explosion protection methods for use in gassy coal mines. This performance criteria guideline is an evaluation of three explosion protection methods of machines electrically powered with voltages up to 15,000 volts ac. A sufficient amount of basic research has been accomplished to verify that the explosion proof and pressurized enclosure methods can provide adequate explosion protection with the present state of the art up to 15,000 volts ac. This routine application of the potted enclosure as a stand alone protection method requires further investigation or development in order to clarify performance criteria and verification certification requirements. An extensive literature search, a series of high voltage tests, and a design evaluation of the three explosion protection methods indicate that the explosion proof, pressurized, and potted enclosures can all be used to enclose up to 15,000 volts ac.

Text mining applied to electronic cardiovascular procedure reports to identify patients with trileaflet aortic stenosis and coronary artery disease.

PubMed

Small, Aeron M; Kiss, Daniel H; Zlatsin, Yevgeny; Birtwell, David L; Williams, Heather; Guerraty, Marie A; Han, Yuchi; Anwaruddin, Saif; Holmes, John H; Chirinos, Julio A; Wilensky, Robert L; Giri, Jay; Rader, Daniel J

2017-08-01

Interrogation of the electronic health record (EHR) using billing codes as a surrogate for diagnoses of interest has been widely used for clinical research. However, the accuracy of this methodology is variable, as it reflects billing codes rather than severity of disease, and depends on the disease and the accuracy of the coding practitioner. Systematic application of text mining to the EHR has had variable success for the detection of cardiovascular phenotypes. We hypothesize that the application of text mining algorithms to cardiovascular procedure reports may be a superior method to identify patients with cardiovascular conditions of interest. We adapted the Oracle product Endeca, which utilizes text mining to identify terms of interest from a NoSQL-like database, for purposes of searching cardiovascular procedure reports and termed the tool "PennSeek". We imported 282,569 echocardiography reports representing 81,164 individuals and 27,205 cardiac catheterization reports representing 14,567 individuals from non-searchable databases into PennSeek. We then applied clinical criteria to these reports in PennSeek to identify patients with trileaflet aortic stenosis (TAS) and coronary artery disease (CAD). Accuracy of patient identification by text mining through PennSeek was compared with ICD-9 billing codes. Text mining identified 7115 patients with TAS and 9247 patients with CAD. ICD-9 codes identified 8272 patients with TAS and 6913 patients with CAD. 4346 patients with AS and 6024 patients with CAD were identified by both approaches. A randomly selected sample of 200-250 patients uniquely identified by text mining was compared with 200-250 patients uniquely identified by billing codes for both diseases. We demonstrate that text mining was superior, with a positive predictive value (PPV) of 0.95 compared to 0.53 by ICD-9 for TAS, and a PPV of 0.97 compared to 0.86 for CAD. These results highlight the superiority of text mining algorithms applied to electronic cardiovascular procedure reports in the identification of phenotypes of interest for cardiovascular research. Copyright © 2017. Published by Elsevier Inc.

Documenting research with transgender and gender diverse people: protocol for an evidence map and thematic analysis.

PubMed

Marshall, Zack; Welch, Vivian; Thomas, James; Brunger, Fern; Swab, Michelle; Shemilt, Ian; Kaposy, Chris

2017-02-20

There is limited information about how transgender, gender diverse, and Two-Spirit (trans) people have been represented and studied by researchers. The objectives of this study are to (1) map and describe trans research in the social sciences, sciences, humanities, health, education, and business, (2) identify evidence gaps and opportunities for more responsible research with trans people, (3) assess the use of text mining for study identification, and (4) increase access to trans research for key stakeholders through the creation of a web-based evidence map. Study design was informed by community consultations and pilot searches. Eligibility criteria were established to include all original research of any design, including trans people or their health information, and published in English in peer-reviewed journals. A complex electronic search strategy based on relevant concepts in 15 databases was developed to obtain a broad range of results linked to transgender, gender diverse, and Two-Spirit individuals and communities. Searches conducted in early 2015 resulted in 25,242 references after removal of duplicates. Based on the number of references, resources, and an objective to capture upwards of 90% of the existing literature, this study is a good candidate for text mining using Latent Dirichlet Allocation to improve efficiency of the screening process. The following information will be collected for evidence mapping: study topic, study design, methods and data sources, recruitment strategies, sample size, sample demographics, researcher name and affiliation, country where research was conducted, funding source, and year of publication. The proposed research incorporates an extensive search strategy, text mining, and evidence map; it therefore has the potential to build on knowledge in several fields. Review results will increase awareness of existing trans research, identify evidence gaps, and inform strategic research prioritization. Publishing the map online will improve access to research for key stakeholders including community members, policy makers, and healthcare providers. This study will also contribute to knowledge in the area of text mining for study identification by providing an example of how semi-automation performs for screening on title and abstract and on full text.

3D Modeling of Landslide in Open-pit Mining on Basis of Ground-based LIDAR Data

NASA Astrophysics Data System (ADS)

Hu, H.; Fernandez-Steeger, T. M.; Azzam, R.; Arnhardt, C.

2009-04-01

Slope stability is not only an important problem which is related to production and safety in open-pit mining, but also very complex task. There are three main reasons which affect the slope stability as follows: geotechnical factors: Geological structure, lithologic characteristics, water, cohesion, friction, etc.; climate factors: Rainfall and temperature; and external factors: Open-pit mining process, explosion vibration, dynamic load, etc.. The 3rd reason, as a specially one in open-pit mining, not only causes some dynamic problems but also induces the fast geometry changing which must be considered in the following research using numerical simulation and stability analysis. Recently, LIDAR technology has been applied in many fields and places in the world wide. Ground-based LIDAR technology with high accuracy up to 3mm increasingly accommodates to monitoring landslides and detecting changing. LIDAR data collection and preprocessing research have been carried out by Department of Engineering Geology and Hydrogeology at RWTH Aachen University. LIDAR data, so-called a point-cloud of mass data in high density can be obtained in short time for the sensitive open-pit mining area by using ground-based LIDAR. To obtain a consistent surface model, it is necessary to set up multiple scans with the ground-based LIDAR. The framework of data preprocessing which can be implemented by Poly-Works is introduced as follows: gross error detection and elimination, integration of reference frame, model fusion of different scans (re-sampled in overlap region), data reduction without removing the useful information which is a challenge and research front in LIDAR data processing. After data preprocessing, 3D surface model can be directly generated in Poly-Works or generated in other software by building the triangular meshes. The 3D surface landslide model can be applied to further researches such as: real time landslide geometry monitoring due to the fast data collection and processing; change detecting by means of overlying different periods of topographic or geometric data; FEM (Finite Element Method) numerical simulation on basis of combining with the geotechnical properties and parameters to analyze slope stability and predict future movements for designing and rectifying the open-pit mining process; using the reverse engineering thought for developing constitutive models. An improved 3D surface model (HRDEM) which is based on fast data collection and precise data processing on basis of ground-based LIDAR technology is important contribution for further researches of slope stability in open-pit mining area.

Estimates and Predictions of Coal Workers’ Pneumoconiosis Cases among Redeployed Coal Workers of the Fuxin Mining Industry Group in China: A Historical Cohort Study

PubMed Central

Han, Bing; Liu, Hongbo; Zhai, Guojiang; Wang, Qun; Liang, Jie; Zhang, Mengcang; Cui, Kai; Shen, Fuhai; Yi, Hongbo; Li, Yuting; Zhai, Yuhan; Sheng, Yang; Chen, Jie

2016-01-01

This research was aimed at estimating possible Coal workers’ pneumoconiosis (CWP) cases as of 2012, and predicting future CWP cases among redeployed coal workers from the Fuxin Mining Industry Group. This study provided the scientific basis for regulations on CWP screening and diagnosis and labor insurance policies for redeployed coal workers of resource-exhausted mines. The study cohort included 19,116 coal workers. The cumulative incidence of CWP was calculated by the life-table method. Possible CWP cases by occupational category were estimated through the average annual incidence rate of CWP and males’ life expectancy. It was estimated that 141 redeployed coal workers might have suffered from CWP as of 2012, and 221 redeployed coal workers could suffer from CWP in the future. It is crucial to establish a set of feasible and affordable regulations on CWP screening and diagnosis as well as labor insurance policies for redeployed coal workers of resource-exhausted coal mines in China. PMID:26845337

Estimates and Predictions of Coal Workers' Pneumoconiosis Cases among Redeployed Coal Workers of the Fuxin Mining Industry Group in China: A Historical Cohort Study.

PubMed

Han, Bing; Liu, Hongbo; Zhai, Guojiang; Wang, Qun; Liang, Jie; Zhang, Mengcang; Cui, Kai; Shen, Fuhai; Yi, Hongbo; Li, Yuting; Zhai, Yuhan; Sheng, Yang; Chen, Jie

2016-01-01

This research was aimed at estimating possible Coal workers' pneumoconiosis (CWP) cases as of 2012, and predicting future CWP cases among redeployed coal workers from the Fuxin Mining Industry Group. This study provided the scientific basis for regulations on CWP screening and diagnosis and labor insurance policies for redeployed coal workers of resource-exhausted mines. The study cohort included 19,116 coal workers. The cumulative incidence of CWP was calculated by the life-table method. Possible CWP cases by occupational category were estimated through the average annual incidence rate of CWP and males' life expectancy. It was estimated that 141 redeployed coal workers might have suffered from CWP as of 2012, and 221 redeployed coal workers could suffer from CWP in the future. It is crucial to establish a set of feasible and affordable regulations on CWP screening and diagnosis as well as labor insurance policies for redeployed coal workers of resource-exhausted coal mines in China.

Unsupervised user similarity mining in GSM sensor networks.

PubMed

Shad, Shafqat Ali; Chen, Enhong

2013-01-01

Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analysis, where mobility profile building is done through significant places extraction, user's actual movement prediction, and context awareness. However, significant places extraction and user's actual movement prediction for mobility profile building are a trivial task. In this paper, we present the user similarity mining-based methodology through user mobility profile building by using the semantic tagging information provided by user and basic GSM network architecture properties based on unsupervised clustering approach. As the mobility information is in low-level raw form, our proposed methodology successfully converts it to a high-level meaningful information by using the cell-Id location information rather than previously used location capturing methods like GPS, Infrared, and Wifi for profile mining and user similarity mining.

Assessment of respirable dust and its free silica contents in different Indian coalmines.

PubMed

Mukherjee, Ashit K; Bhattacharya, Sanat K; Saiyed, Habibullah N

2005-04-01

Assessment of respirable dust, personal exposures of miners and free silica contents in dust were undertaken to find out the associated risk of coal workers' pneumoconiosis in 9 coal mines of Eastern India during 1988-91. Mine Research Establishment (MRE), 113A Gravimetric Dust Sampler (GDS) and personal samplers (AFC 123), Cassella, London, approved by Director General of Mines Safety (DGMS) were used respectively for monitoring of mine air dust and personal exposures of miners. Fourier Transform Infra-red (FTIR) Spectroscopy determined free silica in respirable dusts. Thermal Conditions like Wet Bulb Globe Temperature (WBGT) index, humidity and wind velocity were also recorded during monitoring. The dust levels in the face return air of both, Board & Pillar (B&P) and Long Wall (LW) mining were found above the permissible level recommended by DGMS, Govt. of India. The drilling, blasting and loading are the major dusty operations in B&P method. Exposures of driller and loader were varied between, 0.81-9.48 mg/m3 and 0.05-9.84 mg/m3 respectively in B&P mining, whereas exposures of DOSCO loader, Shearer operator and Power Support Face Worker were varied between 2.65-9.11 mg/m3, 0.22-10.00 mg/m3 and 0.12-9.32 mg/m3 respectively in LW mining. In open cast mining, compressor and driller operators are the major exposed groups. The percentage silica in respirable dusts found below 5% in all most all the workers except among query loaders and drillers of open cast mines.

Intelligent Scheduling for Underground Mobile Mining Equipment

PubMed Central

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine. PMID:26098934

Mine drainage control - design for reclamation and neutralization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koehrsen, L.G.; Grandt, A.F.

1970-01-01

The Peabody Coal Company Mine Drainage Neutralization Plant at the Will Scarlet mine is a versatile, full-scale facility which should add much new dimension to the science of dealing with this troublesome waste in the next several years. Hopefully, this brief outline will give other persons concerned with the mine drainage neutralization a grasp of the scope of the Peabody Research Program. It is our plan to follow this background presentation in another year with discussion of the effectiveness of the research project and the results that have been achieved. The research project reported herein is supported in part bymore » Federal Water Pollution Control Administration Research and Development Grant 14010 DAX.« less

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

Use of the method for addressing the challenges of resources procurement management at a mining enterprise

NASA Astrophysics Data System (ADS)

Petrova, T. V.; Strekalov, S. V.; Novichikhin, A. V.

2017-09-01

The article is devoted to the analysis of possible application of the total cost of ownership method for the purchase of resources at a mining enterprise. The description of the total cost of ownership method and experience of using this method in other spheres is provided. The article identifies the essential components needed to calculate the total cost of ownership of a resource. Particular attention is paid to the ratio of the price of the purchased resource and the total cost of ownership. To justify the relevance of application of this method at a mining enterprise for resources purchase, the technical and economic conditions of mining enterprises have been analyzed, which are quite specific and force to introduce certain adjustments to the application of the considered method and opens up new possibilities for its use. Specific spheres for application of this method at a mining enterprise are determined. The main result of the study is the proposed practical recommendations for the introduction and extension of the practice of using the method when a mining enterprise purchases resources.

Fate of the naturally occurring radioactive materials during treatment of acid mine drainage with coal fly ash and aluminium hydroxide.

PubMed

Madzivire, Godfrey; Maleka, Peane P; Vadapalli, Viswanath R K; Gitari, Wilson M; Lindsay, Robert; Petrik, Leslie F

2014-01-15

Mining of coal is very extensive and coal is mainly used to produce electricity. Coal power stations generate huge amounts of coal fly ash of which a small amount is used in the construction industry. Mining exposes pyrite containing rocks to H2O and O2. This results in the oxidation of FeS2 to form H2SO4. The acidic water, often termed acid mine drainage (AMD), causes dissolution of potentially toxic elements such as, Fe, Al, Mn and naturally occurring radioactive materials such as U and Th from the associated bedrock. This results in an outflow of AMD with high concentrations of sulphate ions, Fe, Al, Mn and naturally occurring radioactive materials. Treatment of AMD with coal fly ash has shown that good quality water can be produced which is suitable for irrigation purposes. Most of the potentially toxic elements (Fe, Al, Mn, etc) and substantial amounts of sulphate ions are removed during treatment with coal fly ash. This research endeavours to establish the fate of the radioactive materials in mine water with coal fly ash containing radioactive materials. It was established that coal fly ash treatment method was capable of removing radioactive materials from mine water to within the target water quality range for drinking water standards. The alpha and beta radioactivity of the mine water was reduced by 88% and 75% respectively. The reduced radioactivity in the mine water was due to greater than 90% removal of U and Th radioactive materials from the mine water after treatment with coal fly ash as ThO2 and UO2. No radioisotopes were found to leach from the coal fly ash into the mine water. Copyright © 2013 Elsevier Ltd. All rights reserved.

Are Lithium Ion Cells Intrinsically Safe?

PubMed Central

Dubaniewicz, Thomas H.; DuCarme, Joseph P.

2015-01-01

National Institute for Occupational Safety and Health researchers are studying the potential for Li-ion-battery thermal runaway from an internal short circuit in equipment approved as permissible for use in underground coal mines. Researchers used a plastic wedge to induce internal short circuits for thermal runaway susceptibility evaluation purposes, which proved to be a more severe test than the flat plate method for selected Li-ion cells. Researchers conducted cell crush tests within a 20-L chamber filled with 6.5% CH4–air to simulate the mining hazard. Results indicate that LG Chem ICR18650S2 LiCoO2 cells pose a CH4 explosion hazard from a cell internal short circuit. Under specified test conditions, A123 Systems 26650 LiFePO4 cells were safer than the LG Chem ICR18650S2 LiCoO2 cells at a conservative statistical significance level. PMID:26166911

U.S. Geological Survey Toxic Substances Hydrology Program: Proceedings of the technical meeting, Charleston, South Carolina, March 8-12, 1999: Volume 1 (Part A)

USGS Publications Warehouse

Morganwalp, David W.; Buxton, Herbert T.

1999-01-01

This report contains papers presented at the seventh Technical Meeting of the U.S. Geological Survey (USGS), Toxic Substances Hydrology (Toxics) Program. The meeting was held March 8-12, 1999, in Charleston, South Carolina. Toxics Program Technical Meetings are held periodically to provide a forum for presentation and discussion of results of recent research activities.The objectives of these meetings are to:Present recent research results to essential stakeholders,Encourage synthesis and integrated interpretations among scientists with different expertise who are working on a contamination issue, andPromote exchange of ideas among scientists working on different projects and issues within the Toxics Program.The Proceedings is published in three volumes. Volume 1 contains papers that report on results of research on contamination from hard-rock mining. Results include research on contamination from hard rock mining in arid southwest alluvial basins, research on hard rock mining in mountainous terrain, and progress from the USGS Abandoned Mine Lands Initiative. This Initiative is designed to develop a watershed-based approach to characterize and remediate contamination from abandoned mine lands and transfer technologies to Federal land management agencies and stakeholders.Volume 2 contains papers on contamination of hydrologic systems and related ecosystems. The papers discuss research on the response of estuarine ecosystems to contamination from human activities. They include research on San Francisco Bay; mercury contamination of aquatic ecosystems; and investigation of the occurrence, distribution, and fate of agricultural chemicals in the Mississippi River Basin. This volume also contains results on development and reconnaissance testing of new methods to detect emerging contaminants in environmental samples.Volume 3 contains papers on subsurface contamination from point sources. The papers discuss research on: hydrocarbons and fuel oxygenates at gasoline release sites; ground-water contamination by crude oil; complex contaminant mixtures from treated wastewater discharges; waste disposal and subsurface transport of contaminants in arid environments; ground water and surface water affected by municipal landfill leachate; natural attenuation of chlorinated solvents; and characterizing flow and transport in fractured rock aquifers.In all, the more than 175 papers contained in this proceedings reflect the contributions of more than 350 scientists who are co-authors. These scientists are from across the USGS, as well as from universities, other Federal and State agencies, and industry.

U.S. Geological Survey Toxic Substances Hydrology Program: Proceedings of the technical meeting, Charleston, South Carolina, March 8-12, 1999: Volume 3 (Part C)

USGS Publications Warehouse

Morganwalp, David W.; Buxton, Herbert T.

1999-01-01

This report contains papers presented at the seventh Technical Meeting of the U.S. Geological Survey (USGS), Toxic Substances Hydrology (Toxics) Program. The meeting was held March 8-12, 1999, in Charleston, South Carolina. Toxics Program Technical Meetings are held periodically to provide a forum for presentation and discussion of results of recent research activities.The objectives of these meetings are to:Present recent research results to essential stakeholders,Encourage synthesis and integrated interpretations among scientists with different expertise who are working on a contamination issue, andPromote exchange of ideas among scientists working on different projects and issues within the Toxics Program.The Proceedings is published in three volumes. Volume 1 contains papers that report on results of research on contamination from hard-rock mining. Results include research on contamination from hard rock mining in arid southwest alluvial basins, research on hard rock mining in mountainous terrain, and progress from the USGS Abandoned Mine Lands Initiative. This Initiative is designed to develop a watershed-based approach to characterize and remediate contamination from abandoned mine lands and transfer technologies to Federal land management agencies and stakeholders.Volume 2 contains papers on contamination of hydrologic systems and related ecosystems. The papers discuss research on the response of estuarine ecosystems to contamination from human activities. They include research on San Francisco Bay; mercury contamination of aquatic ecosystems; and investigation of the occurrence, distribution, and fate of agricultural chemicals in the Mississippi River Basin. This volume also contains results on development and reconnaissance testing of new methods to detect emerging contaminants in environmental samples.Volume 3 contains papers on subsurface contamination from point sources. The papers discuss research on: hydrocarbons and fuel oxygenates at gasoline release sites; ground-water contamination by crude oil; complex contaminant mixtures from treated wastewater discharges; waste disposal and subsurface transport of contaminants in arid environments; ground water and surface water affected by municipal landfill leachate; natural attenuation of chlorinated solvents; and characterizing flow and transport in fractured rock aquifers.In all, the more than 175 papers contained in this proceedings reflect the contributions of more than 350 scientists who are co-authors. These scientists are from across the USGS, as well as from universities, other Federal and State agencies, and industry.

U.S. Geological Survey Toxic Substances Hydrology Program: Proceedings of the technical meeting, Charleston, South Carolina, March 8-12, 1999: Volume 2 (Part B)

USGS Publications Warehouse

Morganwalp, David W.; Buxton, Herbert T.

1999-01-01

This report contains papers presented at the seventh Technical Meeting of the U.S. Geological Survey (USGS), Toxic Substances Hydrology (Toxics) Program. The meeting was held March 8-12, 1999, in Charleston, South Carolina. Toxics Program Technical Meetings are held periodically to provide a forum for presentation and discussion of results of recent research activities.The objectives of these meetings are to:Present recent research results to essential stakeholders,Encourage synthesis and integrated interpretations among scientists with different expertise who are working on a contamination issue, andPromote exchange of ideas among scientists working on different projects and issues within the Toxics Program.The Proceedings is published in three volumes. Volume 1 contains papers that report on results of research on contamination from hard-rock mining. Results include research on contamination from hard rock mining in arid southwest alluvial basins, research on hard rock mining in mountainous terrain, and progress from the USGS Abandoned Mine Lands Initiative. This Initiative is designed to develop a watershed-based approach to characterize and remediate contamination from abandoned mine lands and transfer technologies to Federal land management agencies and stakeholders.Volume 2 contains papers on contamination of hydrologic systems and related ecosystems. The papers discuss research on the response of estuarine ecosystems to contamination from human activities. They include research on San Francisco Bay; mercury contamination of aquatic ecosystems; and investigation of the occurrence, distribution, and fate of agricultural chemicals in the Mississippi River Basin. This volume also contains results on development and reconnaissance testing of new methods to detect emerging contaminants in environmental samples.Volume 3 contains papers on subsurface contamination from point sources. The papers discuss research on: hydrocarbons and fuel oxygenates at gasoline release sites; ground-water contamination by crude oil; complex contaminant mixtures from treated wastewater discharges; waste disposal and subsurface transport of contaminants in arid environments; ground water and surface water affected by municipal landfill leachate; natural attenuation of chlorinated solvents; and characterizing flow and transport in fractured rock aquifers.In all, the more than 175 papers contained in this proceedings reflect the contributions of more than 350 scientists who are co-authors. These scientists are from across the USGS, as well as from universities, other Federal and State agencies, and industry.

Analysis of open-pit mines using high-resolution topography from UAV

NASA Astrophysics Data System (ADS)

Chen, Jianping; Li, Ke; Sofia, Giulia; Tarolli, Paolo

2015-04-01

Among the anthropogenic topographic signatures on the Earth, open-pit mines deserve a great importance, since they significantly affect the Earth's surface and its related processes (e.g. erosion, pollution). Their geomorphological analysis, therefore, represents a real challenge for the Earth science community. The purpose of this research is to characterize the open-pit mining features using a recently published landscape metric, the Slope Local Length of Auto-Correlation (SLLAC) (Sofia et al., 2014), and high-resolution DEMs (Digital Elevation Models) derived from drone surveyed topography. The research focuses on two main case studies of iron mines located in the Beijing district (P.R. China). The main topographic information (Digital Surface Models, DSMs) was derived using Unmanned Aerial Vehicle (UAV) and the Structure from Motion (SfM) photogrammetric technique. The results underline the effectiveness of the adopted methodologies and survey techniques in the characterization of the main geomorphic features of the mines. Thanks to the SLLAC, the terraced area given by multi-benched sideways-moving method for the iron extraction is automatically depicted, and using some SLLAC derived parameters, the related terraces extent is automatically estimated. The analysis of the correlation length orientation, furthermore, allows to identify the terraces orientation respect to the North, and to understand as well the shape of the open-pit area. This provides a basis for a large scale and low cost topographic survey for a sustainable environmental planning and, for example, for the mitigation of environmental anthropogenic impact due to mining. References Sofia G., Marinello F, Tarolli P. 2014. A new landscape metric for the identification of terraced sites: the Slope Local Length of Auto-Correlation (SLLAC). ISPRS Journal of Photogrammetry and Remote Sensing, doi:10.1016/j.isprsjprs.2014.06.018

Economics of Gypsum Production in Iran

NASA Astrophysics Data System (ADS)

Esmaeili, Abdoulkarim

The purpose of this research is to analyze the economics of gypsum production in Iran. The trend in production cost, selling price and profit are used to investigate economics of gypsum production. In addition, the multivariate time series method is used to determine factors affecting gypsum price in domestic market. The results indicated that due to increase in production and inflation, profitability of gypsum production has decreased during recent years. It is concluded that tariff and non-tariff barriers on mines machinery are among reasons for increasing production cost in Iranian gypsum mines. Decreasing such barriers could increase profitability of gypsum production in Iran.

Issues of data governance associated with data mining in medical research: experiences from an empirical study.

PubMed

Nahar, Jesmin; Imam, Tasadduq; Tickle, Kevin S; Garcia-Alonso, Debora

2013-01-01

This chapter is a review of data mining techniques used in medical research. It will cover the existing applications of these techniques in the identification of diseases, and also present the authors' research experiences in medical disease diagnosis and analysis. A computational diagnosis approach can have a significant impact on accurate diagnosis and result in time and cost effective solutions. The chapter will begin with an overview of computational intelligence concepts, followed by details on different classification algorithms. Use of association learning, a well recognised data mining procedure, will also be discussed. Many of the datasets considered in existing medical data mining research are imbalanced, and the chapter focuses on this issue as well. Lastly, the chapter outlines the need of data governance in this research domain.

The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

NASA Astrophysics Data System (ADS)

Huijun, Duan; Shijun, Hao; Jie, Feng

2018-06-01

In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

An empirical method for estimating instream pre-mining pH and dissolved Cu concentration in catchments with acidic drainage and ferricrete

USGS Publications Warehouse

Nimick, D.A.; Gurrieri, J.T.; Furniss, G.

2009-01-01

Methods for assessing natural background water quality of streams affected by historical mining are vigorously debated. An empirical method is proposed in which stream-specific estimation equations are generated from relationships between either pH or dissolved Cu concentration in stream water and the Fe/Cu concentration ratio in Fe-precipitates presently forming in the stream. The equations and Fe/Cu ratios for pre-mining deposits of alluvial ferricrete then were used to reconstruct estimated pre-mining longitudinal profiles for pH and dissolved Cu in three acidic streams in Montana, USA. Primary assumptions underlying the proposed method are that alluvial ferricretes and modern Fe-precipitates share a common origin, that the Cu content of Fe-precipitates remains constant during and after conversion to ferricrete, and that geochemical factors other than pH and dissolved Cu concentration play a lesser role in determining Fe/Cu ratios in Fe-precipitates. The method was evaluated by applying it in a fourth, naturally acidic stream unaffected by mining, where estimated pre-mining pH and Cu concentrations were similar to present-day values, and by demonstrating that inflows, particularly from unmined areas, had consistent effects on both the pre-mining and measured profiles of pH and Cu concentration. Using this method, it was estimated that mining has affected about 480 m of Daisy Creek, 1.8 km of Fisher Creek, and at least 1 km of Swift Gulch. Mean values of pH decreased by about 0.6 pH units to about 3.2 in Daisy Creek and by 1-1.5 pH units to about 3.5 in Fisher Creek. In Swift Gulch, mining appears to have decreased pH from about 5.5 to as low as 3.6. Dissolved Cu concentrations increased due to mining almost 40% in Daisy Creek to a mean of 11.7 mg/L and as much as 230% in Fisher Creek to 0.690 mg/L. Uncertainty in the fate of Cu during the conversion of Fe-precipitates to ferricrete translates to potential errors in pre-mining estimates of as much as 0.25 units for pH and 22% for dissolved Cu concentration. The method warrants further testing in other mined and unmined watersheds. Comparison of pre-mining water-quality estimates derived from the ferricrete and other methods in single watersheds would be particularly valuable. The method has potential for use in monitoring remedial efforts at mine sites with ferricrete deposits. A reasonable remediation objective might be realized when the downstream pattern of Fe/Cu ratios in modern streambed Fe-precipitates corresponds to the pattern in pre-mining alluvial ferricrete deposits along a stream valley.

Novel methods for detecting buried explosive devices

NASA Astrophysics Data System (ADS)

Kercel, Stephen W.; Burlage, Robert S.; Patek, David R.; Smith, Cyrus M.; Hibbs, Andrew D.; Rayner, Timothy J.

1997-07-01

Oak Ridge National Laboratory and Quantum Magnetics, Inc. are exploring novel landmine detection technologies. Technologies considered here include bioreporter bacteria, swept acoustic resonance, nuclear quadrupole resonance (NQR), and semiotic data fusion. Bioreporter bacteria look promising for third-world humanitarian applications; they are inexpensive, and deployment does not require high-tech methods. Swept acoustic resonance may be a useful adjunct to magnetometers in humanitarian demining. For military demining, NQR is a promising method for detecting explosive substances; of 50,000 substances that have been tested, one has an NQR signature that can be mistaken for RDX or TNT. For both military and commercial demining, sensor fusion entails two daunting tasks, identifying fusible features in both present-day and emerging technologies, and devising a fusion algorithm that runs in real-time on cheap hardware. Preliminary research in these areas is encouraging. A bioreporter bacterium for TNT detection is under development. Investigation has just started in swept acoustic resonance as an approach to a cheap mine detector for humanitarian use. Real-time wavelet processing appears to be a key to extending NQR bomb detection into mine detection, including TNT-based mines. Recent discoveries in semiotics may be the breakthrough that will lead to a robust fused detection scheme.

Behavior Correlates of Post-Stroke Disability Using Data Mining and Infographics

PubMed Central

Yoon, Sunmoo; Gutierrez, Jose

2015-01-01

Purpose Disability is a potential risk for stroke survivors. This study aims to identify disability risk factors associated with stroke and their relative importance and relationships from a national behavioral risk factor dataset. Methods Data of post-stroke individuals in the U.S (n=19,603) including 397 variables were extracted from a publically available national dataset and analyzed. Data mining algorithms including C4.5 and linear regression with M5s methods were applied to build association models for post-stroke disability using Weka software. The relative importance and relationship of 70 variables associated with disability were presented in infographics for clinicians to understand easily. Results Fifty-five percent of post-stroke patients experience disability. Exercise, employment and satisfaction of life were relatively important factors associated with disability among stroke patients. Modifiable behavior factors strongly associated with disability include exercise (OR: 0.46, P<0.01) and good rest (OR 0.37, P<0.01). Conclusions Data mining is promising to discover factors associated with post-stroke disability from a large population dataset. The findings can be potentially valuable for establishing the priorities for clinicians and researchers and for stroke patient education. The methods may generalize to other health conditions. PMID:26835413

Intelligent Information Retrieval and Web Mining Architecture Using SOA

ERIC Educational Resources Information Center

El-Bathy, Naser Ibrahim

2010-01-01

The study of this dissertation provides a solution to a very specific problem instance in the area of data mining, data warehousing, and service-oriented architecture in publishing and newspaper industries. The research question focuses on the integration of data mining and data warehousing. The research problem focuses on the development of…

Test area investigation report mine research project GUE-70-14.10, BBC&M Engineering, phase II, executive summary.

DOT National Transportation Integrated Search

2003-06-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,100-foot-long section : of Interstate 70 in Guernsey County, Ohio. Portions of the Project Area pavement were : damaged as a result of mine subsidence. The damaged areas and other min...

Phase I--test area investigation report mine research project GUE-70-14.10, PID no. 18459, Guernsey Co., Ohio.

DOT National Transportation Integrated Search

2001-01-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,200-foot-long section of : Interstate 70 in Guernsey County, Ohio. Portions of the project area pavement were damaged as a : result of mine subsidence. The damaged areas were remediat...

Phase II - Test Area Investigation Report : Mine Research Project GUE - 70-14.10 : Executive Summary

DOT National Transportation Integrated Search

2001-01-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,100-foot-long section : of Interstate 70 in Guernsey County, Ohio. Portions of the Project Area pavement were : damaged as a result of mine subsidence. The damaged areas and other min...

Phase 1 - test area investigation report : mine research project GUE-70-14.10 PID No. 18459

DOT National Transportation Integrated Search

2001-01-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,200-foot-long section of : Interstate 70 in Guernsey County, Ohio. Portions of the project area pavement were damaged as a : result of mine subsidence. The damaged areas were remediat...

iADRs: towards online adverse drug reaction analysis.

PubMed

Lin, Wen-Yang; Li, He-Yi; Du, Jhih-Wei; Feng, Wen-Yu; Lo, Chiao-Feng; Soo, Von-Wun

2012-12-01

Adverse Drug Reaction (ADR) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term post-marketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry. Recently, large numbers of adverse events and the development of data mining technology have motivated the development of statistical and data mining methods for the detection of ADRs. These stand-alone methods, with no integration into knowledge discovery systems, are tedious and inconvenient for users and the processes for exploration are time-consuming. This paper proposes an interactive system platform for the detection of ADRs. By integrating an ADR data warehouse and innovative data mining techniques, the proposed system not only supports OLAP style multidimensional analysis of ADRs, but also allows the interactive discovery of associations between drugs and symptoms, called a drug-ADR association rule, which can be further developed using other factors of interest to the user, such as demographic information. The experiments indicate that interesting and valuable drug-ADR association rules can be efficiently mined.

[Evaluation of environmental conditions: air, water and soil in areas of mining activity in Boyacá, Colombia].

PubMed

Agudelo-Calderón, Carlos A; Quiroz-Arcentales, Leonardo; García-Ubaque, Juan C; Robledo-Martínez, Rocío; García-Ubaque, Cesar A

2016-02-01

Objectives To determine concentrations of PM10, mercury and lead in indoor air of homes, water sources and soil in municipalities near mining operations. Method 6 points were evaluated in areas of influence and 2 in control areas. For measurements of indoor air, we used the NIOSH 600 method (PM10), NIOSH 6009 (mercury) and NIOSH 7300 (lead). For water analysis we used the IDEAM Guide for monitoring discharges. For soil analysis, we used the cold vapor technique (mercury) and atomic absorption (lead). Results In almost all selected households, the average PM10 and mercury concentrations in indoor air exceeded applicable air quality standards. Concentrations of lead were below standard levels. In all water sources, high concentrations of lead were found and in some places within the mining areas, high levels of iron, aluminum and mercury were also found. In soil, mercury concentrations were below the detection level and for lead, differences between the monitored points were observed. Conclusions The results do not establish causal relationships between mining and concentration of these pollutants in the evaluated areas because of the multiplicity of sources in the area. However, such studies provide important information, useful to agents of the environmental health system and researchers. Installation of networks for environmental monitoring to obtain continuous reports is suggested.

Multisource geological data mining and its utilization of uranium resources exploration

NASA Astrophysics Data System (ADS)

Zhang, Jie-lin

2009-10-01

Nuclear energy as one of clear energy sources takes important role in economic development in CHINA, and according to the national long term development strategy, many more nuclear powers will be built in next few years, so it is a great challenge for uranium resources exploration. Research and practice on mineral exploration demonstrates that utilizing the modern Earth Observe System (EOS) technology and developing new multi-source geological data mining methods are effective approaches to uranium deposits prospecting. Based on data mining and knowledge discovery technology, this paper uses multi-source geological data to character electromagnetic spectral, geophysical and spatial information of uranium mineralization factors, and provides the technical support for uranium prospecting integrating with field remote sensing geological survey. Multi-source geological data used in this paper include satellite hyperspectral image (Hyperion), high spatial resolution remote sensing data, uranium geological information, airborne radiometric data, aeromagnetic and gravity data, and related data mining methods have been developed, such as data fusion of optical data and Radarsat image, information integration of remote sensing and geophysical data, and so on. Based on above approaches, the multi-geoscience information of uranium mineralization factors including complex polystage rock mass, mineralization controlling faults and hydrothermal alterations have been identified, the metallogenic potential of uranium has been evaluated, and some predicting areas have been located.

A Volterra series-based method for extracting target echoes in the seafloor mining environment.

PubMed

Zhao, Haiming; Ji, Yaqian; Hong, Yujiu; Hao, Qi; Ma, Liyong

2016-09-01

The purpose of this research was to evaluate the applicability of the Volterra adaptive method to predict the target echo of an ultrasonic signal in an underwater seafloor mining environment. There is growing interest in mining of seafloor minerals because they offer an alternative source of rare metals. Mining the minerals cause the seafloor sediments to be stirred up and suspended in sea water. In such an environment, the target signals used for seafloor mapping are unable to be detected because of the unavoidable presence of volume reverberation induced by the suspended sediments. The detection of target signals in reverberation is currently performed using a stochastic model (for example, the autoregressive (AR) model) based on the statistical characterisation of reverberation. However, we examined a new method of signal detection in volume reverberation based on the Volterra series by confirming that the reverberation is a chaotic signal and generated by a deterministic process. The advantage of this method over the stochastic model is that attributions of the specific physical process are considered in the signal detection problem. To test the Volterra series based method and its applicability to target signal detection in the volume reverberation environment derived from the seafloor mining process, we simulated the real-life conditions of seafloor mining in a water filled tank of dimensions of 5×3×1.8m. The bottom of the tank was covered with 10cm of an irregular sand layer under which 5cm of an irregular cobalt-rich crusts layer was placed. The bottom was interrogated by an acoustic wave generated as 16μs pulses of 500kHz frequency. This frequency is demonstrated to ensure a resolution on the order of one centimetre, which is adequate in exploration practice. Echo signals were collected with a data acquisition card (PCI 1714 UL, 12-bit). Detection of the target echo in these signals was performed by both the Volterra series based model and the AR model. The results obtained confirm that the Volterra series based method is more efficient in the detection of the signal in reverberation than the conventional AR model (the accuracy is 80% for the PIM-Volterra prediction model versus 40% for the AR model). Copyright © 2016 Elsevier B.V. All rights reserved.

Functional evaluation of out-of-the-box text-mining tools for data-mining tasks

PubMed Central

Jung, Kenneth; LePendu, Paea; Iyer, Srinivasan; Bauer-Mehren, Anna; Percha, Bethany; Shah, Nigam H

2015-01-01

Objective The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. In this paper, we quantify this trade-off among text processing systems that make different trade-offs between speed and linguistic understanding. We tested both types of systems in three clinical research tasks: phase IV safety profiling of a drug, learning adverse drug–drug interactions, and learning used-to-treat relationships between drugs and indications. Materials We first benchmarked the accuracy of the NCBO Annotator and REVEAL in a manually annotated, publically available dataset from the 2008 i2b2 Obesity Challenge. We then applied the NCBO Annotator and REVEAL to 9 million clinical notes from the Stanford Translational Research Integrated Database Environment (STRIDE) and used the resulting data for three research tasks. Results There is no significant difference between using the NCBO Annotator and REVEAL in the results of the three research tasks when using large datasets. In one subtask, REVEAL achieved higher sensitivity with smaller datasets. Conclusions For a variety of tasks, employing simple term recognition methods instead of advanced NLP methods results in little or no impact on accuracy when using large datasets. Simpler dictionary-based methods have the advantage of scaling well to very large datasets. Promoting the use of simple, dictionary-based methods for population level analyses can advance adoption of NLP in practice. PMID:25336595

Online Communication Settings and the Qualitative Research Process: Acclimating Students and Novice Researchers.

PubMed

Gregory, Katherine

2018-06-01

In the last 20 years, qualitative research scholars have begun to interrogate methodological and analytic issues concerning online research settings as both data sources and instruments for digital methods. This article examines the adaptation of parts of a qualitative research curriculum for understanding online communication settings. I propose methodological best practices for researchers and educators that I developed while teaching research methods to undergraduate and graduate students across disciplinary departments and discuss obstacles faced during my own research while gathering data from online sources. This article confronts issues concerning the disembodied aspects of applying what in practice should be rooted in a humanistic inquiry. Furthermore, as some approaches to online qualitative research as a digital method grow increasingly problematic with the development of new data mining technologies, I will also briefly touch upon borderline ethical practices involving data-scraping-based qualitative research.

Geovisualization of Local and Regional Migration Using Web-mined Demographics

NASA Astrophysics Data System (ADS)

Schuermann, R. T.; Chow, T. E.

2014-11-01

The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

Illustrated surface mining methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1979-01-01

This manual provides a visual synopsis of surface coal mining methods in the United States. The manual presents various surface mining methods and techniques through artist renderings and appropriate descriptions. The productive coal fields of the United States were divided into four regions according to geology and physiography. A glossay of terminology is included. (DP)

Who Says Your Frames Are Better than Mine? Making the Case for Strategic Framing by Using the Power of Experimental Research

ERIC Educational Resources Information Center

Manuel, Tiffany

2009-01-01

This article details the experimental research on frame effects that provides quantitative evidence that some types of frames have a greater ability to move and affect policy support than others. This method is particularly useful in showing the magnitude by which exposure to alternative ways of thinking about social issues alters the public's…

Knowledge discovery in traditional Chinese medicine: state of the art and perspectives.

PubMed

Feng, Yi; Wu, Zhaohui; Zhou, Xuezhong; Zhou, Zhongmei; Fan, Weiyu

2006-11-01

As a complementary medical system to Western medicine, traditional Chinese medicine (TCM) provides a unique theoretical and practical approach to the treatment of diseases over thousands of years. Confronted with the increasing popularity of TCM and the huge volume of TCM data, historically accumulated and recently obtained, there is an urgent need to explore these resources effectively by the techniques of knowledge discovery in database (KDD). This paper aims at providing an overview of recent KDD studies in TCM field. A literature search was conducted in both English and Chinese publications, and major studies of knowledge discovery in TCM (KDTCM) reported in these materials were identified. Based on an introduction to the state of the art of TCM data resources, a review of four subfields of KDTCM research was presented, including KDD for the research of Chinese medical formula, KDD for the research of Chinese herbal medicine, KDD for TCM syndrome research, and KDD for TCM clinical diagnosis. Furthermore, the current state and main problems in each subfield were summarized based on a discussion of existing studies, and future directions for each subfield were also proposed accordingly. A series of KDD methods are used in existing KDTCM researches, ranging from conventional frequent itemset mining to state of the art latent structure model. Considerable interesting discoveries are obtained by these methods, such as novel TCM paired drugs discovered by frequent itemset analysis, functional community of related genes discovered under syndrome perspective by text mining, the high proportion of toxic plants in the botanical family Ranunculaceae disclosed by statistical analysis, the association between M-cholinoceptor blocking drug and Solanaceae revealed by association rule mining, etc. It is particularly inspiring to see some studies connecting TCM with biomedicine, which provide a novel top-down view for functional genomics research. However, further developments of KDD methods are still expected to better adapt to the features of TCM. Existing studies demonstrate that KDTCM is effective in obtaining medical discoveries. However, much more work needs to be done in order to discover real diamonds from TCM domain. The usage and development of KDTCM in the future will substantially contribute to the TCM community, as well as modern life science.

Applications of Data Mining Methods in the Integrative Medical Studies of Coronary Heart Disease: Progress and Prospect

PubMed Central

Wang, Yixin; Guo, Fang

2014-01-01

A large amount of studies show that real-world study has strong external validity than the traditional randomized controlled trials and can evaluate the effect of interventions in a real clinical setting, which open up a new path for researches of integrative medicine in coronary heart disease. However, clinical data of integrative medicine in coronary heart disease are large in amount and complex in data types, making exploring the appropriate methodology a hot topic. Data mining techniques are to analyze and dig out useful information and knowledge from the mass data to guide people's practices. The present review provides insights for the main features of data mining and their applications of integrative medical studies in coronary heart disease, aiming to analyze the progress and prospect in this field. PMID:25544853

Integration of MOOCs in Advanced Mining Training Programmes

NASA Astrophysics Data System (ADS)

Saveleva, Irina; Greenwald, Oksana; Kolomiets, Svetlana; Medvedeva, Elena

2017-11-01

The paper covers the concept of innovative approaches in education based on incorporating MOOCs options into traditional classroom. It takes a look at the ways higher education instructors working with the mining engineers enrolled in advanced training programmes can brighten, upgrade and facilitate the learning process. The shift of higher education from in-class to online format has changed the learning environment and the methods of teaching including professional retraining courses. In addition, the need of mining companies for managers of a new kind obligates high school retraining centres rapidly move towards the 21st century skill framework. One of widely recognized innovations in the sphere of e-learning is MOOCs (Massive Open Online Courses) that can be used as an effective teaching tool for organizing professional training of managing staff of mining companies within the walls of a university. The authors share their instructional experience and show the benefits of introducing MOOCs options at the courses designed for retraining mining engineers and senior managers of coal enterprises. Though in recent researches the pedagogical value of MOOCs is highly questioned and even negated this invention of the 21st century can become an essential and truly helpful instrument in the hands of educators.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word “data-mining” is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

An examination of the effects of mountaintop removal coal mining on respiratory symptoms and COPD using propensity scores.

PubMed

Hendryx, Michael; Luo, Juhua

2015-01-01

Previous research on public health consequences of mountaintop removal (MTR) coal mining has been limited by the observational nature of the data. The current study used propensity scores, a method designed to overcome this limitation, to draw more confident causal inferences about mining effects on respiratory health using non-experimental data. These data come from a health survey of 682 adults residing in two rural areas of Virginia, USA characterized by the presence or absence of MTR mining. Persons with a history of occupational exposure as coal miners were excluded. Nine covariates including age, sex, current and former smoking, overweight, obesity, high school education, college education, and exposure to coal as a home-heating source were selected to estimate propensity scores. Propensity scores were tested for balance and then used as weights to create quasi-experimental exposed and unexposed groups. Results indicated that persons in the mountaintop mining group had significantly (p < 0.0001) elevated prevalence of respiratory symptoms and chronic obstructive pulmonary disease. The results suggest that impaired respiratory health results from exposure to MTR environments and not from other risks.

The Mining Minds digital health and wellness framework.

PubMed

Banos, Oresti; Bilal Amin, Muhammad; Ali Khan, Wajahat; Afzal, Muhammad; Hussain, Maqbool; Kang, Byeong Ho; Lee, Sungyong

2016-07-15

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people's conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems. This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people's lifestyles and provide a variety of smart coaching and support services. This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework. Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

Moment tensor clustering: a tool to monitor mining induced seismicity

NASA Astrophysics Data System (ADS)

Cesca, Simone; Dahm, Torsten; Tolga Sen, Ali

2013-04-01

Automated moment tensor inversion routines have been setup in the last decades for the analysis of global and regional seismicity. Recent developments could be used to analyse smaller events and larger datasets. In particular, applications to microseismicity, e.g. in mining environments, have then led to the generation of large moment tensor catalogues. Moment tensor catalogues provide a valuable information about the earthquake source and details of rupturing processes taking place in the seismogenic region. Earthquake focal mechanisms can be used to discuss the local stress field, possible orientations of the fault system or to evaluate the presence of shear and/or tensile cracks. Focal mechanism and moment tensor solutions are typically analysed for selected events, and quick and robust tools for the automated analysis of larger catalogues are needed. We propose here a method to perform cluster analysis for large moment tensor catalogues and identify families of events which characterize the studied microseismicity. Clusters include events with similar focal mechanisms, first requiring the definition of distance between focal mechanisms. Different metrics are here proposed, both for the case of pure double couple, constrained moment tensor and full moment tensor catalogues. Different clustering approaches are implemented and discussed. The method is here applied to synthetic and real datasets from mining environments to demonstrate its potential: the proposed cluserting techniques prove to be able to automatically recognise major clusters. An important application for mining monitoring concerns the early identification of anomalous rupture processes, which is relevant for the hazard assessment. This study is funded by the project MINE, which is part of the R&D-Programme GEOTECHNOLOGIEN. The project MINE is funded by the German Ministry of Education and Research (BMBF), Grant of project BMBF03G0737.

Appraisement of environment remote sensing method in mining area

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Zhen, Han; Jiang, Tao; Lei, Liqing; Gong, Cailan

1998-08-01

Coal mining is attached great importance by society as a key profession of environmental pollution. The monitor and protection of coal-mine environment is a developing profession in China. The sulfur dioxide, carbon dioxide, carbon monoxide and other waste gases, which are put out by the spontaneous combustion or weathering of gangue are an important pollution resource of atmosphere. The stack of gangue held down many farmlands. Smoke, coal dust and powder coal ash pollute the environment of mining area and surroundings though the affection of monsoon. The pH value of water which coal mine drained off is low, and the drinking, farming and animal husbandry water where it flowed are affected. The surface subsidence which mining caused is a typical destruction of ground environment. The people pay attention to remote sensing as a method of rapidly, cheaply regional environment investigation. The paper tires making an appraisement of mining area environment monitor by many kind methods of remote sensing from the characteristic of mining area environment.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Virtual Observatories, Data Mining, and Astroinformatics

NASA Astrophysics Data System (ADS)

Borne, Kirk

The historical, current, and future trends in knowledge discovery from data in astronomy are presented here. The story begins with a brief history of data gathering and data organization. A description of the development ofnew information science technologies for astronomical discovery is then presented. Among these are e-Science and the virtual observatory, with its data discovery, access, display, and integration protocols; astroinformatics and data mining for exploratory data analysis, information extraction, and knowledge discovery from distributed data collections; new sky surveys' databases, including rich multivariate observational parameter sets for large numbers of objects; and the emerging discipline of data-oriented astronomical research, called astroinformatics. Astroinformatics is described as the fourth paradigm of astronomical research, following the three traditional research methodologies: observation, theory, and computation/modeling. Astroinformatics research areas include machine learning, data mining, visualization, statistics, semantic science, and scientific data management.Each of these areas is now an active research discipline, with significantscience-enabling applications in astronomy. Research challenges and sample research scenarios are presented in these areas, in addition to sample algorithms for data-oriented research. These information science technologies enable scientific knowledge discovery from the increasingly large and complex data collections in astronomy. The education and training of the modern astronomy student must consequently include skill development in these areas, whose practitioners have traditionally been limited to applied mathematicians, computer scientists, and statisticians. Modern astronomical researchers must cross these traditional discipline boundaries, thereby borrowing the best of breed methodologies from multiple disciplines. In the era of large sky surveys and numerous large telescopes, the potential for astronomical discovery is equally large, and so the data-oriented research methods, algorithms, and techniques that are presented here will enable the greatest discovery potential from the ever-growing data and information resources in astronomy.

Test area investigation report mine research project GUE-70-14.10, BBC&M Engineering, January 2001 I-1, part 1 : executive summary.

DOT National Transportation Integrated Search

2001-01-01

The GUE-70-14.10 Mine Research Project is the investigation of a 2,200-foot-long section of : Interstate 70 in Guernsey County, Ohio. Portions of the project area pavement were damaged as a : result of mine subsidence. The damaged areas were remediat...

Revealing Significant Relations between Chemical/Biological Features and Activity: Associative Classification Mining for Drug Discovery

ERIC Educational Resources Information Center

Yu, Pulan

2012-01-01

Classification, clustering and association mining are major tasks of data mining and have been widely used for knowledge discovery. Associative classification mining, the combination of both association rule mining and classification, has emerged as an indispensable way to support decision making and scientific research. In particular, it offers a…

Mining Quality Phrases from Massive Text Corpora

PubMed Central

Liu, Jialu; Shang, Jingbo; Wang, Chi; Ren, Xiang; Han, Jiawei

2015-01-01

Text data are ubiquitous and play an essential role in big data applications. However, text data are mostly unstructured. Transforming unstructured text into structured units (e.g., semantically meaningful phrases) will substantially reduce semantic ambiguity and enhance the power and efficiency at manipulating such data using database technology. Thus mining quality phrases is a critical research problem in the field of databases. In this paper, we propose a new framework that extracts quality phrases from text corpora integrated with phrasal segmentation. The framework requires only limited training but the quality of phrases so generated is close to human judgment. Moreover, the method is scalable: both computation time and required space grow linearly as corpus size increases. Our experiments on large text corpora demonstrate the quality and efficiency of the new method. PMID:26705375

State-of-the-art study of resource characterization and planning for underground coal mining. Final technical report as of June 30, 1980

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walton, D.; Ingham, W.; Kauffman, P.

With the rapid developments taking place in coal mining technology and due to high investment costs, optimization of the structure of underground coal mines is crucial to the success of the mining project. The structure of a mine, once it is developed, cannot be readily changed and has a decisive influence on the productivity, safety, economics, and production capacity of the mine. The Department of Energy desires to ensure that the resource characterization and planning activity for underground coal mining will focus on those areas that offer the most promise of being advanced. Thus, this project was undertaken by Managementmore » Engineers Incorporated to determine the status in all aspects of the resource characterization and planning activities for underground coal mining as presently performed in the industry. The study team conducted a comprehensive computerized literature search and reviewed the results. From this a selection of the particularly relevant sources were annotated and a reference list was prepared, catalogued by resource characterization and mine planning activity. From this data, and discussions with industry representatives, academia, and research groups, private and federal, an assessment and evaluation was made of the state-of-the-art of each element in the resource characterization and mine planning process. The results of this analysis lead to the identifcation of areas requiring research and, specifically, those areas where DOE research efforts may be focused.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuman, G.E.; Vicklund, L.E.; Belden, S.E.

In 1996, the Wyoming Department of Environmental Quality enacted regulations governing the reestablishment of woody shrubs on mined lands. The regulation required that an average density of one shrub m{sup -2} be reestablished on at least 20% of the disturbed land area and that the shrub composition must include dominant premine species. In Wyoming, and much of the Northern Great Plains, that meant that Artemisia tridentata Nutt. ssp. wyomingensis (Beetle and Young) (Wyoming big sagebrush) had to be reestablished on mined lands. Artemisia tridentata Nutt. ssp. wyomingensis had proven difficult to reestablish on mined lands because of poor quality seed,more » seed dormancy and a poor understanding of the seedbed ecology of this species. Research in the last two decades has produced significant knowledge in the area of direct-seed establishment of Artemisia tridentata Nutt. ssp. wyomingensis on mined lands. Our research has shown that reducing grass seeding rates will reduce competition and result in larger sagebrush plants that are more likely to survive and provide greater structural diversity to the plant community. Economic analyses demonstrated that big sagebrush can be established at a cost of $0.01-0.05 per seedling using direct seeding methods compared to transplanting nursery grown seedlings, estimated to cost $0.72-$1.65 per seedling (depending on size) to grow and from $1.30-$2.40 to plant (flat land to 2:1 slopes). An adequate level of precipitation will be necessary to ensure successful establishment of this species no matter what method of propagation is selected and direct seeding gives greater opportunity for success because of the demonstrated longevity of the seed to germinate 3-5 years after the initial seeding.« less

Trees for strip-mined lands

Treesearch

George Hart; William R. Byrnes

1960-01-01

Open-pit or strip mining has become an important method of mining bituminous coal in Pennsylvania. In 1958 some 19.5 million tons of soft coal - 29 percent of the total bituminous production in the State - were produced by this method.

Detecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach.

PubMed

Lee, Wen-Chung

2014-02-05

The randomized controlled study is the gold-standard research method in biomedicine. In contrast, the validity of a (nonrandomized) observational study is often questioned because of unknown/unmeasured factors, which may have confounding and/or effect-modifying potential. In this paper, the author proposes a perturbation test to detect the bias of unmeasured factors and a perturbation adjustment to correct for such bias. The proposed method circumvents the problem of measuring unknowns by collecting the perturbations of unmeasured factors instead. Specifically, a perturbation is a variable that is readily available (or can be measured easily) and is potentially associated, though perhaps only very weakly, with unmeasured factors. The author conducted extensive computer simulations to provide a proof of concept. Computer simulations show that, as the number of perturbation variables increases from data mining, the power of the perturbation test increased progressively, up to nearly 100%. In addition, after the perturbation adjustment, the bias decreased progressively, down to nearly 0%. The data-mining perturbation analysis described here is recommended for use in detecting and correcting the bias of unmeasured factors in observational studies.

Analysis of occupational health hazards and associated risks in fuzzy environment: a case research in an Indian underground coal mine.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-09-01

This paper presents a unique hierarchical structure on various occupational health hazards including physical, chemical, biological, ergonomic and psychosocial hazards, and associated adverse consequences in relation to an underground coal mine. The study proposes a systematic health hazard risk assessment methodology for estimating extent of hazard risk using three important measuring parameters: consequence of exposure, period of exposure and probability of exposure. An improved decision making method using fuzzy set theory has been attempted herein for converting linguistic data into numeric risk ratings. The concept of 'centre of area' method for generalized triangular fuzzy numbers has been explored to quantify the 'degree of hazard risk' in terms of crisp ratings. Finally, a logical framework for categorizing health hazards into different risk levels has been constructed on the basis of distinguished ranges of evaluated risk ratings (crisp). Subsequently, an action requirement plan has been suggested, which could provide guideline to the managers for successfully managing health hazard risks in the context of underground coal mining exercise.

A field test of electromagnetic geophysical techniques for locating simulated in situ mining leach solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tweeton, D.R.; Hanson, J.C.; Friedel, M.J.

1994-01-01

The US Bureau of Mines, The University of Arizona, Sandia National Laboratories, and Zonge Engineering and Research Organization, Inc., conducted cooperative field tests of six electromagnetic (EM) geophysical methods to compare their effectiveness in locating a brine solution simulating in situ leach solution or a high-conductivity plume of contamination. The brine was approximately 160 m below the surface. The testsite was the University's San Xavier experimental mine near Tucson, AZ. Geophysical surveys using surface and surface-borehole, time-domain electromagnetic (TEM) induction; surface controlled-source audiofrequency magnetotellurics (CSAMT); surface-borehole, frequency-domain electromagnetic (FEM) induction; crosshole FEM; and surface magnetic field ellipticity were conducted beforemore » and during brine injection. The surface TEM data showed a broad decrease in resistivity. CSAMT measurements with the conventional orientation did not detect the brine, but measurements with another orientation indicated some decrease in resistivity. The surface-borehole and crosshole methods located a known fracture and other fracture zones inferred from borehole induction logs. Surface magnetic field ellipticity data showed a broad decrease in resistivity at depth following brine injection.« less

Rockbursting Potential of Kimberlite: A Case Study of Diavik Diamond Mine

NASA Astrophysics Data System (ADS)

Leveille, Paul; Sepehri, Mohammadali; Apel, Derek B.

2017-12-01

The research described in this paper provides information about the rockbursting potential of kimberlite. Kimberlite is a diamond-bearing rock found in deposits around the world including northern Canada. This paper outlines three methods for the prediction of rockbursts based on the properties of a rock. The methods include the: strain energy index, strain energy density, and rock brittleness. Kimberlite samples collected from Diavik, a diamond mine in northern Canada, were tested to define the rock's uniaxial compressive strength, tensile strength, and hysteresis loop. The samples were separated into sub-rock types based on their descriptions from the mine geologists. The results indicate that it is possible to produce rockbursts in kimberlite. It was also observed that the sub-rock types had a range of rockbursting properties. Some types of kimberlite exhibited little to no potential for producing bursts, while other types potentially could produce violent bursts. The diverse nature of kimberlite indicates that the rockbursting properties of the rock should not be generalized and are dependent on the sub-rock type being encountered.

Measuring total mercury due to small-scale gold mining activities to determine community vulnerability in Cihonje, Central Java, Indonesia.

PubMed

Sari, Mega M; Inoue, Takanobu; Matsumoto, Yoshitaka; Yokota, Kuriko

2016-01-01

This research is comparative study of gold mining and non-gold mining areas, using four community vulnerability indicators. Vulnerability indicators are exposure degree, contamination rate, chronic, and acute toxicity. Each indicator used different samples, such as wastewater from gold mining process, river water from Tajum river, human hair samples, and health questionnaire. This research used cold vapor atomic absorption spectrometry to determine total mercury concentration. The result showed that concentration of total mercury was 2,420 times than the maximum content of mercury permitted in wastewater based on the Indonesian regulation. Moreover, the mercury concentration in river water reached 685 ng/l, exceeding the quality threshold standards of the World Health Organization (WHO). The mercury concentration in hair samples obtained from the people living in the research location was considered to identify the health quality level of the people or as a chronic toxicity indicator. The highest mercury concentration--i.e. 17 ng/mg, was found in the gold mining respondents. Therefore, based on the total mercury concentration in the four indicators, the community in the gold mining area were more vulnerable to mercury than communities in non-gold mining areas. It was concluded that the community in gold mining area was more vulnerable to mercury contamination than the community in non-gold mining area.

Mining nonterrestrial resources: Information needs and research topics

NASA Technical Reports Server (NTRS)

Daemen, Jaak J. K.

1992-01-01

An outline of topics we need to understand better in order to apply mining technology to a nonterrestrial environment is presented. The proposed list is not intended to be complete. It aims to identify representative topics that suggest productive research. Such research will reduce the uncertainties associated with extrapolating from conventional earthbound practice to nonterrestrial applications. One objective is to propose projects that should put future discussions of nonterrestrial mining on a firmer, less speculative basis.

Solar Data Mining at Georgia State University

NASA Astrophysics Data System (ADS)

Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.

2016-12-01

In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.

Remediation strategies for historical mining and smelting sites.

PubMed

Dybowska, Agnieszka; Farago, Margaret; Valsami-Jones, Eugenia; Thornton, Iain

2006-01-01

The environmental, social and economic problems associated with abandoned mine sites are serious and global. Environmental damage arising from polluted waters and dispersal of contaminated waste is a feature characteristic of many old mines in North America, Australia, Europe and elsewhere. Today, because of the efficiency of mining operations and legal requirements in many countries for prevention of environmental damage from mining operations, the release of metals to the environment from modern mining is low. However, many mineralized areas that were extensively worked in the 18th and 19th centuries and left abandoned after mining had ceased, have left a legacy of metal contaminated land. Unlike organic chemicals and plastics, metals cannot be degraded chemically or biologically into non-toxic and environmentally neutral constituents. Thus sites contaminated with toxic metals present a particular challenge for remediation. Soil remediation has been the subject of a significant amount of research work in the past decade; this has resulted in a number of remediation options currently available or being developed. Remediation strategies for metal/metalloid contaminated historical mining sites are reviewed and summarized in this article. It focuses on the current applications of in situ remediation with the use of soil amendments (adsorption and precipitation based methods are discussed) and phytoremediation (in situ plant based technology for environmental clean up and restoration). These are promising alternative technologies to traditional options of excavation and ex situ treatment, offering an advantage of being non-invasive and low cost. In particular, they have been shown to be effective in remediation of mining and smelting contaminated sites, although the long-term durability of these treatments cannot be predicted.

The Influence of Surface Coal Mining on Runoff Processes and Stream Chemistry in the Elk Valley, British Colubmbia, Canada

NASA Astrophysics Data System (ADS)

Carey, S. K.; Wellen, C. C.; Shatilla, N. J.

2015-12-01

Surface mining is a common method of accessing coal. In high-elevation environments, vegetation and soils are typically removed prior to the blasting of overburden rock, thereby allowing access to mineable ore. Following this, the removed overburden rock is deposited in adjacent valleys as waste rock spoils. Previous research has identified that areas downstream of surface coal mining have impaired water quality, yet there is limited information about the interaction of hydrology and geochemistry across a range of mining conditions, particularly at the headwater scale. Here, we provide an analysis of an extensive long-term data set of geochemistry and flows across a gradient of coal mining in the Elk Valley, British Columbia, Canada. This work is part of a broader R&D program examining the influence of surface coal mining on hydrological and water quality responses in the Elk Valley aimed at informing effective management responses. Results indicate that water from waste rock piles has an ionic profile distinct from unimpacted catchments. While the concentration of geochemicals increased with the degree of mine impact, the control of hydrological transport capacity over geochemical export did not vary with degree of mine impact. Geochemical export in mine-influenced catchments was limited more strongly by transport capacity than supply, implying that more water moving through the waste rock mobilized more geochemicals. Placement of waste rock within the catchment (headwaters or outlet) did not affect chemical concentrations but did alter the timing with which chemically distinct water mixed. This work advances on results reported earlier using empirical models of selenium loading and further highlights the importance of limiting water inputs into waste rock piles.

Research on parallel algorithm for sequential pattern mining

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Integrating data mining technique and AHP in market analysis to propose new product development in real estate

NASA Astrophysics Data System (ADS)

Yunita; Galinium, M.; Lukas

2017-01-01

New product development in real estate industry is a challenging process since it is related to long term concept and high cost. A newly proposed product development should meet customer need and their preferences which appropriate with customer buying power and company value. This research use data mining for profiling customer transaction and Analytic Hierarchy Process (AHP) method for product selection in new product development. This research utilizes Weka as data mining open source software to profiling data customers. The analysis correlated product preferences and profiling demography such as city, age, gender and occupation. Demography profiles gives description buying power and product preferences. The products proposed are based on customer profiles and rank of the product by AHP method. The product with the highest score will be proposed as new product development. Case studies of this research are real estate projects in Serang, Makassar, and Balikpapan. Makassar and Balikpapan are the project that already gained success and Serang is new project which new products development will be proposed to launch. Based on profiling and product preference of customer in Balikpapan, Makassar, and prospectus of Serang markets, new products development that will be proposed are house type of 120/200 m2 with price around Rp1.300.000.000 and house type of 71/120 m2 with price around Rp800.000.000. The markets of Serang and Balikpapan have similarities in profiles as urban city so the new products development will adopt the succeed story of Balikpapan project.

Big data mining analysis method based on cloud computing

NASA Astrophysics Data System (ADS)

Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao

2017-08-01

Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies.

PubMed

Cohen, Raphael; Elhadad, Michael; Elhadad, Noémie

2013-01-16

The increasing availability of Electronic Health Record (EHR) data and specifically free-text patient notes presents opportunities for phenotype extraction. Text-mining methods in particular can help disease modeling by mapping named-entities mentions to terminologies and clustering semantically related terms. EHR corpora, however, exhibit specific statistical and linguistic characteristics when compared with corpora in the biomedical literature domain. We focus on copy-and-paste redundancy: clinicians typically copy and paste information from previous notes when documenting a current patient encounter. Thus, within a longitudinal patient record, one expects to observe heavy redundancy. In this paper, we ask three research questions: (i) How can redundancy be quantified in large-scale text corpora? (ii) Conventional wisdom is that larger corpora yield better results in text mining. But how does the observed EHR redundancy affect text mining? Does such redundancy introduce a bias that distorts learned models? Or does the redundancy introduce benefits by highlighting stable and important subsets of the corpus? (iii) How can one mitigate the impact of redundancy on text mining? We analyze a large-scale EHR corpus and quantify redundancy both in terms of word and semantic concept repetition. We observe redundancy levels of about 30% and non-standard distribution of both words and concepts. We measure the impact of redundancy on two standard text-mining applications: collocation identification and topic modeling. We compare the results of these methods on synthetic data with controlled levels of redundancy and observe significant performance variation. Finally, we compare two mitigation strategies to avoid redundancy-induced bias: (i) a baseline strategy, keeping only the last note for each patient in the corpus; (ii) removing redundant notes with an efficient fingerprinting-based algorithm. (a)For text mining, preprocessing the EHR corpus with fingerprinting yields significantly better results. Before applying text-mining techniques, one must pay careful attention to the structure of the analyzed corpora. While the importance of data cleaning has been known for low-level text characteristics (e.g., encoding and spelling), high-level and difficult-to-quantify corpus characteristics, such as naturally occurring redundancy, can also hurt text mining. Fingerprinting enables text-mining techniques to leverage available data in the EHR corpus, while avoiding the bias introduced by redundancy.

Testing contamination risk assessment methods for toxic elements from mine waste sites

NASA Astrophysics Data System (ADS)

Abdaal, A.; Jordan, G.; Szilassi, P.; Kiss, J.; Detzky, G.

2012-04-01

Major incidents involving mine waste facilities and poor environmental management practices have left a legacy of thousands of contaminated sites like in the historic mining areas in the Carpathian Basin. Associated environmental risks have triggered the development of new EU environmental legislation to prevent and minimize the effects of such incidents. The Mine Waste Directive requires the risk-based inventory of all mine waste sites in Europe by May 2012. In order to address the mining problems a standard risk-based Pre-selection protocol has been developed by the EU Commission. This paper discusses the heavy metal contamination in acid mine drainage (AMD) for risk assessment (RA) along the Source-Pathway-Receptor chain using decision support methods which are intended to aid national and regional organizations in the inventory and assessment of potentially contaminated mine waste sites. Several recognized methods such as the European Environmental Agency (EEA) standard PRAMS model for soil contamination, US EPA-based AIMSS and Irish HMS-IRC models for RA of abandoned sites are reviewed, compared and tested for the mining waste environment. In total 145 ore mine waste sites have been selected for scientific testing using the EU Pre-selection protocol as a case study from Hungary. The proportion of uncertain to certain responses for a site and for the total number of sites may give an insight of specific and overall uncertainty in the data we use. The Pre-selection questions are efficiently linked to a GIS system as database inquiries using digital spatial data to directly generate answers. Key parameters such as distance to the nearest surface and ground water bodies, to settlements and protected areas are calculated and statistically evaluated using STATGRAPHICS® in order to calibrate the RA models. According to our scientific research results, of the 145 sites 11 sites are the most risky having foundation slope >20o, 57 sites are within distance <500m to the nearest surface water bodies, and 33 sites are within distance <680m to the nearest settlements. Moreover 25 sites lie directly above the 'poor status' ground water bodies and 91 sites are located in the protected Natura2000 sites (distance =0). Analysis of the total score of all sites was performed, resulting in six risk classes, as follows: <21 (class I, 4 sites), 21-31 (class II, 16 sites), 31-42 (class III, 27 sites), 42-54 (class II, 38 sites), 54-66 (class V, 40 sites) and >66 (class VI, 20 sites). The total risk scores and key parameters are provided in separate tables and GIS maps, in order to facilitate interpretation and comparison. Results of the Pre-selection protocol are consistent with those of the screening PRAMS model. KEY WORDS contamination risk assessment, Mine Waste Directive, Pre-selection Protocol, PRA.MS, AIMSS, abandoned mine sites, GIS

Hydro-economic modelling in mining catchments

NASA Astrophysics Data System (ADS)

Ossa Moreno, J. S.; McIntyre, N.; Rivera, D.; Smart, J. C. R.

2017-12-01

Hydro-economic models are gaining momentum because of their capacity to model both the physical processes related to water supply, and socio-economic factors determining water demand. This is particularly valuable in the midst of the large uncertainty upon future climate conditions and social trends. Agriculture, urban uses and environmental flows have received a lot of attention from researchers, as these tend to be the main consumers of water in most catchments. Mine water demand, although very important in several small and medium-sized catchments worldwide, has received less attention and only few models have attempted to reproduce its dynamics with other users. This paper describes an on-going project that addresses this gap, by developing a hydro-economic model in the upper Aconcagua River in Chile. This is a mountain catchment with large scale mining and hydro-power users at high altitudes, and irrigation areas in a downstream valley. Relevant obstacles to the model included the lack of input climate data, which is a common feature in several mining areas, the complex hydrological processes in the area and the difficulty of quantifying the value of water used by mines. A semi-distributed model developed within the Water Evaluation and Planning System (WEAP), was calibrated to reproduce water supply, and this was complemented with an analysis of the value of water for mining based on two methods; water markets and an analysis of its production processes. Agriculture and other users were included through methods commonly used in similar models. The outputs help understanding the value of water in the catchment, and its sensitivity to changes in climate variables, market prices, environmental regulations and changes in the production of minerals, crops and energy. The results of the project highlight the importance of merging hydrology and socio-economic calculations in mining regions, in order to better understand trade-offs and cost of opportunity of using water for an economic activity with high revenues, averse to water risks and with potentially large catchment impacts.

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

ERIC Educational Resources Information Center

Li, Xun

2012-01-01

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

On the development of an underground geoscience laboratory at Boulby in NE England (Invited)

NASA Astrophysics Data System (ADS)

Petley, D. N.; Rosser, N.; Barlow, J.; Brain, M. J.; Lim, M.; Sapsford, M.; Pybus, D.

2009-12-01

The Boulby Mine in NE England is a major potash extraction facility located in NE England. Opened in 1973, the mine extracts both potash and rock salt from Zechstein deposits located at a depth of about 1100 m below the land surface. For the last 20 years the mine has housed an important laboratory built to provide a base for Dark Matter research. However, in the last ten years the mine has progressively become been the site of research into geophysical and geological processes, primarily through a strategic partnership between the mine operators, Cleveland Potash Ltd, and the University of Durham. The site is now the base for an initial proof of concept project, funded by the Regional Development Agency One Northeast, to explore the viability of establishing a permanent geosciences research facility at Boulby. The vision is a facility that provides access for researchers into the range of geological environments at Boulby, extending from the coastal cliffs at the surface, through the access shafts to the deepest potash seams. The facility is designed to host research in geophysics, hydrology, geophysics, geomorphology, geochemistry, microbiology, rock mechanics, mining engineering, petrology and related fields. This proof of concept study has three key strategic aims: 1. To establish the range of uses of a research laboratory at Boulby and to determine the nature of the facilities required; 2. To initiate research programmes into: a. palaeoenvironmental reconstruction of the Zechstein deposits; b. the mechanics of the potash and halite rocks; and c. the mechanisms of failure of the coastal cliffs; 3. To construct an initial four serviced research caverns within the mine. The proof of concept stage of the project is intended to run until September 2010, with development of the facility being completed by 2015. However, the facility is currently in a position to host research projects across a wide range of disciplines.

Proceedings of the International Conference on Educational Data Mining (EDM) (6th, Memphis, TN., USA, July 6-9, 2013)

ERIC Educational Resources Information Center

D'Mello, S. K., Ed.; Calvo, R. A., Ed.; Olney, A., Ed.

2013-01-01

Since its inception in 2008, the Educational Data Mining (EDM) conference series has featured some of the most innovative and fascinating basic and applied research centered on data mining, education, and learning technologies. This tradition of exemplary interdisciplinary research has been kept alive in 2013 as evident through an imaginative,…

Shale Failure Mechanics and Intervention Measures in Underground Coal Mines: Results From 50 Years of Ground Control Safety Research

PubMed Central

2015-01-01

Ground control research in underground coal mines has been ongoing for over 50 years. One of the most problematic issues in underground coal mines is roof failures associated with weak shale. This paper will present a historical narrative on the research the National Institute for Occupational Safety and Health has conducted in relation to rock mechanics and shale. This paper begins by first discussing how shale is classified in relation to coal mining. Characterizing and planning for weak roof sequences is an important step in developing an engineering solution to prevent roof failures. Next, the failure mechanics associated with the weak characteristics of shale will be discussed. Understanding these failure mechanics also aids in applying the correct engineering solutions. The various solutions that have been implemented in the underground coal mining industry to control the different modes of failure will be summarized. Finally, a discussion on current and future research relating to rock mechanics and shale is presented. The overall goal of the paper is to share the collective ground control experience of controlling roof structures dominated by shale rock in underground coal mining. PMID:26549926

Shale Failure Mechanics and Intervention Measures in Underground Coal Mines: Results From 50 Years of Ground Control Safety Research.

PubMed

Murphy, M M

2016-02-01

Ground control research in underground coal mines has been ongoing for over 50 years. One of the most problematic issues in underground coal mines is roof failures associated with weak shale. This paper will present a historical narrative on the research the National Institute for Occupational Safety and Health has conducted in relation to rock mechanics and shale. This paper begins by first discussing how shale is classified in relation to coal mining. Characterizing and planning for weak roof sequences is an important step in developing an engineering solution to prevent roof failures. Next, the failure mechanics associated with the weak characteristics of shale will be discussed. Understanding these failure mechanics also aids in applying the correct engineering solutions. The various solutions that have been implemented in the underground coal mining industry to control the different modes of failure will be summarized. Finally, a discussion on current and future research relating to rock mechanics and shale is presented. The overall goal of the paper is to share the collective ground control experience of controlling roof structures dominated by shale rock in underground coal mining.

Shale Failure Mechanics and Intervention Measures in Underground Coal Mines: Results From 50 Years of Ground Control Safety Research

NASA Astrophysics Data System (ADS)

Murphy, M. M.

2016-02-01

Ground control research in underground coal mines has been ongoing for over 50 years. One of the most problematic issues in underground coal mines is roof failures associated with weak shale. This paper will present a historical narrative on the research the National Institute for Occupational Safety and Health has conducted in relation to rock mechanics and shale. This paper begins by first discussing how shale is classified in relation to coal mining. Characterizing and planning for weak roof sequences is an important step in developing an engineering solution to prevent roof failures. Next, the failure mechanics associated with the weak characteristics of shale will be discussed. Understanding these failure mechanics also aids in applying the correct engineering solutions. The various solutions that have been implemented in the underground coal mining industry to control the different modes of failure will be summarized. Finally, a discussion on current and future research relating to rock mechanics and shale is presented. The overall goal of the paper is to share the collective ground control experience of controlling roof structures dominated by shale rock in underground coal mining.

A Survey of Educational Data-Mining Research

ERIC Educational Resources Information Center

Huebner, Richard A.

2013-01-01

Educational data mining (EDM) is an emerging discipline that focuses on applying data mining tools and techniques to educationally related data. The discipline focuses on analyzing educational data to develop models for improving learning experiences and improving institutional effectiveness. A literature review on educational data mining topics…

Data mining for clustering naming of the village at Java Island

NASA Astrophysics Data System (ADS)

Setiawan Abdullah, Atje; Nurani Ruchjana, Budi; Hidayat, Akik; Akmal; Setiana, Deni

2017-10-01

Clustering of query based data mining to identify the meaning of the naming of the village in Java island, done by exploring the database village with three categories namely: prefix in the naming of the village, syllables contained in the naming of the village, and full word naming of the village which is actually used. While syllables contained in the naming of the village are classified by the behaviour of the culture and character of each province that describes the business, feelings, circumstances, places, nature, respect, plants, fruits, and animals. Sources of data used for the clustering of the naming of the village on the island of Java was obtained from Geospatial Information Agency (BIG) in the form of a complete village name data with the coordinates in six provinces in Java, which is arranged in a hierarchy of provinces, districts / cities, districts and villages. The research method using KDD (Knowledge Discovery in Database) through the process of preprocessing, data mining and postprocessing to obtain knowledge. In this study, data mining applications to facilitate the search query based on the name of the village, using Java software. While the contours of a map is processed using ArcGIS software. The results of the research can give recommendations to stakeholders such as the Department of Tourism to describe the meaning of the classification of naming the village according to the character in each province at Java island.

Mine safety assessment using gray relational analysis and bow tie model

PubMed Central

2018-01-01

Mine safety assessment is a precondition for ensuring orderly and safety in production. The main purpose of this study was to prevent mine accidents more effectively by proposing a composite risk analysis model. First, the weights of the assessment indicators were determined by the revised integrated weight method, in which the objective weights were determined by a variation coefficient method and the subjective weights determined by the Delphi method. A new formula was then adopted to calculate the integrated weights based on the subjective and objective weights. Second, after the assessment indicator weights were determined, gray relational analysis was used to evaluate the safety of mine enterprises. Mine enterprise safety was ranked according to the gray relational degree, and weak links of mine safety practices identified based on gray relational analysis. Third, to validate the revised integrated weight method adopted in the process of gray relational analysis, the fuzzy evaluation method was used to the safety assessment of mine enterprises. Fourth, for first time, bow tie model was adopted to identify the causes and consequences of weak links and allow corresponding safety measures to be taken to guarantee the mine’s safe production. A case study of mine safety assessment was presented to demonstrate the effectiveness and rationality of the proposed composite risk analysis model, which can be applied to other related industries for safety evaluation. PMID:29561875

MINING METHODS AND COSTS, CALYX NOS. 3 AND 8 URANIUM MINES, TEMPLE MOUNTAIN DISTRICT, EMERY COUNTY, UTAH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dare, W.L.

1957-04-01

Descriptions are given of the Calyx No. 3 mine operated by American Reduc Uranium Corp. and Calyx No. 8 operated by Cline Co. The deposits are composed of numerous small, irregular bodies and are worked through 36 inch Calyx drill holes. The U--V ores are concentrated chiefly in the lower 30 feet of the Moss Back sandstone. In general it follows the strnta. The mine is worked by open stoping with random pillar support. The operations and mining practices of these two mines are very similar and typify the mining methods and practioes used by many small U producers onmore » the Colorado Plateau. (R.V.J.)« less

An evaluation of problems arising from acid mine drainage in the vicinity of Shasta Lake, Shasta County, California

USGS Publications Warehouse

Fuller, Richard H.; Shay, J.M.; Ferreira, R.F.; Hoffman, R.J.

1978-01-01

Streams draining the mined areas of massive sulfide ore deposits in the Shasta Mining Districts of northern California are generally acidic and contain large concentrations of dissolved metals, including iron, copper, and zinc. The streams, including Flat, Little Backbone, Spring, West Squaw, Horse, and Zinc Creeks, discharge into Shasta Reservoir and the Sacramento River and have caused numerous fish kills. The sources of pollution are discharge from underground mines, streams that flow into open pits, and streams that flow through pyritic mine dumps where the oxidation of pyrite and other sulfide minerals results in the production of acid and the mobilization of metals. Suggested methods of treatment include the use of air and hydraulic seals in the mines, lime neutralization of mine effluent, channeling of runoff and mine effluent away from mine and tailing areas, and the grading and sealing of mine dumps. A comprehensive preabatement and postabatement program is recommended to evaluate the effects of any treatment method used. (Woodard-USGS)

Causes Of Low Efficiency Of Combined Ventilation System In Coal Mines In Resolving The Problem Of Air Leaks (Inflows) Between Levels And Surface

NASA Astrophysics Data System (ADS)

Popov, Valeriy; Filatov, Yuriy; Lee, Hee; Golik, Anatoliy

2017-11-01

The paper discusses the problem of the underground mining safety control. The long-term air intake to coal accumulations is reviewed as one of the reasons of endogenous fires during mining. The methods of combating air leaks (inflows) in order to prevent endogenous fires are analyzed. The calculations showing the discrepancy between the design calculations for the mine ventilation, disregarding a number of mining-andgeological and mining-engineering factors, and the actual conditions of mining are given. It is proved that the conversion of operating mines to combined (pressure and exhaust) ventilation system in order to reduce the endogenous fire hazard of underground mining is unreasonable due to impossibility of providing an optimal distribution of aerodynamic pressure in mines. The conversion does not exclude the entry of air into potentially hazardous zones of endogenous fires. The essence of the combined application of positive and negative control methods for the distribution of air pressure is revealed. It consists of air doors installation in easily ventilated airways and installation of pressure equalization chambers equipped with auxiliary fans near the stoppings, working sections and in parallel airways.The effectiveness of the combined application of negative and positive control methods for the air pressure distribution in order to reduce endogenous fire hazard of mining operations is proved.

Mining research: the respective roles of government and private institutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyd, J.

1978-01-01

The extractive industries in the U.S. in 1975 produced only 4.2% of the GNP; yet, 18% of the economy is engaged directly in processing or in converting these minerals into usable forms. None of the remaining portions of the economy can perform without products of the extractive industries. Mr. Boyd delineates and explains the respective roles of the mining industry, the mining-machinery industry, the Federal government, and those research institutions engaged in mining or related research. He further examines the views of the various segments of the mining and minerals community, outlines the major issues involved, and arrives at conclusionsmore » tempered by his long and diversified experience in the field. Emphasis is placed on the activities of the Bureau of Mines (BuM). The main finding of the study is that the government as a whole must recognize that mining research is essential, and be prepared to adjust it's financial and organizational structure accordingly. Emphasis must be directed away from compliance with detailed regulations, which become obsolete very quickly, to education and cooperation. The BuM cannot do this itself. The matter is of such basic importance to the nation, and involves so many diverse jurisdictions, as to require attention from the highest levels of the Executive Branch and several committees of the Congress. (MCW)« less

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

Application of text mining in the biomedical domain.

PubMed

Fleuren, Wilco W M; Alkema, Wynand

2015-03-01

In recent years the amount of experimental data that is produced in biomedical research and the number of papers that are being published in this field have grown rapidly. In order to keep up to date with developments in their field of interest and to interpret the outcome of experiments in light of all available literature, researchers turn more and more to the use of automated literature mining. As a consequence, text mining tools have evolved considerably in number and quality and nowadays can be used to address a variety of research questions ranging from de novo drug target discovery to enhanced biological interpretation of the results from high throughput experiments. In this paper we introduce the most important techniques that are used for a text mining and give an overview of the text mining tools that are currently being used and the type of problems they are typically applied for. Copyright © 2015 Elsevier Inc. All rights reserved.

Association Rule Mining from an Intelligent Tutor

ERIC Educational Resources Information Center

Dogan, Buket; Camurcu, A. Yilmaz

2008-01-01

Educational data mining is a very novel research area, offering fertile ground for many interesting data mining applications. Educational data mining can extract useful information from educational activities for better understanding and assessment of the student learning process. In this way, it is possible to explore how students learn topics in…

30 CFR 90.3 - Part 90 option; notice of eligibility; exercise of option.

Code of Federal Regulations, 2014 CFR

2014-07-01

... as measured by the Mining Research Establishment (MRE) instrument. When the approved sampling device... concentrations. Mechanized mining unit (MMU). A unit of mining equipment including hand loading equipment used for the production of material; or a specialized unit which uses mining equipment other than specified...

Efficacy Evaluation of Current and Future Naval Mine Warfare Neutralization Method

DTIC Science & Technology

2016-12-01

Distribution is unlimited. EFFICACY EVALUATION OF CURRENT AND FUTURE NAVAL MINE WARFARE NEUTRALIZATION METHOD by Team MIW Cohort SE311-152O...EFFICACY EVALUATION OF CURRENT AND FUTURE NAVAL MINE WARFARE NEUTRALIZATION METHOD 5. FUNDING NUMBERS 6. AUTHOR (S) Team MIW, Systems Engineering...NEUTRALIZATION METHOD Team MIW, Systems Engineering Cohort SE311-152O Submitted in partial fulfillment of the requirements for the degrees of

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Mapping of the dilemma of mining against forest and conservation in the Lom and Djérem Division, Cameroon

NASA Astrophysics Data System (ADS)

Tchindjang, Mesmin; Voundi, Eric; Mbevo Fendoung, Philippes; Haman, Unusa; Saha, Frédéric; Casimir Njombissie Petcheu, Igor

2018-05-01

Mining practices in Cameroon began since the colonial period. The artisanal mining sector before independence contributed to 11-20 % of GDP. From 2000, the rich potential of the Cameroonian subsoil attract many foreign investors with over 600 research and mining permits already granted during the last decade. But, Cameroonian forests also have a long history from the colonial period to the pre-sent. However, mining activities in forest environments are governed by two different legal frameworks, including mining code i.e. Law No. 001 of 16 April 2001 organizing the mining industry and Law No. 94-01 of 20 January 1994 governing forests, wildlife and fisheries. Therefore, in the absence of detailed studies of these laws, there are conflicts of interests, rights and obligations that overlap, requiring research needs and taking appropriate decisions. The objective of this research in the Lom and Djérem division is to study, apart from the proliferation of mining li-censes and actors, the dilemma as well as the impact of the extension of mining activities on the degradation of forest cover. Using geospatial tools through multi-temporal and multisensor satellite images (Landsat from 1976 to 2015, IKONOS, GEOEYE, Google Earth) coupled with field investigations; we mapped the dynamic of different forms of land use (mining permits, FMU and protected areas of permanent forest estate) and highlighted paradoxically the conflict of land use. We came to the conclusion that the rhythm of issuing mining permits and authorizations in this forestall zone is so fast that one can wonder whether we still find a patch of forest within 50 years.

Effects of granularity on the natural classification of loose cover layer rock

NASA Astrophysics Data System (ADS)

Zhang, Shuhui; Wang, Peng; Zhang, Zhiqiang

2018-03-01

In the sublevel caving method, with developing depth of underground mines increasing, the ore loss and dilution is become more and more remarkable that is due to the natural classification of loose cover layer rock. Therefore, this paper researches that granularity are one of the main factors affecting the natural classification, and carries out a physical simulation experiment of loose cover layer rock granularity effects of natural classification. Through the experiment we found that granularity has important effect on natural classification. Under the condition of the same weight, we found the closer of granularities that consist of cover layer rock, the less prone to natural classification. Otherwise, it will be prone to natural classification. This study has a guiding significance for a mine, forming a scientific and reasonable cover layer rock, and reducing the ore loss and dilution in the mining process.

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

Effects of abandoned arsenic mine on water resources pollution in north west of iran.

PubMed

Hajalilou, Behzad; Mosaferi, Mohammad; Khaleghi, Fazel; Jadidi, Sakineh; Vosugh, Bahram; Fatehifar, Esmail

2011-01-01

Pollution due to mining activities could have an important role in health and welfare of people who are living in mining area. When mining operation finishes, environ-ment of mining area can be influenced by related pollution e.g. heavy metals emission to wa-ter resources. The present study was aimed to evaluate Valiloo abandoned arsenic mine ef-fects on drinking water resources quality and possible health effects on the residents of min-ing area in the North West of Iran. Water samples and some limited composite wheat samples in downstream of min-ing area were collected. Water samples were analyzed for chemical parameters according to standard methods. For determination of arsenic in water samples, Graphite Furnace Atomic Absorption Spectrometric Method (GFAAS) and for wheat samples X - Ray Fluorescence (XRF) and Inductively Coupled Plasma Method (ICP) were used. Information about possible health effects due to exposure to arsenic was collected through interviews in studied villages and health center of Herris City. The highest concentrations of arsenic were measured near the mine (as high as 2000 µg/L in Valiloo mine opening water). With increasing distance from the mine, concentration was decreased. Arsenic was not detectable in any of wheat samples. Fortunately, no health effects had been reported between residents of studied area due to exposure to arsenic. Valiloo abandoned arsenic mine has caused release of arsenic to the around en-vironment of the mine, so arsenic concentration has been increased in the groundwater and also downstream river that requires proper measures to mitigate spread of arsenic.

Exploration of the association rules mining technique for the signal detection of adverse drug events in spontaneous reporting systems.

PubMed

Wang, Chao; Guo, Xiao-Jing; Xu, Jin-Fang; Wu, Cheng; Sun, Ya-Lin; Ye, Xiao-Fei; Qian, Wei; Ma, Xiu-Qiang; Du, Wen-Min; He, Jia

2012-01-01

The detection of signals of adverse drug events (ADEs) has increased because of the use of data mining algorithms in spontaneous reporting systems (SRSs). However, different data mining algorithms have different traits and conditions for application. The objective of our study was to explore the application of association rule (AR) mining in ADE signal detection and to compare its performance with that of other algorithms. Monte Carlo simulation was applied to generate drug-ADE reports randomly according to the characteristics of SRS datasets. Thousand simulated datasets were mined by AR and other algorithms. On average, 108,337 reports were generated by the Monte Carlo simulation. Based on the predefined criterion that 10% of the drug-ADE combinations were true signals, with RR equaling to 10, 4.9, 1.5, and 1.2, AR detected, on average, 284 suspected associations with a minimum support of 3 and a minimum lift of 1.2. The area under the receiver operating characteristic (ROC) curve of the AR was 0.788, which was equivalent to that shown for other algorithms. Additionally, AR was applied to reports submitted to the Shanghai SRS in 2009. Five hundred seventy combinations were detected using AR from 24,297 SRS reports, and they were compared with recognized ADEs identified by clinical experts and various other sources. AR appears to be an effective method for ADE signal detection, both in simulated and real SRS datasets. The limitations of this method exposed in our study, i.e., a non-uniform thresholds setting and redundant rules, require further research.

Differentially Private Frequent Subgraph Mining

PubMed Central

Xu, Shengzhi; Xiong, Li; Cheng, Xiang; Xiao, Ke

2016-01-01

Mining frequent subgraphs from a collection of input graphs is an important topic in data mining research. However, if the input graphs contain sensitive information, releasing frequent subgraphs may pose considerable threats to individual's privacy. In this paper, we study the problem of frequent subgraph mining (FGM) under the rigorous differential privacy model. We introduce a novel differentially private FGM algorithm, which is referred to as DFG. In this algorithm, we first privately identify frequent subgraphs from input graphs, and then compute the noisy support of each identified frequent subgraph. In particular, to privately identify frequent subgraphs, we present a frequent subgraph identification approach which can improve the utility of frequent subgraph identifications through candidates pruning. Moreover, to compute the noisy support of each identified frequent subgraph, we devise a lattice-based noisy support derivation approach, where a series of methods has been proposed to improve the accuracy of the noisy supports. Through formal privacy analysis, we prove that our DFG algorithm satisfies ε-differential privacy. Extensive experimental results on real datasets show that the DFG algorithm can privately find frequent subgraphs with high data utility. PMID:27616876

Unsupervised User Similarity Mining in GSM Sensor Networks

PubMed Central

Shad, Shafqat Ali; Chen, Enhong

2013-01-01

Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analysis, where mobility profile building is done through significant places extraction, user's actual movement prediction, and context awareness. However, significant places extraction and user's actual movement prediction for mobility profile building are a trivial task. In this paper, we present the user similarity mining-based methodology through user mobility profile building by using the semantic tagging information provided by user and basic GSM network architecture properties based on unsupervised clustering approach. As the mobility information is in low-level raw form, our proposed methodology successfully converts it to a high-level meaningful information by using the cell-Id location information rather than previously used location capturing methods like GPS, Infrared, and Wifi for profile mining and user similarity mining. PMID:23576905

Data Processing and Text Mining Technologies on Electronic Medical Records: A Review

PubMed Central

Sun, Wencheng; Li, Yangyang; Liu, Fang; Fang, Shengqun; Wang, Guoyan

2018-01-01

Currently, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed, and treatment results. EMR has been recognized as a valuable resource for large-scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy, and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation, and data reduction. For semistructured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (named-entity recognition) and RE (relation extraction). This paper focuses on the process of EMR processing and emphatically analyzes the key techniques. In addition, we make an in-depth study on the applications developed based on text mining together with the open challenges and research issues for future work. PMID:29849998

A hybrid feature selection method using multiclass SVM for diagnosis of erythemato-squamous disease

NASA Astrophysics Data System (ADS)

Maryam, Setiawan, Noor Akhmad; Wahyunggoro, Oyas

2017-08-01

The diagnosis of erythemato-squamous disease is a complex problem and difficult to detect in dermatology. Besides that, it is a major cause of skin cancer. Data mining implementation in the medical field helps expert to diagnose precisely, accurately, and inexpensively. In this research, we use data mining technique to developed a diagnosis model based on multiclass SVM with a novel hybrid feature selection method to diagnose erythemato-squamous disease. Our hybrid feature selection method, named ChiGA (Chi Square and Genetic Algorithm), uses the advantages from filter and wrapper methods to select the optimal feature subset from original feature. Chi square used as filter method to remove redundant features and GA as wrapper method to select the ideal feature subset with SVM used as classifier. Experiment performed with 10 fold cross validation on erythemato-squamous diseases dataset taken from University of California Irvine (UCI) machine learning database. The experimental result shows that the proposed model based multiclass SVM with Chi Square and GA can give an optimum feature subset. There are 18 optimum features with 99.18% accuracy.

Influence of the Roof Movement Control Method on the Stability of Remnant

NASA Astrophysics Data System (ADS)

Adach-Pawelus, Karolina

2017-12-01

In the underground mines, there are geological and mining situations that necessitate leaving behind remnants in the mining field. Remnants, in the form of small, irregular parcels, are usually separated in the case of: significant problems with maintaining roof stability, high rockburst hazard, the occurrence of complex geological conditions and for random reasons (ore remnants), as well as for economic reasons (undisturbed rock remnants). Remnants left in the mining field become sites of high stress values concentration and may affect the rock in their vicinity. The values of stress inside the remnant and its vicinity, as well as the stability of the remnant, largely depend on the roof movement control method used in the mining field. The article presents the results of the numerical analysis of the influence of roof movement control method on remnant stability and the geomechanical situation in the mining field. The numerical analysis was conducted for the geological and mining conditions characteristic of Polish underground copper mines owned by KGHM Polska Miedz S.A. Numerical simulations were performed in a plane strain state by means of Phase 2 v. 8.0 software, based on the finite element method. The behaviour of remnant and rock mass in its vicinity was simulated in the subsequent steps of the room and pillar mining system for three types of roof movement control method: roof deflection, dry backfill and hydraulic backfill. The parameters of the rock mass accepted for numerical modelling were calculated by means of RocLab software on the basis of the Hoek-Brown classification. The Mohr-Coulomb strength criterion was applied.

Text mining for traditional Chinese medical knowledge discovery: a survey.

PubMed

Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

2010-08-01

Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

Functional evaluation of out-of-the-box text-mining tools for data-mining tasks.

PubMed

Jung, Kenneth; LePendu, Paea; Iyer, Srinivasan; Bauer-Mehren, Anna; Percha, Bethany; Shah, Nigam H

2015-01-01

The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. In this paper, we quantify this trade-off among text processing systems that make different trade-offs between speed and linguistic understanding. We tested both types of systems in three clinical research tasks: phase IV safety profiling of a drug, learning adverse drug-drug interactions, and learning used-to-treat relationships between drugs and indications. We first benchmarked the accuracy of the NCBO Annotator and REVEAL in a manually annotated, publically available dataset from the 2008 i2b2 Obesity Challenge. We then applied the NCBO Annotator and REVEAL to 9 million clinical notes from the Stanford Translational Research Integrated Database Environment (STRIDE) and used the resulting data for three research tasks. There is no significant difference between using the NCBO Annotator and REVEAL in the results of the three research tasks when using large datasets. In one subtask, REVEAL achieved higher sensitivity with smaller datasets. For a variety of tasks, employing simple term recognition methods instead of advanced NLP methods results in little or no impact on accuracy when using large datasets. Simpler dictionary-based methods have the advantage of scaling well to very large datasets. Promoting the use of simple, dictionary-based methods for population level analyses can advance adoption of NLP in practice. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Macromolecule mass spectrometry: citation mining of user documents.

PubMed

Kostoff, Ronald N; Bedford, Clifford D; del Río, J Antonio; Cortes, Héctor D; Karypis, George

2004-03-01

Identifying research users, applications, and impact is important for research performers, managers, evaluators, and sponsors. Identification of the user audience and the research impact is complex and time consuming due to the many indirect pathways through which fundamental research can impact applications. This paper identified the literature pathways through which two highly-cited papers of 2002 Chemistry Nobel Laureates Fenn and Tanaka impacted research, technology development, and applications. Citation Mining, an integration of citation bibliometrics and text mining, was applied to the >1600 first generation Science Citation Index (SCI) citing papers to Fenn's 1989 Science paper on Electrospray Ionization for Mass Spectrometry, and to the >400 first generation SCI citing papers to Tanaka's 1988 Rapid Communications in Mass Spectrometry paper on Laser Ionization Time-of-Flight Mass Spectrometry. Bibliometrics was performed on the citing papers to profile the user characteristics. Text mining was performed on the citing papers to identify the technical areas impacted by the research, and the relationships among these technical areas.

Challenges in recovering resources from acid mine drainage

USGS Publications Warehouse

Nordstrom, D. Kirk; Bowell, Robert J.; Campbell, Kate M.; Alpers, Charles N.

2017-01-01

Metal recovery from mine waters and effluents is not a new approach but one that has occurred largely opportunistically over the last four millennia. Due to the need for low-cost resources and increasingly stringent environmental conditions, mine waters are being considered in a fresh light with a designed, deliberate approach to resource recovery often as part of a larger water treatment evaluation. Mine water chemistry is highly dependent on many factors including geology, ore deposit composition and mineralogy, mining methods, climate, site hydrology, and others. Mine waters are typically Ca-Mg-SO4±Al±Fe with a broad range in pH and metal content. The main issue in recovering components of these waters having potential economic value, such as base metals or rare earth elements, is the separation of these from more reactive metals such as Fe and Al. Broad categories of methods for separating and extracting substances from acidic mine drainage are chemical and biological. Chemical methods include solution, physicochemical, and electrochemical technologies. Advances in membrane techniques such as reverse osmosis have been substantial and the technique is both physical and chemical. Biological methods may be further divided into microbiological and macrobiological, but only the former is considered here as a recovery method, as the latter is typically used as a passive form of water treatment.

A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.

PubMed

Shimazaki, Kei-ichi; Kushida, Tatsuya

2010-06-01

Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the "analysis paralysis" associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.

Text mining patents for biomedical knowledge.

PubMed

Rodriguez-Esteban, Raul; Bundschus, Markus

2016-06-01

Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

42 CFR 84.3 - Respirators for mine rescue or other emergency use in mines.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 1 2014-10-01 2014-10-01 false Respirators for mine rescue or other emergency use in mines. 84.3 Section 84.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES APPROVAL OF RESPIRATORY PROTECTIVE...

42 CFR 84.3 - Respirators for mine rescue or other emergency use in mines.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 1 2010-10-01 2010-10-01 false Respirators for mine rescue or other emergency use in mines. 84.3 Section 84.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES APPROVAL OF RESPIRATORY PROTECTIVE...

42 CFR 84.3 - Respirators for mine rescue or other emergency use in mines.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 1 2013-10-01 2013-10-01 false Respirators for mine rescue or other emergency use in mines. 84.3 Section 84.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES APPROVAL OF RESPIRATORY PROTECTIVE...

42 CFR 84.3 - Respirators for mine rescue or other emergency use in mines.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 42 Public Health 1 2012-10-01 2012-10-01 false Respirators for mine rescue or other emergency use in mines. 84.3 Section 84.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES APPROVAL OF RESPIRATORY PROTECTIVE...

42 CFR 84.3 - Respirators for mine rescue or other emergency use in mines.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 1 2011-10-01 2011-10-01 false Respirators for mine rescue or other emergency use in mines. 84.3 Section 84.3 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES APPROVAL OF RESPIRATORY PROTECTIVE...

Distributed communications and control network for robotic mining

NASA Technical Reports Server (NTRS)

Schiffbauer, William H.

1989-01-01

The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.

Comparsion analysis of data mining models applied to clinical research in traditional Chinese medicine.

PubMed

Zhao, Yufeng; Xie, Qi; He, Liyun; Liu, Baoyan; Li, Kun; Zhang, Xiang; Bai, Wenjing; Luo, Lin; Jing, Xianghong; Huo, Ruili

2014-10-01

To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine (TCM) diagnosis and therapy. Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy. Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes. The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared. By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

Reinventing the U.S. Bureau of Mines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, R.L.

1995-10-01

The changes in the US Bureau of Mines (USBM) are discussed. Beginning this year, the Bureau will focus its scientific research efforts in four critical areas. These areas are: (1) health and safety; (2) materials research (which will be accomplished in partnership with the private sector); (3) environmental remediation; and (4) pollution prevention and control. In addition to the very important scientific research that is going on, the US Bureau of Mines: collects and publishes consumption and supply data and information on 100 commodities for the 60 most important mineral producing, consuming and trading countries; and analyzes minerals related issues,more » such as proposed mining law reform legislation and proposed mine waste regulations, and assists in federal ecosystem planning efforts. On December 30, 1994, Secretary Babbitt signed a secretarial order implementing an organizational structure to allow the USBM to go forward in this new research focus. In Fiscal Year 1995, Congress appropriated funds to the USBM to focus research in this organizational structure. The USBM has experienced major funding reductions in the Clinton Administration. The whole Federal government is getting smaller. The USBM workforce is comparable in size to what it was three decades ago.« less

North American Bats and Mines Project: A cooperative approach for integrating bat conservation and mine-land reclamation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ducummon, S.L.

Inactive underground mines now provide essential habitat for more than half of North America`s 44 bat species, including some of the largest remaining populations. Thousands of abandoned mines have already been closed or are slated for safety closures, and many are destroyed during renewed mining in historic districts. The available evidence suggests that millions of bats have already been lost due to these closures. Bats are primary predators of night-flying insects that cost American farmers and foresters billions of dollars annually, therefore, threats to bat survival are cause for serious concern. Fortunately, mine closure methods exist that protect both batsmore » and humans. Bat Conservation International (BCI) and the USDI-Bureau of Land Management founded the North American Bats and Mines Project to provide national leadership and coordination to minimize the loss of mine-roosting bats. This partnership has involved federal and state mine-land and wildlife managers and the mining industry. BCI has trained hundreds of mine-land and wildlife managers nationwide in mine assessment techniques for bats and bat-compatible closure methods, published technical information on bats and mine-land management, presented papers on bats and mines at national mining and wildlife conferences, and collaborated with numerous federal, state, and private partners to protect some of the most important mine-roosting bat populations. Our new mining industry initiative, Mining for Habitat, is designed to develop bat habitat conservation and enhancement plans for active mining operations. It includes the creation of cost-effective artificial underground bat roosts using surplus mining materials such as old mine-truck tires and culverts buried beneath waste rock.« less

Landfill mining: Case study of a successful metals recovery project.

PubMed

Wagner, Travis P; Raymond, Tom

2015-11-01

Worldwide, the generation of municipal solid waste (MSW) is increasing and landfills continue to be the dominant method for managing solid waste. Because of inadequate diversion of reusable and recoverable materials, MSW landfills continue to receive significant quantities of recyclable materials, especially metals. The economic value of landfilled metals is significant, fostering interest worldwide in recovering the landfilled metals through mining. However, economically viable landfill mining for metals has been elusive due to multiple barriers including technological challenges and high costs of processing waste. The objective of this article is to present a case study of an economically successful landfill mining operation specifically to recover metals. The mining operation was at an ashfill, which serves a MSW waste-to-energy facility. Landfill mining operations began in November 2011. Between December 2011 and March 2015, 34,352 Mt of ferrous and non-ferrous metals were recovered and shipped for recycling, which consisted of metals >125 mm (5.2%), 50-125 mm (85.9%), <50mm (3.4%), zorba (4.6%), and mixed products (0.8%). The conservative estimated value of the recovered metal was $7.42 million. Mining also increased the landfill's airspace by 10,194 m(3) extending the life of the ashfill with an estimated economic value of $267,000. The estimated per-Mt cost for the extraction of metal was $158. This case study demonstrates that ashfills can be profitably mined for metals without financial support from government. Although there are comparatively few ashfills, the results and experience obtained from this case study can help foster further research into the potential recovery of metals from raw, landfilled MSW. Copyright © 2015 Elsevier Ltd. All rights reserved.

Allegheny woodrat (Neotoma magister) use of rock drainage channels on reclaimed mines in southern West Virginia

USGS Publications Warehouse

Chamblin, H.D.; Wood, P.B.; Edwards, J.W.

2004-01-01

Allegheny woodrats (Neotoma magister) currently receive protected status throughout their range due to population declines. Threats associated with habitat fragmentation (e.g., introduced predators, disease, loss of connectivity among subpopulations and habitat loss) may explain why Allegheny woodrats are no longer found in many areas where they existed just 25 y ago. In southern West Virginia, surface coal mining is a major cause of forest fragmentation. Furthermore, mountaintop mining, the prevalent method in the region, results in a loss of rock outcrops and cliffs within forested areas, typical habitat of the Allegheny woodrat To determine the extent that Allegheny woodrats make use of reclaimed mine land, particularly rock drainages built during reclamation, we sampled 24 drainage channels on reclaimed surface mines in southern West Virginia, collected habitat data at each site and used logistic regression to identify habitat variables related to Allegheny woodrat presence. During 187 trap nights, 13 adult, 2 subadult and 8 juvenile Allegheny woodrats were captured at 13 of the 24 sites. Percent of rock as a groundcover and density of stems >15 cm diameter-at-breast-height (DBH) were related to Allegheny woodrat presence and were significantly greater at sites where Allegheny woodrats were present than absent. Sites where Allegheny woodrats were present differed substantially from other described habitats in West Virginia, though they may simulate boulder piles that occur naturally. Our findings suggest the need for additional research to examine the dynamics between Allegheny woodrat populations inhabiting rock outcrops in forests adjacent to mines and populations inhabiting constructed drainage channels on reclaimed mines. However, if Allegheny woodrats can use human-created habitat, our results will be useful to surface mine reclamation and to other mitigation efforts where rocky habitats are lost or disturbed.

Contributions of Anthropology to the Study of Adolescence

ERIC Educational Resources Information Center

Schlegel, Alice; Hewlett, Bonnie L.

2011-01-01

Adolescence researchers can turn to anthropology to learn the methods of ethnography and cultural comparisons, and they can mine its large database of information on cultures worldwide. But anthropology's single most important contribution is the concept of culture, the mosaic of a group's learned and shared, or at least understood, beliefs,…

A Data Analytical Framework for Improving Real-Time, Decision Support Systems in Healthcare

ERIC Educational Resources Information Center

Yahav, Inbal

2010-01-01

In this dissertation we develop a framework that combines data mining, statistics and operations research methods for improving real-time decision support systems in healthcare. Our approach consists of three main concepts: data gathering and preprocessing, modeling, and deployment. We introduce the notion of offline and semi-offline modeling to…

A Decision Support System for Predicting Students' Performance

ERIC Educational Resources Information Center

Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis

2016-01-01

Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…

Predicting Academic Performance by Data Mining Methods

ERIC Educational Resources Information Center

Vandamme, J. -P.; Meskens, N.; Superby, J. -F.

2007-01-01

Academic failure among first-year university students has long fuelled a large number of debates. Many educational psychologists have tried to understand and then explain it. Many statisticians have tried to foresee it. Our research aims to classify, as early in the academic year as possible, students into three groups: the "low-risk"…

Mining Mineral Aggregates in Urban Areas.

ERIC Educational Resources Information Center

Thomson, Robert D.

This study can be used in a geographic research methods course to show how nearest-neighbor analysis and regression analysis can be used to study various aspects of land use. An analysis of the sand, gravel, and crushed stone industry in three urban areas of Pennsylvania, Massachusetts, and Florida illustrates the locational problems faced by…

Cost estimates and economic evaluations for conceptual LLRW disposal facility designs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baird, R.D.; Chau, N.; Breeds, C.D.

1995-12-31

Total life-cycle costs were estimated in support of the New York LLRW Siting Commission`s project to select a disposal method from four near-surface LLRW disposal methods (namely, uncovered above-grade vaults, covered above-grade vaults, below-grade vaults, and augered holes) and two mined methods (namely, vertical shaft mines and drift mines). Conceptual designs for the disposal methods were prepared and used as the basis for the cost estimates. Typical economic performance of each disposal method was assessed. Life-cycle costs expressed in 1994 dollars ranged from $ 1,100 million (for below-grade vaults and both mined disposal methods) to $2,000 million (for augered holes).more » Present values ranged from $620 million (for below-grade vaults) to $ 1,100 million (for augered holes).« less

Simulation and Measurement of Medium-Frequency Signals Coupling From a Line to a Loop Antenna

PubMed Central

Damiano, Nicholas W.; Li, Jingcheng; Zhou, Chenming; Brocker, Donovan E.; Qin, Yifeng; Werner, Douglas H.; Werner, Pingjuan L.

2016-01-01

The underground-mining environment can affect radio-signal propagation in various ways. Understanding these effects is especially critical in evaluating communications systems used during normal mining operations and during mine emergencies. One of these types of communications systems relies on medium-frequency (MF) radio frequencies. This paper presents the simulation and measurement results of recent National Institute for Occupational Safety and Health (NIOSH) research aimed at investigating MF coupling between a transmission line (TL) and a loop antenna in an underground coal mine. Two different types of measurements were completed: 1) line-current distribution and 2) line-to-antenna coupling. Measurements were taken underground in an experimental coal mine and on a specially designed surface test area. The results of these tests are characterized by current along a TL and voltage induced in the loop from a line. This paper concludes with a discussion of issues for MF TLs. These include electromagnetic fields at the ends of the TL, connection of the ends of the TL, the effect of other conductors underground, and the proximity of coal or earth. These results could help operators by providing examples of these challenges that may be experienced underground and a method by which to measure voltage induced by a line. PMID:27784954

Investigating the formation of acid mine drainage of Toledo pyrite concentrate using column cells

NASA Astrophysics Data System (ADS)

Aguila, Diosa Marie

2018-01-01

Acid mine drainage (AMD) is an inevitable problem in mining and has adverse effects in water quality. Studying AMD formation will be valuable in controlling the composition of mine waters and in planning the rehabilitation method for a mine. In this research, kinetics of AMD formation of Toledo pyrite was studied using two column experiments. The mechanisms of AMD formation and the effects of various factors on pH drop were first studied. Another column test was done for validation and to study the role of Fe2+/Fe3+ ratio in the change of leachate pH. The first experiment revealed that time and particle size are the most significant factors. It was also observed that the sudden pH drop during the starting hours was due to cracks formed from beneficiation, and the formation of Fe(OH)3. The laddered behavior of pH thereafter was due to decrease in formation of Fe(OH)3, and the precipitates in pyrite surface that lowered the surface area available for pyrite oxidation. The results of the second experiment validated the laddered behavior of pH. It was also observed that particle size distribution and pyrite surface were affected by the change in pH. Fe2+/Fe3+ ratio of leachate generally decreased as pH dropped.

Autochthonous microbe-assisted phytoremediation of brown coal mine overburden soil

NASA Astrophysics Data System (ADS)

Hamidović, Saud; Teodorović, Smilja; Lalević, Blažo; Karličić, Vera; Jovanović, Ljubinko; Kiković, Dragan; Raičević, Vera

2015-04-01

One of the largest brown coal mines in Bosnia and Herzegovina (BiH), Kakanj, has been exploited for over a hundred years. As a consequence of decades of exploitation, severe biocenosis disturbance and degradation of the entire ecosystem have occurred, resulting in overburden soil formation. A significant challenge in remediation of degraded mining areas is difficulty in creating conditions favorable for vegetation growth. Thus, numerous remediation technologies have focused on increasing soil nutrient composition, as well as the number and activity of plant growth-promoting bacteria (PGPB), given that they stimulate host plant growth by increasing the availability of essential nutrients (phosphorus, nitrogen, manganese, iron), producing phytohormones, and providing protection from pathogens. The main objective of this research was to characterize autochthonous plant and microbial overburden communities and access their ability to restore these contaminated soils. Phytocenological analysis of vegetation and plant species was performed according to Flora Europaea (2001), from 2011 - 2013. Our results show that plant species were not detected at mine overburden soil in 2011. However, we detected presence of a single plant species, Amaranthus albus L., in 2012. Further, we recorded the presence of five families (Amaranthaceae, Chenopodiaceae, Convolvulaceae, Poaceae and Polygonaceae) in 2013. Microbial abundance and enzymatic activity were also examined during the same period. The diversity of microbial populations in the first year was rather small. Two Bacillus spp., B. simplex and a B. cereus group member, indigenous to mine overburden were isolated and identified using standard macroscopic and microscopic, as well as molecular techniques (Hamidovic et al., submitted). Phosphate solubilizing activity of bacteria was tested on National Botanical Research Institute's phosphate growth medium (1999). Production of ammonia was determined in peptone water with Nessler's reagent. Siderophore production was detected by the method of Schwyn and Neilands, 1987 and quantitative analysis of IAA was performed using the method of Patten and Glick, 2002. Tested PGP activity of the two native Bacillus isolates, under laboratory conditions, indicated that they have the potential to stimulate plant growth. Further, their role in the production of ammonia, phosphate dissolving, and IAA production indicates that they may contribute to the restoration of vegetation cover and habitat stability. These complex interactions between indigenous microbial populations and plant roots can serve as a basis for effective ecoremediation strategies to repairing mine overburden soil.

Total Factor Productivity Growth, Technical Progress & Efficiency Change in Vietnam Coal Industry - Nonparametric Approach

NASA Astrophysics Data System (ADS)

Phuong, Vu Hung

2018-03-01

This research applies Data Envelopment Analysis (DEA) approach to analyze Total Factor Productivity (TFP) and efficiency changes in Vietnam coal mining industry from 2007 to 2013. The TFP of Vietnam coal mining companies decreased due to slow technological progress and unimproved efficiency. The decadence of technical efficiency in many enterprises proved that the coal mining industry has a large potential to increase productivity through technical efficiency improvement. Enhancing human resource training, technology and research & development investment could help the industry to improve efficiency and productivity in Vietnam coal mining industry.

A planetary nervous system for social mining and collective awareness

NASA Astrophysics Data System (ADS)

Giannotti, F.; Pedreschi, D.; Pentland, A.; Lukowicz, P.; Kossmann, D.; Crowley, J.; Helbing, D.

2012-11-01

We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.

Combined mine tremors source location and error evaluation in the Lubin Copper Mine (Poland)

NASA Astrophysics Data System (ADS)

Leśniak, Andrzej; Pszczoła, Grzegorz

2008-08-01

A modified method of mine tremors location used in Lubin Copper Mine is presented in the paper. In mines where an intensive exploration is carried out a high accuracy source location technique is usually required. The effect of the flatness of the geophones array, complex geological structure of the rock mass and intense exploitation make the location results ambiguous in such mines. In the present paper an effective method of source location and location's error evaluations are presented, combining data from two different arrays of geophones. The first consists of uniaxial geophones spaced in the whole mine area. The second is installed in one of the mining panels and consists of triaxial geophones. The usage of the data obtained from triaxial geophones allows to increase the hypocenter vertical coordinate precision. The presented two-step location procedure combines standard location methods: P-waves directions and P-waves arrival times. Using computer simulations the efficiency of the created algorithm was tested. The designed algorithm is fully non-linear and was tested on the multilayered rock mass model of the Lubin Copper Mine, showing a computational better efficiency than the traditional P-wave arrival times location algorithm. In this paper we present the complete procedure that effectively solves the non-linear location problems, i.e. the mine tremor location and measurement of the error propagation.

The landscape for epigenetic/epigenomic biomedical resources

PubMed Central

Shakya, Kabita; O'Connell, Mary J.; Ruskin, Heather J.

2012-01-01

Recent advances in molecular biology and computational power have seen the biomedical sector enter a new era, with corresponding development of Bioinformatics as a major discipline. Generation of enormous amounts of data has driven the need for more advanced storage solutions and shared access through a range of public repositories. The number of such biomedical resources is increasing constantly and mining these large and diverse data sets continues to present real challenges. This paper attempts a general overview of currently available resources, together with remarks on their data mining and analysis capabilities. Of interest here is the recent shift in focus from genetic to epigenetic/epigenomic research and the emergence and extension of resource provision to support this both at local and global scale. Biomedical text and numerical data mining are both considered, the first dealing with automated methods for analyzing research content and information extraction, and the second (broadly) with pattern recognition and prediction. Any summary and selection of resources is inherently limited, given the spectrum available, but the aim is to provide a guideline for the assessment and comparison of currently available provision, particularly as this relates to epigenetics/epigenomics. PMID:22874136

Chapter J: Issues and challenges in the application of geostatistics and spatial-data analysis to the characterization of sand-and-gravel resources

USGS Publications Warehouse

Hack, Daniel R.

2005-01-01

Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors as common drilling methods jeopardizing the accuracy of the size-distribution curve, the application of formal geostatistical principles has other limitations. Many of the variables used in evaluating gravel deposits, including such sedimentologic parameters as sorting and such United Soil Classification System parameters as gradation coefficient, are nonadditive. Also, uniform sampling methods, such as drilling, are relatively uncommon, and sampling is generally accomplished by a combination of boreholes, water-well logs, test pits, trenches, stratigraphic columns from exposures, and, possibly, some geophysical cross sections. When evaluated in consideration of the fact that uniform mining blocks are also uncommon in practice, subsequent complexities in establishment of the volume/variance relation are inevitable. Several approaches exist to confront the limitations of geostatistical methods in evaluating sand-and-gravel deposits. Initially, we must acknowledge the practical requirements of the aggregate industry, as well as the limitations of the data collected by that industry, as a function of what the industry requires at the practical level, and consider that broader acceptance of formal geostatistics may require modifications of typical exploration and sampling protocols. Future investigations should utilize data from the full spectrum of sand-and-gravel deposits (flood plain, glacial, catastrophic flood, and marine), integrate such other disci plines as sedimentology and geophysics into the research, develop commodity-specific approaches to nonadditive variables, and include the results of comparative drilling.

Storing and using health data in a virtual private cloud.

PubMed

Regola, Nathan; Chawla, Nitesh V

2013-03-13

Electronic health records are being adopted at a rapid rate due to increased funding from the US federal government. Health data provide the opportunity to identify possible improvements in health care delivery by applying data mining and statistical methods to the data and will also enable a wide variety of new applications that will be meaningful to patients and medical professionals. Researchers are often granted access to health care data to assist in the data mining process, but HIPAA regulations mandate comprehensive safeguards to protect the data. Often universities (and presumably other research organizations) have an enterprise information technology infrastructure and a research infrastructure. Unfortunately, both of these infrastructures are generally not appropriate for sensitive research data such as HIPAA, as they require special accommodations on the part of the enterprise information technology (or increased security on the part of the research computing environment). Cloud computing, which is a concept that allows organizations to build complex infrastructures on leased resources, is rapidly evolving to the point that it is possible to build sophisticated network architectures with advanced security capabilities. We present a prototype infrastructure in Amazon's Virtual Private Cloud to allow researchers and practitioners to utilize the data in a HIPAA-compliant environment.

30 CFR 75.215 - Longwall mining systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Longwall mining systems. 75.215 Section 75.215... MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.215 Longwall mining systems. For each longwall mining section, the roof control plan shall specify— (a) The methods that will be used to maintain...

30 CFR 75.215 - Longwall mining systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Longwall mining systems. 75.215 Section 75.215... MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.215 Longwall mining systems. For each longwall mining section, the roof control plan shall specify— (a) The methods that will be used to maintain...

INITIATIVES AND TREATMENT OF MERCURY IN ABANDONED MINES

EPA Science Inventory

This presentation discusses EPA's research activities and mitigation activities for mercury contaminated mine sites at the International meeting on mercury and artisanal gold mining in Lima, Peru. The topics discussed included the toxicological and enviornmental tasks associated ...

40 CFR 440.50 - Applicability; description of the titanium ore subcategory.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) mills beneficiating titanium ores by electrostatic methods, magnetic and physical methods, or flotation methods; and (c) mines engaged in the dredge mining of placer deposits of sands containing rutile... methods in conjunction with electrostatic or magnetic methods). ...

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

Gene prioritization and clustering by multi-view text mining

PubMed Central

2010-01-01

Background Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. Results We present a multi-view approach to retrieve biomedical knowledge using different controlled vocabularies. These controlled vocabularies are selected on the basis of nine well-known bio-ontologies and are applied to index the vast amounts of gene-based free-text information available in the MEDLINE repository. The text mining result specified by a vocabulary is considered as a view and the obtained multiple views are integrated by multi-source learning algorithms. We investigate the effect of integration in two fundamental computational disease gene identification tasks: gene prioritization and gene clustering. The performance of the proposed approach is systematically evaluated and compared on real benchmark data sets. In both tasks, the multi-view approach demonstrates significantly better performance than other comparing methods. Conclusions In practical research, the relevance of specific vocabulary pertaining to the task is usually unknown. In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification. PMID:20074336

Risk Assessment of Heavy Metals in Abandoned Mine Lands as Signifcant Contamination Problem in Romania

NASA Astrophysics Data System (ADS)

Horvath, E.; Jordan, G.; Fugedi, U.; Bartha, A.; Kuti, L.; Heltai, G.; Kalmar, J.; Waldmann, I.; Napradean, I.; Damian, G.

2009-04-01

INTRODUCTION Wide-spread environmental contamination associated with historic mining in Europe has triggered social responses to improve related environmental legislation, the environmental assessment and management methods for the mining industry. Pollution by acid mine drainage (AMD) from ore and coal mining is the outstanding and most important source of mining-induced environmental pollution. Younger et al. (2002) estimates that watercourses polluted by coal mine drainage could be in the order of 2,000 to 3,000 km, and 1,000 to 1,500 km polluted by metal mine discharges for the EU 15 Member States (Younger et al. 2002). Significance of contamination risk posed by mining is also highlighted by mine accidents such as those in Baia Mare, Romania in 2002 and in Aznalcollar, Spain in 1999 (Jordan and D'Alessandro 2004). The new EU Mine Waste Directive (Directive 2006/21/EC) requires the risk-based inventory of abandoned mines in the EU. The cost-effective implementation of the inventory is especially demanding in countries with extensive historic mining and great number of abandoned mine sites, like Romania. The problem is further complicated in areas with trans-boundary effects. The objective of this investigation to carry out the risk-based contamination assessment of a mine site with possible trans-boundary effects in Romania. Assessment follows the source-pathway-receptor chain with a special attention to heavy metal leaching from waste dumps as sources and to transport modelling along surface water pathways. STUDY AREA In this paper the Baiut mine catchment located in the Gutai Mts., Romania, close to the Hungarian border is studied. The polymetallic deposites in the Tertiary Inner-Carpathian Volcanic Arc are exposed by a series of abandoned Zn and Pb mines first operated in the 14th century. Elevation in the high relief catchment ranges from 449m to 1044m. Geology is characterised by andesites hosting the ore deposits and paleogene sediments dominating at the lower topographic elevations. Several mine adits, waste rock dumps are located along the main stream and a large tailings dump is found next to village Baiut just above the receiving floodplain. Predominant land cover is coniferous and mixed forests with agricultural lands on the downstream floodplain. METHODS Six samples at vaious depths were collected from the two major waste rock dumps in the headwater area, and the large tailings dump was also sampled for heavy metal source characterisation. 11 stream sediment samples were collected along the main surface water contamination transport pathway, and a further 11 soil samples were collected in 2 boreholes in the receptor floodplain in October 2008. Besides background stream sediment samples, samples from the exposed rock formations were also collected in order to capture natural background geochemistry in the studied mineralised area. The collected waste rock, stream sediment, soil and rock samples are analysed for total chemical composition (major elements and heavy metals) by ICP-MS spectroscopy, and XRD is used for the determination of mineralogical composition. Rock sample mineralogy is further investigated in thin-sections by petrological microscopy. According to EU legislation expectations, a special emphasis is taken on the determination of metal mobility from the waste rock dumps and various leaching tests are performed and compared including US EPA, USGS and ISO methods. A simple cathcment-based distributed sediment transport model (Jordan et al, 2005; Jordan et al. 2005, 2008) is used to decribe the pathways and quantities of particle-bound contamination. RESULTS AND CONCLUSIONS Results show that (1) sediments are an efficient means for the preliminary inventory of mine contamination as a preparation for the more detailed hydrological sampling and assessment, and (2) the risk-based contamination assessment of mining sites often located in diverse geological, hydrological and landcover environment requires careful and successive sampling design and a tiered assessment approach. Leaching tests are shown cost-efficient and informative methods for source (hazard) characterisation. REFERENCES Directive 2006/21/EC the European Parliament and of the Council on the management of waste from extractive industries and amending Directive 2004/35/EC. Commission of the European Communities, Brussels. Jordan G. and D'Alessandro M. (eds) (2004) Mining, Mining Waste and Related Environmental Issues: Problems and Solutions in the Central and Eastern European Candidate Countries. Joint Research Centre of the European Commission, Ispra. LB-NA-20868-EN-C. Jordan G., van Rompaey A., Szilassi P., Csillag G., Mannaerts C. and Woldai T. (2005) Historical land use changes and their impact on sediment fluxes in the Balaton basin (Hungary). Agriculture, Ecosystems and Environment, 108, 119-133. Jordan G., van Rompaey A., Somody A., Fügedi U., Bats M. and Farsang A. (2008) Spatial Modelling of Contamination in a Catchment Area Impacted by Mining: a Case Study for the Recsk Copper Mines, Hungary. Journal of Land Contamination and Reclamation (in press). Younger P.L., Banwart S.A., Hedin R.S. (2002) Mine water. Hydrology, pollution, remediation. Kluwer Academic Publishers, Dodrecht.

Geophysical Technologies to Image Old Mine Works

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanaan Hanna; Jim Pfeiffer

2007-01-15

ZapataEngineering, Blackhawk Division performed geophysical void detection demonstrations for the US Department of Labor Mine Safety and Health Administration (MSHA). The objective was to advance current state-of-practices of geophysical technologies for detecting underground mine voids. The presence of old mine works above, adjacent, or below an active mine presents major health and safety hazards to miners who have inadvertently cut into locations with such features. In addition, the presence of abandoned mines or voids beneath roadways and highway structures may greatly impact the performance of the transportation infrastructure in terms of cost and public safety. Roads constructed over abandoned minesmore » are subject to potential differential settlement, subsidence, sinkholes, and/or catastrophic collapse. Thus, there is a need to utilize geophysical imaging technologies to accurately locate old mine works. Several surface and borehole geophysical imaging methods and mapping techniques were employed at a known abandoned coal mine in eastern Illinois to investigate which method best map the location and extent of old works. These methods included: 1) high-resolution seismic (HRS) using compressional P-wave (HRPW) and S-wave (HRSW) reflection collected with 3-D techniques; 2) crosshole seismic tomography (XHT); 3) guided waves; 4) reverse vertical seismic profiling (RVSP); and 5) borehole sonar mapping. In addition, several exploration borings were drilled to confirm the presence of the imaged mine voids. The results indicated that the RVSP is the most viable method to accurately detect the subsurface voids with horizontal accuracy of two to five feet. This method was then applied at several other locations in Colorado with various topographic, geologic, and cultural settings for the same purpose. This paper presents the significant results obtained from the geophysical investigations in Illinois.« less

Recovery technologies for building materials

NASA Astrophysics Data System (ADS)

Karu, Veiko; Nurme, Martin; Valgma, Ingo

2015-04-01

Mining industry provides building materials for construction. Civil engineers have settled the quality parameters for construction materials. When we produce high quality building materials from carbonate rock (limestone, dolostone), then the estimated waste share is 25% to 30%, depending on crushing principles and rock quality. The challenge is to find suitable technology for waste recovery. During international mining waste related cooperation project MIN-NOVATION (www.min-novation.eu), partners mapped possibilities for waste recovery in mining industry and pointed out good examples and case studies. One example from Estonia showed that when we produce limestone aggregate, then we produce up to 30% waste material (fines with size 0-4mm). This waste material we can see as secondary raw material for building materials. Recovery technology for this fine grained material has been achieved with CDE separation plant. During the process the plant washes out minus 63 micron material from the limestone fines. This technology allows us to use 92% of all limestone reserves. By-product from 63 microns to 4 mm we can use as filler in concrete or as fine limestone aggregate for building or building materials. MIN-NOVATION project partners also established four pilot stations to study other mineral waste recovery technologies and solutions. Main aims on this research are to find the technology for recovery of mineral wastes and usage for new by-products from mineral mining waste. Before industrial production, testing period or case studies are needed. This research is part of the study of Sustainable and environmentally acceptable Oil shale mining No. 3.2.0501.11-0025 http://mi.ttu.ee/etp and the project B36 Extraction and processing of rock with selective methods - http://mi.ttu.ee/separation; http://mi.ttu.ee/miningwaste/

Spatial Data Mining for Estimating Cover Management Factor of Universal Soil Loss Equation

NASA Astrophysics Data System (ADS)

Tsai, F.; Lin, T. C.; Chiang, S. H.; Chen, W. W.

2016-12-01

Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes long-term soil erosion processes. Among the six different soil erosion risk factors of USLE, the cover-management factor (C-factor) is related to land-cover/land-use. The value of C-factor ranges from 0.001 to 1, so it alone might cause a thousandfold difference in a soil erosion analysis using USLE. The traditional methods for the estimation of USLE C-factor include in situ experiments, soil physical parameter models, USLE look-up tables with land use maps, and regression models between vegetation indices and C-factors. However, these methods are either difficult or too expensive to implement in large areas. In addition, the values of C-factor obtained using these methods can not be updated frequently, either. To address this issue, this research developed a spatial data mining approach to estimate the values of C-factor with assorted spatial datasets for a multi-temporal (2004 to 2008) annual soil loss analysis of a reservoir watershed in northern Taiwan. The idea is to establish the relationship between the USLE C-factor and spatial data consisting of vegetation indices and texture features extracted from satellite images, soil and geology attributes, digital elevation model, road and river distribution etc. A decision tree classifier was used to rank influential conditional attributes in the preliminary data mining. Then, factor simplification and separation were considered to optimize the model and the random forest classifier was used to analyze 9 simplified factor groups. Experimental results indicate that the overall accuracy of the data mining model is about 79% with a kappa value of 0.76. The estimated soil erosion amounts in 2004-2008 according to the data mining results are about 50.39 - 74.57 ton/ha-year after applying the sediment delivery ratio and correction coefficient. Comparing with estimations calculated with C-factors from look-up tables, the soil erosion values estimated with C-factors generated from spatial data mining results are more in agreement with the values published by the watershed administration authority.

Improvement of a method for positioning of pithead by considering motion of the surface water

NASA Astrophysics Data System (ADS)

Yi, H.; Lee, D. K.

2016-12-01

Underground mining has weakness compared with open pit mining in aspects of efficiency, economy and working environment. However, the method has applied for the development of a deep orebody. Development plan is established when the economic valuation and technical analysis of the deposits is completed through exploration of mineral resources. Development is a process to open a passage from the ground surface to the orebody as one of the steps of mining process. In the planning, there are details such as pithead positioning, mining method selection, and shaft design, etc. Among these, pithead positioning is implemented by considering infrastructures, watershed, geology, and economy. In this study, we propose a method to consider the motion of the surface waters in order to improve the existing pithead positioning techniques. The method contemplates the terrain around the mine and makes the surface water flow information. Then, the drainage treatment cost for each candidate location of pithead is suggested. This study covers the concept and design of the scheme.

A software tool for determination of breast cancer treatment methods using data mining approach.

PubMed

Cakır, Abdülkadir; Demirel, Burçin

2011-12-01

In this work, breast cancer treatment methods are determined using data mining. For this purpose, software is developed to help to oncology doctor for the suggestion of application of the treatment methods about breast cancer patients. 462 breast cancer patient data, obtained from Ankara Oncology Hospital, are used to determine treatment methods for new patients. This dataset is processed with Weka data mining tool. Classification algorithms are applied one by one for this dataset and results are compared to find proper treatment method. Developed software program called as "Treatment Assistant" uses different algorithms (IB1, Multilayer Perception and Decision Table) to find out which one is giving better result for each attribute to predict and by using Java Net beans interface. Treatment methods are determined for the post surgical operation of breast cancer patients using this developed software tool. At modeling step of data mining process, different Weka algorithms are used for output attributes. For hormonotherapy output IB1, for tamoxifen and radiotherapy outputs Multilayer Perceptron and for the chemotherapy output decision table algorithm shows best accuracy performance compare to each other. In conclusion, this work shows that data mining approach can be a useful tool for medical applications particularly at the treatment decision step. Data mining helps to the doctor to decide in a short time.

A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks

ERIC Educational Resources Information Center

Anaya, Antonio R.; Boticario, Jesus G.

2009-01-01

Data mining methods are successful in educational environments to discover new knowledge or learner skills or features. Unfortunately, they have not been used in depth with collaboration. We have developed a scalable data mining method, whose objective is to infer information on the collaboration during the collaboration process in a…

Methods and costs of thin-seam mining. Final report, 25 September 1977-24 January 1979. [Thin seam in association with a thick seam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finch, T.E.; Fidler, E.L.

1981-02-01

This report defines the state of the art (circa 1978) in removing thin coal seams associated with vastly thicker seams found in the surface coal mines of the western United States. New techniques are evaluated and an innovative method and machine is proposed. Western states resource recovery regulations are addressed and representative mining operations are examined. Thin seam recovery is investigated through its effect on (1) overburden removal, (2) conventional seam extraction methods, and (3) innovative techniques. Equations and graphs are used to accommodate the variable stratigraphic positions in the mining sequence on which thin seams occur. Industrial concern andmore » agency regulations provided the impetus for this study of total resource recovery. The results are a compendium of thin seam removal methods and costs. The work explains how the mining industry recovers thin coal seams in western surface mines where extremely thick seams naturally hold the most attention. It explains what new developments imply and where to look for new improvements and their probable adaptability.« less

Research status and future trends on surface pre-grouting technology in reforming wall rock of vertical shafts in coal mines in China

NASA Astrophysics Data System (ADS)

Wang, Hua

2018-02-01

In the mine construction, the surface pre-grouting technology is an important method to prevent water blast in excavation process of vertical shaft when the shaft must pass through the thick, water-rich and high water-pressure bedrock aquifer. It has been nearly 60 years since the technology was used to reform wall rock of vertical shaft in coal mine in China for the first time, and the existing technology can basically meet the needs of constructing 1000m deep vertical shaft. Firstly, the article introduces that in view of Magg’s spherical seepage theory and Karol’s spherical seepage theory, Chinese scholars found that the diffusion of grout from borehole into the surrounding strata in horizontal direction is irregular through a lot of research and engineering practice of using the surface pre-grouting technology to reform wall rock of vertical shafts, and put forward the selecting principles of grout’s effective diffusion radius in one grouting engineering; Secondly, according to the shape of the grouting boreholes, surface pre-grouting technology of vertical shaft is divided into two stages: vertical borehole stage and S-type borehole stage. Thirdly, the development status of grouting materials and grouting equipment for the technology is introduced. Fourthly, grouting mode, stage height and pressure of the technology are introduced. Finally, it points out that with the increasing depth of coal mining in China, the technology of reforming wall rock of 1000~2000m deep vertical shafts will face many problems, such as grouting theory, grouting equipment, grouting finishing standard, testing and evaluation of grouting effect, and so on. And it put forward a preliminary approach to solving these problems. This paper points out future research directions of the surface pre-grouting technology in China.

2nd International Symposium on Fundamental Aspects of Rare-earth Elements Mining and Separation and Modern Materials Engineering (REES-2015)

NASA Astrophysics Data System (ADS)

Tavadyan, Levon, Prof; Sachkov, Viktor, Prof; Godymchuk, Anna, Dr.; Bogdan, Anna

2016-01-01

The 2nd International Symposium «Fundamental Aspects of Rare-earth Elements Mining and Separation and Modern Materials Engineering» (REES2015) was jointly organized by Tomsk State University (Russia), National Academy of Science (Armenia), Shenyang Polytechnic University (China), Moscow Institute of Physics and Engineering (Russia), Siberian Physical-technical Institute (Russia), and Tomsk Polytechnic University (Russia) in September, 7-15, 2015, Belokuriha, Russia. The Symposium provided a high quality of presentations and gathered engineers, scientists, academicians, and young researchers working in the field of rare and rare earth elements mining, modification, separation, elaboration and application, in order to facilitate aggregation and sharing interests and results for a better collaboration and activity visibility. The goal of the REES2015 was to bring researchers and practitioners together to share the latest knowledge on rare and rare earth elements technologies. The Symposium was aimed at presenting new trends in rare and rare earth elements mining, research and separation and recent achievements in advanced materials elaboration and developments for different purposes, as well as strengthening the already existing contacts between manufactures, highly-qualified specialists and young scientists. The topics of the REES2015 were: (1) Problems of extraction and separation of rare and rare earth elements; (2) Methods and approaches to the separation and isolation of rare and rare earth elements with ultra-high purity; (3) Industrial technologies of production and separation of rare and rare earth elements; (4) Economic aspects in technology of rare and rare earth elements; and (5) Rare and rare earth based materials (application in metallurgy, catalysis, medicine, optoelectronics, etc.). We want to thank the Organizing Committee, the Universities and Sponsors supporting the Symposium, and everyone who contributed to the organization of the event and to publication of this proceeding.

Experience in the Education of Engineers from Vietnam in the Faculty of Mining and Geoengineering AGH

NASA Astrophysics Data System (ADS)

Cała, Marek; Borowski, Marek

2018-03-01

The AGH University of Science and Technology collaborates closely with other universities, economic units, governmental and local administrative bodies. International cooperation plays a very important role in the academic research. The AGH University of Science and Technology has signed many collaboration agreements. They aim at multidimensional cooperation in the fields of education and academic research. AGH UST has always focused on collaboration with business and industry. In recent years, the global economy is undergoing massive transformations, what creates new challenges to companies and educational institutions that cater to the needs of industry. The expansion of business enterprises is largely dependent on their employees' expertise, skills and levels of competence. Certified engineers are provided by universities. Therefore, the qualifications of the graduates are determined by the curriculum and teaching methods, as well as the available educational and research facilities. Of equal importance is the qualified academic staff. Human activities in the field of engineering require finding solutions to problems of various nature and magnitude. An engineer's work consists in the design, construction, modification and maintenance of useful devices, processes and systems, using scientific and technical knowledge. In order to design complex engineering solutions, an engineer uses his imagination, experience, analytical skills, logical reasoning and makes conscious use of his knowledge. At the Faculty of Mining and Geoengineering of the AGH University of Science and Technology in Cracow, 15 engineers from Vietnam are studying Mining and Geology at the second-cycle studies (specialization: mine ventilation). The solutions proposed in the field of the engineers' education guarantee that foreign students gain both engineering knowledge and problem-solving skills. Therefore, the study programme was complemented by a series of practical aspects.

Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014)

ERIC Educational Resources Information Center

Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed.

2014-01-01

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

Mine Burial Assessment State-of the Art in Prediction and Modeling Workshop and Initiation of Technical Program

DTIC Science & Technology

2000-09-30

Burial Assessment State-of-the Art Science , Technology, and Modeling. A Review of Coastal Research, Modeling, and Naval Operational Needs in Shallow Water...the ONR Mine Burial Prediction Program are summarized below. 1) Completed comprehensive technical reports: a. Mine Burial Assessment, State-of-the Art ... Science , Technology, and Modeling. A review of Coastal Research, Modeling, and Naval Operational Needs in Shallow Water Environments with

Preliminary study of detection of buried landmines using a programmable hyperspectral imager

NASA Astrophysics Data System (ADS)

McFee, John E.; Ripley, Herb T.; Buxton, Roger; Thriscutt, Andrew M.

1996-05-01

Experiments were conducted to determine if buried mines could be detected by measuring the change in reflectance spectra of vegetation above mine burial sites. Mines were laid using hand methods and simulated mechanical methods and spectral images were obtained over a three month period using a casi hyperspectral imager scanned from a personnel lift. Mines were not detectable by measurement of the shift of the red edge of vegetative spectra. By calculating the linear correlation coefficient image, some mines in light vegetative cover (grass, grass/blueberries) were apparently detected, but mines buried in heavy vegetation cover (deep ferns) were not detectable. Due to problems with ground truthing, accurate probabilities of detection and false alarm rates were not obtained.

Research the dynamical characteristics of slow deformation waves as a rock massif response to explosions during its outworking

NASA Astrophysics Data System (ADS)

Hachay, Olga; Khachay, Oleg; Shipeev, Oleg

2015-04-01

As a result of long-term natural geomechanics and geophysical observation data on mines of complex ore rocks, generalization of the non-linear reaction of rock massif to heavy dynamic influences have been established. In addition, pendulum type waves have been observed and the sources of them have been located inside geoblocks of different hierarchic levels (Oparin et al., 2010). At the same time, these waves propagate with wide low (compared with seismic waves) velocity values (Kurlenja et al., 1993; Oparin et al., 2006). Research into the massif state with the use of the dynamic systems theory approach (Naimark et al., 2009; Chulichkov, 2003; Hachay et al., 2010) has been developed to ascertain the criteria of dissipative regimes changing for real rock massifs, which are under heavy man-caused influence. To realize such research we used the data from the seismic record of the Tashtagol mine for the two-year period from June 2006 up to June 2008. We used the space-time coordinates for all dynamic massif event responses, which occurred during that period inside the mine space and for the explosions - values fixed by seismic station energy (Hachay et al., 2010). The phase diagrams of the massif state for the northern and southern parts of the mine space were plotted in coordinates Ev(t) and d(Ev(t))/dt, t - time - in parts of 24 hours, Ev - the dissipated massive seismic energy - in joules. Hachay et al., (2010) analysed the morphology of seismic response phase trajectories on the explosion influences during different serial intervals in the southern part of the mine. In that period, according to data for different explosions in the mine, the majority of the total energy had been injected into the southern part of the mine. Moreover, at the end of 2007, just in the southern part, the strongest rock burst during the whole history of the working mine happened. We developed a new processing method of seismological information in real, which we can use directly in the mine to estimate the changing state of the rock burst in the massif by its outworking. As a result we have selected a typical morphology of massif response phase trajectories, which were locally, over time, in a stable state: on the phase plane the local area presented as a ball of twisted trajectories with some not far removed points from the ball, which had not exceeded energy of more than 105 joules. For some time intervals those removed points exceeded 105 joules, achieving 106 joules and even 109 joules (Hachay et al., 2010). Introduction of the additional velocity parameter of slow deformation wave propagation allowed us, with the use of phase diagrams, to identify the hierarchic structure. Further, we can use that information for the modelling and interpretation of seismic and deformation waves in hierarchic structures (Hachay et al., 2012). That method can be useful in building-up an understanding of the resonance outshooting of catastrophic dynamic events and prevent these events. References 1.Chulichkov A. (2003) Mathematical models of nonlinear dynamics. Moscow: Phismatlit. 294p. 2.Hachay O., Khachay O.Yu., Klimko V., et al. (2010) Reflection of synergetic features of rock massif state under the man-caused influence from the data of a seismological catalogue. Mining Information-Analytic Bulletin, Moscow, Mining book, 6, pp.259-271. 3.Hachay O., Khachay A.Yu. (2012) Research of stress-deforming state of hierarchic medium. Proceedings of the Third Tectonics and Physics Conference at the Institute of the Physics of the Earth 8-12 October 2012, Moscow, IFZ RAS, pp.114-117. 4.Kurlenja M., Oparin V., Vostrikov V. (1993) About forming elastic wave trains by impulse excitation of block medium. Waves of pendulum type Uμ. DAN USSR, V.133, 4, pp.475-481. 5.Naimark Yu., Landa P. (2009). Stochastic and chaotic oscillations. Moscow, Knigniy dom ,'LIBROKOM', 424 p. 7.Oparin V., Vostrikov V., Tapsiev A. et al. (2006) About one kinematic criterion of forecasting of the limiting massif state with use of seismological data , FTPRPI, 6, pp.3-10.

Behavior Correlates of Post-Stroke Disability Using Data Mining and Infographics.

PubMed

Yoon, Sunmoo; Gutierrez, Jose

Disability is a potential risk for stroke survivors. This study aims to identify disability risk factors associated with stroke and their relative importance and relationships from a national behavioral risk factor dataset. Data of post-stroke individuals in the U.S (n=19,603) including 397 variables were extracted from a publically available national dataset and analyzed. Data mining algorithms including C4.5 and linear regression with M5s methods were applied to build association models for post-stroke disability using Weka software. The relative importance and relationship of 70 variables associated with disability were presented in infographics for clinicians to understand easily. Fifty-five percent of post-stroke patients experience disability. Exercise, employment and satisfaction of life were relatively important factors associated with disability among stroke patients. Modifiable behavior factors strongly associated with disability include exercise (OR: 0.46, P<0.01) and good rest (OR 0.37, P<0.01). Data mining is promising to discover factors associated with post-stroke disability from a large population dataset. The findings can be potentially valuable for establishing the priorities for clinicians and researchers and for stroke patient education. The methods may generalize to other health conditions.

Research on PM2.5 time series characteristics based on data mining technology

NASA Astrophysics Data System (ADS)

Zhao, Lifang; Jia, Jin

2018-02-01

With the development of data mining technology and the establishment of environmental air quality database, it is necessary to discover the potential correlations and rules by digging the massive environmental air quality information and analyzing the air pollution process. In this paper, we have presented a sequential pattern mining method based on the air quality data and pattern association technology to analyze the PM2.5 time series characteristics. Utilizing the real-time monitoring data of urban air quality in China, the time series rule and variation properties of PM2.5 under different pollution levels are extracted and analyzed. The analysis results show that the time sequence features of the PM2.5 concentration is directly affected by the alteration of the pollution degree. The longest time that PM2.5 remained stable is about 24 hours. As the pollution degree gets severer, the instability time and step ascending time gradually changes from 12-24 hours to 3 hours. The presented method is helpful for the controlling and forecasting of the air quality while saving the measuring costs, which is of great significance for the government regulation and public prevention of the air pollution.

Occupational respiratory diseases in the South African mining industry.

PubMed

Nelson, Gill

2013-01-24

Crystalline silica and asbestos are common minerals that occur throughout South Africa, exposure to either causes respiratory disease. Most studies on silicosis in South Africa have been cross-sectional and long-term trends have not been reported. Although much research has been conducted on the health effects of silica dust and asbestos fibre in the gold-mining and asbestos-mining sectors, little is known about their health effects in other mining sectors. The aims of this thesis were to describe silicosis trends in gold miners over three decades, and to explore the potential for diamond mine workers to develop asbestos-related diseases and platinum mine workers to develop silicosis. Mine workers for the three sub-studies were identified from a mine worker autopsy database at the National Institute for Occupational Health. From 1975 to 2007, the proportions of white and black gold mine workers with silicosis increased from 18 to 22% and from 3 to 32% respectively. Cases of diamond and platinum mine workers with asbestos-related diseases and silicosis, respectively, were also identified. The trends in silicosis in gold miners at autopsy clearly demonstrate the failure of the gold mines to adequately control dust and prevent occupational respiratory disease. The two case series of diamond and platinum mine workers contribute to the evidence for the risk of asbestos-related diseases in diamond mine workers and silicosis in platinum mine workers, respectively. The absence of reliable environmental dust measurements and incomplete work history records impedes occupational health research in South Africa because it is difficult to identify and/or validate sources of dust exposure that may be associated with occupational respiratory disease.

Atmospheric particulate matter size distribution and concentration in West Virginia coal mining and non-mining areas.

PubMed

Kurth, Laura M; McCawley, Michael; Hendryx, Michael; Lusk, Stephanie

2014-07-01

People who live in Appalachian areas where coal mining is prominent have increased health problems compared with people in non-mining areas of Appalachia. Coal mines and related mining activities result in the production of atmospheric particulate matter (PM) that is associated with human health effects. There is a gap in research regarding particle size concentration and distribution to determine respiratory dose around coal mining and non-mining areas. Mass- and number-based size distributions were determined with an Aerodynamic Particle Size and Scanning Mobility Particle Sizer to calculate lung deposition around mining and non-mining areas of West Virginia. Particle number concentrations and deposited lung dose were significantly greater around mining areas compared with non-mining areas, demonstrating elevated risks to humans. The greater dose was correlated with elevated disease rates in the West Virginia mining areas. Number concentrations in the mining areas were comparable to a previously documented urban area where number concentration was associated with respiratory and cardiovascular disease.

Utility of hyperspectral imagers in the mining industry: Italy's gypsum reserves

NASA Astrophysics Data System (ADS)

Wilson, Janette H.; Greenberger, Rebecca N.

2014-05-01

The mining industry is plagued with socioeconomic and safety roadblocks with not many solutions in the midst of a demanding market. As more and more geologic research using hyperspectral technology has been performed, along with an affordable price point for commercial use of hyperspectral technology, the benefits of hyperspectral imaging to the mining industry has become apparent. This study identifies the key areas of use for hyperspectral imaging in the mining industry through a case study of gypsum mine samples obtained from a mine in central Tuscany.

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Martin, Dawn (Elliott); Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Improve Data Mining and Knowledge Discovery through the use of MatLab

NASA Technical Reports Server (NTRS)

Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Data-Rich Astronomy: Mining Sky Surveys with PhotoRApToR

NASA Astrophysics Data System (ADS)

Cavuoti, Stefano; Brescia, Massimo; Longo, Giuseppe

2014-05-01

In the last decade a new generation of telescopes and sensors has allowed the production of a very large amount of data and astronomy has become a data-rich science. New automatic methods largely based on machine learning are needed to cope with such data tsunami. We present some results in the fields of photometric redshifts and galaxy classification, obtained using the MLPQNA algorithm available in the DAMEWARE (Data Mining and Web Application Resource) for the SDSS galaxies (DR9 and DR10). We present PhotoRApToR (Photometric Research Application To Redshift): a Java based desktop application capable to solve regression and classification problems and specialized for photo-z estimation.

Tools for Educational Data Mining: A Review

ERIC Educational Resources Information Center

Slater, Stefan; Joksimovic, Srecko; Kovanovic, Vitomir; Baker, Ryan S.; Gasevic, Dragan

2017-01-01

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

Site investigation report mine research project GUE 70-14.10, Guernsey, Ohio.

DOT National Transportation Integrated Search

2003-06-01

Geophysical investigative techniques can be a valuable supplement to standard subsurface investigations for the : evaluation of abandoned underground coal mine workings and their potential impacts at the ground surface. The GUE : 70 - 14.10 Mine Rese...

Mapping biomedical concepts onto the human genome by mining literature on chromosomal aberrations

PubMed Central

Van Vooren, Steven; Thienpont, Bernard; Menten, Björn; Speleman, Frank; Moor, Bart De; Vermeesch, Joris; Moreau, Yves

2007-01-01

Biomedical literature provides a rich but unstructured source of associations between chromosomal regions and biomedical concepts. By mining MEDLINE abstracts, we annotate the human genome at the level of cytogenetic bands. Our method creates a set of chromosomal aberration maps that associate cytogenetic bands to biomedical concepts from a variety of controlled vocabularies, including disease, dysmorphology, anatomy, development and Gene Ontology branches. The association between a band (e.g. 4p16.3) and a concept (e.g. microcephaly) is assessed by the statistical overrepresentation of this concept in the abstracts relating to this band. Our method is validated using existing genome annotation resources and known chromosomal aberration maps and is further illustrated through a case study on heart disease. Our chromosomal aberration maps provide diagnostics support to clinical geneticists, aid cytogeneticists to interpret and report cytogenetic findings and support researchers interested in human gene function. The method is available as a web application, aBandApart, at http://www.esat.kuleuven.be/abandapart/. PMID:17403693

Coal supply and cost under technological and environmental uncertainty

NASA Astrophysics Data System (ADS)

Chan, Melissa

This thesis estimates available coal resources, recoverability, mining costs, environmental impacts, and environmental control costs for the United States under technological and environmental uncertainty. It argues for a comprehensive, well-planned research program that will resolve resource uncertainty, and innovate new technologies to improve recovery and environmental performance. A stochastic process and cost (constant 2005) model for longwall, continuous, and surface mines based on current technology and mining practice data was constructed. It estimates production and cost ranges within 5-11 percent of 2006 prices and production rates. The model was applied to the National Coal Resource Assessment. Assuming the cheapest mining method is chosen to extract coal, 250-320 billion tons are recoverable. Two-thirds to all coal resource can be mined at a cost less than 4/mmBTU. If U.S. coal demand substantially increases, as projected by alternate Energy Information Administration (EIA), resources might not last more than 100 years. By scheduling cost to meet EIA projected demand, estimated cost uncertainty increases over time. It costs less than 15/ton to mine in the first 10 years of a 100 year time period, 10-30/ton in the following 50 years, and 15-$90/ton thereafter. Environmental impacts assessed are subsidence from underground mines, surface mine pit area, erosion, acid mine drainage, air pollutant and methane emissions. The analysis reveals that environmental impacts are significant and increasing as coal demand increases. Control technologies recommended to reduce these impacts are backfilling underground mines, surface pit reclamation, substitution of robotic underground mining systems for surface pit mining, soil replacement for erosion, placing barriers between exposed coal and the elements to avoid acid formation, and coalbed methane development to avoid methane emissions during mining. The costs to apply these technologies to meet more stringent environmental regulation scenarios are estimated. The results show that the cost of meeting these regulatory scenarios could increase mining costs two to six times the business as usual cost, which could significantly affect the cost of coal-powered electricity generation. This thesis provides a first estimate of resource availability, mining cost, and environmental impact assessment and cost analysis. Available resource is not completely reported, so the available estimate is lower than actual resource. Mining costs are optimized, so provide a low estimate of potential costs. Environmental impact estimates are on the high end of potential impact that may be incurred because it is assumed that impact is unavoidable. Control costs vary. Estimated cost to control subsidence and surface mine pit impacts are suitable estimates of the cost to reduce land impacts. Erosion control and robotic mining system costs are lower, and methane and acid mine drainage control costs are higher, than they may be in the case that these impacts must be reduced.

USGS Abandoned Mine Lands Research Presented at the NAAMLP Meeting in Billings, Mont., Sept. 25, 2006

USGS Publications Warehouse

Johnson, Kate; Church, Stan

2006-01-01

The following talk was an invited presentation given at the National Association of Abandoned Mine Lands Programs meeting in Billings, Montana on Sept. 25, 2006. The objective of the talk was to outline the scope of the U.S. Geological Survey research, past, present and future, in the area of abandoned mine research. Two large Professional Papers have come out of our AML studies: Nimick, D.A., Church, S.E., and Finger, S.E., eds., 2004, Integrated investigations of environmental effects of historical mining in the Basin and Boulder mining districts, Boulder River watershed, Jefferson County, Montana: U.S. Geological Survey Professional Paper 1652, 524 p., 2 plates, 1 DVD, URL: http://pubs.er.usgs.gov/usgspubs/pp/pp1652 Church, S.E., von Guerard, Paul, and Finger, S.E., eds., 2006, Integrated Investigations of Environmental Effects of Historical Mining in the Animas River Watershed, San Juan County, Colorado: U.S. Geological Survey Professional Paper 1651, 1,096 p., 6 plates, 1 DVD (in press). Additional publications and links can be found on the USGS AML website at URL: http://amli.usgs.gov/ or are accessible from the USGS Mineral Resource Program website at URL: http://minerals.usgs.gov/.

Social impact assessment in mining projects in Northern Finland: Comparing practice to theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suopajärvi, Leena, E-mail: leena.suopajarvi@ulapland.fi

The paper discusses social impact assessments (SIA) for mining projects in light of the international principles and guidelines for such assessments and the academic literature in the field. The data consist of environmental impact assessment (EIA) programmes and reports for six mining projects that have started up in northern Finland in the 2000s. A first observation is that the role of the SIAs in the EIA programmes and reports studied was quite minor: measured in number of pages, the assessments account for three or four percent of the total. This study analyses the data collection, research methodology and conceptual premisesmore » used in the SIAs. It concludes that the assessments do not fully meet the high standards of the international principles and guidelines set out for them: for example, elderly men are over-represented in the data and no efforts were made to identify and bring to the fore vulnerable groups. Moreover, the reliability of the assessments is difficult to gauge, because the qualitative methods are not described and where quantitative methods were used, details such as non-response rates to questionnaires are not discussed. At the end of the paper, the SIAs are discussed in terms of Jürgen Habermas' theory of knowledge interests, with the conclusion that the assessments continue the empirical analytical tradition of the social sciences and exhibit a technical knowledge interest. -- Highlights: • Paper investigates social impact assessments in Finnish mining projects. • Role of social impact assessment is minor in whole EIA-process. • Mining SIAs give the voice for elderly men, vulnerable groups are not identified. • Assessment of SIAs is difficult because of lacking transparency in reporting. • SIAs belong to empirical analytical tradition with technical knowledge interest.« less

LANDSAT inventory of surface-mined areas using extendible digital techniques

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schultz, D. T.; Buchman, N.

1975-01-01

Multispectral LANDSAT imagery was analyzed to provide a rapid and accurate means of identification, classification, and measurement of strip-mined surfaces in Western Maryland. Four band analysis allows distinction of a variety of strip-mine associated classes, but has limited extendibility. A method for surface area measurements of strip mines, which is both geographically and temporally extendible, has been developed using band-ratioed LANDSAT reflectance data. The accuracy of area measurement by this method, averaged over three LANDSAT scenes taken between September 1972 and July 1974, is greater than 93%. Total affected acreage of large (50 hectare/124 acre) mines can be measured to within 1.0%.

Community- and family-level factors influence care-giver choice to screen blood lead levels of children in a mining community.

PubMed

Moodie, S M; Tsui, E K; Silbergeld, E K

2010-07-01

Bunker Hill, in Kellogg, Idaho, formerly a lead mine (1884-1981) and smelter (1917-1981), is now a Superfund site listed on the Environmental Protection Agency's (EPA) National Priorities List. Lead contamination from the site is widespread due to past smelter discharges to land, water, and air, placing children at risk for both exposure to lead and resultant health effects of lead. Since 1983, the EPA has used child blood lead levels to inform the clean-up standards for the Bunker Hill Superfund site. This study was undertaken to examine factors that have contributed to the significant fall-off in the rates and numbers of children being screened for blood lead in Kellogg (number screened decreased from 195 to 8 from 2002 to 2007). The goal of this research project was to define community- and family-level factors which influence care-giver choice to screen blood lead levels of their children in this environment. This formative research study used mixed methods and was comprised of three research components: (1) preliminary interviews using community-based participatory research methods to define key research questions of relevance to community members, government and NGOs working in relation to the Bunker Hill clean-up; (2) a quantitative analysis of a cross-sectional household survey conducted with adult care-givers about child blood lead screening in Kellogg; and (3) ethnographic community rapid assessment methods formed the in-depth interview process and qualitative analysis. The survey showed the likelihood of blood lead screening that for children under the age of 18 years increases 34% with each one-year increase in current age of the child (95% CI, 1.08-1.67, p-value=0.009), and decreases 45% with annual household income greater than $10,000 (95% CI, 0.35-0.88, p-value=0.013). Sibling birth order increased the likelihood of blood lead screening by 61% (95% CI, 1.04-2.48, p-value=0.032) for each successive child. Female children were rated by their care-givers as 3.7 times less agitated or easily angered than male children (95% CI, 1.5-8.8, p-value=0.005). Across all levels of interviews, regulators, residents, and non-governmental organization representatives reported that Kellogg's long history as a mining town has continued to influence attitudes and actions of care-givers to access blood lead screening for their children. The mining context has been described as instilling stigmas, parental blame and a sense of shame about lead exposure and resultant health effects. Children under 6 years of age are currently the least likely to have been screened for lead in Kellogg and screening rates decreased in the 2000s. According to most indicators, socio-economic status did not influence the likelihood of a care-giver to screen children's blood lead levels. However, children in homes with an annual income below $10,000 were more likely to have been screened than the rest of the population. Former concerted screening efforts, including outreach, support, follow-up, and financial incentives in the 1980s-1990s to screen children, may have influenced low-income residents. Programmatic outreach for children under 6 years of age in Kellogg should focus on increasing female child and first child blood lead screening, rather than targeting only low-income families, by improving approaches to promotion, implementation and environmental follow-up for child lead screening. Some families have resided in Kellogg for five to six generations, and the long-term mining context influences community values and perceptions of lead exposure and screening for children through a conflicted combination of pride in the mining history, attachment to the past economy that supported the community in juxtaposition to the personalized blame, shame, guilt, and stigma associated with children having high blood lead levels. Health communication and other programs should prioritize methods of reducing parental feelings of blame, shame and guilt, and stigmas associated with the health effects of lead in a way that respects the pride of former mine workers, their families, and the history of the town. 2010 Elsevier Inc. All rights reserved.

Rehabilitation of gypsum-mined lands in the Indian desert

USGS Publications Warehouse

Sharma, K.D.; Kumar, S.; Gough, L.P.

2001-01-01

The economic importance of mining in the Indian Desert is second only to agriculture. Land disturbed by mining, however, has only recently been the focus of rehabilitation efforts. This research assesses the success of rehabilitation plans used to revegetate gypsum mine spoils within the environmental constraints of the north-west Indian hot-desert ecosystem. The rehabilitation plan first examined both mined and unmined areas and established assessments of existing vegetative cover and the quality of native soils and mine spoils. Tests were made on the effect of the use, and conservation, of available water through rainwater harvesting, amendment application (for physical and chemical spoil modification), plant establishment protocols, and the selection of appropriate germ plasm. Our results show that the resulting vegetative cover is capable of perpetuating itself under natural conditions while concurrently meeting the needs of farmers. Although the mine spoils are deficient in organic matter and phosphorus, they possess adequate amounts of all other nutrients. Total boron concentrations (>5.0 mg kg-1) in both the topsail and mine spoil indicate potentially phytotoxic conditions. Electrical conductance of mine spoil is 6-10 times higher than for topsail with a near-neutral pH. Populations of spoil fungi, Azotobactor, and nitrifying bacteria are low. The soil moisture storage in rainwater harvesting plots increased by 8% over the control and 48% over the unmined area. As a result of rehabilitation efforts, mine spoils show a steady buildup in organic carbon, and P and K due to the decomposition of farmyard manure and the contribution of nitrogen fixation by the established leguminous plant species. The rehabilitation protocol used at the site appears to have been successful. Following revegetation of the area with a mixture of trees, shrubs, and grasses, native implanted species have become established. Species diversity, measured in terms of species richness, increased after one year and then gradually declined over time; the decline was the result of the loss of annual species. The study not only develops methods of gypsum mine land rehabilitation but also helps in understanding processes of rehabilitation success in arid regions and emphasizes the importance of long-term monitoring of rehabilitation success. Copyright ?? 2001 Taylor & Francis.

Review and Evaluation of Current Training Programs Found in Various Mining Environments. Final Report. Volume I, Summary.

ERIC Educational Resources Information Center

Adkins, John; And Others

A project was designed to produce a broad description of current mining training programs and to evaluate their effectiveness with respect to reducing mine injuries. The research strategy was built on the ranking of mines according to the effectiveness of their training with an effective training effort being defined as that training which is…

Data Mining in Social Media

NASA Astrophysics Data System (ADS)

Barbier, Geoffrey; Liu, Huan

The rise of online social media is providing a wealth of social network data. Data mining techniques provide researchers and practitioners the tools needed to analyze large, complex, and frequently changing social media data. This chapter introduces the basics of data mining, reviews social media, discusses how to mine social media data, and highlights some illustrative examples with an emphasis on social networking sites and blogs.

Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, Brian; Elmore, Ryan; Getman, Dan

This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).

Numerical linear algebra in data mining

NASA Astrophysics Data System (ADS)

Eldén, Lars

Ideas and algorithms from numerical linear algebra are important in several areas of data mining. We give an overview of linear algebra methods in text mining (information retrieval), pattern recognition (classification of handwritten digits), and PageRank computations for web search engines. The emphasis is on rank reduction as a method of extracting information from a data matrix, low-rank approximation of matrices using the singular value decomposition and clustering, and on eigenvalue methods for network analysis.

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

Bibliography of surface-mine reclamation research: 1976-1993

Treesearch

Jerry T. Crews

1999-01-01

Contains citations for 177 articles and publications that describe research on or related to reclamation of surface-mined lands conducted from 1976 through 1993 by scientists with the Northeastern Forest Experiment Station and cooperating organizations. A subject index is included.

Data Mining Web Services for Science Data Repositories

NASA Astrophysics Data System (ADS)

Graves, S.; Ramachandran, R.; Keiser, K.; Maskey, M.; Lynnes, C.; Pham, L.

2006-12-01

The maturation of web services standards and technologies sets the stage for a distributed "Service-Oriented Architecture" (SOA) for NASA's next generation science data processing. This architecture will allow members of the scientific community to create and combine persistent distributed data processing services and make them available to other users over the Internet. NASA has initiated a project to create a suite of specialized data mining web services designed specifically for science data. The project leverages the Algorithm Development and Mining (ADaM) toolkit as its basis. The ADaM toolkit is a robust, mature and freely available science data mining toolkit that is being used by several research organizations and educational institutions worldwide. These mining services will give the scientific community a powerful and versatile data mining capability that can be used to create higher order products such as thematic maps from current and future NASA satellite data records with methods that are not currently available. The package of mining and related services are being developed using Web Services standards so that community-based measurement processing systems can access and interoperate with them. These standards-based services allow users different options for utilizing them, from direct remote invocation by a client application to deployment of a Business Process Execution Language (BPEL) solutions package where a complex data mining workflow is exposed to others as a single service. The ability to deploy and operate these services at a data archive allows the data mining algorithms to be run where the data are stored, a more efficient scenario than moving large amounts of data over the network. This will be demonstrated in a scenario in which a user uses a remote Web-Service-enabled clustering algorithm to create cloud masks from satellite imagery at the Goddard Earth Sciences Data and Information Services Center (GES DISC).

A Principal Component Analysis/Fuzzy Comprehensive Evaluation for Rockburst Potential in Kimberlite

NASA Astrophysics Data System (ADS)

Pu, Yuanyuan; Apel, Derek; Xu, Huawei

2018-02-01

Kimberlite is an igneous rock which sometimes bears diamonds. Most of the diamonds mined in the world today are found in kimberlite ores. Burst potential in kimberlite has not been investigated, because kimberlite is mostly mined using open-pit mining, which poses very little threat of rock bursting. However, as the mining depth keeps increasing, the mines convert to underground mining methods, which can pose a threat of rock bursting in kimberlite. This paper focuses on the burst potential of kimberlite at a diamond mine in northern Canada. A combined model with the methods of principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) is developed to process data from 12 different locations in kimberlite pipes. Based on calculated 12 fuzzy evaluation vectors, 8 locations show a moderate burst potential, 2 locations show no burst potential, and 2 locations show strong and violent burst potential, respectively. Using statistical principles, a Mahalanobis distance is adopted to build a comprehensive fuzzy evaluation vector for the whole mine and the final evaluation for burst potential is moderate, which is verified by a practical rockbursting situation at mine site.

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

NASA Astrophysics Data System (ADS)

Xu, Bing; Liu, Liqun

To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

The Mine Working's Roof Stress-strain State Research in the Perspective of Development of New Coal Deposits of Kuzbass

NASA Astrophysics Data System (ADS)

Kostyuk, Svetlana; Bedarev, Nikolay; Lyubimov, Oleg; Shaikhislamov, Arthur

2017-11-01

The present now normative and information base is regulating of the Kuzbass coal seams treatment but is not considering of the mining-geological and mining-engineering conditions for new coal deposits. The analysis of works for the research of the rock pressure manifestation shows that in many cases numerous results require of the practical confirmation in mine conditions directly, and also confirmation by the physical models. This work reflects one of the stages of research on changing the stress-strain state of the massif with the formation of unloading zones, increased rock pressure, and recovery. As an example, the results of the information analysis obtained by means of contour and depth benchmarks on the ventilation drift in the course of the 34 seam treatment at the "Tagaryshskaya" mine are presented. The differences of the analyzed results from the results obtained in the conditions of other mines are established. The values of the drift's roof stratification on the contour and at the distance from the contour of 1.0 to 4.0 m are given. The revealed maximums of the rock pressure and pressure changes in the hydraulic supports of the complex used for movement are presented. Recommendations on the choice of the anchor's length taking into account the roof stratification size are given. The further research stages on models from equivalent materials at various geometric scales are proposed.

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

A Method of Effective Quarry Water Purifying Using Artificial Filtering Arrays

NASA Astrophysics Data System (ADS)

Tyulenev, M.; Garina, E.; Khoreshok, A.; Litvin, O.; Litvin, Y.; Maliukhina, E.

2017-01-01

The development of open pit mining in the large coal basins of Russia and other countries increases their negative impact on the environment. Along with the damage of land and air pollution by dust and combustion gases of blasting, coal pits have a significant negative impact on water resources. Polluted quarry water worsens the ecological situation on a much larger area than covered by air pollution and land damage. This significantly worsens the conditions of people living in cities and towns located near the coal pits, and complicates the subsequent restoration of the environment, irreversibly destroying the nature. Therefore, the research of quarry wastewater purifying is becoming an important mater for scholars of technical colleges and universities in the regions with developing open-pit mining. This paper describes the method of determining the basic parameters of the artificial filtering arrays formed on coal pits of Kuzbass (Western Siberia, Russia), and gives recommendations on its application.

76 FR 20940 - Troy Mine, Incorporated, Troy Mine Revised Reclamation Plan, Kootenai National Forest, Lincoln...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-14

... mine. The ore is mined using the ``room-and-pillar method.'' The mine permit area covers 2,782 acres of.... Production stopped in 1993 and reinitiated in 2005 and is projected to continue for 3-5 years until the... evaluations necessary to complete design of reclamation elements that include a short-term water management...

Mercury contamination from historical gold mining in California

USGS Publications Warehouse

Alpers, Charles N.; Hunerlach, Michael P.; May, Jason T.; Hothem, Roger L.

2005-01-01

Mercury contamination from historical gold mines represents a potential risk to human health and the environment. This fact sheet provides background information on the use of mercury in historical gold mining and processing operations in California, with emphasis on historical hydraulic mining areas. It also describes results of recent USGS projects that address the potential risks associated with mercury contamination. Miners used mercury (quicksilver) to recover gold throughout the western United States. Gold deposits were either hardrock (lode, gold-quartz veins) or placer (alluvial, unconsolidated gravels). Underground methods (adits and shafts) were used to mine hardrock gold deposits. Hydraulic, drift, or dredging methods were used to mine the placer gold deposits. Mercury was used to enhance gold recovery in all the various types of mining operations; historical records indicate that more mercury was used and lost at hydraulic mines than at other types of mines. On the basis of USGS studies and other recent work, a better understanding is emerging of mercury distribution, ongoing transport, transformation processes, and the extent of biological uptake in areas affected by historical gold mining. This information has been used extensively by federal, state, and local agencies responsible for resource management and public health in California.

Mine wastes and human health

USGS Publications Warehouse

Plumlee, Geoffrey S.; Morman, Suzette A.

2011-01-01

Historical mining and mineral processing have been linked definitively to health problems resulting from occupational and environmental exposures to mine wastes. Modern mining and processing methods, when properly designed and implemented, prevent or greatly reduce potential environmental health impacts. However, particularly in developing countries, there are examples of health problems linked to recent mining. In other cases, recent mining has been blamed for health problems but no clear links have been found. The types and abundances of potential toxicants in mine wastes are predictably influenced by the geologic characteristics of the deposit being mined. Hence, Earth scientists can help understand, anticipate, and mitigate potential health issues associated with mining and mineral processing.

PERFORMING QUALITY FLOW MEASUREMENTS AT MINE SITES

EPA Science Inventory

Accurate flow measurement data is vital to research, monitoring, and remediation efforts at mining sites. This guidebook has been prepared to provide a summary of information relating to the performance of low measurements, and how this information can be applied at mining sites....

Accessing Cloud Properties and Satellite Imagery: A tool for visualization and data mining

NASA Astrophysics Data System (ADS)

Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.

2016-12-01

Providing public access to imagery of cloud macro and microphysical properties and the underlying satellite imagery is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and system that allows end users to easily browse cloud information and satellite imagery that is otherwise difficult to acquire and manipulate. The tool has two uses, one to visualize the data and the other to access the data directly. It uses a widely used access protocol, the Open Geospatial Consortium's Web Map and Processing Services, to encourage user to access the data we produce. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud. One goal of the tool is to provide a demonstration of the back end capability to end users so that they can use the dynamically generated imagery and data as an input to their own work flows or to set up data mining constraints. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information and satellite imagery accessible and easily searchable. Increasingly, information is used in a "mash-up" form where multiple sources of information are combined to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much cutting edge scientific knowledge, observations and products available to the citizen science, research and interested communities for these kinds of "mash-ups" as well as provide a means for automated systems to data mine our information. This tool and access method provides a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

30 CFR 77.1000 - Highwalls, pits and spoil banks; plans.

Code of Federal Regulations, 2010 CFR

2010-07-01

... safe working conditions. The mining methods employed by the operator shall be selected to insure... Section 77.1000 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2013 CFR

2013-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2012 CFR

2012-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2011 CFR

2011-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

Surface mining

Treesearch

Robert Leopold; Bruce Rowland; Reed Stalder

1979-01-01

The surface mining process consists of four phases: (1) exploration; (2) development; (3) production; and (4) reclamation. A variety of surface mining methods has been developed, including strip mining, auger, area strip, open pit, dredging, and hydraulic. Sound planning and design techniques are essential to implement alternatives to meet the myriad of laws,...