Using an improved association rules mining optimization algorithm in web-based mobile-learning system

NASA Astrophysics Data System (ADS)

Huang, Yin; Chen, Jianhua; Xiong, Shaojun

2009-07-01

Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

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.

LavaNet—Neural network development environment in a general mine planning package

NASA Astrophysics Data System (ADS)

Kapageridis, Ioannis Konstantinou; Triantafyllou, A. G.

2011-04-01

LavaNet is a series of scripts written in Perl that gives access to a neural network simulation environment inside a general mine planning package. A well known and a very popular neural network development environment, the Stuttgart Neural Network Simulator, is used as the base for the development of neural networks. LavaNet runs inside VULCAN™—a complete mine planning package with advanced database, modelling and visualisation capabilities. LavaNet is taking advantage of VULCAN's Perl based scripting environment, Lava, to bring all the benefits of neural network development and application to geologists, mining engineers and other users of the specific mine planning package. LavaNet enables easy development of neural network training data sets using information from any of the data and model structures available, such as block models and drillhole databases. Neural networks can be trained inside VULCAN™ and the results be used to generate new models that can be visualised in 3D. Direct comparison of developed neural network models with conventional and geostatistical techniques is now possible within the same mine planning software package. LavaNet supports Radial Basis Function networks, Multi-Layer Perceptrons and Self-Organised Maps.

Automatic mapping of strip mine operations from spacecraft data. [Ohio

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Reed, L. E.; Pettyjohn, W. A.

1974-01-01

The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically-correct map overlays, at scales from 1:24,000 to 1:250,000, showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers were also produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping and reclamation. NASA C-130 photography acquired on 7 September 1973 when compared with the ERTS products generated from the 3 September 1973 tape established the categorization accuracy to be better than 90%. It is estimated that the stripping and reclamation maps and data were produced from the ERTS CCTs at a tenth of the cost of conventional techniques.

Design of intelligent proximity detection zones to prevent striking and pinning fatalities around continuous mining machines.

PubMed

Bissert, P T; Carr, J L; DuCarme, J P; Smith, A K

2016-01-01

The continuous mining machine is a key piece of equipment used in underground coal mining operations. Over the past several decades these machines have been involved in a number of mine worker fatalities. Proximity detection systems have been developed to avert hazards associated with operating continuous mining machines. Incorporating intelligent design into proximity detection systems allows workers greater freedom to position themselves to see visual cues or avoid other hazards such as haulage equipment or unsupported roof or ribs. However, intelligent systems must be as safe as conventional proximity detection systems. An evaluation of the 39 fatal accidents for which the Mine Safety and Health Administration has published fatality investigation reports was conducted to determine whether the accident may have been prevented by conventional or intelligent proximity. Multiple zone configurations for the intelligent systems were studied to determine how system performance might be affected by the zone configuration. Researchers found that 32 of the 39 fatalities, or 82 percent, may have been prevented by both conventional and intelligent proximity systems. These results indicate that, by properly configuring the zones of an intelligent proximity detection system, equivalent protection to a conventional system is possible.

A sentence sliding window approach to extract protein annotations from biomedical articles

PubMed Central

Krallinger, Martin; Padron, Maria; Valencia, Alfonso

2005-01-01

Background Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations. Results The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of correct extractions of individual entities (i.e. proteins and GO terms) involved in the relationships used for the annotations was significantly higher than the correct extractions of the complete annotations (protein-function relations). Conclusion We explored the use of averaging sentence sliding windows for information extraction, especially in a context where conventional training data is unavailable. The combination of our approach with more refined statistical estimators and machine learning techniques might be a way to improve annotation extraction for future biomedical text mining applications. PMID:15960831

Reclaimed mineland curve number response to temporal distribution of rainfall

USGS Publications Warehouse

Warner, R.C.; Agouridis, C.T.; Vingralek, P.T.; Fogle, A.W.

2010-01-01

The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound. ?? 2010 American Water Resources Association.

Long Term Monitoring of Ground Motions in Upper Silesia Coal Basin (USCB) Using Satellite Radar Interferometry

NASA Astrophysics Data System (ADS)

Graniczny, Marek; Przylucka, Maria; Kowalski, Zbigniew

2016-08-01

Subsidence hazard and risk within the USCB are usually connected with the deep coal mining. In such cases, the surface becomes pitted with numerous collapse cavities or basins which depth may even reach tens of meters. The subsidence is particularly dangerous because of causing severe damage to gas and water pipelines, electric cables, and to sewage disposal systems. The PGI has performed various analysis of InSAR data in this area, including all three SAR bands (X, C and L) processed by DInSAR, PSInSAR and SqueeSAR techniques. These analyses of both conventional and advanced DInSAR approaches have proven to be effective to detect the extent and the magnitude of mining subsidence impact on urban areas. In this study an analysis of two series of subsequent differential interferograms obtained in the DInSAR technique are presented. SAR scenes are covering two periods and were acquired by two different satellites: ALOS-P ALSAR data from 22/02/2007- 27/05/2008 and TerraSAR-X data from 05/07/2011-21/06/2012. The analysis included determination of the direction and development of subsidence movement in relation to the mining front and statistic comparison between range and value of maximum subsidence detected for each mining area. Detailed studies were performed for Bobrek-Centrum mining area. They included comparison of mining fronts and location of the extracted coal seams with the observed subsidence on ALOS-P ALSAR InSAR interferograms. The data can help in estimation not only the range of the subsidence events, but also its value, direction of changes and character of the motion.

Service-based analysis of biological pathways

PubMed Central

Zheng, George; Bouguettaya, Athman

2009-01-01

Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403

Comparison of coarse coal dust sampling techniques in a laboratory-simulated longwall section.

PubMed

Patts, Justin R; Barone, Teresa L

2017-05-01

Airborne coal dust generated during mining can deposit and accumulate on mine surfaces, presenting a dust explosion hazard. When assessing dust hazard mitigation strategies for airborne dust reduction, sampling is done in high-velocity ventilation air, which is used to purge the mining face and gallery tunnel. In this environment, the sampler inlet velocity should be matched to the air stream velocity (isokinetic sampling) to prevent oversampling of coarse dust at low sampler-to-air velocity ratios. Low velocity ratios are often encountered when using low flow rate, personal sampling pumps commonly used in underground mines. In this study, with a goal of employing mine-ready equipment, a personal sampler was adapted for area sampling of coarse coal dust in high-velocity ventilation air. This was done by adapting an isokinetic nozzle to the inlet of an Institute of Occupational Medicine (Edinburgh, Scotland) sampling cassette (IOM). Collected dust masses were compared for the modified IOM isokinetic sampler (IOM-MOD), the IOM without the isokinetic nozzle, and a conventional dust sampling cassette without the cyclone on the inlet. All samplers were operated at a flow rate typical of personal sampling pumps: 2 L/min. To ensure differences between collected masses that could be attributed to sampler design and were not influenced by artifacts from dust concentration gradients, relatively uniform and repeatable dust concentrations were demonstrated in the sampling zone of the National Institute for Occupational Safety and Health experimental mine gallery. Consistent with isokinetic theory, greater differences between isokinetic and non-isokinetic sampled masses were found for larger dust volume-size distributions and higher ventilation air velocities. Since isokinetic sampling is conventionally used to determine total dust concentration, and isokinetic sampling made a difference in collected masses, the results suggest when sampling for coarse coal dust the IOM-MOD may improve airborne coarse dust assessments over "off-the-shelf" sampling cassettes.

Comparison of coarse coal dust sampling techniques in a laboratory-simulated longwall section

PubMed Central

Patts, Justin R.; Barone, Teresa L.

2017-01-01

Airborne coal dust generated during mining can deposit and accumulate on mine surfaces, presenting a dust explosion hazard. When assessing dust hazard mitigation strategies for airborne dust reduction, sampling is done in high-velocity ventilation air, which is used to purge the mining face and gallery tunnel. In this environment, the sampler inlet velocity should be matched to the air stream velocity (isokinetic sampling) to prevent oversampling of coarse dust at low sampler-to-air velocity ratios. Low velocity ratios are often encountered when using low flow rate, personal sampling pumps commonly used in underground mines. In this study, with a goal of employing mine-ready equipment, a personal sampler was adapted for area sampling of coarse coal dust in high-velocity ventilation air. This was done by adapting an isokinetic nozzle to the inlet of an Institute of Occupational Medicine (Edinburgh, Scotland) sampling cassette (IOM). Collected dust masses were compared for the modified IOM isokinetic sampler (IOM-MOD), the IOM without the isokinetic nozzle, and a conventional dust sampling cassette without the cyclone on the inlet. All samplers were operated at a flow rate typical of personal sampling pumps: 2 L/min. To ensure differences between collected masses that could be attributed to sampler design and were not influenced by artifacts from dust concentration gradients, relatively uniform and repeatable dust concentrations were demonstrated in the sampling zone of the National Institute for Occupational Safety and Health experimental mine gallery. Consistent with isokinetic theory, greater differences between isokinetic and non-isokinetic sampled masses were found for larger dust volume-size distributions and higher ventilation air velocities. Since isokinetic sampling is conventionally used to determine total dust concentration, and isokinetic sampling made a difference in collected masses, the results suggest when sampling for coarse coal dust the IOM-MOD may improve airborne coarse dust assessments over “off-the-shelf” sampling cassettes. PMID:27792474

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

76 FR 45300 - Notice of Issuance of Materials License SUA-1597 and Record of Decision for Uranerz Energy...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-28

... considered but eliminated from detailed analysis include conventional uranium mining and milling, conventional mining and heap leach processing, alternative site location, alternate lixiviants, and alternate...'s Agencywide Document Access and Management System (ADAMS), which provides text and image files of...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2011 CFR

2011-07-01

... air will be used to determine the average concentration for that mechanized mining unit. (e) Unless... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section...

40 CFR 144.6 - Classification of wells.

Code of Federal Regulations, 2010 CFR

2010-07-01

... including: (1) Mining of sulfur by the Frasch process; (2) In situ production of uranium or other metals; this category includes only in-situ production from ore bodies which have not been conventionally mined... are brought to the surface in connection with natural gas storage operations, or conventional oil or...

40 CFR 144.6 - Classification of wells.

Code of Federal Regulations, 2011 CFR

2011-07-01

... including: (1) Mining of sulfur by the Frasch process; (2) In situ production of uranium or other metals; this category includes only in-situ production from ore bodies which have not been conventionally mined... are brought to the surface in connection with natural gas storage operations, or conventional oil or...

40 CFR 144.6 - Classification of wells.

Code of Federal Regulations, 2012 CFR

2012-07-01

... including: (1) Mining of sulfur by the Frasch process; (2) In situ production of uranium or other metals; this category includes only in-situ production from ore bodies which have not been conventionally mined... are brought to the surface in connection with natural gas storage operations, or conventional oil or...

40 CFR 144.6 - Classification of wells.

Code of Federal Regulations, 2013 CFR

2013-07-01

... including: (1) Mining of sulfur by the Frasch process; (2) In situ production of uranium or other metals; this category includes only in-situ production from ore bodies which have not been conventionally mined... are brought to the surface in connection with natural gas storage operations, or conventional oil or...

40 CFR 144.6 - Classification of wells.

Code of Federal Regulations, 2014 CFR

2014-07-01

... including: (1) Mining of sulfur by the Frasch process; (2) In situ production of uranium or other metals; this category includes only in-situ production from ore bodies which have not been conventionally mined... are brought to the surface in connection with natural gas storage operations, or conventional oil or...

Automated strip-mine and reclamation mapping from ERTS

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Reed, L. E.; Pettyjohn, W. A.

1974-01-01

The author has identified the following significant results. Computer processing techniques were applied to ERTS-1 computer-compatible tape (CCT) data acquired in August 1972 on the Ohio Power Company's coal mining operation in Muskingum County, Ohio. Processing results succeeded in automatically classifying, with an accuracy greater than 90%: (1) stripped earth and major sources of erosion; (2) partially reclaimed areas and minor sources of erosion; (3) water with sedimentation; (4) water without sedimentation; and (5) vegetation. Computer-generated tables listing the area in acres and square kilometers were produced for each target category. Processing results also included geometrically corrected map overlays, one for each target category, drawn on a transparent material by a pen under computer control. Each target category is assigned a distinctive color on the overlay to facilitate interpretation. The overlays, drawn at a scale of 1:250,000 when placed over an AMS map of the same area, immediately provided map locations for each target. These mapping products were generated at a tenth of the cost of conventional mapping techniques.

Coalbed methane: Clean energy for the world

USGS Publications Warehouse

Ahmed, A.-J.; Johnston, S.; Boyer, C.; Lambert, S.W.; Bustos, O.A.; Pashin, J.C.; Wray, A.

2009-01-01

Coalbed methane (CBM) has the potential to emerge as a significant clean energy resource. It also has the potential to replace other diminishing hydrocarbon reserves. The latest developments in technologies and methodologies are playing a key role in harnessing this unconventional resource. Some of these developments include adaptations of existing technologies used in conventional oil and gas generations, while others include new applications designed specifically to address coal's unique properties. Completion techniques have been developed that cause less damage to the production mechanisms of coal seams, such as those occurring during cementing operations. Stimulation fluids have also been engineered specifically to enhance CBM production. Deep coal deposits that remain inaccessible by conventional mining operations offer CBM development opportunities.

76 FR 53500 - Notice of the Nuclear Regulatory Commission Issuance of Materials License SUA-1598 and Record of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-26

... (ADAMS), which provides text and image files of the NRC's public documents in the NRC Library at http... considered, but eliminated from detailed analysis, include conventional uranium mining and milling, conventional mining and heap leach processing, alternate lixiviants, and alternative wastewater disposal...

New approach to generating insights for aging research based on literature mining and knowledge integration

PubMed Central

Kwon, Yeondae; Natori, Yukikazu

2017-01-01

The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from. We demonstrate that our approach provides useful information that deepens insights on future trends which differs from data obtained conventionally, and this methodology is already paving the way for a new field in aging-related research based on literature mining. One compelling example of this is how our new approach can be a useful tool in drug repositioning. PMID:28817730

Advanced subsidence monitoring using persistent scatterer interferometry for Jharia Coal Field, Dhanbad, India

NASA Astrophysics Data System (ADS)

Thapa, Shailaja; Chatterjee, R. S.; Kumar, Dheeraj; Singh, K. B.; Sengar, Vivek

2017-10-01

This paper presents a spatiotemporal study of surface subsidence over urban area due to coal mining using Persistent scatterer interferometry. In the past few years Differential Interferometric Synthetic Aperture Radar has emerged as a very useful remote sensing technique for measuring land subsidence. It plays a vital role in insitu subsidence prediction of coal mining area. However there are some limitation viz. atmospheric decorrelation, temporal decorrelation and spatial decorrelation with conventional D-InSAR techniques, which can be overcome up to certain extent by using multiinterferogram framework approach. The Persistent Scatterer interferometry technique comprises of more number of SAR datasets, it only concentrates over the pixel which remain coherent over long time period. Persistent Scatterer interferometry makes deformation measurement on permanent scattering location for the targeted ground surface. Mainly, these permanent scatterer are manmade features like metallic bridges, dams, antennae roof of buildings etc. apart that some permanent scatterer may comprise of prominent stable natural targets. The results obtained from PS-InSAR gives more precised measurement of surface deformation. Total eight ALOS PALSAR scenes covering the time period from 2007 to 2010 have been utilized to produce ground deformation map using PSInSAR techniques for Jharia Coal field, Dhanbad. This is proven technique, which helps to identify the persistent land surface movement .The results were analyzed Sijua area in Jharia coalfield. The subsidence fringes were demarcated over the entire study area. The PSInSAR results were validated using precision leveling data provided by mining authorities. The results demonstrates that PSInSAR can be used as potential tool to highlight the subsidence prone area depending upon the spatial and temporal coherency of SAR data.

Geomorphic reclmation of a coal refuse pile

NASA Astrophysics Data System (ADS)

Hopkinson, L. C.; Quaranta, J.

2017-12-01

Geomorphic reclamation is a technique that may offer opportunities to improve mine reclamation in Central Appalachia. The design approach is based on constructing a steady-state, mature landform condition and takes into account the long-term climatic conditions, soil types, terrain grade, and vegetation. Geomorphic reclamation has been applied successfully in semi-arid regions but has not yet been applied in Central Appalachia. This work describes a demonstration study where geomorphic landforming techniques are being applied to a coarse coal refuse pile in southern West Virginia, USA. The reclamation design includes four geomorphic watersheds that radially drain runoff from the pile. Each watershed has one central draining channel and incorporates compound slope profiles similarly to naturally eroded slopes. Planar slopes were also included to maintain the impacted area. The intent is to alter the hydrology to decrease water quality treatment costs. The excavation cut and fill volumes are comparable to those of more conventional refuse pile reclamation designs. If proven successful then this technique can be part of a cost-effective solution to improve water quality at active and future refuse facilities, abandoned mine lands, bond forfeiture sites, landfills, and major earthmoving activities within the region.

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.

Actinorhizal Alder Phytostabilization Alters Microbial Community Dynamics in Gold Mine Waste Rock from Northern Quebec: A Greenhouse Study

PubMed Central

Callender, Katrina L.; Roy, Sébastien; Khasa, Damase P.; Whyte, Lyle G.; Greer, Charles W.

2016-01-01

Phytotechnologies are rapidly replacing conventional ex-situ remediation techniques as they have the added benefit of restoring aesthetic value, important in the reclamation of mine sites. Alders are pioneer species that can tolerate and proliferate in nutrient-poor, contaminated environments, largely due to symbiotic root associations with the N2-fixing bacteria, Frankia and ectomycorrhizal (ECM) fungi. In this study, we investigated the growth of two Frankia-inoculated (actinorhizal) alder species, A. crispa and A. glutinosa, in gold mine waste rock from northern Quebec. Alder species had similar survival rates and positively impacted soil quality and physico-chemical properties in similar ways, restoring soil pH to neutrality and reducing extractable metals up to two-fold, while not hyperaccumulating them into above-ground plant biomass. A. glutinosa outperformed A. crispa in terms of growth, as estimated by the seedling volume index (SVI), and root length. Pyrosequencing of the bacterial 16S rRNA gene for bacteria and the ribosomal internal transcribed spacer (ITS) region for fungi provided a comprehensive, direct characterization of microbial communities in gold mine waste rock and fine tailings. Plant- and treatment-specific shifts in soil microbial community compositions were observed in planted mine residues. Shannon diversity and the abundance of microbes involved in key ecosystem processes such as contaminant degradation (Sphingomonas, Sphingobium and Pseudomonas), metal sequestration (Brevundimonas and Caulobacter) and N2-fixation (Azotobacter, Mesorhizobium, Rhizobium and Pseudomonas) increased over time, i.e., as plants established in mine waste rock. Acetate mineralization and most probable number (MPN) assays showed that revegetation positively stimulated both bulk and rhizosphere communities, increasing microbial density (biomass increase of 2 orders of magnitude) and mineralization (five-fold). Genomic techniques proved useful in investigating tripartite (plant-bacteria-fungi) interactions during phytostabilization, contributing to our knowledge in this field of study. PMID:26928913

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2011 CFR

2011-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2013 CFR

2013-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2014 CFR

2014-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2012 CFR

2012-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

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.

A Computational Approach to Qualitative Analysis in Large Textual Datasets

PubMed Central

Evans, Michael S.

2014-01-01

In this paper I introduce computational techniques to extend qualitative analysis into the study of large textual datasets. I demonstrate these techniques by using probabilistic topic modeling to analyze a broad sample of 14,952 documents published in major American newspapers from 1980 through 2012. I show how computational data mining techniques can identify and evaluate the significance of qualitatively distinct subjects of discussion across a wide range of public discourse. I also show how examining large textual datasets with computational methods can overcome methodological limitations of conventional qualitative methods, such as how to measure the impact of particular cases on broader discourse, how to validate substantive inferences from small samples of textual data, and how to determine if identified cases are part of a consistent temporal pattern. PMID:24498398

Mining Land Subsidence Monitoring Using SENTINEL-1 SAR Data

NASA Astrophysics Data System (ADS)

Yuan, W.; Wang, Q.; Fan, J.; Li, H.

2017-09-01

In this paper, DInSAR technique was used to monitor land subsidence in mining area. The study area was selected in the coal mine area located in Yuanbaoshan District, Chifeng City, and Sentinel-1 data were used to carry out DInSAR techniqu. We analyzed the interferometric results by Sentinel-1 data from December 2015 to May 2016. Through the comparison of the results of DInSAR technique and the location of the mine on the optical images, it is shown that DInSAR technique can be used to effectively monitor the land subsidence caused by underground mining, and it is an effective tool for law enforcement of over-mining.

A life-cycle description of underground coal mining

NASA Technical Reports Server (NTRS)

Lavin, M. L.; Borden, C. S.; Duda, J. R.

1978-01-01

An initial effort to relate the major technological and economic variables which impact conventional underground coal mining systems, in order to help identify promising areas for advanced mining technology is described. The point of departure is a series of investment analyses published by the United States Bureau of Mines, which provide both the analytical framework and guidance on a choice of variables.

Probabilistic Model and Analysis of Conventional Preinstalled Mine Field Defense.

DTIC Science & Technology

1980-09-01

process to model the one or two positions of mines in the mine field. The duel between the anti-tank weapon and offensive tanks crossing the field is...mine field. The duel between the anti-tank weapon and offensive tanks crossing the field is modeled with a con- tinuous time Markov chain. Some...11 B. DUEL ------------------------------------------- 15 IV. DUEL

Utilizing Skylab data in on-going resources management programs in the state of Ohio

NASA Technical Reports Server (NTRS)

Baldridge, P. E. (Principal Investigator); Goesling, P. H.; Martin, T. A.; Wukelic, G. E.; Stephan, J. G.; Smail, H. E.; Ebbert, T. F.

1975-01-01

The author has identified the following significant results. The use of Skylab imagery for total area woodland surveys was found to be more accurate and cheaper than conventional surveys using aerial photo-plot techniques. Machine-aided (primarily density slicing) analyses of Skylab 190A and 190B color and infrared color photography demonstrated the feasibility of using such data for differentiating major timber classes including pines, hardwoods, mixed, cut, and brushland providing such analyses are made at scales of 1:24,000 and larger. Manual and machine-assisted image analysis indicated that spectral and spatial capabilities of Skylab EREP photography are adequate to distinguish most parameters of current, coal surface mining concern associated with: (1) active mining, (2) orphan lands, (3) reclaimed lands, and (4) active reclamation. Excellent results were achieved when comparing Skylab and aerial photographic interpretations of detailed surface mining features. Skylab photographs when combined with other data bases (e.g., census, agricultural land productivity, and transportation networks), provide a comprehensive, meaningful, and integrated view of major elements involved in the urbanization/encroachment process.

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

Electroflotation

NASA Astrophysics Data System (ADS)

Chen, Xueming; Chen, Guohua

Electroflotation (EF) is the flotation using electrolytically generated bubbles of hydrogen and oxygen for separating suspended substances from aqueous phases. This process was first proposed by Elmore in 1905 for flotation of valuable minerals from ores. Compared with the conventional dissolved air flotation (DAF), EF has many advantages, including high flotation efficiency, compact units, easy operation, and less maintenance. Therefore, EF is an attractive alternative to DAF. This technique has been proven very effective in treating oily wastewater or oil-water emulsion, mining wastewater, groundwater, food processing wastewater, restaurant wastewater, industrial sewage, heavy metals containing effluent, and many other water and wastewaters.

Measuring MERCI: exploring data mining techniques for examining the neurologic outcomes of stroke patients undergoing endo-vascular therapy at Erlanger Southeast Stroke Center.

PubMed

McNabb, Matthew; Cao, Yu; Devlin, Thomas; Baxter, Blaise; Thornton, Albert

2012-01-01

Mechanical Embolus Removal in Cerebral Ischemia (MERCI) has been supported by medical trials as an improved method of treating ischemic stroke past the safe window of time for administering clot-busting drugs, and was released for medical use in 2004. The importance of analyzing real-world data collected from MERCI clinical trials is key to providing insights on the effectiveness of MERCI. Most of the existing data analysis on MERCI results has thus far employed conventional statistical analysis techniques. To the best of our knowledge, advanced data analytics and data mining techniques have not yet been systematically applied. To address the issue in this thesis, we conduct a comprehensive study on employing state of the art machine learning algorithms to generate prediction criteria for the outcome of MERCI patients. Specifically, we investigate the issue of how to choose the most significant attributes of a data set with limited instance examples. We propose a few search algorithms to identify the significant attributes, followed by a thorough performance analysis for each algorithm. Finally, we apply our proposed approach to the real-world, de-identified patient data provided by Erlanger Southeast Regional Stroke Center, Chattanooga, TN. Our experimental results have demonstrated that our proposed approach performs well.

An Evaluation of Pixel-Based Methods for the Detection of Floating Objects on the Sea Surface

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Barnich, Olivier; Lapierre, Fabian; Van Droogenbroeck, Marc; Philips, Wilfried; Acheroy, Marc

2010-12-01

Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.

Environmental Decision Making on Acid Mine Drainage Issues in South Africa: An Argument for the Precautionary Principle.

PubMed

Morodi, T J; Mpofu, Charles

2017-06-28

This paper examines the issue of acid mine drainage in South Africa and environmental decision making processes that could be taken to mitigate the problem in the context of both conventional risk assessment and the precautionary principle. It is argued that conventional risk assessment protects the status quo and hence cannot be entirely relied upon as an effective tool to resolve environmental problems in the context of South Africa, a developing country with complex environmental health concerns. The complexity of the environmental issues is discussed from historical and political perspectives. An argument is subsequently made that the precautionary principle is an alternative tool, and its adoption can be used to empower local communities. This work, therefore, adds to new knowledge by problematising conventional risk assessment and proposing the framing of the acid mine drainage issues in a complex and contextual scenario of a developing country-South Africa.

Field Observations of Methane Emissions from Unconventional and Conventional Fossil Fuel Exploration

NASA Astrophysics Data System (ADS)

Dubey, M.; Lindenmaier, R.; Arata, C.; Costigan, K. R.; Frankenberg, C.; Kort, E. A.; Rahn, T. A.; Henderson, B. G.; Love, S. P.; Aubrey, A. D.

2013-12-01

Energy from methane (CH4) has lower carbon dioxide and air pollutant emissions per unit energy produced than coal or oil making it a desirable fossil fuel. Hydraulic fracturing is allowing United States to harvest the nation's abundant domestic shale gas reservoirs to achieve energy independence. However, CH4 is a gas that is hard to contain during mining, processing, transport and end-use. Therefore fugitive CH4 leaks occur that are reported in bottom up inventories by the EPA. Recent targeted field observations at selected plays have provided top down CH4 leak estimates that are larger than the reported EPA inventories. Furthermore, no long-term regional baselines are available to delineate leaks from unconventional mining operations from historical conventional mining. We will report and compare observations of fugitive CH4 leaks from conventional and unconventional mining to understand changes from technology shifts. We will report in situ and regional column measurements of CH4, its isotopologue 13CH4 and ethane (C2H6) at our Four Corners site near Farmington, NM. The region has substantial coal bed methane, conventional oil and gas production, processing and distribution with minimal hydraulic fracturing activity. We observe large enhancements in in situ and regional column CH4 with distinct time dependence. Our in situ 13CH4 observations and remote C2H6/CH4 provide strong evidence of thermogenic sources. Comparisons of WRF-simulations with emissions inventory (Edgar) with our observations show that the fugitive CH4 leaks from conventional mining are 3 times greater than reported. We also compare in situ mobile surveys of fugitive CH4 and 13CH4 leak signals in basins with conventional (San Juan) mining and unconventional (Permian and Powder River) mining. A large number of active and closed wells were sampled in these regions. Furthermore, play scale surveys on public roads allowed us to gain a regional perspective. The composition of atmospheric 13CH4 observed in the Powder River basin was lighter than the Permian and San Juan basins indicating a higher microbial generated fraction. More extensive and larger CH4 enhancements were measured in the Permian basin that could be a result of the large expansion of unconventional oil and gas production in this region. However, there are variations amongst wells and plays suggesting that operator practices and reservoir formation play a role in determining the fugitive leaks.

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

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

40 CFR 144.81 - Does this subpart apply to me?

Code of Federal Regulations, 2013 CFR

2013-07-01

... electric power; (12) Wells used for solution mining of conventional mines such as stopes leaching; (13... auto body repair shop, automotive repair shop, new and used car dealership, specialty repair shop (e.g...

40 CFR 144.81 - Does this subpart apply to me?

Code of Federal Regulations, 2012 CFR

2012-07-01

... electric power; (12) Wells used for solution mining of conventional mines such as stopes leaching; (13... auto body repair shop, automotive repair shop, new and used car dealership, specialty repair shop (e.g...

40 CFR 144.81 - Does this subpart apply to me?

Code of Federal Regulations, 2011 CFR

2011-07-01

... electric power; (12) Wells used for solution mining of conventional mines such as stopes leaching; (13... auto body repair shop, automotive repair shop, new and used car dealership, specialty repair shop (e.g...

Proceedings, 95th regular meeting: The Rocky Mountain Coal Mining Institute

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

Finnie, D.G.

1999-07-01

In addition to the nine convention papers published in these proceedings, information is given on the membership and organization of the Rocky Mountain Coal Mining Institute. The papers are concerned with the economics and management of coal companies, occupational safety of their employees, public anxiety of the environmental impacts of surface mining, and contracting for mining equipment maintenance. Papers have been processed separately for inclusion on the data base.

A primer to frequent itemset mining for bioinformatics

PubMed Central

Naulaerts, Stefan; Meysman, Pieter; Bittremieux, Wout; Vu, Trung Nghia; Vanden Berghe, Wim; Goethals, Bart

2015-01-01

Over the past two decades, pattern mining techniques have become an integral part of many bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining techniques designed to identify elements that frequently co-occur. An archetypical example is the identification of products that often end up together in the same shopping basket in supermarket transactions. A number of algorithms have been developed to address variations of this computationally non-trivial problem. Frequent itemset mining techniques are able to efficiently capture the characteristics of (complex) data and succinctly summarize it. Owing to these and other interesting properties, these techniques have proven their value in biological data analysis. Nevertheless, information about the bioinformatics applications of these techniques remains scattered. In this primer, we introduce frequent itemset mining and their derived association rules for life scientists. We give an overview of various algorithms, and illustrate how they can be used in several real-life bioinformatics application domains. We end with a discussion of the future potential and open challenges for frequent itemset mining in the life sciences. PMID:24162173

APPLYING DATA MINING APPROACHES TO FURTHER ...

EPA Pesticide Factsheets

This dataset will be used to illustrate various data mining techniques to biologically profile the chemical space. This dataset will be used to illustrate various data mining techniques to biologically profile the chemical space.

A systematic mapping study of process mining

NASA Astrophysics Data System (ADS)

Maita, Ana Rocío Cárdenas; Martins, Lucas Corrêa; López Paz, Carlos Ramón; Rafferty, Laura; Hung, Patrick C. K.; Peres, Sarajane Marques; Fantinato, Marcelo

2018-05-01

This study systematically assesses the process mining scenario from 2005 to 2014. The analysis of 705 papers evidenced 'discovery' (71%) as the main type of process mining addressed and 'categorical prediction' (25%) as the main mining task solved. The most applied traditional technique is the 'graph structure-based' ones (38%). Specifically concerning computational intelligence and machine learning techniques, we concluded that little relevance has been given to them. The most applied are 'evolutionary computation' (9%) and 'decision tree' (6%), respectively. Process mining challenges, such as balancing among robustness, simplicity, accuracy and generalization, could benefit from a larger use of such techniques.

To Walk the Earth in Safety: The United States’ Commitment to Humanitarian Mine Action and Conventional Weapons Destruction

DTIC Science & Technology

2008-06-01

Organization of American States 42 Mine Action Information Center 46 Mine Detection Dog Center 48 for Southeast Europe International Trust Fund for...probes. Mine detecting dogs (MDDs), and mechanical demining tools, such as flails and tillers, are also used. Other bio-sensors such as bees and...members; the survivor must overcome both physical difficulties and feelings of inadequacy or worthlessness to regain a productive life. For these

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.

¡VAMOS! (Viable Alternative Mine Operating System) - a 'Horizon 2020' project

NASA Astrophysics Data System (ADS)

Sword, Cameron; Bodo, Balazs; Kapusniak, Stef; Bosman, Frank; Rainbird, Jenny; Silva, Eduardo

2017-04-01

The 42-month ¡VAMOS! project (Viable Alternative Mine Operating System, Grant Agreement 642477, www.vamos-project.eu), funded by the EC H2020 Programme, will enable access to high-grade EU reserves of mineral ore-bodies by developing an innovative clean and low visibility mining technique. The project will demonstrate the technological and economic viability of the underwater extraction of metallic mineral deposits which are currently technologically, economically, and environmentally unobtainable. In doing so, ¡VAMOS! hopes to encourage investment in abandoned open-pit mines and prospective mines, helping to put the EU back on a level playing field with the rest of the world in terms of access to strategically important minerals. The ¡VAMOS! concept is defined by a remotely-operated underwater mining vehicle, adapted and improved from existing subsea mining technology. Operating in tandem with an HROV, the mining vehicle will connect to a flexible riser through which slurried mined material will be pumped from the mudline to onshore dewatering facilities via a floating mobile deployment-module, on which will be fitted a bypass system linked to an LIBS, allowing real-time grade-control. Analysis of European and national regulation and stakeholder assessments found there is significant support for developing the technology among local communities and governments. An initial environmental assessment of the potential impact of the innovative mining operation concluded the project has a smaller environmental footprint than conventional mining operations: this is due to factors including the quieter operation and absence of blasting, zero water-table flux, and the higher stripping ratio enabled by higher fluid pressure acting on the sidewalls of the mine. The prototypes are currently in their construction phase following a final design freeze in October 2016. Work is now underway on the foresight visioning, economic evaluation and policy guidelines for the ¡VAMOS! methodology and technologies; the project team will be identifying key areas of research interest and assessing the micro and macroeconomic impact of ¡VAMOS!. The deadline for the completion of the underwater mining vehicle prototype is May 2017, and the HROV hardware and software is to be completed by July 2017. Site-tests will take place in the months after the build completion at a number of unique abandoned mines across Europe, with final proof of operational viability due by November 2017.

Use of hold-gro erosion control fabric in the establishment of plant species on coal mine soil.

PubMed

Day, A D; Ludeke, K L

1986-09-01

Experiments were conducted on the Black Mesa Coal Mine, Kayenta, Arizona in 1977 and 1978 to study the effectiveness of Hold-Gro Erosion Control Fabric (a product from the Gulf States Paper Corporation, Tuscaloosa, Alabama) in the establishment of plants on coal mine soil following the surface mining of coal. Four plant species were planted: (1) spring barley (Horduem vulgare L.), an annual grass (2) crested wheatgrass (Agropyron cristatum L.), a perennial grass (3) alfalfa (lucerne) (Medicago sativa L.), a perennial legume and (4) fourwing saltbush (Atriplex canescens Pursh.), a perennial shrub. Seeds of each plant species were planted in reclaimed coal mine soil in the spring of the year by both broadcast seeding (conventional culture) and the incorporation of seeds in Hold-Gro Erosion Control Fabric. Average numbers of seedlings established and percent ground cover for all species studied were higher in areas where conventional culture was used than they were in areas where seeds were incorporated in Hold-Gro Erosion Control Fabric. The incorporation of seeds in Hold-Gro Erosion Control Fabric in the establishment of plant species on coal mine soil was not an effective cultural practice in the southwestern United States.

Comparative analysis of data mining techniques for business data

NASA Astrophysics Data System (ADS)

Jamil, Jastini Mohd; Shaharanee, Izwan Nizal Mohd

2014-12-01

Data mining is the process of employing one or more computer learning techniques to automatically analyze and extract knowledge from data contained within a database. Companies are using this tool to further understand their customers, to design targeted sales and marketing campaigns, to predict what product customers will buy and the frequency of purchase, and to spot trends in customer preferences that can lead to new product development. In this paper, we conduct a systematic approach to explore several of data mining techniques in business application. The experimental result reveals that all data mining techniques accomplish their goals perfectly, but each of the technique has its own characteristics and specification that demonstrate their accuracy, proficiency and preference.

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

Utilizing hydrologic, statistical, and geochemical tools to assess uranium mobility in surface and near-surface environments

NASA Astrophysics Data System (ADS)

Naftz, D. L.; Walton-Day, K. E.; Fuller, C.; Dam, W. L.; Briggs, M. A.; Snyder, T.

2015-12-01

Legacy uranium (U) mining and processing activities have resulted in soil and water contamination on Federal, state, and tribal lands in the western United States. Sites include legacy mill sites associated with U extraction now managed by the Department of Energy and thousands of waste dumps associated with U exploration, mining, and processing. Recently (2012), over 400,000 hectares of federally managed land in northern Arizona was withdrawn from consideration of mining for a 20-year period to protect the Grand Canyon watershed from potentially adverse effects of U mineral exploration and development. Ore from active and recently active U mines in the Colorado Plateau, the Henry Mountains Complex, and the Arizona Strip is transported to the only currently (2015) active conventional mill site in the western United States, located in Utah. Previous and ongoing U.S. Geological Survey assessments to examine U mobility at a variety of legacy and active sites associated with ore exploration, extraction, and processing will be presented as field-scale examples. Topics associated with site investigations will include: (1) offsite migration of radionuclides associated with the operation of the White Mesa U mill; (2) long-term contaminant transport from legacy U waste dumps on Bureau of Land Management regulated land in Utah; (3) application of incremental soil sampling techniques to determine pre- and post-mining radionuclide levels associated with planned and operating U mines in northern Arizona; (4) application of fiber optic digital temperature sensing equipment to identify areas where shallow groundwater containing elevated U levels may be discharging to a river adjacent to a reclaimed mill site in central Wyoming; and (5) field-scale manipulation of groundwater chemistry to limit U migration from a legacy upgrader site in southeastern Utah.

Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types

PubMed Central

Austin, Peter C.; Tu, Jack V.; Ho, Jennifer E.; Levy, Daniel; Lee, Douglas S.

2014-01-01

Objective Physicians classify patients into those with or without a specific disease. Furthermore, there is often interest in classifying patients according to disease etiology or subtype. Classification trees are frequently used to classify patients according to the presence or absence of a disease. However, classification trees can suffer from limited accuracy. In the data-mining and machine learning literature, alternate classification schemes have been developed. These include bootstrap aggregation (bagging), boosting, random forests, and support vector machines. Study design and Setting We compared the performance of these classification methods with those of conventional classification trees to classify patients with heart failure according to the following sub-types: heart failure with preserved ejection fraction (HFPEF) vs. heart failure with reduced ejection fraction (HFREF). We also compared the ability of these methods to predict the probability of the presence of HFPEF with that of conventional logistic regression. Results We found that modern, flexible tree-based methods from the data mining literature offer substantial improvement in prediction and classification of heart failure sub-type compared to conventional classification and regression trees. However, conventional logistic regression had superior performance for predicting the probability of the presence of HFPEF compared to the methods proposed in the data mining literature. Conclusion The use of tree-based methods offers superior performance over conventional classification and regression trees for predicting and classifying heart failure subtypes in a population-based sample of patients from Ontario. However, these methods do not offer substantial improvements over logistic regression for predicting the presence of HFPEF. PMID:23384592

Data Mining Techniques Applied to Hydrogen Lactose Breath Test.

PubMed

Rubio-Escudero, Cristina; Valverde-Fernández, Justo; Nepomuceno-Chamorro, Isabel; Pontes-Balanza, Beatriz; Hernández-Mendoza, Yoedusvany; Rodríguez-Herrera, Alfonso

2017-01-01

Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production. Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients. Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of each of the samples taken throughout the test. Analysis of the hydrogen breath test data sets using data mining techniques has identified new patterns of hydrogen generation upon lactose absorption. We can see the potential of application of data mining techniques to clinical data sets. These results offer promising data for future research on the relations between gut microbiota produced hydrogen and its link to clinical symptoms.

Flooded Underground Coal Mines: A Significant Source of Inexpensive Geothermal Energy

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

Watzlaf, G.R.; Ackman, T.E.

2007-04-01

Many mining regions in the United States contain extensive areas of flooded underground mines. The water within these mines represents a significant and widespread opportunity for extracting low-grade, geothermal energy. Based on current energy prices, geothermal heat pump systems using mine water could reduce the annual costs for heating to over 70 percent compared to conventional heating methods (natural gas or heating oil). These same systems could reduce annual cooling costs by up to 50 percent over standard air conditioning in many areas of the country. (Formatted full-text version is released by permission of publisher)

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

NASA Astrophysics Data System (ADS)

Sharma, Anuj; Kumar Panigrahi, Prabin

2012-02-01

With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing system of the organization in identifying the accounting frauds has lead to use of specialized procedures to detect financial accounting fraud, collective known as forensic accounting. Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques based accounting fraud detection. The systematic and comprehensive literature review of the data mining techniques applicable to financial accounting fraud detection may provide a foundation to future research in this field. The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions to the problems inherent in the detection and classification of fraudulent data.

Evaluating bump control techniques through convergence monitoring

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

Campoli, A.A.

1987-07-01

A coal mine bump is the violent failure of a pillar or pillars due to overstress. Retreat coal mining concentrates stresses on the pillars directly outby gob areas, and the situation becomes critical when mining a coalbed encased in rigid associated strata. Bump control techniques employed by the Olga Mine, McDowell County, WV, were evaluated through convergence monitoring in a Bureau of Mines study. Olga uses a novel pillar splitting mining method to extract 55-ft by 70-ft chain pillars, under 1,100 to 1,550 ft of overburden. Three rows of pillars are mined simultaneously to soften the pillar line and reducemore » strain energy storage capacity. Localized stress reduction (destressing) techniques, auger drilling and shot firing, induced approximately 0.1 in. of roof-to-floor convergence in ''high'' -stress pillars near the gob line. Auger drilling of a ''low''-stress pillar located between two barrier pillars produced no convergence effects.« less

40 CFR 434.74 - Effluent limitations attainable by application of the best conventional pollutant control...

Code of Federal Regulations, 2010 CFR

2010-07-01

... application of the best conventional pollutant control technology (BCT). 434.74 Section 434.74 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) EFFLUENT GUIDELINES AND STANDARDS COAL MINING POINT... Effluent limitations attainable by application of the best conventional pollutant control technology (BCT...

Use of an Annular Silicon Drift Detector (SDD) Versus a Conventional SDD Makes Phase Mapping a Practical Solution for Rare Earth Mineral Characterization.

PubMed

Teng, Chaoyi; Demers, Hendrix; Brodusch, Nicolas; Waters, Kristian; Gauvin, Raynald

2018-06-04

A number of techniques for the characterization of rare earth minerals (REM) have been developed and are widely applied in the mining industry. However, most of them are limited to a global analysis due to their low spatial resolution. In this work, phase map analyses were performed on REM with an annular silicon drift detector (aSDD) attached to a field emission scanning electron microscope. The optimal conditions for the aSDD were explored, and the high-resolution phase maps generated at a low accelerating voltage identify phases at the micron scale. In comparisons between an annular and a conventional SDD, the aSDD performed at optimized conditions, making the phase map a practical solution for choosing an appropriate grinding size, judging the efficiency of different separation processes, and optimizing a REM beneficiation flowsheet.

Deep-sea mining: potential environmental, legal, economic, and societal implications - an interdisciplinary research.

PubMed

Koschinsky, Andrea; Heinrich, Luise; Boehnke, Klaus; Cohrs, J Christopher; Markus, Till; Shani, Maor; Singh, Pradeep; Stegen, Karen Smith; Werner, Welf

2018-06-19

Deep-sea mining refers to the retrieval of marine mineral resources such as manganese nodules, ferromanganese crusts and seafloor massive sulfide deposits, which contain a variety of metals that serve as crucial raw materials for a range of applications, from electronic devices to renewable energy technologies to construction materials. With the intent of decreasing dependence on imports, supporting the economy and potentially even overcoming the environmental problems related to conventional terrestrial mining, a number of public and private institutions have re-discovered their interest in exploring the prospects of deep-sea mining, which had been deemed economically and technically unfeasible in the early 1980 s. To date, many national and international research projects are grappling to understand the economic environmental, social and legal implications of potential commercial deep-sea mining operations: a challenging endeavor due to the complexity of direct impacts and spill-over effects. In this paper, we present a comprehensive overview of the current state of knowledge in the aforementioned fields as well as a comparison of the impacts associated with conventional terrestrial mining. Furthermore, we identify knowledge gaps that should be urgently addressed to ensure that the world at large benefits from safe, efficient and environmentally-sound mining procedures. We conclude by highlighting the need for interdisciplinary research and international cooperation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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.

Lithologic and structural mapping of the Abiete-Toko gold district in southern Cameroon, using Landsat 7 ETM+/SRTM

NASA Astrophysics Data System (ADS)

Binam Mandeng, Eugène Pascal; Bondjè Bidjeck, Louise Marie; Takodjou Wambo, Jonas Didero; Taku, Agbor; Bineli Betsi, Thierry; Solange Ipan, Antoinette; Tchami Nfada, Lionel; Bitom Dieudonné, Lucien

2018-03-01

The geology of the Abiete-Toko gold district in South Cameroon is investigated using a combination of Landsat 7 ETM+/SRTM image processing techniques, conventional geologic field mapping and geostatistical analysis. The satellite images were treated using Principal Component Analysis and Sobel filters to separate the background noise from lithotectonic structures which were matched with field data. The results show that this area has been affected by a polyphase deformation represented by S1 foliation, Sc1 schistosity, L1 lineation, S2 foliation, F2 folds, and F3 shear zones and faults. A detailed analysis of all the structures led to the identification of two major networks of dextral and sinistral shear zones oriented WNW-ESE and NE-SW, respectively. These results may serve in mining prospection, especially in the search for tectonically controlled primary mineralization and so may significantly guide the exploration of primary gold mineralization in the Abiete-Toko area subjected to years of artisanal gold mining.

A strategy for selecting data mining techniques in metabolomics.

PubMed

Banimustafa, Ahmed Hmaidan; Hardy, Nigel W

2012-01-01

There is a general agreement that the development of metabolomics depends not only on advances in chemical analysis techniques but also on advances in computing and data analysis methods. Metabolomics data usually requires intensive pre-processing, analysis, and mining procedures. Selecting and applying such procedures requires attention to issues including justification, traceability, and reproducibility. We describe a strategy for selecting data mining techniques which takes into consideration the goals of data mining techniques on the one hand, and the goals of metabolomics investigations and the nature of the data on the other. The strategy aims to ensure the validity and soundness of results and promote the achievement of the investigation goals.

Data mining techniques for assisting the diagnosis of pressure ulcer development in surgical patients.

PubMed

Su, Chao-Ton; Wang, Pa-Chun; Chen, Yan-Cheng; Chen, Li-Fei

2012-08-01

Pressure ulcer is a serious problem during patient care processes. The high risk factors in the development of pressure ulcer remain unclear during long surgery. Moreover, past preventive policies are hard to implement in a busy operation room. The objective of this study is to use data mining techniques to construct the prediction model for pressure ulcers. Four data mining techniques, namely, Mahalanobis Taguchi System (MTS), Support Vector Machines (SVMs), decision tree (DT), and logistic regression (LR), are used to select the important attributes from the data to predict the incidence of pressure ulcers. Measurements of sensitivity, specificity, F(1), and g-means were used to compare the performance of four classifiers on the pressure ulcer data set. The results show that data mining techniques obtain good results in predicting the incidence of pressure ulcer. We can conclude that data mining techniques can help identify the important factors and provide a feasible model to predict pressure ulcer development.

Estimating procedure times for surgeries by determining location parameters for the lognormal model.

PubMed

Spangler, William E; Strum, David P; Vargas, Luis G; May, Jerrold H

2004-05-01

We present an empirical study of methods for estimating the location parameter of the lognormal distribution. Our results identify the best order statistic to use, and indicate that using the best order statistic instead of the median may lead to less frequent incorrect rejection of the lognormal model, more accurate critical value estimates, and higher goodness-of-fit. Using simulation data, we constructed and compared two models for identifying the best order statistic, one based on conventional nonlinear regression and the other using a data mining/machine learning technique. Better surgical procedure time estimates may lead to improved surgical operations.

Introduction to the JASIST Special Topic Issue on Web Retrieval and Mining: A Machine Learning Perspective.

ERIC Educational Resources Information Center

Chen, Hsinchun

2003-01-01

Discusses information retrieval techniques used on the World Wide Web. Topics include machine learning in information extraction; relevance feedback; information filtering and recommendation; text classification and text clustering; Web mining, based on data mining techniques; hyperlink structure; and Web size. (LRW)

Lunar site characterization and mining

NASA Technical Reports Server (NTRS)

Glass, Charles E.

1992-01-01

Lunar mining requirements do not appear to be excessively demanding in terms of volume of material processed. It seems clear, however, that the labor-intensive practices that characterize terrestrial mining will not suffice at the low-gravity, hard-vacuum, and inaccessible sites on the Moon. New research efforts are needed in three important areas: (1) to develop high-speed, high-resolution through-rock vision systems that will permit more detailed and efficient mine site investigation and characterization; (2) to investigate the impact of lunar conditions on our ability to convert conventional mining and exploration equipment to lunar prototypes; and (3) to develop telerobotic or fully robotic mining systems for operations on the Moon and other bodies in the inner solar system. Other aspects of lunar site characterization and mining are discussed.

Sizing criteria for a low footprint passive mine water treatment system.

PubMed

Sapsford, D J; Williams, K P

2009-02-01

The objective of this paper is to present data from a novel vertical flow mine water treatment system, demonstrate how these data can be used to generate sizing formulae for this technology, and present a comparison between the size of system based on these formulae and those of conventionally designed passive systems. The paper focuses on passive treatment of circum-neutral ferruginous mine waters bearing up to 50 mgl(-1) of iron in either ferrous or ferric form. The Vertical Flow Reactor (VFR) operates by passing mine water down through an accreting bed of ochre, the ochre bed being responsible for the intensification of iron removal by self-filtration and/or autocatalytic iron oxidation and precipitation. Key to the design and operation of the VFR system is the decrease in permeability in this ochre bed over time. The paper demonstrates that the VFR system can remove iron at many times the 10 g/m2/day removal rate - an often employed figure for the sizing of aerobic settling ponds and wetlands. The paper demonstrates that VFRs are viable and novel passive treatment system for mine waters with a smaller footprint than conventional systems.

Identification of Response Options to Artisanal and Small-Scale Gold Mining (ASGM) in Ghana via the Delphi Process.

PubMed

Basu, Avik; Phipps, Sean; Long, Rachel; Essegbey, George; Basu, Niladri

2015-09-10

The Delphi technique is a means of facilitating discussion among experts in order to develop consensus, and can be used for policy formulation. This article describes a modified Delphi approach in which 27 multi-disciplinary academics and 22 stakeholders from Ghana and North America were polled about ways to address negative effects of small-scale gold mining (ASGM) in Ghana. In early 2014, the academics, working in disciplinary groups, synthesized 17 response options based on data aggregated during an Integrated Assessment of ASGM in Ghana. The researchers participated in two rounds of Delphi polling in March and April 2014, during which 17 options were condensed into 12. Response options were rated via a 4-point Likert scale in terms of benefit (economic, environmental, and benefit to people) and feasibility (economic, social/cultural, political, and implementation). The six highest-scoring options populated a third Delphi poll, which 22 stakeholders from diverse sectors completed in April 2015. The academics and stakeholders also prioritized the response options using ranking exercises. The technique successfully gauged expert opinion on ASGM, and helped identify potential responses, policies and solutions for the sector. This is timely given that improvement to the ASGM sector is an important component within the UN Minamata Convention.

Identification of Response Options to Artisanal and Small-Scale Gold Mining (ASGM) in Ghana via the Delphi Process

PubMed Central

Basu, Avik; Phipps, Sean; Long, Rachel; Essegbey, George; Basu, Niladri

2015-01-01

The Delphi technique is a means of facilitating discussion among experts in order to develop consensus, and can be used for policy formulation. This article describes a modified Delphi approach in which 27 multi-disciplinary academics and 22 stakeholders from Ghana and North America were polled about ways to address negative effects of small-scale gold mining (ASGM) in Ghana. In early 2014, the academics, working in disciplinary groups, synthesized 17 response options based on data aggregated during an Integrated Assessment of ASGM in Ghana. The researchers participated in two rounds of Delphi polling in March and April 2014, during which 17 options were condensed into 12. Response options were rated via a 4-point Likert scale in terms of benefit (economic, environmental, and benefit to people) and feasibility (economic, social/cultural, political, and implementation). The six highest-scoring options populated a third Delphi poll, which 22 stakeholders from diverse sectors completed in April 2015. The academics and stakeholders also prioritized the response options using ranking exercises. The technique successfully gauged expert opinion on ASGM, and helped identify potential responses, policies and solutions for the sector. This is timely given that improvement to the ASGM sector is an important component within the UN Minamata Convention. PMID:26378557

Estimated water requirements for the conventional flotation of copper ores

USGS Publications Warehouse

Bleiwas, Donald I.

2012-01-01

This report provides a perspective on the amount of water used by a conventional copper flotation plant. Water is required for many activities at a mine-mill site, including ore production and beneficiation, dust and fire suppression, drinking and sanitation, and minesite reclamation. The water required to operate a flotation plant may outweigh all of the other uses of water at a mine site, [however,] and the need to maintain a water balance is critical for the plant to operate efficiently. Process water may be irretrievably lost or not immediately available for reuse in the beneficiation plant because it has been used in the production of backfill slurry from tailings to provide underground mine support; because it has been entrapped in the tailings stored in the TSF, evaporated from the TSF, or leaked from pipes and (or) the TSF; and because it has been retained as moisture in the concentrate. Water retained in the interstices of the tailings and the evaporation of water from the surface of the TSF are the two most significant contributors to water loss at a conventional flotation circuit facility.

The Mercury Problem in Artisanal and Small‐Scale Gold Mining

PubMed Central

2018-01-01

Abstract Mercury‐dependent artisanal and small‐scale gold mining (ASGM) is the largest source of mercury pollution on Earth. In this practice, elemental mercury is used to extract gold from ore as an amalgam. The amalgam is typically isolated by hand and then heated—often with a torch or over a stove—to distill the mercury and isolate the gold. Mercury release from tailings and vaporized mercury exceed 1000 tonnes each year from ASGM. The health effects on the miners are dire, with inhaled mercury leading to neurological damage and other health issues. The communities near these mines are also affected due to mercury contamination of water and soil and subsequent accumulation in food staples, such as fish—a major source of dietary protein in many ASGM regions. The risks to children are also substantial, with mercury emissions from ASGM resulting in both physical and mental disabilities and compromised development. Between 10 and 19 million people use mercury to mine for gold in more than 70 countries, making mercury pollution from ASGM a global issue. With the Minamata Convention on Mercury entering force this year, there is political motivation to help overcome the problem of mercury in ASGM. In this effort, chemists can play a central role. Here, the problem of mercury in ASGM is reviewed with a discussion on how the chemistry community can contribute solutions. Introducing portable and low‐cost mercury sensors, inexpensive and scalable remediation technologies, novel methods to prevent mercury uptake in fish and food crops, and efficient and easy‐to‐use mercury‐free mining techniques are all ways in which the chemistry community can help. To meet these challenges, it is critical that new technologies or techniques are low‐cost and adaptable to the remote and under‐resourced areas in which ASGM is most common. The problem of mercury pollution in ASGM is inherently a chemistry problem. We therefore encourage the chemistry community to consider and address this issue that affects the health of millions of people. PMID:29314284

The Mercury Problem in Artisanal and Small-Scale Gold Mining.

PubMed

Esdaile, Louisa J; Chalker, Justin M

2018-05-11

Mercury-dependent artisanal and small-scale gold mining (ASGM) is the largest source of mercury pollution on Earth. In this practice, elemental mercury is used to extract gold from ore as an amalgam. The amalgam is typically isolated by hand and then heated-often with a torch or over a stove-to distill the mercury and isolate the gold. Mercury release from tailings and vaporized mercury exceed 1000 tonnes each year from ASGM. The health effects on the miners are dire, with inhaled mercury leading to neurological damage and other health issues. The communities near these mines are also affected due to mercury contamination of water and soil and subsequent accumulation in food staples, such as fish-a major source of dietary protein in many ASGM regions. The risks to children are also substantial, with mercury emissions from ASGM resulting in both physical and mental disabilities and compromised development. Between 10 and 19 million people use mercury to mine for gold in more than 70 countries, making mercury pollution from ASGM a global issue. With the Minamata Convention on Mercury entering force this year, there is political motivation to help overcome the problem of mercury in ASGM. In this effort, chemists can play a central role. Here, the problem of mercury in ASGM is reviewed with a discussion on how the chemistry community can contribute solutions. Introducing portable and low-cost mercury sensors, inexpensive and scalable remediation technologies, novel methods to prevent mercury uptake in fish and food crops, and efficient and easy-to-use mercury-free mining techniques are all ways in which the chemistry community can help. To meet these challenges, it is critical that new technologies or techniques are low-cost and adaptable to the remote and under-resourced areas in which ASGM is most common. The problem of mercury pollution in ASGM is inherently a chemistry problem. We therefore encourage the chemistry community to consider and address this issue that affects the health of millions of people. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Evaluation of Aster Images for Characterization and Mapping of Amethyst Mining Residues

NASA Astrophysics Data System (ADS)

Markoski, P. R.; Rolim, S. B. A.

2012-07-01

The objective of this work was to evaluate the potential of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), subsystems VNIR (Visible and Near Infrared) and SWIR (Short Wave Infrared) images, for discrimination and mapping of amethyst mining residues (basalt) in the Ametista do Sul Region, Rio Grande do Sul State, Brazil. This region provides the most part of amethyst mining of the World. The basalt is extracted during the mining process and deposited outside the mine. As a result, mounts of residues (basalt) rise up. These mounts are many times smaller than ASTER pixel size (VNIR - 15 meters and SWIR - 30 meters). Thus, the pixel composition becomes a mixing of various materials, hampering its identification and mapping. Trying to solve this problem, multispectral algorithm Maximum Likelihood (MaxVer) and the hyperspectral technique SAM (Spectral Angle Mapper) were used in this work. Images from ASTER subsystems VNIR and SWIR were used to perform the classifications. SAM technique produced better results than MaxVer algorithm. The main error found by the techniques was the mixing between "shadow" and "mining residues/basalt" classes. With the SAM technique the confusion decreased because it employed the basalt spectral curve as a reference, while the multispectral techniques employed pixels groups that could have spectral mixture with other targets. The results showed that in tropical terrains as the study area, ASTER data can be efficacious for the characterization of mining residues.

Reduction of airborne radioactive dust by means of a charged water spray.

PubMed

Bigu, J; Grenier, M G

1989-07-01

An electrostatic precipitator based on charged water spray technology has been used in an underground uranium mine to control long-lived radioactive dust and short-lived aerosol concentration in a mine gallery where dust from a rock breaking/ore transportation operation was discharged. Two main sampling stations were established: one upstream of the dust precipitator and one downstream. In addition, dust samplers were placed at different locations between the dust discharge and the end of the mine gallery. Long-lived radioactive dust was measured using cascade impactors and nylon cyclone dust samplers, and measurement of the radioactivity on the samples was carried out by conventional methods. Radon and thoron progeny were estimated using standard techniques. Experiments were conducted under a variety of airflow conditions. A maximum radioactive dust reduction of about 40% (approximately 20% caused by gravitational settling) at a ventilation rate of 0.61 m3/sec was obtained as a result of the combined action of water scrubbing and electrostatic precipitation by the charged water spray electrostatic precipitator. This represents the optimum efficiency attained within the range of ventilation rates investigated. The dust reduction efficiency of the charged water spray decreased with increasing ventilation rate, i.e., decreasing air residence time, and hence, reduced dust cloud/charged water droplets mixing time.

76 FR 51274 - Supplemental Nutrition Assistance Program: Major System Failures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-18

... data mining as necessary to determine if losses are occurring in the process of issuing benefits. It is... further by using data mining techniques on States' data or analyzing QC data for error patterns that may... conjunction with an additional sample of cases. Data mining techniques may be employed when QC data cannot...

Assessment of practicality of remote sensing techniques for a study of the effects of strip mining in Alabama

NASA Technical Reports Server (NTRS)

Hughes, T. H.; Dillion, A. C., III; White, J. R., Jr.; Drummond, S. E., Jr.; Hooks, W. G.

1975-01-01

Because of the volume of coal produced by strip mining, the proximity of mining operations, and the diversity of mining methods (e.g. contour stripping, area stripping, multiple seam stripping, and augering, as well as underground mining), the Warrior Coal Basin seemed best suited for initial studies on the physical impact of strip mining in Alabama. Two test sites, (Cordova and Searles) representative of the various strip mining techniques and environmental problems, were chosen for intensive studies of the correlation between remote sensing and ground truth data. Efforts were eventually concentrated in the Searles Area, since it is more accessible and offers a better opportunity for study of erosional and depositional processes than the Cordova Area.

Environmental characterisation of coal mine waste rock in the field: an example from New Zealand

NASA Astrophysics Data System (ADS)

Hughes, J.; Craw, D.; Peake, B.; Lindsay, P.; Weber, P.

2007-08-01

Characterisation of mine waste rock with respect to acid generation potential is a necessary part of routine mine operations, so that environmentally benign waste rock stacks can be constructed for permanent storage. Standard static characterisation techniques, such as acid neutralisation capacity (ANC), maximum potential acidity, and associated acid-base accounting, require laboratory tests that can be difficult to obtain rapidly at remote mine sites. We show that a combination of paste pH and a simple portable carbonate dissolution test, both techniques that can be done in the field in a 15 min time-frame, is useful for distinguishing rocks that are potentially acid-forming from those that are acid-neutralising. Use of these techniques could allow characterisation of mine wastes at the metre scale during mine excavation operations. Our application of these techniques to pyrite-bearing (total S = 1-4 wt%) but variably calcareous coal mine overburden shows that there is a strong correlation between the portable carbonate dissolution technique and laboratory-determined ANC measurements (range of 0-10 wt% calcite equivalent). Paste pH measurements on the same rocks are bimodal, with high-sulphur, low-calcite rocks yielding pH near 3 after 10 min, whereas high-ANC rocks yield paste pH of 7-8. In our coal mine example, the field tests were most effective when used in conjunction with stratigraphy. However, the same field tests have potential for routine use in any mine in which distinction of acid-generating rocks from acid-neutralising rocks is required. Calibration of field-based acid-base accounting characteristics of the rocks with laboratory-based static and/or kinetic tests is still necessary.

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.

Research on preventive technologies for bed-separation water hazard in China coal mines

NASA Astrophysics Data System (ADS)

Gui, Herong; Tong, Shijie; Qiu, Weizhong; Lin, Manli

2018-03-01

Bed-separation water is one of the major water hazards in coal mines. Targeted researches on the preventive technologies are of paramount importance to safe mining. This article studied the restrictive effect of geological and mining factors, such as lithological properties of roof strata, coal seam inclination, water source to bed separations, roof management method, dimensions of mining working face, and mining progress, on the formation of bed-separation water hazard. The key techniques to prevent bed-separation water-related accidents include interception, diversion, destructing the buffer layer, grouting and backfilling, etc. The operation and efficiency of each technique are corroborated in field engineering cases. The results of this study will offer reference to countries with similar mining conditions in the researches on bed-separation water burst and hazard control in coal mines.

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.

Evaluation of the Kloswall longwall mining system

NASA Astrophysics Data System (ADS)

Guay, P. J.

1982-04-01

A new longwal mining system specifically designed to extract a very deep web (48 inches or deeper) from a longwall panel was studied. Productivity and cost analysis comparing the new mining system with a conventional longwall operation taking a 30 inch wide web is presented. It is shown that the new system will increase annual production and return on investment in most cases. Conceptual drawings and specifications for a high capacity three drum shearer and a unique shield type of roof support specifically designed for very wide web operation are reported. The advantages and problems associated with wide web mining in general and as they relate specifically to the equipment selected for the new mining system are discussed.

Survey of Natural Language Processing Techniques in Bioinformatics.

PubMed

Zeng, Zhiqiang; Shi, Hua; Wu, Yun; Hong, Zhiling

2015-01-01

Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we aim to search for knowledge on biology, retrieve references using text mining methods, and reconstruct databases. For example, protein-protein interactions and gene-disease relationship can be mined from PubMed. Then, we analyze the applications of text mining and natural language processing techniques in bioinformatics, including predicting protein structure and function, detecting noncoding RNA. Finally, numerous methods and applications, as well as their contributions to bioinformatics, are discussed for future use by text mining and natural language processing researchers.

76 FR 5216 - Notice of Availability of Final Supplemental Environmental Impact Statement for the Nichols Ranch...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-28

... Uranium Recovery Project, located in the Pumpkin Buttes Uranium Mining District within the Powder River.... Alternatives that were considered, but were eliminated from detailed analysis, include conventional mining and... an Agencywide Documents and Management System (ADAMS), which provides text and image files of the NRC...

Comparing digital data processing techniques for surface mine and reclamation monitoring

NASA Technical Reports Server (NTRS)

Witt, R. G.; Bly, B. G.; Campbell, W. J.; Bloemer, H. H. L.; Brumfield, J. O.

1982-01-01

The results of three techniques used for processing Landsat digital data are compared for their utility in delineating areas of surface mining and subsequent reclamation. An unsupervised clustering algorithm (ISOCLS), a maximum-likelihood classifier (CLASFY), and a hybrid approach utilizing canonical analysis (ISOCLS/KLTRANS/ISOCLS) were compared by means of a detailed accuracy assessment with aerial photography at NASA's Goddard Space Flight Center. Results show that the hybrid approach was superior to the traditional techniques in distinguishing strip mined and reclaimed areas.

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

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.

Ten million tragedies, one step at a time

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

Wurst, J.

Lacking the drama of nuclear weapons, ballistic missiles, or handguns, land mines have generally escaped professional and public attention. As land mines begin to be perceived as obstacles to post-war peacebuilding, some humanitarian groups and a few governments are preparing to fight the production and distribution of these weapons. Last year, a coalition of humanitarian groups including Human Rights Watch, Handicap International, Physicians for Human Rights, and the Vietman Veterans of America Foundation (VVAF) launched an international campaign to ban the production and sale of mines; the United Nations began exploring its options, and some governments called for strengthening anmore » existing convention that was designed to control mines. This article describes the types of land mines and ways in which they are used, estimates some numbers of people injured by land mines in various conflicts, and discusses the market for land mines. Measures for exposing the land mine business and for clearing existing mines are discussed.« less

Data Mining in Child Welfare.

ERIC Educational Resources Information Center

Schoech, Dick; Quinn, Andrew; Rycraft, Joan R.

2000-01-01

Examines the historical and larger context of data mining and describes data mining processes, techniques, and tools. Illustrates these using a child welfare dataset concerning the employee turnover that is mined, using logistic regression and a Bayesian neural network. Discusses the data mining process, the resulting models, their predictive…

Thin seam miner/trench mining concepts for Illinois Basin surface coal mines

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

Caudle, R.D.; Lall, V.

1985-07-01

A hybrid surface/underground mining concept, trench-auger mining is an attempt to increase the depth to which coal seams can be surface mined economically by reducing the amount of overburden which must be removed and reclaimed. In this concept the coal seam is first exposed by digging a series of parallel trenches 400 to 1200 ft apart with conventional surface mining equipment. After surface mining the coal from the bottom of the trench, the coal under the surface between the trenches would be extracted with extended-depth augers, operating from the bottoms of the trenches. The RSV Mining Equipment Co. of Hollandmore » has developed a Thin Seam Miner (TSM). The TSM is essentially a remotely controlled, continuous underground mining machine. The hydraulically driven drum cutter head and coal handling auger flights can be operated from a distance outside the underground mine workings. The purpose of this study is to develop and evaluate Thin Seam Miner/Trench Mining (TSM/TM) concepts for use under conditions existing in the Illinois Coal Basin.« less

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

Alternatives to Anti-Personnel Landmines (Solutions de remplacement aux mines antipersonnel)

DTIC Science & Technology

2003-05-01

remplacement ont un prix : elles sont plus pesantes sur le plan logistique et impliquent des risques opérationnels pour les forces de l’OTAN. En...très importante, de l’interopérabilité dans le transfert de secteurs qui ont été minés par un pays non-signataire de la Convention d’Ottawa. Le...SEINE CEDEX, FRANCE RTO TECHNICAL REPORT 40(I) Alternatives to Anti-Personnel Landmines (Solutions de remplacement aux mines antipersonnel) Military

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.

Transport of explosives I: TNT in soil and its equilibrium vapor

NASA Astrophysics Data System (ADS)

Baez, Bibiana; Correa, Sandra N.; Hernandez-Rivera, Samuel P.; de Jesus, Maritza; Castro, Miguel E.; Mina, Nairmen; Briano, Julio G.

2004-09-01

Landmine detection is an important task for military operations and for humanitarian demining. Conventional methods for landmine detection involve measurements of physical properties. Several of these methods fail on the detection of modern mines with plastic enclosures. Methods based on the detection signature explosives chemicals such as TNT and DNT are specific to landmines and explosive devices. However, such methods involve the measurements of the vapor trace, which can be deceiving of the actual mine location because of the complex transport phenomena that occur in the soil neighboring the buried landmine. We report on the results of the study of the explosives subject to similar environmental conditions as the actual mines. Soil samples containing TNT were used to study the effects of aging, temperature and moisture under controlled conditions. The soil used in the investigation was Ottawa sand. A JEOL GCMate II gas chromatograph +/- mass spectrometer coupled to a Tunable Electron Energy Monochromator (TEEM-GC/MS) was used to develop the method of analysis of explosives under enhanced detection conditions. Simultaneously, a GC with micro cell 63Ni, Electron Capture Detector (μECD) was used for analysis of TNT in sand. Both techniques were coupled with Solid-Phase Micro Extraction (SPME) methodology to collect TNT doped sand samples. The experiments were done in both, headspace and immersion modes of SPME for sampling of explosives. In the headspace experiments it was possible to detect appreciable TNT vapors as early as 1 hour after of preparing the samples, even at room temperature (20 °C). In the immersion experiments, I-SPME technique allowed for the detection of concentrations as low as 0.010 mg of explosive per kilogram of soil.

Mössbauer, TEM/SAED and XRD investigation on waste dumps of the Valea lui Stan gold mines

NASA Astrophysics Data System (ADS)

Constantinescu, Serban Grigore; Udubasa, Sorin S.; Udubasa, Gheorghe; Kuncser, Victor; Popescu-Pogrion, Nicoleta; Mercioniu, Ionel; Feder, Marcel

2012-03-01

The complementary investigation techniques, Mössbauer spectroscopy, transmission electron microscopy with selected area electron diffraction (TEM/SAED), X-ray diffraction (XRD) have been used to investigate the fate of the Valea lui Stan, Romania, gold-ore nanoscale-minerals during the long time of residence in the waste dumps. The preliminary investigations showed such waste dumps to contain significant amount of metals which cannot be identified by conventional methods. An intense research activity started up in order to evaluate the possibilities to recycle Valea lui Stan waste dumps and to recover metals by chemical or phytoextraction procedures. The waste dumps naturally show different mineral constituents with clay minerals as major phases, observed by XRD-technique. Although the waste dumps materials have whitish-yellowish colours, MÖSSBAUER technique evidences the presence of the finely dispersed iron bearing minerals. The authors are focusing to inspect and analyze Fe-compounds in the samples collected from Valea lui Stan's waste dumps in order to identify the magnetic phases by Mössbauer technique.

Comparison of soil pollution concentrations determined using AAS and portable XRF techniques.

PubMed

Radu, Tanja; Diamond, Dermot

2009-11-15

Past mining activities in the area of Silvermines, Ireland, have resulted in heavily polluted soils. The possibility of spreading pollution to the surrounding areas through dust blow-offs poses a potential threat for the local communities. Conventional environmental soil and dust analysis techniques are very slow and laborious and consequently there is a need for fast and accurate analytical methods, which can provide real-time in situ pollution mapping. Laboratory-based aqua regia acid digestion of the soil samples collected in the area followed by the atomic absorption spectrophotometry (AAS) analysis confirmed very high pollution, especially by Pb, As, Cu, and Zn. In parallel, samples were analyzed using portable X-ray fluorescence radioisotope and miniature tube powered (XRF) NITON instruments and their performance was compared. Overall, the portable XRF instrument gave excellent correlation with the laboratory-based reference AAS method.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

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.

Edu-Mining for Book Recommendation for Pupils

ERIC Educational Resources Information Center

Nagata, Ryo; Takeda, Keigo; Suda, Koji; Kakegawa, Junichi; Morihiro, Koichiro

2009-01-01

This paper proposes a novel method for recommending books to pupils based on a framework called Edu-mining. One of the properties of the proposed method is that it uses only loan histories (pupil ID, book ID, date of loan) whereas the conventional methods require additional information such as taste information from a great number of users which…

Synergies of solar energy use in the desalination of seawater: A case study in northern Chile

NASA Astrophysics Data System (ADS)

Servert, Jorge F.; Cerrajero, Eduardo; Fuentealba, Edward L.

2016-05-01

The mining industry is a great consumer of water for hydrometallurgical processes. Despite the efforts in minimizing the use of fresh water through reuse, recycling and process intensification, water demand for mining is expected to rise a 40% from 2013 to 2020. For seawater to be an alternative to groundwater, it must be pumped up to the mine (thousands of meters uphill) and desalinated. These processes require intensive energy and investment in desalination and piping/pumping facilities. A conventional solution for this process would be desalination by reverse osmosis at sea level, powered by electricity from the grid, and further pumping of the desalinated water uphill. This paper compares the feasibility of two solar technologies versus the "conventional" option. LCOW (Levelized Cost of Water) was used as a comparative indicator among the studied solutions, with values for a lifetime of 10, 15, 20 and 25 years, calculated using a real discount rate equal to 12%. The LCOW is lower in all cases for the RO + grid solution. The cost of desalination, ignoring the contribution of pumping, is similar for the three technologies from twenty years of operation. The use of solar energy to desalinate sea water for consumption in the mines of the Atacama region is technically feasible. However, due to the extra costs from pumping whole seawater, and not just the desalinated water, solar solutions are less competitive than the conventional process.

Explosion-assisted preparation of dispersed gold-bearing different-grade ore for selective mining

NASA Astrophysics Data System (ADS)

Trubachev, AI; Zykov, NV

2017-02-01

It is found that there are transient zones (between quality and off-quality ore areas) with the respective content of useful component in an ore body, and a variant of explosive treatment of such zones before the selective mining is put forward. Practicability of two processing technologies is evaluated: processing of high-grade and low-grade ore from the transient zones and heap leaching of metals from the low-grade and impoverished ore. Open mining technology is conventional truck-and-shovel scheme, with distributed ore flows to processing plant and (or) to heap leaching, which generally enhances the mine efficiency.

A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

NASA Astrophysics Data System (ADS)

Demigha, Souâd.

2016-03-01

The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

Proceedings: Fourth Workshop on Mining Scientific Datasets

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

Kamath, C

Commercial applications of data mining in areas such as e-commerce, market-basket analysis, text-mining, and web-mining have taken on a central focus in the JCDD community. However, there is a significant amount of innovative data mining work taking place in the context of scientific and engineering applications that is not well represented in the mainstream KDD conferences. For example, scientific data mining techniques are being developed and applied to diverse fields such as remote sensing, physics, chemistry, biology, astronomy, structural mechanics, computational fluid dynamics etc. In these areas, data mining frequently complements and enhances existing analysis methods based on statistics, exploratorymore » data analysis, and domain-specific approaches. On the surface, it may appear that data from one scientific field, say genomics, is very different from another field, such as physics. However, despite their diversity, there is much that is common across the mining of scientific and engineering data. For example, techniques used to identify objects in images are very similar, regardless of whether the images came from a remote sensing application, a physics experiment, an astronomy observation, or a medical study. Further, with data mining being applied to new types of data, such as mesh data from scientific simulations, there is the opportunity to apply and extend data mining to new scientific domains. This one-day workshop brings together data miners analyzing science data and scientists from diverse fields to share their experiences, learn how techniques developed in one field can be applied in another, and better understand some of the newer techniques being developed in the KDD community. This is the fourth workshop on the topic of Mining Scientific Data sets; for information on earlier workshops, see http://www.ahpcrc.org/conferences/. This workshop continues the tradition of addressing challenging problems in a field where the diversity of applications is matched only by the opportunities that await a practitioner.« less

CARIBIAM: constrained Association Rules using Interactive Biological IncrementAl Mining.

PubMed

Rahal, Imad; Rahhal, Riad; Wang, Baoying; Perrizo, William

2008-01-01

This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the literature, ARM has been noted for producing an overwhelming number of rules. This work proposes a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to investigators in an incremental and interactive manner.

Technique for predicting ground-water discharge to surface coal mines and resulting changes in head

USGS Publications Warehouse

Weiss, L.S.; Galloway, D.L.; Ishii, Audrey L.

1986-01-01

Changes in seepage flux and head (groundwater level) from groundwater drainage into a surface coal mine can be predicted by a technique that considers drainage from the unsaturated zone. The user applies site-specific data to precalculated head and seepage-flux profiles. Groundwater flow through hypothetical aquifer cross sections was simulated using the U.S. Geological Survey finite-difference model, VS2D, which considers variably saturated two-dimensional flow. Conceptual models considered were (1) drainage to a first cut, and (2) drainage to multiple cuts, which includes drainage effects of an area surface mine. Dimensionless head and seepage flux profiles from 246 simulations are presented. Step-by-step instructions and examples are presented. Users are required to know aquifer characteristics and to estimate size and timing of the mine operation at a proposed site. Calculated groundwater drainage to the mine is from one excavated face only. First cut considers confined and unconfined aquifers of a wide range of permeabilities; multiple cuts considers unconfined aquifers of higher permeabilities only. The technique, developed for Illinois coal-mining regions that use area surface mining and evaluated with an actual field example, will be useful in assessing potential hydrologic impacts of mining. Application is limited to hydrogeologic settings and mine operations similar to those considered. Fracture flow, recharge, and leakage are nor considered. (USGS)

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques.

PubMed

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M; Anticoi, Hernán Francisco; Guash, Eduard

2018-03-07

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector-either surface or underground mining-based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Data Mining: Going beyond Traditional Statistics

ERIC Educational Resources Information Center

Zhao, Chun-Mei; Luan, Jing

2006-01-01

The authors provide an overview of data mining, giving special attention to the relationship between data mining and statistics to unravel some misunderstandings about the two techniques. (Contains 1 figure.)

Mine Water Treatment in Hongai Coal Mines

NASA Astrophysics Data System (ADS)

Dang, Phuong Thao; Dang, Vu Chi

2018-03-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2012 CFR

2012-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2014 CFR

2014-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

30 CFR 70.207 - Bimonthly sampling; mechanized mining units.

Code of Federal Regulations, 2013 CFR

2013-07-01

... sampling device as follows: (1) Conventional section using cutting machine. On the cutting machine operator or on the cutting machine within 36 inches inby the normal working position; (2) Conventional section shooting off the solid. On the loading machine operator or on the loading machine within 36 inches inby the...

Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches.

PubMed

Zounemat-Kermani, Mohammad; Ramezani-Charmahineh, Abdollah; Adamowski, Jan; Kisi, Ozgur

2018-06-13

Chlorination, the basic treatment utilized for drinking water sources, is widely used for water disinfection and pathogen elimination in water distribution networks. Thereafter, the proper prediction of chlorine consumption is of great importance in water distribution network performance. In this respect, data mining techniques-which have the ability to discover the relationship between dependent variable(s) and independent variables-can be considered as alternative approaches in comparison to conventional methods (e.g., numerical methods). This study examines the applicability of three key methods, based on the data mining approach, for predicting chlorine levels in four water distribution networks. ANNs (artificial neural networks, including the multi-layer perceptron neural network, MLPNN, and radial basis function neural network, RBFNN), SVM (support vector machine), and CART (classification and regression tree) methods were used to estimate the concentration of residual chlorine in distribution networks for three villages in Kerman Province, Iran. Produced water (flow), chlorine consumption, and residual chlorine were collected daily for 3 years. An assessment of the studied models using several statistical criteria (NSC, RMSE, R 2 , and SEP) indicated that, in general, MLPNN has the greatest capability for predicting chlorine levels followed by CART, SVM, and RBF-ANN. Weaker performance of the data-driven methods in the water distribution networks, in some cases, could be attributed to improper chlorination management rather than the methods' capability.

In-situ identification of anti-personnel mines using acoustic resonant spectroscopy

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

Perry, R L; Roberts, R S

1999-02-01

A new technique for identifying buried Anti-Personnel Mines is described, and a set of preliminary experiments designed to assess the feasibility of this technique is presented. Analysis of the experimental results indicates that the technique has potential, but additional work is required to bring the technique to fruition. In addition to the experimental results presented here, a technique used to characterize the sensor employed in the experiments is detailed.

Responses of Terrestrial Herpetofauna to Persistent, Novel Ecosystems Resulting from Mountaintop Removal Mining

Treesearch

Jennifer M. Williams; Donald J. Brown; Petra B. Wood

2017-01-01

Mountaintop removal mining is a large-scale surface mining technique that removes entire floral and faunal communities, along with soil horizons located above coal seams. In West Virginia, the majority of this mining occurs on forested mountaintops. However, after mining ceases the land is typically reclaimed to grasslands and shrublands, resulting in novel ecosystems...

Using Open Web APIs in Teaching Web Mining

ERIC Educational Resources Information Center

Chen, Hsinchun; Li, Xin; Chau, M.; Ho, Yi-Jen; Tseng, Chunju

2009-01-01

With the advent of the World Wide Web, many business applications that utilize data mining and text mining techniques to extract useful business information on the Web have evolved from Web searching to Web mining. It is important for students to acquire knowledge and hands-on experience in Web mining during their education in information systems…

New Projections of Global Forest Carbon and Ecosystems at Risk for Increased Greenhouse Gas Emissions From Disturbance and Forest Degradation

NASA Astrophysics Data System (ADS)

Klooster, S.; Potter, C. S.; Genovese, V. B.; Gross, P. M.; Kumar, V.; Boriah, S.; Mithal, V.; Castilla-Rubio, J.

2009-12-01

Widely cited forest carbon values from look-up tables and statistical correlations with aboveground biomass have proven to be inadequate to discern details of national carbon stocks in forest pools. Similarly, global estimates based on biome-average (tropical, temperate, boreal, etc.) carbon measurements are generally insufficient to support REDD incentives (Reductions in Emission from Deforestation in Developing countries). The NASA-CASA (Carnegie-Ames-Stanford Approach) ecosystem model published by Potter et al. (1999 and 2003) offers several unique advantages for carbon accounting that cannot be provided by conventional inventory techniques. First, CASA uses continuous satellite observations to map land cover status and changes in vegetation on a monthly time interval over the past 25 years. NASA satellites observe areas that are too remote or rugged for conventional inventory-based techniques to measure. Second, CASA estimates both aboveground and belowground pools of carbon in all ecosystems (forests, shrublands, croplands, and rangelands). Carbon storage estimates for forests globally are currently being estimated for the Cisco Planetary Skin open collaborative platform (www.planetaryskin.org ) in a new series of CASA model runs using the latest input data from the NASA MODIS satellites, from 2000 to the present. We have also developed an approach for detection of large-scale ecosystem disturbance (LSED) events based on sustained declines in the same satellite greenness data used for CASA modeling. This approach is global in scope, covers more than a decade of observations, and encompasses all potential categories of major ecosystem disturbance - physical, biogenic, and anthropogenic, using advanced methods of data mining and analysis. In addition to quantifying forest areas at various levels of risk for loss of carbon storage capacity, our data mining approaches for LSED events can be adapted to detect and map biophysically unsuitable areas for deforestation worldwide and to develop carbon risk scoring algorithms that can enable large scale finance for conservation and reforestation efforts globally.

Baseline studies on the feasibility of detecting a coal/shale interface with a self-powered sensitized pick

NASA Technical Reports Server (NTRS)

Anderson, G. R., II

1981-01-01

The feasibility of utilizing a sensitized pick to discriminate between cutting coal and roof material during the longwall mining process was investigated. A conventional longwall mining pick was instrumented and cutting force magnitudes were determined for a variety of materials, including Illinois #6 coal, shale type materials, and synthetic coal/shale materials.

Characterization of seven United States coal regions. The development of optimal terrace pit coal mining systems

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

Wimer, R.L.; Adams, M.A.; Jurich, D.M.

1981-02-01

This report characterizes seven United State coal regions in the Northern Great Plains, Rocky Mountain, Interior, and Gulf Coast coal provinces. Descriptions include those of the Fort Union, Powder River, Green River, Four Corners, Lower Missouri, Illinois Basin, and Texas Gulf coal resource regions. The resource characterizations describe geologic, geographic, hydrologic, environmental and climatological conditions of each region, coal ranks and qualities, extent of reserves, reclamation requirements, and current mining activities. The report was compiled as a basis for the development of hypothetical coal mining situations for comparison of conventional and terrace pit surface mining methods, under contract to themore » Department of Energy, Contract No. DE-AC01-79ET10023, entitled The Development of Optimal Terrace Pit Coal Mining Systems.« less

Data-Mining Technologies for Diabetes: A Systematic Review

PubMed Central

Marinov, Miroslav; Mosa, Abu Saleh Mohammad; Yoo, Illhoi; Boren, Suzanne Austin

2011-01-01

Background The objective of this study is to conduct a systematic review of applications of data-mining techniques in the field of diabetes research. Method We searched the MEDLINE database through PubMed. We initially identified 31 articles by the search, and selected 17 articles representing various data-mining methods used for diabetes research. Our main interest was to identify research goals, diabetes types, data sets, data-mining methods, data-mining software and technologies, and outcomes. Results The applications of data-mining techniques in the selected articles were useful for extracting valuable knowledge and generating new hypothesis for further scientific research/experimentation and improving health care for diabetes patients. The results could be used for both scientific research and real-life practice to improve the quality of health care diabetes patients. Conclusions Data mining has played an important role in diabetes research. Data mining would be a valuable asset for diabetes researchers because it can unearth hidden knowledge from a huge amount of diabetes-related data. We believe that data mining can significantly help diabetes research and ultimately improve the quality of health care for diabetes patients. PMID:22226277

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,...

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…

A Comparative Study of Data Mining Techniques on Football Match Prediction

NASA Astrophysics Data System (ADS)

Rosli, Che Mohamad Firdaus Che Mohd; Zainuri Saringat, Mohd; Razali, Nazim; Mustapha, Aida

2018-05-01

Data prediction have become a trend in today’s business or organization. This paper is set to predict match outcomes for association football from the perspective of football club managers and coaches. This paper explored different data mining techniques used for predicting the match outcomes where the target class is win, draw and lose. The main objective of this research is to find the most accurate data mining technique that fits the nature of football data. The techniques tested are Decision Trees, Neural Networks, Bayesian Network, and k-Nearest Neighbors. The results from the comparative experiments showed that Decision Trees produced the highest average prediction accuracy in the domain of football match prediction by 99.56%.

Using text-mining techniques in electronic patient records to identify ADRs from medicine use.

PubMed

Warrer, Pernille; Hansen, Ebba Holme; Juhl-Jensen, Lars; Aagaard, Lise

2012-05-01

This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text searching of outpatient visit notes and inpatient discharge summaries to more advanced techniques involving natural language processing (NLP) of inpatient discharge summaries. Performance appeared to increase with the use of NLP, although many ADRs were still missed. Due to differences in study design and populations, various types of ADRs were identified and thus we could not make comparisons across studies. The review underscores the feasibility and potential of text mining to investigate narrative documents in EPRs for ADRs. However, more empirical studies are needed to evaluate whether text mining of EPRs can be used systematically to collect new information about ADRs. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

Using text-mining techniques in electronic patient records to identify ADRs from medicine use

PubMed Central

Warrer, Pernille; Hansen, Ebba Holme; Juhl-Jensen, Lars; Aagaard, Lise

2012-01-01

This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text searching of outpatient visit notes and inpatient discharge summaries to more advanced techniques involving natural language processing (NLP) of inpatient discharge summaries. Performance appeared to increase with the use of NLP, although many ADRs were still missed. Due to differences in study design and populations, various types of ADRs were identified and thus we could not make comparisons across studies. The review underscores the feasibility and potential of text mining to investigate narrative documents in EPRs for ADRs. However, more empirical studies are needed to evaluate whether text mining of EPRs can be used systematically to collect new information about ADRs. PMID:22122057

Post-acquisition data mining techniques for LC-MS/MS-acquired data in drug metabolite identification.

PubMed

Dhurjad, Pooja Sukhdev; Marothu, Vamsi Krishna; Rathod, Rajeshwari

2017-08-01

Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

Knowledge Discovery and Data Mining: An Overview

NASA Technical Reports Server (NTRS)

Fayyad, U.

1995-01-01

The process of knowledge discovery and data mining is the process of information extraction from very large databases. Its importance is described along with several techniques and considerations for selecting the most appropriate technique for extracting information from a particular data set.

Application of Information-Theoretic Data Mining Techniques in a National Ambulatory Practice Outcomes Research Network

PubMed Central

Wright, Adam; Ricciardi, Thomas N.; Zwick, Martin

2005-01-01

The Medical Quality Improvement Consortium data warehouse contains de-identified data on more than 3.6 million patients including their problem lists, test results, procedures and medication lists. This study uses reconstructability analysis, an information-theoretic data mining technique, on the MQIC data warehouse to empirically identify risk factors for various complications of diabetes including myocardial infarction and microalbuminuria. The risk factors identified match those risk factors identified in the literature, demonstrating the utility of the MQIC data warehouse for outcomes research, and RA as a technique for mining clinical data warehouses. PMID:16779156

Prediction of pork quality parameters by applying fractals and data mining on MRI.

PubMed

Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés; Amigo, José Manuel; Dahl, Anders B; ErsbØll, Bjarne K; Antequera, Teresa

2017-09-01

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy. Copyright © 2017. Published by Elsevier Ltd.

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

NASA Astrophysics Data System (ADS)

Park, J.; Yoo, K.

2013-12-01

For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

Restoring Forests and Associated Ecosystem Services on Appalachian Coal Surface Mines

NASA Astrophysics Data System (ADS)

Zipper, Carl E.; Burger, James A.; Skousen, Jeffrey G.; Angel, Patrick N.; Barton, Christopher D.; Davis, Victor; Franklin, Jennifer A.

2011-05-01

Surface coal mining in Appalachia has caused extensive replacement of forest with non-forested land cover, much of which is unmanaged and unproductive. Although forested ecosystems are valued by society for both marketable products and ecosystem services, forests have not been restored on most Appalachian mined lands because traditional reclamation practices, encouraged by regulatory policies, created conditions poorly suited for reforestation. Reclamation scientists have studied productive forests growing on older mine sites, established forest vegetation experimentally on recent mines, and identified mine reclamation practices that encourage forest vegetation re-establishment. Based on these findings, they developed a Forestry Reclamation Approach (FRA) that can be employed by coal mining firms to restore forest vegetation. Scientists and mine regulators, working collaboratively, have communicated the FRA to the coal industry and to regulatory enforcement personnel. Today, the FRA is used routinely by many coal mining firms, and thousands of mined hectares have been reclaimed to restore productive mine soils and planted with native forest trees. Reclamation of coal mines using the FRA is expected to restore these lands' capabilities to provide forest-based ecosystem services, such as wood production, atmospheric carbon sequestration, wildlife habitat, watershed protection, and water quality protection to a greater extent than conventional reclamation practices.

Prereduction and melting of domestic titaniferous materials

NASA Astrophysics Data System (ADS)

Nafziger, R. H.; Jordan, R. R.

1983-03-01

Two domestic ilmenites and one titaniferous magnetite were prereduced by the United States Department of the Interior, Bureau of Mines, in a batch rotary kiln with coal char to assess the feasibility of this technique in improving melting operations and subsequent electric furnace processing. All three prereduced titaniferous materials were melted satisfactorily in an electric arc furnace to produce iron as a metal suitable for further refining to steel; metallizations ranging from 63 to 83 pct of the iron oxides were achieved. The ilmenites yielded titanium enriched slags that were amenable to further processing by conventional methods. Prereduction decreased electrode consumption during furnace operation and also conserved expensive electrical energy that otherwise must be used to reduce and melt totally the entire titaniferous materials charge.

Microwave assisted hard rock cutting

DOEpatents

Lindroth, David P.; Morrell, Roger J.; Blair, James R.

1991-01-01

An apparatus for the sequential fracturing and cutting of subsurface volume of hard rock (102) in the strata (101) of a mining environment (100) by subjecting the volume of rock to a beam (25) of microwave energy to fracture the subsurface volume of rock by differential expansion; and , then bringing the cutting edge (52) of a piece of conventional mining machinery (50) into contact with the fractured rock (102).

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.

A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

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

Kevin McCarthy; Milos Manic

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presentsmore » an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.« less

Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine

NASA Astrophysics Data System (ADS)

Erdogan, Gamze; Yavuz, Mahmut

2017-12-01

The underground mine planning and design optimisation process have received little attention because of complexity and variability of problems in underground mines. Although a number of optimisation studies and software tools are available and some of them, in special, have been implemented effectively to determine the ultimate-pit limits in an open pit mine, there is still a lack of studies for optimisation of ultimate stope boundaries in underground mines. The proposed approaches for this purpose aim at maximizing the economic profit by selecting the best possible layout under operational, technical and physical constraints. In this paper, the existing three heuristic techniques including Floating Stope Algorithm, Maximum Value Algorithm and Mineable Shape Optimiser (MSO) are examined for optimisation of stope layout in a case study. Each technique is assessed in terms of applicability, algorithm capabilities and limitations considering the underground mine planning challenges. Finally, the results are evaluated and compared.

Evaluation of the environmental contamination at an abandoned mining site using multivariate statistical techniques--the Rodalquilar (Southern Spain) mining district.

PubMed

Bagur, M G; Morales, S; López-Chicano, M

2009-11-15

Unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal component analysis, factor analysis and linear discriminant analysis have been applied to water samples recollected in Rodalquilar mining district (Southern Spain) in order to identify different sources of environmental pollution caused by the abandoned mining industry. The effect of the mining activity on waters was monitored determining the concentration of eleven elements (Mn, Ba, Co, Cu, Zn, As, Cd, Sb, Hg, Au and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). The Box-Cox transformation has been used to transform the data set in normal form in order to minimize the non-normal distribution of the geochemical data. The environmental impact is affected mainly by the mining activity developed in the zone, the acid drainage and finally by the chemical treatment used for the benefit of gold.

Application of text mining for customer evaluations in commercial banking

NASA Astrophysics Data System (ADS)

Tan, Jing; Du, Xiaojiang; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

Nowadays customer attrition is increasingly serious in commercial banks. To combat this problem roundly, mining customer evaluation texts is as important as mining customer structured data. In order to extract hidden information from customer evaluations, Textual Feature Selection, Classification and Association Rule Mining are necessary techniques. This paper presents all three techniques by using Chinese Word Segmentation, C5.0 and Apriori, and a set of experiments were run based on a collection of real textual data that includes 823 customer evaluations taken from a Chinese commercial bank. Results, consequent solutions, some advice for the commercial bank are given in this paper.

Introduction to the mining of clinical data.

PubMed

Harrison, James H

2008-03-01

The increasing volume of medical data online, including laboratory data, represents a substantial resource that can provide a foundation for improved understanding of disease presentation, response to therapy, and health care delivery processes. Data mining supports these goals by providing a set of techniques designed to discover similarities and relationships between data elements in large data sets. Currently, medical data have several characteristics that increase the difficulty of applying these techniques, although there have been notable medical data mining successes. Future developments in integrated medical data repositories, standardized data representation, and guidelines for the appropriate research use of medical data will decrease the barriers to mining projects.

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

PubMed Central

Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M.; Anticoi, Hernán Francisco; Guash, Eduard

2018-01-01

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents. PMID:29518921

Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

NASA Astrophysics Data System (ADS)

Soltanmohammadi, Hossein; Osanloo, Morteza; Aghajani Bazzazi, Abbas

2009-08-01

This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.

Application of remote-sensing techniques to hydrologic studies in selected coal-mine areas of southeastern Kansas

USGS Publications Warehouse

Kenny, J.F.; McCauley, J.R.

1983-01-01

Disturbances resulting from intensive coal mining in the Cherry Creek basin of southeastern Kansas were investigated using color and color-infrared aerial photography in conjunction with water-quality data from simultaneously acquired samples. Imagery was used to identify the type and extent of vegetative cover on strip-mined lands and the extent and success of reclamation practices. Drainage patterns, point sources of acid mine drainage, and recharge areas for underground mines were located for onsite inspection. Comparison of these interpretations with water-quality data illustrated differences between the eastern and western parts of the Cherry Creek basin. Contamination in the eastern part is due largely to circulation of water from unreclaimed strip mines and collapse features through the network of underground mines and subsequent discharge of acidic drainage through seeps. Contamination in the western part is primarily caused by runoff and seepage from strip-mined lands in which surfaces have frequently been graded and limed but are generally devoid of mature stands of soil-anchoring vegetation. The successful use of aerial photography in the study of Cherry Creek basin indicates the potential of using remote-sensing techniques in studies of other coal-mined regions. (USGS)

30 CFR 282.28 - Environmental protection measures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... recent research or improved monitoring techniques. (5) When prototype test mining is proposed, the lessee...) The sampling techniques and procedures to be used to acquire the needed data and information; (ii) The... evaluation of the approved Delineation, Testing, or Mining Plan. The Director's review of the air quality...

Analyzing Teaching Performance of Instructors Using Data Mining Techniques

ERIC Educational Resources Information Center

Mardikyan, Sona; Badur, Bertain

2011-01-01

Student evaluations to measure the teaching effectiveness of instructor's are very frequently applied in higher education for many years. This study investigates the factors associated with the assessment of instructors teaching performance using two different data mining techniques; stepwise regression and decision trees. The data collected…

Monitoring and inversion on land subsidence over mining area with InSAR technique

USGS Publications Warehouse

Wang, Y.; Zhang, Q.; Zhao, C.; Lu, Z.; Ding, X.

2011-01-01

The Wulanmulun town, located in Inner Mongolia, is one of the main mining areas of Shendong Company such as Shangwan coal mine and Bulianta coal mine, which has been suffering serious mine collapse with the underground mine withdrawal. We use ALOS/PALSAR data to extract land deformation under these regions, in which Small Baseline Subsets (SBAS) method was applied. Then we compared InSAR results with the underground mining activities, and found high correlations between them. Lastly we applied Distributed Dislocation (Okada) model to invert the mine collapse mechanism. ?? 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

15 CFR 970.600 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

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.

Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

NASA Technical Reports Server (NTRS)

Bloemer, H. H. L.; Brumfield, J. O.; Campbell, W. J.; Witt, R. G.; Bly, B. G.

1981-01-01

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.

Applying Web Usage Mining for Personalizing Hyperlinks in Web-Based Adaptive Educational Systems

ERIC Educational Resources Information Center

Romero, Cristobal; Ventura, Sebastian; Zafra, Amelia; de Bra, Paul

2009-01-01

Nowadays, the application of Web mining techniques in e-learning and Web-based adaptive educational systems is increasing exponentially. In this paper, we propose an advanced architecture for a personalization system to facilitate Web mining. A specific Web mining tool is developed and a recommender engine is integrated into the AHA! system in…

COMPARISON OF DATA FROM SYNTHETIC LEACHATE AND DIRECT SAMPLING OF ACID DRAINAGE FROM MINE WASTES: IMPLICATIONS FOR MERCURY TRANSPORT AND WASTE MANAGEMENT

EPA Science Inventory

The Sulphur Bank Mercury Mine (SBMM) in Lake County, California operated from the 1860s through the 1950's. Mining for sulfur started with surface operations and progressed to shaft, then open pit techniques to obtain mercury. Mining has resulted in deposition of approximately ...

Mine Sweeping System for Magnetic and Non-Magnetic Mines.

DTIC Science & Technology

1994-12-29

be detected. One example of the latter type of system is a conventional sonar device wherein a directional beam of acoustic energy periodically...Although satisfactory for many uses, sonar devices have several inherent limitations. Nearby objects can cause echoes and these may obscure the echo of...electromagnetic signal and sends it to the preamplifier 601. The preamplifier 601 increases the strength of the received electrical signal before sending it

Life cycle Greenhouse gas emissions of current Oil Sands Technologies: surface mining and in situ applications.

PubMed

Bergerson, Joule A; Kofoworola, Oyeshola; Charpentier, Alex D; Sleep, Sylvia; Maclean, Heather L

2012-07-17

Life cycle greenhouse gas (GHG) emissions associated with two major recovery and extraction processes currently utilized in Alberta's oil sands, surface mining and in situ, are quantified. Process modules are developed and integrated into a life cycle model-GHOST (GreenHouse gas emissions of current Oil Sands Technologies) developed in prior work. Recovery and extraction of bitumen through surface mining and in situ processes result in 3-9 and 9-16 g CO(2)eq/MJ bitumen, respectively; upgrading emissions are an additional 6-17 g CO(2)eq/MJ synthetic crude oil (SCO) (all results are on a HHV basis). Although a high degree of variability exists in well-to-wheel emissions due to differences in technologies employed, operating conditions, and product characteristics, the surface mining dilbit and the in situ SCO pathways have the lowest and highest emissions, 88 and 120 g CO(2)eq/MJ reformulated gasoline. Through the use of improved data obtained from operating oil sands projects, we present ranges of emissions that overlap with emissions in literature for conventional crude oil. An increased focus is recommended in policy discussions on understanding interproject variability of emissions of both oil sands and conventional crudes, as this has not been adequately represented in previous studies.

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

ERIC Educational Resources Information Center

Hung, Jui-Long; Crooks, Steven M.

2009-01-01

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

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...

Analysis of Hospital Processes with Process Mining Techniques.

PubMed

Orellana García, Arturo; Pérez Alfonso, Damián; Larrea Armenteros, Osvaldo Ulises

2015-01-01

Process mining allows for discovery, monitoring, and improving processes identified in information systems from their event logs. In hospital environments, process analysis has been a crucial factor for cost reduction, control and proper use of resources, better patient care, and achieving service excellence. This paper presents a new component for event logs generation in the Hospital Information System or HIS, developed at University of Informatics Sciences. The event logs obtained are used for analysis of hospital processes with process mining techniques. The proposed solution intends to achieve the generation of event logs in the system with high quality. The performed analyses allowed for redefining functions in the system and proposed proper flow of information. The study exposed the need to incorporate process mining techniques in hospital systems to analyze the processes execution. Moreover, we illustrate its application for making clinical and administrative decisions for the management of hospital activities.

Subsidence monitoring within the Athens Basin (Greece) using space radar interferometric techniques

NASA Astrophysics Data System (ADS)

Parcharidis, I.; Lagios, E.; Sakkas, V.; Raucoules, D.; Feurer, D.; Mouelic, S. L.; King, C.; Carnec, C.; Novali, F.; Ferretti, A.; Capes, R.; Cooksley, G.

2006-05-01

The application of conventional SAR Interferometry (InSAR) together with the two techniques of sub-centimeteraccuracy, the Stacking and the Permanent Scatterers (PS) Interferometry, were used to study the ground deformation in the broader area of Athens for the period 1992 to 2002. Using the Stacking interfero-metricmethod, 55 ERS-1&2 SAR scenes, between 1992 and 2002, were acquired producing 264 differential interferograms. Among these only 60 were finally selected as fulfilling certain criteria. The co-seismic deforma-tionassociated with the Athens Earthquake (Mw = 5 9, September 7, 1999) was excluded from the analytical procedure in an attempt to present results of only aseismic character. In total ground subsidence results of about12 mm in the southern suburbs of Athens, but higher value of about 40 mm in the northern ones for the period 1992-2002. Based on the PS technique, a precise average annual deformation rate-map was generated for the period 1992-1999, ending just before the Athens earthquake event. Both circular and elongated-shape areas of subsidence are recognizable especially in the northern part of the Athens Basin (3-4 mm/yr), as well as at its southern part (1-3 mm/yr). In addition, a rate of 2-3 mm/yr is also yielded for some part of the Athens city center. Subsidence rates of 1-2 mm/yr are measured at the western part of the basin over an area of old mining activities, and around the newly built Syntagma Metro Station. The correlation of the observed deformation pat-ternswith respect to the spatial distribution of water pumping, older mining activities, metro line tunneling and other local geological parameters is examined and discussed.

Big data analytics in hyperspectral imaging for detection of microbial colonies on agar plates (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yoon, Seung-Chul; Park, Bosoon; Lawrence, Kurt C.

2017-05-01

Various types of optical imaging techniques measuring light reflectivity and scattering can detect microbial colonies of foodborne pathogens on agar plates. Until recently, these techniques were developed to provide solutions for hypothesis-driven studies, which focused on developing tools and batch/offline machine learning methods with well defined sets of data. These have relatively high accuracy and rapid response time because the tools and methods are often optimized for the collected data. However, they often need to be retrained or recalibrated when new untrained data and/or features are added. A big-data driven technique is more suitable for online learning of new/ambiguous samples and for mining unknown or hidden features. Although big data research in hyperspectral imaging is emerging in remote sensing and many tools and methods have been developed so far in many other applications such as bioinformatics, the tools and methods still need to be evaluated and adjusted in applications where the conventional batch machine learning algorithms were dominant. The primary objective of this study is to evaluate appropriate big data analytic tools and methods for online learning and mining of foodborne pathogens on agar plates. After the tools and methods are successfully identified, they will be applied to rapidly search big color and hyperspectral image data of microbial colonies collected over the past 5 years in house and find the most probable colony or a group of colonies in the collected big data. The meta-data, such as collection time and any unstructured data (e.g. comments), will also be analyzed and presented with output results. The expected results will be novel, big data-driven technology to correctly detect and recognize microbial colonies of various foodborne pathogens on agar plates.

New applications for phosphoric acid fuel cells

NASA Astrophysics Data System (ADS)

Stickles, R. P.; Breuer, C. T.

1983-11-01

New applications for phosphoric acid fuel cells were identified and evaluated. Candidates considered included all possibilities except grid connected electric utility applications, on site total energy systems, industrial cogeneration, opportunistic use of waste hydrogen, space and military applications, and applications smaller than 10 kW. Applications identified were screened, with the most promising subjected to technical and economic evaluation using a fuel cell and conventional power system data base developed in the study. The most promising applications appear to be the underground mine locomotive and the railroad locomotive. Also interesting are power for robotic submersibles and Arctic villages. The mine locomotive is particularly attractive since it is expected that the fuel cell could command a very high price and still be competitive with the conventionally used battery system. The railroad locomotive's attractiveness results from the (smaller) premium price which the fuel cell could command over the conventional diesel electric system based on its superior fuel efficiency, and on the large size of this market and the accompanying opportunities for manufacturing economy.

Feasibility of new ladle-treated Hadfield steel for mining purposes

NASA Astrophysics Data System (ADS)

El Fawkhry, M. K.

2018-03-01

A debate has arisen over the possibility of using a new ladle-treated Hadfield steel instead of conventional heat-treated Hadfield steel in mining applications. This debate might be solved by identifying the differences between the mechanical properties and strain-hardening properties of conventional heat-treated Hadfield steel and its counterpart ladle-treated Hadfield steel. Tensile and compression tests demonstrated that the ductility of ladle-treated Hadfield steel is similar to that of conventional heat-treated steel. However, the strain-hardening property of the ladle-treated Hadfield steel is almost two times higher than that of the heat-treated Hadfield steel. The results of this study demonstrate that the improvement of the strain-hardening behavior is attributable to the low stacking-fault energy of the main austenite matrix, which results from the high segregation coefficient of carbon and manganese solutes of the main austenite matrix into the new eutectic phase. Superior wear abrasion resistance is a potential consequence of different strain-hardening properties under low and high loads.

New applications for phosphoric acid fuel cells

NASA Technical Reports Server (NTRS)

Stickles, R. P.; Breuer, C. T.

1983-01-01

New applications for phosphoric acid fuel cells were identified and evaluated. Candidates considered included all possibilities except grid connected electric utility applications, on site total energy systems, industrial cogeneration, opportunistic use of waste hydrogen, space and military applications, and applications smaller than 10 kW. Applications identified were screened, with the most promising subjected to technical and economic evaluation using a fuel cell and conventional power system data base developed in the study. The most promising applications appear to be the underground mine locomotive and the railroad locomotive. Also interesting are power for robotic submersibles and Arctic villages. The mine locomotive is particularly attractive since it is expected that the fuel cell could command a very high price and still be competitive with the conventionally used battery system. The railroad locomotive's attractiveness results from the (smaller) premium price which the fuel cell could command over the conventional diesel electric system based on its superior fuel efficiency, and on the large size of this market and the accompanying opportunities for manufacturing economy.

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

Personal cooling in hot workings

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

Tuck, M.A.

1999-07-01

The number of mines experiencing climatic difficulties worldwide is increasing. In a large number of cases these climatic difficulties are confined to working areas only or to specific locations within working areas. Thus the problem in these mines can be described as highly localized, due to a large extent not to high rock temperatures but due to machine heat loads and low airflow rates. Under such situations conventional means of controlling the climate can be inapplicable and/or uneconomic. One possible means of achieving the required level of climatic control, to ensure worker health and safety whilst achieving economic gains, ismore » to adopt a system of active man cooling. This is the reverse of normal control techniques where the cooling power of the ventilating air is enhanced in some way. Current methods of active man cooling include ice jackets and various umbilical cord type systems. These have numerous drawbacks, such as limited useful exposure times and limitations to worker mobility. The paper suggests an alternative method of active man cooling than those currently available and reviews the design criteria for such a garment. The range of application of such a garment is discussed, under both normal and emergency situations.« less

Industrial chimney monitoring - contemporary methods

NASA Astrophysics Data System (ADS)

Kaszowska, Olga; Gruchlik, Piotr; Mika, Wiesław

2018-04-01

The paper presents knowledge acquired during the monitoring of a flue-gas stack, performed as part of technical and scientific surveillance of mining activity and its impact on industrial objects. The chimney is located in an area impacted by mining activity since the 1970s, from a coal mine which is no longer in existence. In the period of 2013-16, this area was subject to mining carried out by a mining entrepreneur who currently holds a license to excavate hard coal. Periodic measurements of the deflection of the 113-meter chimney are performed using conventional geodetic methods. The GIG used 3 methods to observe the stack: landbased 3D laser scanning, continuous deflection monitoring with a laser sensor, and drone-based visual inspections. The drone offered the possibility to closely inspect the upper sections of the flue-gas stack, which are difficult to see from the ground level.

Multivariate matrix model for source identification of inrush water: A case study from Renlou and Tongting coal mine in northern Anhui province, China

NASA Astrophysics Data System (ADS)

Zhang, Jun; Yao, Duoxi; Su, Yue

2018-02-01

Under the current situation of energy demand, coal is still one of the major energy sources in China for a certain period of time, so the task of coal mine safety production remains arduous. In order to identify the water source of the mine accurately, this article takes the example from Renlou and Tongting coal mines in the northern Anhui mining area. A total of 7 conventional water chemical indexes were selected, including Ca2+, Mg2+, Na++K+, Cl-, SO4 2-, HCO3 - and TDS, to establish a multivariate matrix model for the source identifying inrush water. The results show that the model is simple and is rarely limited by the quantity of water samples, and the recognition effect is ideal, which can be applied to the control and treatment for water inrush.

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

30 CFR 282.23 - Testing Plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, REGULATION, AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR... lessee needs more information to develop a detailed Mining Plan than is obtainable under an approved... techniques or technology or mining equipment, or to determine environmental effects by a pilot test mining...

Ultrasensitive Speciation Analysis of Mercury in Rice by Headspace Solid Phase Microextraction Using Porous Carbons and Gas Chromatography-Dielectric Barrier Discharge Optical Emission Spectrometry.

PubMed

Lin, Yao; Yang, Yuan; Li, Yuxuan; Yang, Lu; Hou, Xiandeng; Feng, Xinbin; Zheng, Chengbin

2016-03-01

Rice consumption is a primary pathway for human methylmercury (MeHg) exposure in inland mercury mining areas of Asia. In addition, the use of iodomethane, a common fumigant that significantly accelerates the methylation of mercury in soil under sunlight, could increase the MeHg exposure from rice. Conventional hyphenated techniques used for mercury speciation analysis are usually too costly for most developing countries. Consequently, there is an increased interest in the development of sensitive and inexpensive methods for the speciation of mercury in rice. In this work, gas chromatography (GC) coupled to dielectric barrier discharge optical emission spectrometry (DBD-OES) was developed for the speciation analysis of mercury in rice. Prior to GC-DBD-OES analysis, mercury species were derivatized to their volatile species with NaBPh4 and preconcentrated by headspace solid phase microextraction using porous carbons. Limits of detection of 0.5 μg kg(-1) (0.16 ng), 0.75 μg kg(-1) (0.24 ng), and 1.0 μg kg(-1) (0.34 ng) were obtained for Hg(2+), CH3Hg(+), and CH3CH2Hg(+), respectively, with relative standard deviations (RSDs) better than 5.2% and 6.8% for one fiber or fiber-to-fiber mode, respectively. Recoveries of 90-105% were obtained for the rice samples, demonstrating the applicability of the proposed technique. Owing to the small size, low power, and low gas consumption of DBD-OES as well as efficient extraction of mercury species by porous carbons headspace solid phase micro-extraction, the proposed technique provides several advantages including compactness, cost-effectiveness, and potential to couple with miniature GC to accomplish the field speciation of mercury in rice compared to conventional hyphenated techniques.

Utilization of volume correlation filters for underwater mine identification in LIDAR imagery

NASA Astrophysics Data System (ADS)

Walls, Bradley

2008-04-01

Underwater mine identification persists as a critical technology pursued aggressively by the Navy for fleet protection. As such, new and improved techniques must continue to be developed in order to provide measurable increases in mine identification performance and noticeable reductions in false alarm rates. In this paper we show how recent advances in the Volume Correlation Filter (VCF) developed for ground based LIDAR systems can be adapted to identify targets in underwater LIDAR imagery. Current automated target recognition (ATR) algorithms for underwater mine identification employ spatial based three-dimensional (3D) shape fitting of models to LIDAR data to identify common mine shapes consisting of the box, cylinder, hemisphere, truncated cone, wedge, and annulus. VCFs provide a promising alternative to these spatial techniques by correlating 3D models against the 3D rendered LIDAR data.

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.

Critical analysis of world uranium resources

USGS Publications Warehouse

Hall, Susan; Coleman, Margaret

2013-01-01

The U.S. Department of Energy, Energy Information Administration (EIA) joined with the U.S. Department of the Interior, U.S. Geological Survey (USGS) to analyze the world uranium supply and demand balance. To evaluate short-term primary supply (0–15 years), the analysis focused on Reasonably Assured Resources (RAR), which are resources projected with a high degree of geologic assurance and considered to be economically feasible to mine. Such resources include uranium resources from mines currently in production as well as resources that are in the stages of feasibility or of being permitted. Sources of secondary supply for uranium, such as stockpiles and reprocessed fuel, were also examined. To evaluate long-term primary supply, estimates of uranium from unconventional and from undiscovered resources were analyzed. At 2010 rates of consumption, uranium resources identified in operating or developing mines would fuel the world nuclear fleet for about 30 years. However, projections currently predict an increase in uranium requirements tied to expansion of nuclear energy worldwide. Under a low-demand scenario, requirements through the period ending in 2035 are about 2.1 million tU. In the low demand case, uranium identified in existing and developing mines is adequate to supply requirements. However, whether or not these identified resources will be developed rapidly enough to provide an uninterrupted fuel supply to expanded nuclear facilities could not be determined. On the basis of a scenario of high demand through 2035, 2.6 million tU is required and identified resources in operating or developing mines is inadequate. Beyond 2035, when requirements could exceed resources in these developing properties, other sources will need to be developed from less well-assured resources, deposits not yet at the prefeasibility stage, resources that are currently subeconomic, secondary sources, undiscovered conventional resources, and unconventional uranium supplies. This report’s analysis of 141 mines that are operating or are being actively developed identifies 2.7 million tU of in-situ uranium resources worldwide, approximately 2.1 million tU recoverable after mining and milling losses were deducted. Sixty-four operating mines report a total of 1.4 million tU of in-situ RAR (about 1 million tU recoverable). Seventy-seven developing mines/production centers report 1.3 million tU in-situ Reasonably Assured Resources (RAR) (about 1.1 million tU recoverable), which have a reasonable chance of producing uranium within 5 years. Most of the production is projected to come from conventional underground or open pit mines as opposed to in-situ leach mines. Production capacity in operating mines is about 76,000 tU/yr, and in developing mines is estimated at greater than 52,000 tU/yr. Production capacity in operating mines should be considered a maximum as mines seldom produce up to licensed capacity due to operational difficulties. In 2010, worldwide mines operated at 70 percent of licensed capacity, and production has never exceeded 89 percent of capacity. The capacity in developing mines is not always reported. In this study 35 percent of developing mines did not report a target licensed capacity, so estimates of future capacity may be too low. The Organisation for Economic Co-operation and Development’s Nuclear Energy Agency (NEA) and International Atomic Energy Agency (IAEA) estimate an additional 1.4 million tU economically recoverable resources, beyond that identified in operating or developing mines identified in this report. As well, 0.5 million tU in subeconomic resources, and 2.3 million tU in the geologically less certain inferred category are identified worldwide. These agencies estimate 2.2 million tU in secondary sources such as government and commercial stockpiles and re-enriched uranium tails. They also estimate that unconventional uranium supplies (uraniferous phosphate and black shale deposits) may contain up to 7.6 million tU. Although unconventional resources are currently subeconomic, the improvement of extraction techniques or the production of coproducts may make extraction of uranium from these types of deposits profitable. A large undiscovered resource base is reported by these agencies, however this class of resource should be considered speculative and will require intensive exploration programs to adequately define them as mineable. These resources may all contribute to uranium supply that would fuel the world nuclear fleet well beyond that calculated in this report. Production of resources in both operating and developing uranium mines is subject to uncertainties caused by technical, legal, regulatory, and financial challenges that combined to create long timelines between deposit discovery and mine production. This analysis indicates that mine development is proceeding too slowly to fully meet requirements for an expanded nuclear power reactor fleet in the near future (to 2035), and unless adequate secondary or unconventional resources can be identified, imbalances in supply and demand may occur.

Intelligent and integrated techniques for coalbed methane (CBM) recovery and reduction of greenhouse gas emission.

PubMed

Qianting, Hu; Yunpei, Liang; Han, Wang; Quanle, Zou; Haitao, Sun

2017-07-01

Coalbed methane (CBM) recovery is a crucial approach to realize the exploitation of a clean energy and the reduction of the greenhouse gas emission. In the past 10 years, remarkable achievements on CBM recovery have been obtained in China. However, some key difficulties still exist such as long borehole drilling in complicated geological condition, and poor gas drainage effect due to low permeability. In this study, intelligent and integrated techniques for CBM recovery are introduced. These integrated techniques mainly include underground CBM recovery techniques and ground well CBM recovery techniques. The underground CBM recovery techniques consist of the borehole formation technique, gas concentration improvement technique, and permeability enhancement technique. According to the division of mining-induced disturbance area, the ground well arrangement area and well structure type in mining-induced disturbance developing area and mining-induced disturbance stable area are optimized to significantly improve the ground well CBM recovery. Besides, automatic devices such as drilling pipe installation device are also developed to achieve remote control of data recording, which makes the integrated techniques intelligent. These techniques can provide key solutions to some long-term difficulties in CBM recovery.

Assessment of hospital processes using a process mining technique: Outpatient process analysis at a tertiary hospital.

PubMed

Yoo, Sooyoung; Cho, Minsu; Kim, Eunhye; Kim, Seok; Sim, Yerim; Yoo, Donghyun; Hwang, Hee; Song, Minseok

2016-04-01

Many hospitals are increasing their efforts to improve processes because processes play an important role in enhancing work efficiency and reducing costs. However, to date, a quantitative tool has not been available to examine the before and after effects of processes and environmental changes, other than the use of indirect indicators, such as mortality rate and readmission rate. This study used process mining technology to analyze process changes based on changes in the hospital environment, such as the construction of a new building, and to measure the effects of environmental changes in terms of consultation wait time, time spent per task, and outpatient care processes. Using process mining technology, electronic health record (EHR) log data of outpatient care before and after constructing a new building were analyzed, and the effectiveness of the technology in terms of the process was evaluated. Using the process mining technique, we found that the total time spent in outpatient care did not increase significantly compared to that before the construction of a new building, considering that the number of outpatients increased, and the consultation wait time decreased. These results suggest that the operation of the outpatient clinic was effective after changes were implemented in the hospital environment. We further identified improvements in processes using the process mining technique, thereby demonstrating the usefulness of this technique for analyzing complex hospital processes at a low cost. This study confirmed the effectiveness of process mining technology at an actual hospital site. In future studies, the use of process mining technology will be expanded by applying this approach to a larger variety of process change situations. Copyright © 2016. Published by Elsevier Ireland Ltd.

SEASONAL VARIATIONS OF DISSOLVED MERCURY CONCENTRATIONS AT THE SULPHUR BANK MERCURY MINE, CLEAR LAKE, CALIFORNIA: IMPLICATIONS FOR MINE DRAINAGE MONITORING

EPA Science Inventory

The Sulphur Bank Mercury Mine in Lake County, California (SBMM) was operated from the 1860s through the 1950s. Mining for sulfur started with surface operations and then progressed to shaft and later open pit techniques to obtain mercury. SBMM is located adjacent to the shore o...

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.

Drugging the gut microbiome.

PubMed

Garber, Ken

2015-03-01

Using conventional drug discovery and novel synthetic biology approaches, some investigators and companies are mining our resident microbes and their metabolites for targets in small-molecule drug programs. Ken Garber reports.

Recommendation in Higher Education Using Data Mining Techniques

ERIC Educational Resources Information Center

Vialardi, Cesar; Bravo, Javier; Shafti, Leila; Ortigosa, Alvaro

2009-01-01

One of the main problems faced by university students is to take the right decision in relation to their academic itinerary based on available information (for example courses, schedules, sections, classrooms and professors). In this context, this work proposes the use of a recommendation system based on data mining techniques to help students to…

Physics Mining of Multi-Source Data Sets

NASA Technical Reports Server (NTRS)

Helly, John; Karimabadi, Homa; Sipes, Tamara

2012-01-01

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

In Situ Fixation of Metal(loid)s in Contaminated Soils: A Comparison of Conventional, Opportunistic, and Engineered Soil Amendments

EPA Science Inventory

This study aimed to assess and compare the in vitro and in vivo bioaccessibility/bioavailability of As and Pb in a mining contaminated soil (As 2267 mg kg^-1, Pb 1126 mg kg^-1), after the addition of conventional (phosphoric acid), opportunistic ...

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

Not Available

This paper is actually a composite of two papers dealing with automation and computerized control of underground mining equipment. The paper primarily discusses drills, haulage equipment, and tunneling machines. It compares performance and cost benefits of conventional equipment to the new automated methods. The company involved are iron ore mining companies in Scandinavia. The papers also discusses the different equipment using air power, water power, hydraulic power, and computer power. The different drill rigs are compared for performance and cost.

Phytostabilization of Mining Soils By the Plant Anthyllis Vulneraria: A Micro-XRF and XAS Study

NASA Astrophysics Data System (ADS)

Isaure, M. P.

2014-12-01

Mine tailings are typical highly metal contaminated areas with very scarce vegetation. They are affected by intensive rain and wind erosion processes, thus representing a source of environmental and health hazard. Due to their large area and high level of contamination, conventional remediation techniques are not appropriate, and phytostabilization has emerged as an alternative technique during the last decade. The legume plant Anthyllis vulneraria has been identified as a pionner plant to revegetalize mining sites from South of France where an experimental site has been set up for 10 years. Our objective was to clarify the role of Anthyllis vulneraria in the distribution and speciation of Cd and Zn in the soil. For that, we used a combination of micro X-ray fluorescence (μXRF) and micro X-ray Absorption Near Edge Structure spectroscopy (μXANES) combined to Extended X-ray Absorption Fine Structure spectroscopy (EXAFS). Results showed that the vegetation process had homogeneized the metal distribution in the soil compared to unvegetalized soil, and had decreased the Zn and Cd amount in the surface soil. Undisturbed cross-sections of soils showed that the top of the rhizosphere was highly enriched with organic matter after 10 years of vegetalization. Cd and Zn forms, mainly identified as CdCO3 and ZnCO3 in the unvegetalized soil, did not change significantly in the bulk rhizosphere but investigations at the micrometer scale allowed the identification of Cd and Zn organic phases in the upper part, probably related to the shoots decomposition, and thus to the organic matter recycling. At the close vicinity of the roots, some minor organic metallic forms were found whilst CdCO3 and ZnCO3 minerals were still present, thus highlighting the low direct impact of the roots in the soil. Finally, this study indicated that the direct impact of the plant on Cd and Zn speciation in the soil was weak, while an indirect effect resulting from shoots decomposition could be observed.

Monitoring the growth or decline of vegetation on mine dumps

NASA Technical Reports Server (NTRS)

Gilbertson, B. P. (Principal Investigator)

1975-01-01

The author has identified the following signficant results. It was established that particular mine dumps throughout the entire test area can be detected and identified. It was also established that patterns of vegetative growth on the mine dumps can be recognized from a simple visual analysis of photographic images. Because vegetation tends to occur in patches on many mine dumps, it is unsatisfactory to classify complete dumps into categories of percentage vegetative cover. A more desirable approach is to classify the patches of vegetation themselves. The coarse resolution of conventional densitometers restricts the accuracy of this procedure, and consequently a direct analysis of ERTS CCT's is preferred. A set of computer programs was written to perform the data reading and manipulating functions required for basic CCT analysis.

Optically powered remote gas monitor

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

Dubaniewicz, T.H. Jr.; Chilton, J.E.

1995-12-31

Many mines rely on toxic gas sensors to help maintain a safe and healthy work environment. This report describes a prototype monitoring system developed by the US Bureau of Mines (USBM) that uses light to power and communicate with several remote toxic gas sensors. The design is based on state-of-art optical-to-electrical power converters, solid-state diode lasers, and fiber optics. This design overcomes several problems associated with conventional wire-based systems by providing complete electrical isolation between the remote sensors and the central monitor. The prototype performed well during a 2-week field trial in the USBM Pittsburgh Research Center Safety Research Coalmore » Mine.« less

Uranium aqueous speciation in the vicinity of the former uranium mining sites using the diffusive gradients in thin films and ultrafiltration techniques.

PubMed

Drozdzak, Jagoda; Leermakers, Martine; Gao, Yue; Elskens, Marc; Phrommavanh, Vannapha; Descostes, Michael

2016-03-24

The performance of the Diffusive Gradients in Thin films (DGT) technique with Chelex(®)-100, Metsorb™ and Diphonix(®) as binding phases was evaluated in the vicinity of the former uranium mining sites of Chardon and L'Ecarpière (Loire-Atlantique department in western France). This is the first time that the DGT technique with three different binding agents was employed for the aqueous U determination in the context of uranium mining environments. The fractionation and speciation of uranium were investigated using a multi-methodological approach using filtration (0.45 μm, 0.2 μm), ultrafiltration (500 kDa, 100 kDa and 10 kDa) coupled to geochemical speciation modelling (PhreeQC) and the DGT technique. The ultrafiltration data showed that at each sampling point uranium was present mostly in the 10 kDa truly dissolved fraction and the geochemical modelling speciation calculations indicated that U speciation was markedly predominated by CaUO2(CO3)3(2-). In natural waters, no significant difference was observed in terms of U uptake between Chelex(®)-100 and Metsorb™, while similar or inferior U uptake was observed on Diphonix(®) resin. In turn, at mining influenced sampling spots, the U accumulation on DGT-Diphonix(®) was higher than on DGT-Chelex(®)-100 and DGT-Metsorb™, probably because their performance was disturbed by the extreme composition of the mining waters. The use of Diphonix(®) resin leads to a significant advance in the application and development of the DGT technique for determination of U in mining influenced environments. This investigation demonstrated that such multi-technique approach provides a better picture of U speciation and enables to assess more accurately the potentially bioavailable U pool. Copyright © 2016 Elsevier B.V. All rights reserved.

Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.

PubMed

Li, Shuang; Liu, Bing; Zhang, Chen

2016-01-01

Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons

NASA Astrophysics Data System (ADS)

Takadama, Keiki; Hirose, Kazuyuki; Matsushima, Hiroyasu; Hattori, Kiyohiko; Nakajima, Nobuo

This paper proposes the sleep stage estimation method that can provide an accurate estimation for each person without connecting any devices to human's body. In particular, our method learns the appropriate multiple band-pass filters to extract the specific wave pattern of heartbeat, which is required to estimate the sleep stage. For an accurate estimation, this paper employs Learning Classifier System (LCS) as the data-mining techniques and extends it to estimate the sleep stage. Extensive experiments on five subjects in mixed health confirm the following implications: (1) the proposed method can provide more accurate sleep stage estimation than the conventional method, and (2) the sleep stage estimation calculated by the proposed method is robust regardless of the physical condition of the subject.

Solid fossil-fuel recovery by electrical induction heating in situ - A proposal

NASA Astrophysics Data System (ADS)

Fisher, S.

1980-04-01

A technique, termed electrical induction heating, is proposed for in situ processes of energy production from solid fossil fuels, such as bitumen production from underground distillation of oil sand; oil by underground distillation of oil shale; petroleum from heavy oil by underground mobilization of heavy oil, from either residues of conventional liquid petroleum deposits or new deposits of viscous oil; methane and coal tar from lignite and coal deposits by underground distillation of coal; and generation of electricity by surface combustion of low calorific-value gas from underground coke gasification by combustion of the organic residue left from the underground distillation of coal by induction heating. A method of surface distillation of mined coking coal by induction heating to produce coke, methane, and coal tar is also proposed.

Earth Conductivity Estimation from Through-the-Earth Measurements of 94 Coal Mines Using Different Electromagnetic Models

PubMed Central

Yan, Lincan; Waynert, Joseph; Sunderman, Carl

2015-01-01

Through-the-Earth (TTE) communication systems require minimal infrastructure to operate. Hence, they are assumed to be more survivable and more conventional than other underground mine communications systems. This survivability is a major advantage for TTE systems. In 2006, Congress passed the Mine Improvement and New Emergency Response Act (MINER Act), which requires all underground coal mines to install wireless communications systems. The intent behind this mandate is for trapped miners to be able to communicate with surface personnel after a major accident-hence, the interest in TTE communications. To determine the likelihood of establishing a TTE communication link, it would be ideal to be able to predict the apparent conductivity of the overburden above underground mines. In this paper, all 94 mine TTE measurement data collected by Bureau of Mines in the 1970s and early 1980s, are analyzed for the first time to determine the apparent conductivity of the overburden based on three different models: a homogenous half-space model, a thin sheet model, and an attenuation factor or Q-factor model. A statistical formula is proposed to estimate the apparent earth conductivity for a specific mine based on the TTE modeling results given the mine depth and signal frequency. PMID:26213457

Earth Conductivity Estimation from Through-the-Earth Measurements of 94 Coal Mines Using Different Electromagnetic Models.

PubMed

Yan, Lincan; Waynert, Joseph; Sunderman, Carl

2014-10-01

Through-the-Earth (TTE) communication systems require minimal infrastructure to operate. Hence, they are assumed to be more survivable and more conventional than other underground mine communications systems. This survivability is a major advantage for TTE systems. In 2006, Congress passed the Mine Improvement and New Emergency Response Act (MINER Act), which requires all underground coal mines to install wireless communications systems. The intent behind this mandate is for trapped miners to be able to communicate with surface personnel after a major accident-hence, the interest in TTE communications. To determine the likelihood of establishing a TTE communication link, it would be ideal to be able to predict the apparent conductivity of the overburden above underground mines. In this paper, all 94 mine TTE measurement data collected by Bureau of Mines in the 1970s and early 1980s, are analyzed for the first time to determine the apparent conductivity of the overburden based on three different models: a homogenous half-space model, a thin sheet model, and an attenuation factor or Q-factor model. A statistical formula is proposed to estimate the apparent earth conductivity for a specific mine based on the TTE modeling results given the mine depth and signal frequency.

Process Mining Online Assessment Data

ERIC Educational Resources Information Center

Pechenizkiy, Mykola; Trcka, Nikola; Vasilyeva, Ekaterina; van der Aalst, Wil; De Bra, Paul

2009-01-01

Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for…

Study on online community user motif using web usage mining

NASA Astrophysics Data System (ADS)

Alphy, Meera; Sharma, Ajay

2016-04-01

The Web usage mining is the application of data mining, which is used to extract useful information from the online community. The World Wide Web contains at least 4.73 billion pages according to Indexed Web and it contains at least 228.52 million pages according Dutch Indexed web on 6th august 2015, Thursday. It’s difficult to get needed data from these billions of web pages in World Wide Web. Here is the importance of web usage mining. Personalizing the search engine helps the web user to identify the most used data in an easy way. It reduces the time consumption; automatic site search and automatic restore the useful sites. This study represents the old techniques to latest techniques used in pattern discovery and analysis in web usage mining from 1996 to 2015. Analyzing user motif helps in the improvement of business, e-commerce, personalisation and improvement of websites.

Contribution to understanding the post-mining landscape - Application of airborn LiDAR and historical maps at the example from Silesian Upland (Poland)

NASA Astrophysics Data System (ADS)

Gawior, D.; Rutkiewicz, P.; Malik, I.; Wistuba, M.

2017-11-01

LiDAR data provide new insights into the historical development of mining industry recorded in the topography and landscape. In the study on the lead ore mining in the 13th-17th century we identified remnants of mining activity in relief that are normally obscured by dense vegetation. The industry in Tarnowice Plateau was based on exploitation of galena from the bedrock. New technologies, including DEM from airborne LiDAR provide show that present landscape and relief of post-mining area under study developed during several, subsequent phases of exploitation when different techniques of exploitation were used and probably different types of ores were exploited. Study conducted on the Tarnowice Plateau proved that combining GIS visualization techniques with historical maps, among all geological maps, is a promising approach in reconstructing development of anthropogenic relief and landscape..

Exploring patterns of epigenetic information with data mining techniques.

PubMed

Aguiar-Pulido, Vanessa; Seoane, José A; Gestal, Marcos; Dorado, Julián

2013-01-01

Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are mitotically and/or meiotically heritable determining gene expression and cellular differentiation, as well as cellular fate. Epigenetic lesions and genetic mutations are acquired by individuals during their life and accumulate with ageing. Both defects, either together or individually, can result in losing control over cell growth and, thus, causing cancer development. Data mining techniques could be then used to extract the previous patterns. This work reviews some of the most important applications of data mining to epigenetics.

Data Mining for Financial Applications

NASA Astrophysics Data System (ADS)

Kovalerchuk, Boris; Vityaev, Evgenii

This chapter describes Data Mining in finance by discussing financial tasks, specifics of methodologies and techniques in this Data Mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based and relational methodologies. The second part of the chapter discusses Data Mining models and practice in finance. It covers use of neural networks in portfolio management, design of interpretable trading rules and discovering money laundering schemes using decision rules and relational Data Mining methodology.

Examining Mobile Learning Trends 2003-2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

ERIC Educational Resources Information Center

Hung, Jui-Long; Zhang, Ke

2012-01-01

This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four…

Restoration of tropical moist forest on bauxite mined lands in the Brazilian Amazon

Treesearch

John A Parrotta; Oliver H. Knowles

1999-01-01

We evaluated forest structure and composition in 9- to 13-year-old stands established on a bauxite-mined site at Trombetas (Pará), Brazil, using four different reforestation techniques following initial site preparation and topsoil replacement. These techniques included reliance on natural forest regeneration, mixed commercial species plantings of mostly exotic timber...

Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

ERIC Educational Resources Information Center

Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

2017-01-01

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

Coalbed methane: from hazard to resource

USGS Publications Warehouse

Flores, R.M.

1998-01-01

Coalbed gas, which mainly consists of methane, has remained a major hazard affecting safety and productivity in underground coal mines for more than 100 yr. Coalbed gas emissions have resulted in outbursts and explosions where ignited by open lights, smoking or improper use of black blasting powder, and machinery operations. Investigations of coal gas outbursts and explosions during the past century were aimed at predicting and preventing this mine hazard. During this time, gas emissions were diluted with ventilation by airways (eg, tunnels, vertical and horizontal drillholes, shsfts) and by drainage boreholes. The 1970s 'energy crisis' led to studies of the feasibility of producing the gas for commercial use. Subsequent research on the origin, accumulation, distribution, availability, and recoverability has been pursued vigorously during the past two decades. Since the 1970s research investigations on the causes and effects of coal mine outbursts and gas emissions have led to major advances towards the recovery and development of coalbed methane for commercial use. Thus, coalbed methane as a mining hazard was harnessed as a conventional gas resource.Coalbed gas, which mainly consists of methane, has remained a major hazard affecting safety and productivity in underground coal mines for more than 100 years. Coalbed gas emissions have resulted in outbursts and explosions where ignited by open lights, smoking or improper use of black blasting powder, and machinery operations. Investigations of coal gas outbursts and explosions during the past century were aimed at predicting and preventing this mine hazard. During this time, gas emissions were diluted with ventilation by airways (e.g., tunnels, vertical and horizontal drillholes, shafts) and by drainage boreholes. The 1970's `energy crisis' led to studies of the feasibility of producing the gas for commercial use. Subsequent research on the origin, accumulation, distribution, availability, and recoverability has been pursued vigorously during the past two decades. Since the 1970's research investigations on the causes and effects of coal mine outbursts and gas emissions have led to major advances towards the recovery and development of coalbed methane for commercial use. Thus, coalbed methane as a mining hazard was harnessed as a conventional gas resource.

An Evaluation of Text Mining Tools as Applied to Selected Scientific and Engineering Literature.

ERIC Educational Resources Information Center

Trybula, Walter J.; Wyllys, Ronald E.

2000-01-01

Addresses an approach to the discovery of scientific knowledge through an examination of data mining and text mining techniques. Presents the results of experiments that investigated knowledge acquisition from a selected set of technical documents by domain experts. (Contains 15 references.) (Author/LRW)

Visual Based Retrieval Systems and Web Mining--Introduction.

ERIC Educational Resources Information Center

Iyengar, S. S.

2001-01-01

Briefly discusses Web mining and image retrieval techniques, and then presents a summary of articles in this special issue. Articles focus on Web content mining, artificial neural networks as tools for image retrieval, content-based image retrieval systems, and personalizing the Web browsing experience using media agents. (AEF)

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)

Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

ERIC Educational Resources Information Center

Emond, Bruno; Buffett, Scott

2015-01-01

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

ERIC Educational Resources Information Center

Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

2013-01-01

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

Video mining using combinations of unsupervised and supervised learning techniques

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Miyahara, Koji; Peker, Kadir A.; Radhakrishnan, Regunathan; Xiong, Ziyou

2003-12-01

We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised discovery of patterns in audio-visual content. Such purely unsupervised discovery is readily applicable to video surveillance as well as to consumer video browsing applications. We interpret video mining as content-adaptive or "blind" content processing, in which the first stage is content characterization and the second stage is event discovery based on the characterization obtained in stage 1. We discuss the target applications and find that using a purely unsupervised approach are too computationally complex to be implemented on our product platform. We then describe various combinations of unsupervised and supervised learning techniques that help discover patterns that are useful to the end-user of the application. We target consumer video browsing applications such as commercial message detection, sports highlights extraction etc. We employ both audio and video features. We find that supervised audio classification combined with unsupervised unusual event discovery enables accurate supervised detection of desired events. Our techniques are computationally simple and robust to common variations in production styles etc.

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

Haneş and Valea Vinului (Romania) closed mines Acid Mine Drainages (AMDs)--actual condition and passive treatment remediation proposal.

PubMed

Măicăneanu, Andrada; Bedelean, Horea; Ardelean, Marius; Burcă, Silvia; Stanca, Maria

2013-10-01

Acid Mine Drainages (AMDs) from Haneş and Valea Vinului (Romania) closed mines were considered for characterization and treatment using a local zeolitic volcanic tuff, ZVT, (Măcicaş, Cluj County, Romania). Water samples were collected from two locations, before and after discharging point in case of Haneş mine, and on three horizons in case of Valea Vinului mine. Physico-chemical (pH, total solid, heavy metal ions concentration) analyses showed that the environment is strongly affected by these AMD discharges even if the mines were closed years ago. Iron, manganese and zinc were the main pollutants identified in Haneş mine AMD, while zinc is the one mainly present in case of Valea Vinului AMD. A batch technique (no stirring) in which the ZVT was put in contact with the AMD sample was proposed as a passive remediation technique. ZVT successfully remove heavy metal ion from AMD. According to heavy metal ion concentrations, removal efficiencies are reaching 100%, varying as follows, Fe(2+)>Zn(2+)>Mn(2+). When the ZVT was compared with two cationic resins (strong, SAR and weak acid, WAR) the following series was depicted, SAR>ZVT>WAR. Copyright © 2013 Elsevier Ltd. All rights reserved.

Biogeochemical behaviour and bioremediation of uranium in waters of abandoned mines.

PubMed

Mkandawire, Martin

2013-11-01

The discharges of uranium and associated radionuclides as well as heavy metals and metalloids from waste and tailing dumps in abandoned uranium mining and processing sites pose contamination risks to surface and groundwater. Although many more are being planned for nuclear energy purposes, most of the abandoned uranium mines are a legacy of uranium production that fuelled arms race during the cold war of the last century. Since the end of cold war, there have been efforts to rehabilitate the mining sites, initially, using classical remediation techniques based on high chemical and civil engineering. Recently, bioremediation technology has been sought as alternatives to the classical approach due to reasons, which include: (a) high demand of sites requiring remediation; (b) the economic implication of running and maintaining the facilities due to high energy and work force demand; and (c) the pattern and characteristics of contaminant discharges in most of the former uranium mining and processing sites prevents the use of classical methods. This review discusses risks of uranium contamination from abandoned uranium mines from the biogeochemical point of view and the potential and limitation of uranium bioremediation technique as alternative to classical approach in abandoned uranium mining and processing sites.

Advances in Machine Learning and Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

Way, Michael J.; Scargle, Jeffrey D.; Ali, Kamal M.; Srivastava, Ashok N.

2012-03-01

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

Privacy Preserving Technique for Euclidean Distance Based Mining Algorithms Using a Wavelet Related Transform

NASA Astrophysics Data System (ADS)

Kadampur, Mohammad Ali; D. v. L. N., Somayajulu

Privacy preserving data mining is an art of knowledge discovery without revealing the sensitive data of the data set. In this paper a data transformation technique using wavelets is presented for privacy preserving data mining. Wavelets use well known energy compaction approach during data transformation and only the high energy coefficients are published to the public domain instead of the actual data proper. It is found that the transformed data preserves the Eucleadian distances and the method can be used in privacy preserving clustering. Wavelets offer the inherent improved time complexity.

Survey of Analysis of Crime Detection Techniques Using Data Mining and Machine Learning

NASA Astrophysics Data System (ADS)

Prabakaran, S.; Mitra, Shilpa

2018-04-01

Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.

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.

Distributions and concentrations of thallium in surface waters of a region impacted by historical metal mining (Cornwall, UK).

PubMed

Tatsi, Kristi; Turner, Andrew

2014-03-01

Thallium is a highly toxic heavy metal whose concentrations and distributions in the aquatic environment are poorly defined. In this study, concentrations of aqueous and total Tl have been measured in water samples from a variety of rivers and effluents (the latter related to historical metal mining) in the county of Cornwall, SW England. Aqueous concentrations ranged from about 13 ng L(-1) in a river whose catchment contained no metal mines to 2,640 ng L(-1) in water abstracted directly from an abandoned mine shaft. Concentrations of Tl in rivers were greatest in the vicinity of mine-related effluents, with a maximum value measured of about 770 ng L(-1). Thallium was not efficiently removed by the conventional, active treatment of mine water, and displayed little interaction with suspended particles. Its mobility in surface waters, coupled with concentrations that are close to a quality guideline of 800 ng L(-1), is cause for concern. Accordingly, we recommend that the metal is more closely monitored in this and other regions impacted by mining activities. Copyright © 2013 Elsevier B.V. All rights reserved.

Passive IR polarization sensors: a new technology for mine detection

NASA Astrophysics Data System (ADS)

Barbour, Blair A.; Jones, Michael W.; Barnes, Howard B.; Lewis, Charles P.

1998-09-01

The problem of mine and minefield detection continues to provide a significant challenge to sensor systems. Although the various sensor technologies (infrared, ground penetrating radar, etc.) may excel in certain situations there does not exist a single sensor technology that can adequately detect mines in all conditions such as time of day, weather, buried or surface laid, etc. A truly robust mine detection system will likely require the fusion of data from multiple sensor technologies. The performance of these systems, however, will ultimately depend on the performance of the individual sensors. Infrared (IR) polarimetry is a new and innovative sensor technology that adds substantial capabilities to the detection of mines. IR polarimetry improves on basic IR imaging by providing improved spatial resolution of the target, an inherent ability to suppress clutter, and the capability for zero (Delta) T imaging. Nichols Research Corporation (Nichols) is currently evaluating the effectiveness of IR polarization for mine detection. This study is partially funded by the U.S. Army Night Vision & Electronic Sensors Directorate (NVESD). The goal of the study is to demonstrate, through phenomenology studies and limited field trials, that IR polarizaton outperforms conventional IR imaging in the mine detection arena.

Data mining and visualization techniques

DOEpatents

Wong, Pak Chung [Richland, WA; Whitney, Paul [Richland, WA; Thomas, Jim [Richland, WA

2004-03-23

Disclosed are association rule identification and visualization methods, systems, and apparatus. An association rule in data mining is an implication of the form X.fwdarw.Y where X is a set of antecedent items and Y is the consequent item. A unique visualization technique that provides multiple antecedent, consequent, confidence, and support information is disclosed to facilitate better presentation of large quantities of complex association rules.

[Analysis of syndrome discipline of generalized anxiety disorder using data mining techniques].

PubMed

Tang, Qi-sheng; Sun, Wen-jun; Qu, Miao; Guo, Dong-fang

2012-09-01

To study the use of data mining techniques in analyzing the syndrome discipline of generalized anxiety disorder (GAD). From August 1, 2009 to July 31, 2010, 705 patients with GAD in 10 hospitals of Beijing were investigated over one year. Data mining techniques, such as Bayes net and cluster analysis, were used to analyze the syndrome discipline of GAD. A total of 61 symptoms of GAD were screened out. By using Bayes net, nine syndromes of GAD were abstracted based on the symptoms. Eight syndromes were abstracted by cluster analysis. After screening for duplicate syndromes and combining the experts' experience and traditional Chinese medicine theory, six syndromes of GAD were defined. These included depressed liver qi transforming into fire, phlegm-heat harassing the heart, liver depression and spleen deficiency, heart-kidney non-interaction, dual deficiency of the heart and spleen, and kidney deficiency and liver yang hyperactivity. Based on the results, the draft of Syndrome Diagnostic Criteria for Generalized Anxiety Disorder was developed. Data mining techniques such as Bayes net and cluster analysis have certain future potential for establishing syndrome models and analyzing syndrome discipline, thus they are suitable for the research of syndrome differentiation.

Evaluation of the mining techniques in constructing a traditional Chinese-language nursing recording system.

PubMed

Liao, Pei-Hung; Chu, William; Chu, Woei-Chyn

2014-05-01

In 2009, the Department of Health, part of Taiwan's Executive Yuan, announced the advent of electronic medical records to reduce medical expenses and facilitate the international exchange of medical record information. An information technology platform for nursing records in medical institutions was then quickly established, which improved nursing information systems and electronic databases. The purpose of the present study was to explore the usability of the data mining techniques to enhance completeness and ensure consistency of nursing records in the database system.First, the study used a Chinese word-segmenting system on common and special terms often used by the nursing staff. We also used text-mining techniques to collect keywords and create a keyword lexicon. We then used an association rule and artificial neural network to measure the correlation and forecasting capability for keywords. Finally, nursing staff members were provided with an on-screen pop-up menu to use when establishing nursing records. Our study found that by using mining techniques we were able to create a powerful keyword lexicon and establish a forecasting model for nursing diagnoses, ensuring the consistency of nursing terminology and improving the nursing staff's work efficiency and productivity.

Data mining in child welfare.

PubMed

Schoech, D; Quinn, A; Rycraft, J R

2000-01-01

Data mining is the sifting through of voluminous data to extract knowledge for decision making. This article illustrates the context, concepts, processes, techniques, and tools of data mining, using statistical and neural network analyses on a dataset concerning employee turnover. The resulting models and their predictive capability, advantages and disadvantages, and implications for decision support are highlighted.

Redundancy and Novelty Mining in the Business Blogosphere

ERIC Educational Resources Information Center

Tsai, Flora S.; Chan, Kap Luk

2010-01-01

Purpose: The paper aims to explore the performance of redundancy and novelty mining in the business blogosphere, which has not been studied before. Design/methodology/approach: Novelty mining techniques are implemented to single out novel information out of a massive set of text documents. This paper adopted the mixed metric approach which…

Reforestation of mined land in the northeastern and north-central U.S.

Treesearch

Walter H. Davidson; Russell J. Hutnik; Delbert E. Parr

1984-01-01

This paper reviews the state of the art of surface mine reclamation for forestry in Pennsylvania, Maryland, West Virginia, Ohio, Indiana, and Illinois. Legislative constraints, socioeconomic issues, factors limiting the success of reforestation efforts, post-mining land-use trends, species options, and establishment techniques are discussed. Sources of assistance to...

Identifying Learning Behaviors by Contextualizing Differential Sequence Mining with Action Features and Performance Evolution

ERIC Educational Resources Information Center

Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Our learning-by-teaching environment, Betty's Brain, captures a wealth of data on students' learning interactions as they teach a virtual agent. This paper extends an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs sequence mining techniques to…

Efficient Execution Methods of Pivoting for Bulk Extraction of Entity-Attribute-Value-Modeled Data

PubMed Central

Luo, Gang; Frey, Lewis J.

2017-01-01

Entity-attribute-value (EAV) tables are widely used to store data in electronic medical records and clinical study data management systems. Before they can be used by various analytical (e.g., data mining and machine learning) programs, EAV-modeled data usually must be transformed into conventional relational table format through pivot operations. This time-consuming and resource-intensive process is often performed repeatedly on a regular basis, e.g., to provide a daily refresh of the content in a clinical data warehouse. Thus, it would be beneficial to make pivot operations as efficient as possible. In this paper, we present three techniques for improving the efficiency of pivot operations: 1) filtering out EAV tuples related to unneeded clinical parameters early on; 2) supporting pivoting across multiple EAV tables; and 3) conducting multi-query optimization. We demonstrate the effectiveness of our techniques through implementation. We show that our optimized execution method of pivoting using these techniques significantly outperforms the current basic execution method of pivoting. Our techniques can be used to build a data extraction tool to simplify the specification of and improve the efficiency of extracting data from the EAV tables in electronic medical records and clinical study data management systems. PMID:25608318

Increasing the Reliability of the Work of Artificial Filtering Arrays for the Purification of Quarry Waste Water

NASA Astrophysics Data System (ADS)

Tyulenev, Maxim; Lesin, Yury; Litvin, Oleg; Maliukhina, Elena; Abay, Asmelash

2017-11-01

Features of geological structure of the Kuznetsk coal basin stipulate the application of a low-cost open technique of coal mining, which is more advantageous both from the economic standpoint, and by safety criteria of mining. However, open mining affects significantly the water resources of region. Intensive pollution of reservoirs and water courses, exhaustion of the underground water-bearing layers, violation of a hydrographic network, etc. be-long to the main disadvantages of an open technique of coal mining. Besides, the volume of the water coming into the mining producers exceeds signi-ficantly the needed quantity. According to the data of annual reports of ecology and natural resources department, 348.277 million m3 of water were ta-ken away during production of soft coal, brown coal and lignum fossil from waters of Kemerovo region in 2013 (mostly from underground water objects (96,5%) when draining of mine openings). At the same time, only 87.018 million m3 of water (25%) has been used within a year.

Field test of an alternative longwall gate road design

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

Cox, R.M.; Vandergrift, T.L.; McDonnell, J.P.

1994-01-01

The US Bureau of Mines (USBM) MULSIM/ML modeling technique has been used to analyze anticipated stress distributions for a proposed alternative longwall gate road design for a western Colorado coal mine. The model analyses indicated that the alternative gate road design would reduce stresses in the headgate entry. To test the validity of the alternative gate road design under actual mining conditions, a test section of the alternative system was incorporated into a subsequent set of gate roads developed at the mine. The alternative gate road test section was instrumented with borehole pressure cells, as part of an ongoing USBMmore » research project to monitor ground pressure changes as longwall mining progressed. During the excavation of the adjacent longwall panels, the behavior of the alternative gate road system was monitored continuously using the USBM computer-assisted Ground Control Management System. During these field tests, the alternative gate road system was first monitored and evaluated as a headgate, and later monitored and evaluated as a tailgate. The results of the field tests confirmed the validity of using the MULSIM/NL modeling technique to evaluate mine designs.« less

All-Optical Fibre Networks For Coal Mines

NASA Astrophysics Data System (ADS)

Zientkiewicz, Jacek K.

1987-09-01

A topic of the paper is fiber-optic integrated network (FOIN) suited to the most hostile environments existing in coal mines. The use of optical fibres for transmission of mine instrumentation data offers the prospects of improved safety and immunity to electromagnetic interference (EMI). The feasibility of optically powered sensors has opened up new opportunities for research into optical signal processing architectures. This article discusses a new fibre-optic sensor network involving a time domain multiplexing(TDM)scheme and optical signal processing techniques. The pros and cons of different FOIN topologies with respect to coal mine applications are considered. The emphasis has been placed on a recently developed all-optical fibre network using spread spectrum code division multiple access (COMA) techniques. The all-optical networks have applications in explosive environments where electrical isolation is required.

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.

Development and application of biotechnologies in the metal mining industry.

PubMed

Johnson, D Barrie

2013-11-01

Metal mining faces a number of significant economic and environmental challenges in the twenty-first century for which established and emerging biotechnologies may, at least in part, provide the answers. Bioprocessing of mineral ores and concentrates is already used in variously engineered formats to extract base (e.g., copper, cobalt, and nickel) and precious (gold and silver) metals in mines throughout the world, though it remains a niche technology. However, current projections of an increasing future need to use low-grade primary metal ores, to reprocess mine wastes, and to develop in situ leaching technologies to extract metals from deep-buried ore bodies, all of which are economically more amenable to bioprocessing than conventional approaches (e.g., pyrometallurgy), would suggest that biomining will become more extensively utilized in the future. Recent research has also shown that bioleaching could be used to process a far wider range of metal ores (e.g., oxidized ores) than has previously been the case. Biotechnologies are also being developed to control mine-related pollution, including securing mine wastes (rocks and tailings) by using "ecological engineering" approaches, and also to remediate and recover metals from waste waters, such as acid mine drainage. This article reviews the current status of biotechnologies within the mining sector and considers how these may be developed and applied in future years.

Non-destructive analysis of sensory traits of dry-cured loins by MRI-computer vision techniques and data mining.

PubMed

Caballero, Daniel; Antequera, Teresa; Caro, Andrés; Ávila, María Del Mar; G Rodríguez, Pablo; Perez-Palacios, Trinidad

2017-07-01

Magnetic resonance imaging (MRI) combined with computer vision techniques have been proposed as an alternative or complementary technique to determine the quality parameters of food in a non-destructive way. The aim of this work was to analyze the sensory attributes of dry-cured loins using this technique. For that, different MRI acquisition sequences (spin echo, gradient echo and turbo 3D), algorithms for MRI analysis (GLCM, NGLDM, GLRLM and GLCM-NGLDM-GLRLM) and predictive data mining techniques (multiple linear regression and isotonic regression) were tested. The correlation coefficient (R) and mean absolute error (MAE) were used to validate the prediction results. The combination of spin echo, GLCM and isotonic regression produced the most accurate results. In addition, the MRI data from dry-cured loins seems to be more suitable than the data from fresh loins. The application of predictive data mining techniques on computational texture features from the MRI data of loins enables the determination of the sensory traits of dry-cured loins in a non-destructive way. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Multisensor fusion for the detection of mines and minelike targets

NASA Astrophysics Data System (ADS)

Hanshaw, Terilee

1995-06-01

The US Army's Communications and Electronics Command through the auspices of its Night Vision and Electronics Sensors Directorate (CECOM-NVESD) is actively applying multisensor techniques to the detection of mine targets. This multisensor research results from the 'detection activity' with its broad range of operational conditions and targets. Multisensor operation justifies significant attention by yielding high target detection and low false alarm statistics. Furthermore, recent advances in sensor and computing technologies make its practical application realistic and affordable. The mine detection field-of-endeavor has since its WWI baptismal investigated the known spectra for applicable mine observation phenomena. Countless sensors, algorithms, processors, networks, and other techniques have been investigated to determine candidacy for mine detection. CECOM-NVESD efforts have addressed a wide range of sensors spanning the spectrum from gravity field perturbations, magentic field disturbances, seismic sounding, electromagnetic fields, earth penetrating radar imagery, and infrared/visible/ultraviolet surface imaging technologies. Supplementary analysis has considered sensor candidate applicability by testing under field conditions (versus laboratory), in determination of fieldability. As these field conditions directly effect the probability of detection and false alarms, sensor employment and design must be considered. Consequently, as a given sensor's performance is influenced directly by the operational conditions, tradeoffs are necessary. At present, mass produced and fielded mine detection techniques are limited to those incorporating a single sensor/processor methodology such as, pulse induction and megnetometry, as found in hand held detectors. The most sensitive fielded systems can detect minute metal components in small mine targets but result in very high false alarm rates reducing velocity in operation environments. Furthermore, the actual speed of advance for the entire mission (convoy, movement to engagement, etc.) is determined by the level of difficulty presented in clearance or avoidance activities required in response to the potential 'targets' marked throughout a detection activity. Therefore the application of fielded hand held systems to convoy operations in clearly impractical. CECOM-NVESD efforts are presently seeking to overcome these operational limitations by substantially increasing speed of detection while reducing the false alarm rate through the application of multisensor techniques. The CECOM-NVESD application of multisensor techniques through integration/fusion methods will be defined in this paper.

Percolator: Scalable Pattern Discovery in Dynamic Graphs

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

Choudhury, Sutanay; Purohit, Sumit; Lin, Peng

We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walkingmore » through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.« less

Corner-cutting mining assembly

DOEpatents

Bradley, J.A.

1981-07-01

This invention resulted from a contract with the United States Department of Energy and relates to a mining tool. More particularly, the invention relates to an assembly capable of drilling a hole having a square cross-sectional shape with radiused corners. In mining operations in which conventional auger-type drills are used to form a series of parallel, cylindrical holes in a coal seam, a large amount of coal remains in place in the seam because the shape of the holes leaves thick webs between the holes. A higher percentage of coal can be mined from a seam by a means capable of drilling holes having a substantially square cross section. It is an object of this invention to provide an improved mining apparatus by means of which the amount of coal recovered from a seam deposit can be increased. Another object of the invention is to provide a drilling assembly which cuts corners in a hole having a circular cross section. These objects and other advantages are attained by a preferred embodiment of the invention.

GENERAL EXTERIOR VIEW, LOOKING NORTHEAST, OF THE SURFACE PLANT WITH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

GENERAL EXTERIOR VIEW, LOOKING NORTHEAST, OF THE SURFACE PLANT WITH CONVEYORS. JIM WALTER RESOURCES INC. MINING DIVISION OPERATES FOUR UNDERGROUND COAL MINES IN THE BLUE CREEK COAL FIELD OF BIRMINGHAM DISTRICT, THREE IN TUSCALOOSA COUNTY AND ONE IN JEFFERSON COUNTY. TOTAL ANNUAL PRODUCTION IS 8,000,000 TONS. AT 2,300 DEEP, JIM WALTER'S BROOKWOOD MINES ARE THE DEEPEST UNDERGROUND COAL MINES IN NORTH AMERICA. THEY PRODUCE A HIGH-GRADE MEDIUM VOLATILE LOW SULPHUR METALLURGICAL COAL. THE BROOKWOOD NO. 5 MINE (PICTURED IN THIS PHOTOGRAPH) EMPLOYS THE LONGWALL MINING TECHNIQUES WITH BELTS CONVEYING COAL FROM UNDERGROUND OPERATIONS TO THE SURFACE. - JIm Walter Resources, Incorporated, Brookwood No. 5 Mine, 12972 Lock 17 Road, Brookwood, Tuscaloosa County, AL

Use of an automatic earth resistivity system for detection of abandoned mine workings

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

Peters, W.R.; Burdick, R.

1982-04-01

Under the sponsorship of the US Bureau of Mines, a surface-operated automatic high resolution earth resistivity system and associated computer data processing techniques have been designed and constructed for use as a potential means of detecting abandoned coal mine workings. The hardware and software aspects of the new system are described together with applications of the method to the survey and mapping of abandoned mine workings.

Exploring the social determinants of mental health service use using intersectionality theory and CART analysis.

PubMed

Cairney, John; Veldhuizen, Scott; Vigod, Simone; Streiner, David L; Wade, Terrance J; Kurdyak, Paul

2014-02-01

Fewer than half of individuals with a mental disorder seek formal care in a given year. Much research has been conducted on the factors that influence service use in this population, but the methods generally used cannot easily identify the complex interactions that are thought to exist. In this paper, we examine predictors of subsequent service use among respondents to a population health survey who met criteria for a past-year mood, anxiety or substance-related disorder. To determine service use, we use an administrative database including all physician consultations in the period of interest. To identify predictors, we use classification tree (CART) analysis, a data mining technique with the ability to identify unsuspected interactions. We compare results to those from logistic regression models. We identify 1213 individuals with past-year disorder. In the year after the survey, 24% (n=312) of these had a mental health-related physician consultation. Logistic regression revealed that age, sex and marital status predicted service use. CART analysis yielded a set of rules based on age, sex, marital status and income adequacy, with marital status playing a role among men and by income adequacy important among women. CART analysis proved moderately effective overall, with agreement of 60%, sensitivity of 82% and specificity of 53%. Results highlight the potential of data-mining techniques to uncover complex interactions, and offer support to the view that the intersection of multiple statuses influence health and behaviour in ways that are difficult to identify with conventional statistics. The disadvantages of these methods are also discussed.

Hydraulic Fracturing Mineback Experiment in Complex Media

NASA Astrophysics Data System (ADS)

Green, S. J.; McLennan, J. D.

2012-12-01

Hydraulic fracturing (or "fracking") for the recovery of gas and liquids from tight shale formations has gained much attention. This operation which involves horizontal well drilling and massive hydraulic fracturing has been developed over the last decade to produce fluids from extremely low permeability mudstone and siltstone rocks with high organic content. Nearly thirteen thousand wells and about one hundred and fifty thousand stages within the wells were fractured in the US in 2011. This operation has proven to be successful, causing hundreds of billions of dollars to be invested and has produced an abundance of natural gas and is making billions of barrels of hydrocarbon liquids available for the US. But, even with this commercial success, relatively little is clearly known about the complexity--or lack of complexity--of the hydraulic fracture, the extent that the newly created surface area contacts the high Reservoir Quality rock, nor the connectivity and conductivity of the hydraulic fractures created. To better understand this phenomena in order to improve efficiency, a large-scale mine-back experiment is progressing. The mine-back experiment is a full-scale hydraulic fracture carried out in a well-characterized environment, with comprehensive instrumentation deployed to measure fracture growth. A tight shale mudstone rock geologic setting is selected, near the edge of a formation where one to two thousand feet difference in elevation occurs. From the top of the formation, drilling, well logging, and hydraulic fracture pumping will occur. From the bottom of the formation a horizontal tunnel will be mined using conventional mining techniques into the rock formation towards the drilled well. Certain instrumentation will be located within this tunnel for observations during the hydraulic fracturing. After the hydraulic fracturing, the tunnel will be extended toward the well, with careful mapping of the created hydraulic fracture. Fracturing fluid will be traceable, as will injected proppant, in order to demarcate in-situ fracture paths and fluid and proppant progression. This underground experiment is referred to as a "mine-back experiment". Several mine-back experiments have been conducted in the past, and have demonstrated complex, diffuse fracture systems in coals and bundled fracture systems in some sandstones. No mine-back experiment has been conducted in the tight shales; but, economics and environmental considerations dictate that more definitive measurements will be extremely helpful to establish fracture growth patterns and to validate monitoring methods such as micro-seismic measurements. This presentation discusses the mine-back experiment and presents details of geologic setting, hydraulic fracturing, and the excavation required before and after the hydraulic fracture. The mine-back experiment will provide ground-truth assessment of hydraulic fracturing, geologic forecasting, micro-seismicity, and other information.

Hunting Sea Mines with UUV-Based Magnetic and Electro-Optic Sensors

DTIC Science & Technology

2010-06-01

assembly of four 3-axis fluxgate magnetometers and (c) magnetometer package for underwater deployment in flooded body section. data are automatically...features the Real-time Tracking Gradiometer (RTG), which is a multi-channel tensor gradiometer using conventional fluxgate technology. Also in this...integrated together into a Bluefin12 AUV [5]. A. RTG Sensor Technology The RTG is a multi-channel tensor gradiometer using conventional fluxgate

Characterization of particulate emissions from Australian open-cut coal mines: Toward improved emission estimates.

PubMed

Richardson, Claire; Rutherford, Shannon; Agranovski, Igor

2018-06-01

Given the significance of mining as a source of particulates, accurate characterization of emissions is important for the development of appropriate emission estimation techniques for use in modeling predictions and to inform regulatory decisions. The currently available emission estimation methods for Australian open-cut coal mines relate primarily to total suspended particulates and PM 10 (particulate matter with an aerodynamic diameter <10 μm), and limited data are available relating to the PM 2.5 (<2.5 μm) size fraction. To provide an initial analysis of the appropriateness of the currently available emission estimation techniques, this paper presents results of sampling completed at three open-cut coal mines in Australia. The monitoring data demonstrate that the particulate size fraction varies for different mining activities, and that the region in which the mine is located influences the characteristics of the particulates emitted to the atmosphere. The proportion of fine particulates in the sample increased with distance from the source, with the coarse fraction being a more significant proportion of total suspended particulates close to the source of emissions. In terms of particulate composition, the results demonstrate that the particulate emissions are predominantly sourced from naturally occurring geological material, and coal comprises less than 13% of the overall emissions. The size fractionation exhibited by the sampling data sets is similar to that adopted in current Australian emission estimation methods but differs from the size fractionation presented in the U.S. Environmental Protection Agency methodology. Development of region-specific emission estimation techniques for PM 10 and PM 2.5 from open-cut coal mines is necessary to allow accurate prediction of particulate emissions to inform regulatory decisions and for use in modeling predictions. Development of region-specific emission estimation techniques for PM 10 and PM 2.5 from open-cut coal mines is necessary to allow accurate prediction of particulate emissions to inform regulatory decisions and for use in modeling predictions. Comprehensive air quality monitoring was undertaken, and corresponding recommendations were provided.

Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS

USGS Publications Warehouse

Chirico, Peter G.; Dewitt, Jessica D.

2017-01-01

This study evaluates the use of a small unmanned aerial system (UAS) to collect imagery over artisanal mining sites in West Africa. The purpose of this study is to consider how very high-resolution imagery and digital surface models (DSMs) derived from structure-from-motion (SfM) photogrammetric techniques from a small UAS can fill the gap in geospatial data collection between satellite imagery and data gathered during field work to map and monitor informal mining sites in tropical environments. The study compares both wide-angle and narrow field of view camera systems in the collection and analysis of high-resolution orthoimages and DSMs of artisanal mining pits. The results of the study indicate that UAS imagery and SfM photogrammetric techniques permit DSMs to be produced with a high degree of precision and relative accuracy, but highlight the challenges of mapping small artisanal mining pits in remote and data sparse terrain.

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Computer-aided visual assessment in mine planning and design

Treesearch

Michael Hatfield; A. J. LeRoy Balzer; Roger E. Nelson

1979-01-01

A computer modeling technique is described for evaluating the visual impact of a proposed surface mine located within the viewshed of a national park. A computer algorithm analyzes digitized USGS baseline topography and identifies areas subject to surface disturbance visible from the park. Preliminary mine and reclamation plan information is used to describe how the...

Learner Typologies Development Using OIndex and Data Mining Based Clustering Techniques

ERIC Educational Resources Information Center

Luan, Jing

2004-01-01

This explorative data mining project used distance based clustering algorithm to study 3 indicators, called OIndex, of student behavioral data and stabilized at a 6-cluster scenario following an exhaustive explorative study of 4, 5, and 6 cluster scenarios produced by K-Means and TwoStep algorithms. Using principles in data mining, the study…

A Quantitative Analysis of Organizational Factors That Relate to Data Mining Success

ERIC Educational Resources Information Center

Huebner, Richard A.

2017-01-01

The ubiquity of data in various forms has fueled the need for advanced data-mining techniques within organizations. The advent of data mining methods used to uncover hidden nuggets of information buried within large data sets has also fueled the need for determining how these unique projects can be successful. There are many challenges associated…

Educational Data Mining Applications and Tasks: A Survey of the Last 10 Years

ERIC Educational Resources Information Center

Bakhshinategh, Behdad; Zaiane, Osmar R.; ElAtia, Samira; Ipperciel, Donald

2018-01-01

Educational Data Mining (EDM) is the field of using data mining techniques in educational environments. There exist various methods and applications in EDM which can follow both applied research objectives such as improving and enhancing learning quality, as well as pure research objectives, which tend to improve our understanding of the learning…

Rule-based statistical data mining agents for an e-commerce application

NASA Astrophysics Data System (ADS)

Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

2003-03-01

Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

Application of Modern Tools and Techniques for Mine Safety & Disaster Management

NASA Astrophysics Data System (ADS)

Kumar, Dheeraj

2016-04-01

The implementation of novel systems and adoption of improvised equipment in mines help mining companies in two important ways: enhanced mine productivity and improved worker safety. There is a substantial need for adoption of state-of-the-art automation technologies in the mines to ensure the safety and to protect health of mine workers. With the advent of new autonomous equipment used in the mine, the inefficiencies are reduced by limiting human inconsistencies and error. The desired increase in productivity at a mine can sometimes be achieved by changing only a few simple variables. Significant developments have been made in the areas of surface and underground communication, robotics, smart sensors, tracking systems, mine gas monitoring systems and ground movements etc. Advancement in information technology in the form of internet, GIS, remote sensing, satellite communication, etc. have proved to be important tools for hazard reduction and disaster management. This paper is mainly focused on issues pertaining to mine safety and disaster management and some of the recent innovations in the mine automations that could be deployed in mines for safe mining operations and for avoiding any unforeseen mine disaster.

Stability assessment of the chemical composition of the treated mining water used to replenish the cooling circuit in Jaworzno III Power Plant - Power Plant II

NASA Astrophysics Data System (ADS)

Karpiński, Marcin; Kmiecik, Ewa

2017-11-01

In Poland, electricity is still produced mainly in conventional power plants where fuel and water are materials necessary to generate the electricity. Even in modern power plants operating according to the principles of the sustainable development, this involves a high intake of water and considerable production of wastewater. This, in turn, necessi-tates the application of some technological solutions aimed at limiting the negative impact on the environment. The Jaworzno III Power Plant - Power Plant II is located in Jaworzno, Silesian Province, Poland. In order to minimise the negative impact on the surface water, the plant replenishes the cooling circuit with the mining water obtained from the closed-down Jan Kanty mine. The paper presents a stability assessment of the chemical composition of the treated mining water used to replenish the cooling circuit based on the data from 2007-2017.

Prior to the Oral Therapy, What Do We Know About HCV-4 in Egypt: A Randomized Survey of Prevalence and Risks Using Data Mining Computed Analysis

PubMed Central

Abd Elrazek, Abd Elrazek; Bilasy, Shymaa E.; Elbanna, Abduh E. M.; Elsherif, Abd Elhalim A.

2014-01-01

Abstract Hepatitis C virus (HCV) affects over 180 million people worldwide and it's the leading cause of chronic liver diseases and hepatocellular carcinoma. HCV is classified into seven major genotypes and a series of subtypes. In general, HCV genotype 4 (HCV-4) is common in the Middle East and Africa, where it is responsible for more than 80% of HCV infections. Although HCV-4 is the cause of approximately 20% of the 180 million cases of chronic hepatitis C worldwide, it has not been a major subject of research yet. The aim of the current study is to survey the morbidities and disease complications among Egyptian population infected with HCV-4 using data mining advanced computing methods mainly and other complementary statistical analysis. Six thousand six hundred sixty subjects, aged between 17 and 58 years old, from different Egyptian Governorates were screened for HCV infection by ELISA and qualitative PCR. HCV-positive patients were further investigated for the incidence of liver cirrhosis and esophageal varices. Obtained data were analyzed by data mining approach. Among 6660 subjects enrolled in this survey, 1018 patients (15.28%) were HCV-positive. Proportion of infected-males was significantly higher than females; 61.6% versus 38.4% (P = 0.0052). Around two-third of infected-patients (635/1018; 62.4%) were presented with liver cirrhosis. Additionally, approximately half of the cirrhotic patients (301/635; 47.4%) showed degrees of large esophageal varices (LEVs), with higher variceal grade observed in males. Age for esophageal variceal development was 47 ± 1. Data mining analysis yielded esophageal wall thickness (>6.5 mm), determined by conventional U/S, as the only independent predictor for esophageal varices. This study emphasizes the high prevalence of HCV infection among Egyptian population, in particular among males. Egyptians with HCV-4 infection are at a higher risk to develop cirrhotic liver and esophageal varices. Data mining, a new analytic technique in medical field, shed light in this study on the clinical importance of esophageal wall thickness as a useful predictor for risky esophageal varices using decision tree algorithm. PMID:25526438

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.

Hybrid Technology of Hard Coal Mining from Seams Located at Great Depths

NASA Astrophysics Data System (ADS)

Czaja, Piotr; Kamiński, Paweł; Klich, Jerzy; Tajduś, Antoni

2014-10-01

Learning to control fire changed the life of man considerably. Learning to convert the energy derived from combustion of coal or hydrocarbons into another type of energy, such as steam pressure or electricity, has put him on the path of scientific and technological revolution, stimulating dynamic development. Since the dawn of time, fossil fuels have been serving as the mankind's natural reservoir of energy in an increasingly great capacity. A completely incomprehensible refusal to use fossil fuels causes some local populations, who do not possess a comprehensive knowledge of the subject, to protest and even generate social conflicts as an expression of their dislike for the extraction of minerals. Our times are marked by the search for more efficient ways of utilizing fossil fuels by introducing non-conventional technologies of exploiting conventional energy sources. During apartheid, South Africa demonstrated that cheap coal can easily satisfy total demand for liquid and gaseous fuels. In consideration of current high prices of hydrocarbon media (oil and gas), gasification or liquefaction of coal seems to be the innovative technology convergent with contemporary expectations of both energy producers as well as environmentalists. Known mainly from literature reports, underground coal gasification technologies can be brought down to two basic methods: - shaftless method - drilling, in which the gasified seam is uncovered using boreholes drilled from the surface, - shaft method, in which the existing infrastructure of underground mines is used to uncover the seams. This paper presents a hybrid shaft-drilling approach to the acquisition of primary energy carriers (methane and syngas) from coal seams located at great depths. A major advantage of this method is the fact that the use of conventional coal mining technology requires the seams located at great depths to be placed on the off-balance sheet, while the hybrid method of underground gasification enables them to become a source of additional energy for the economy. It should be noted, however, that the shaft-drilling method cannot be considered as an alternative to conventional methods of coal extraction, but rather as a complementary and cheaper way of utilizing resources located almost beyond the technical capabilities of conventional extraction methods due to the associated natural hazards and high costs of combating them. This article presents a completely different approach to the issue of underground coal gasification. Repurposing of the already fully depreciated mining infrastructure for the gasification process may result in a large value added of synthesis gas production and very positive economic effect.

Data mining and medical world: breast cancers' diagnosis, treatment, prognosis and challenges.

PubMed

Oskouei, Rozita Jamili; Kor, Nasroallah Moradi; Maleki, Saeid Abbasi

2017-01-01

The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task. Data mining has various techniques for extracting valuable information or knowledge from data. These techniques are applicable for all data that are collected inall fields of science. Several research investigations are published about applications of data mining in various fields of sciences such as defense, banking, insurances, education, telecommunications, medicine and etc. This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now. Further, the main challenges in these area is presented in this investigation. Since several research studies currently are going on in this issues, therefore, it is necessary to have a complete survey about all researches which are completed up to now, along with the results of those studies and important challenges which are currently exist in this area for helping young researchers and presenting to them the main problems that are still exist in this area.

Data mining and medical world: breast cancers’ diagnosis, treatment, prognosis and challenges

PubMed Central

Oskouei, Rozita Jamili; Kor, Nasroallah Moradi; Maleki, Saeid Abbasi

2017-01-01

The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task. Data mining has various techniques for extracting valuable information or knowledge from data. These techniques are applicable for all data that are collected inall fields of science. Several research investigations are published about applications of data mining in various fields of sciences such as defense, banking, insurances, education, telecommunications, medicine and etc. This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now. Further, the main challenges in these area is presented in this investigation. Since several research studies currently are going on in this issues, therefore, it is necessary to have a complete survey about all researches which are completed up to now, along with the results of those studies and important challenges which are currently exist in this area for helping young researchers and presenting to them the main problems that are still exist in this area. PMID:28401016

Application of the Deformation Information System for automated analysis and mapping of mining terrain deformations - case study from SW Poland

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Grzempowski, Piotr; Milczarek, Wojciech; Nowacka, Anna

2015-04-01

Monitoring, mapping and modelling of mining induced terrain deformations are important tasks for quantifying and minimising threats that arise from underground extraction of useful minerals and affect surface infrastructure, human safety, the environment and security of the mining operation itself. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and expanding with the progress in geographical information technologies. These include for example: terrestrial geodetic measurements, Global Navigation Satellite Systems, remote sensing, GIS based modelling and spatial statistics, finite element method modelling, geological modelling, empirical modelling using e.g. the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The presentation shows the results of numerical modelling and mapping of mining terrain deformations for two cases of underground mining sites in SW Poland, hard coal one (abandoned) and copper ore (active) using the functionalities of the Deformation Information System (DIS) (Blachowski et al, 2014 @ http://meetingorganizer.copernicus.org/EGU2014/EGU2014-7949.pdf). The functionalities of the spatial data modelling module of DIS have been presented and its applications in modelling, mapping and visualising mining terrain deformations based on processing of measurement data (geodetic and GNSS) for these two cases have been characterised and compared. These include, self-developed and implemented in DIS, automation procedures for calculating mining terrain subsidence with different interpolation techniques, calculation of other mining deformation parameters (i.e. tilt, horizontal displacement, horizontal strain and curvature), as well as mapping mining terrain categories based on classification of the values of these parameters as used in Poland. Acknowledgments. This work has been financed from the National Science Centre Project "Development of a numerical method of mining ground deformation modelling in complex geological and mining conditions" UMO-2012/07/B/ST10/04297 executed at the Faculty of Geoengineering, Mining and Geology of the Wroclaw University of Technology (Poland).

Estimating natural background groundwater chemistry, Questa molybdenum mine, New Mexico

USGS Publications Warehouse

Verplanck, Phillip L.; Nordstrom, D. Kirk; Plumlee, Geoffrey S.; Walker, Bruce M.; Morgan, Lisa A.; Quane, Steven L.

2010-01-01

This 2 1/2 day field trip will present an overview of a U.S. Geological Survey (USGS) project whose objective was to estimate pre-mining groundwater chemistry at the Questa molybdenum mine, New Mexico. Because of intense debate among stakeholders regarding pre-mining groundwater chemistry standards, the New Mexico Environment Department and Chevron Mining Inc. (formerly Molycorp) agreed that the USGS should determine pre-mining groundwater quality at the site. In 2001, the USGS began a 5-year, multidisciplinary investigation to estimate pre-mining groundwater chemistry utilizing a detailed assessment of a proximal natural analog site and applied an interdisciplinary approach to infer pre-mining conditions. The trip will include a surface tour of the Questa mine and key locations in the erosion scar areas and along the Red River. The trip will provide participants with a detailed understanding of geochemical processes that influence pre-mining environmental baselines in mineralized areas and estimation techniques for determining pre-mining baseline conditions.

Unmanned Mine of the 21st Centuries

NASA Astrophysics Data System (ADS)

Semykina, Irina; Grigoryev, Aleksandr; Gargayev, Andrey; Zavyalov, Valeriy

2017-11-01

The article is analytical. It considers the construction principles of the automation system structure which realize the concept of «unmanned mine». All of these principles intend to deal with problems caused by a continuous complication of mining-and-geological conditions at coalmine such as the labor safety and health protection, the weak integration of different mining automation subsystems and the deficiency of optimal balance between a quantity of resource and energy consumed by mining machines and their throughput. The authors describe the main problems and neck stage of mining machines autonomation and automation subsystem. The article makes a general survey of the applied «unmanned technology» in the field of mining such as the remotely operated autonomous complexes, the underground positioning systems of mining machines using infrared radiation in mine workings etc. The concept of «unmanned mine» is considered with an example of the robotic road heading machine. In the final, the authors analyze the techniques and methods that could solve the task of underground mining without human labor.

Child Labor and Environmental Health: Government Obligations and Human Rights

PubMed Central

Amon, Joseph J.; Buchanan, Jane; Cohen, Jane; Kippenberg, Juliane

2012-01-01

The Convention concerning the Prohibition and Immediate Action for the Elimination of the Worst Forms of Child Labour was adopted by the International Labour Organization in 1999. 174 countries around the world have signed or ratified the convention, which requires countries to adopt laws and implement programs to prohibit and eliminate child labor that poses harms to health or safety. Nonetheless, child labor continues to be common in the agriculture and mining sectors, where safety and environmental hazards pose significant risks. Drawing upon recent human rights investigations of child labor in tobacco farming in Kazakhstan and gold mining in Mali, the role of international human rights mechanisms, advocacy with government and private sector officials, and media attention in reducing harmful environmental exposures of child workers is discussed. Human rights-based advocacy in both cases was important to raise attention and help ensure that children are protected from harm. PMID:23316246

Industrial Use of Synchrotron Radiation:. Love at Second Sight

NASA Astrophysics Data System (ADS)

Hormes, Josef; Warner, Jeffrey

2012-06-01

Synchrotron radiation (SR) has become one of the most valuable tools for many areas of basic and applied research. In some cases, techniques have been developed that rely completely on the specific properties of synchrotron radiation; in many other cases, using synchrotron radiation has opened completely new and exciting opportunities for conventional techniques. In this chapter, the challenges, problems, and advantages of the industrial use of synchrotron radiation will be highlighted, in an admittedly subjective way, based on the experience of the authors at various synchrotron radiation facilities. "Typical" examples of industrial use of SR will be discussed for all areas of industrial activities, i.e., production, quality control and control of regulatory requirements, and research and development. Emphasis will be put on examples from R&D as this is the most intensively used area. Because this field is much too broad for a complete review here, examples will focus on applications from just three major sectors: biotechnology, pharmaceuticals and cosmetics, and automotive and mining. Environmental research is a fourth area that will be partly covered in the section on regulatory requirements.

Semi-automated contour recognition using DICOMautomaton

NASA Astrophysics Data System (ADS)

Clark, H.; Wu, J.; Moiseenko, V.; Lee, R.; Gill, B.; Duzenli, C.; Thomas, S.

2014-03-01

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

Data Mining Methods for Recommender Systems

NASA Astrophysics Data System (ADS)

Amatriain, Xavier; Jaimes*, Alejandro; Oliver, Nuria; Pujol, Josep M.

In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

Integrated mined-area reclamation and land-use planning. Volume 3C. A case study of surface mining and reclamation planning: Georgia Kaolin Company Clay Mines, Washington County, Georgia

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

Guernsey, J L; Brown, L A; Perry, A O

1978-02-01

This case study examines the reclamation practices of the Georgia Kaolin's American Industrial Clay Company Division, a kaolin producer centered in Twiggs, Washington, and Wilkinson Counties, Georgia. The State of Georgia accounts for more than one-fourth of the world's kaolin production and about three-fourths of U.S. kaolin output. The mining of kaolin in Georgia illustrates the effects of mining and reclaiming lands disturbed by area surface mining. The disturbed areas are reclaimed under the rules and regulations of the Georgia Surface Mining Act of 1968. The natural conditions influencing the reclamation methodologies and techniques are markedly unique from those ofmore » other mining operations. The environmental disturbances and procedures used in reclaiming the kaolin mined lands are reviewed and implications for planners are noted.« less

Use of an automatic resistivity system for detecting abandoned mine workings

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

Peters, W.R.; Burdick, R.G.

1983-01-01

A high-resolution earth resistivity system has been designed and constructed for use as a means of detecting abandoned coal mine workings. The automatic pole-dipole earth resistivity technique has already been applied to the detection of subsurface voids for military applications. The hardware and software of the system are described, together with applications for surveying and mapping abandoned coal mine workings. Field tests are presented to illustrate the detection of both air-filled and water-filled mine workings.

Preventing spontaneous combustion after mine closing

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

Lewicki, G.

1987-11-01

The author explains how the Northern Coal Company and a Houston-based firefighting firm developed an innovative technique to reduce the risk of spontaneous combustion after mine closing in its Rienau number2 Mine. The ''Light Water TM'' ATC series of firefighting foam concentrates were designed for extinguishing flammable liquid fires. By slightly altering the chemicals, the concentrates could be used to seal the coal ribs, floor, and roof, reducing the risk of combustion. Subsequent monitoring of the mine has identified no signs of heating.

Artisanal and Small-Scale Gold Mining Without Mercury

EPA Pesticide Factsheets

Mercury-free techniques are safer for miners, their families and local communities. They can also help miners qualify for certification under fair-mined standards, potentially allowing them to market their gold at higher prices.

The Pollution Detectives: Part II. Lead and Zinc Mining.

ERIC Educational Resources Information Center

Sanderson, P. L.

1988-01-01

Describes a field trip taken to an old mining area to study water pollution. Discussed are methods for silt analysis, reagent preparation, color charts, techniques, fieldwork, field results, and a laboratory study. (CW)

Preliminary report on the coal resources of the Dickenson area, Billings, Dunn, and Stark counties, North Dakota

USGS Publications Warehouse

Menge, Michael L.

1977-01-01

The Dickinson area is underlain by the coal-bearing Fort Union Formation (Paleocene). The Fort Union in this area contains nine potentially economic coal beds. Five of these beds are, either all or in part, shallow enough to be economically extracted by conventional strip-mining methods, while the remaining four deeper beds represent future possible strip-mining, in situ, or shaft-mining coal resources. The Fort Union coal beds in the Dickinson area are relatively flat lying (dips are less than 1??) and only slightly influenced by faulting and both depositional and post-depositional channeling. Topography, coal thickness, and minimum overburden all combine to give the Dickinson area an excellent future coal resource development potential.

A demonstration of ERTS-1 analog and digital techniques applied to strip mining in Maryland and West Virginia

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schubert, J.

1974-01-01

The largest contour strip mining operations in western Maryland and West Virginia are located within the Georges Creek and the Upper Potomac Basins. These two coal basins lie within the Georges Creek (Wellersburg) syncline. The disturbed strip mine areas were delineated with the surrounding geological and vegetation features using ERTS-1 data in both analog (imagery) and digital form. The two digital systems used were: (1) the ERTS-Analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values, and (2) the LARS Automatic Data Processing System. The digital techniques being developed will later be incorporated into a data base for land use planning. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and indicate where future reclamation and revegetation may be necessary.

An integrated environment monitoring system for underground coal mines--Wireless Sensor Network subsystem with multi-parameter monitoring.

PubMed

Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

2014-07-21

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

75 FR 52780 - Notice of Availability of Final Supplemental Environmental Impact Statement for the Moore Ranch...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-27

... considered, but were eliminated from detailed analysis include: conventional mining (whether by open pit or... Agencywide Documents and Management System (ADAMS), which provides text and image files of the NRC's public...

Proof of concept : biocement for road repair.

DOT National Transportation Integrated Search

2015-03-01

Road repair is an expensive operation every year. This cost can be greatly reduced if waste materials from the mining and biofuel : industries can be used to substitute conventional materials for road repair or construction. The objective of this pro...

The design and implementation of web mining in web sites security

NASA Astrophysics Data System (ADS)

Li, Jian; Zhang, Guo-Yin; Gu, Guo-Chang; Li, Jian-Li

2003-06-01

The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illegal access can be avoided. Firstly, the system for discovering the patterns of information leakages in CGI scripts from Web log data was proposed. Secondly, those patterns for system administrators to modify their codes and enhance their Web site security were provided. The following aspects were described: one is to combine web application log with web log to extract more information, so web data mining could be used to mine web log for discovering the information that firewall and Information Detection System cannot find. Another approach is to propose an operation module of web site to enhance Web site security. In cluster server session, Density-Based Clustering technique is used to reduce resource cost and obtain better efficiency.

Methodology of Estimation of Methane Emissions from Coal Mines in Poland

NASA Astrophysics Data System (ADS)

Patyńska, Renata

2014-03-01

Based on a literature review concerning methane emissions in Poland, it was stated in 2009 that the National Greenhouse Inventory 2007 [13] was published. It was prepared firstly to meet Poland's obligations resulting from point 3.1 Decision no. 280/2004/WE of the European Parliament and of the Council of 11 February 2004, concerning a mechanism for monitoring community greenhouse gas emissions and for implementing the Kyoto Protocol and secondly, for the United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol. The National Greenhouse Inventory states that there are no detailed data concerning methane emissions in collieries in the Polish mining industry. That is why the methane emission in the methane coal mines of Górnośląskie Zagłębie Węglowe - GZW (Upper Silesian Coal Basin - USCB) in Poland was meticulously studied and evaluated. The applied methodology for estimating methane emission from the GZW coal mining system was used for the four basic sources of its emission. Methane emission during the mining and post-mining process. Such an approach resulted from the IPCC guidelines of 2006 [10]. Updating the proposed methods (IPCC2006) of estimating the methane emissions of hard coal mines (active and abandoned ones) in Poland, assumes that the methane emission factor (EF) is calculated based on methane coal mine output and actual values of absolute methane content. The result of verifying the method of estimating methane emission during the mining process for Polish coal mines is the equation of methane emission factor EF.

Growth and Heavy Metal Accumulation of Koelreuteria Paniculata Seedlings and Their Potential for Restoring Manganese Mine Wastelands in Hunan, China

PubMed Central

Huang, Zhihong; Xiang, Wenhua; Ma, Yu’e; Lei, Pifeng; Tian, Dalun; Deng, Xiangwen; Yan, Wende; Fang, Xi

2015-01-01

The planting of trees on mine wastelands is an effective, long-term technique for phytoremediation of heavy metal-contaminated wastes. In this study, a pot experiment with seedlings of Koelreuteria paniculata under six treatments of local mine wastes was designed to determine the major constraints on tree establishment and to evaluate the feasibility of planting K. paniculata on manganese mine wastelands. Results showed that K. paniculata grew well in mine tailings, and also under a regime of equal amounts of mine tailings and soil provided in adjacent halves of pots. In contrast, mine sludge did not favor survival and growth because its clay texture limited fine root development. The bio-concentration factor and the translocation factor were mostly less than 1, indicating a low phytoextraction potential for K. paniculata. K. paniculata is suited to restore manganese mine sludge by mixing the mine sludge with local mine tailings or soil. PMID:25654773

Monitoring of the mercury mining site Almadén implementing remote sensing technologies.

PubMed

Schmid, Thomas; Rico, Celia; Rodríguez-Rastrero, Manuel; José Sierra, María; Javier Díaz-Puente, Fco; Pelayo, Marta; Millán, Rocio

2013-08-01

The Almadén area in Spain has a long history of mercury mining with prolonged human-induced activities that are related to mineral extraction and metallurgical processes before the closure of the mines and a more recent post period dominated by projects that reclaim the mine dumps and tailings and recuperating the entire mining area. Furthermore, socio-economic alternatives such as crop cultivation, livestock breeding and tourism are increasing in the area. Up till now, only scattered information on these activities is available from specific studies. However, improved acquisition systems using satellite borne data in the last decades opens up new possibilities to periodically study an area of interest. Therefore, comparing the influence of these activities on the environment and monitoring their impact on the ecosystem vastly improves decision making for the public policy makers to implement appropriate land management measures and control environmental degradation. The objective of this work is to monitor environmental changes affected by human-induced activities within the Almadén area occurring before, during and after the mine closure over a period of nearly three decades. To achieve this, data from numerous sources at different spatial scales and time periods are implemented into a methodology based on advanced remote sensing techniques. This includes field spectroradiometry measurements, laboratory analyses and satellite borne data of different surface covers to detect land cover and use changes throughout the mining area. Finally, monitoring results show that the distribution of areas affected by mercury mining is rapidly diminishing since activities ceased and that rehabilitated mining areas form a new landscape. This refers to mine tailings that have been sealed and revegetated as well as an open pit mine that has been converted to an "artificial" lake surface. Implementing a methodology based on remote sensing techniques that integrate data from several sources at different scales greatly improves the regional characterization and monitoring of an area dominated by mercury mining activities. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparison of marginal accuracy of castings fabricated by conventional casting technique and accelerated casting technique: an in vitro study.

PubMed

Reddy, S Srikanth; Revathi, Kakkirala; Reddy, S Kranthikumar

2013-01-01

Conventional casting technique is time consuming when compared to accelerated casting technique. In this study, marginal accuracy of castings fabricated using accelerated and conventional casting technique was compared. 20 wax patterns were fabricated and the marginal discrepancy between the die and patterns were measured using Optical stereomicroscope. Ten wax patterns were used for Conventional casting and the rest for Accelerated casting. A Nickel-Chromium alloy was used for the casting. The castings were measured for marginal discrepancies and compared. Castings fabricated using Conventional casting technique showed less vertical marginal discrepancy than the castings fabricated by Accelerated casting technique. The values were statistically highly significant. Conventional casting technique produced better marginal accuracy when compared to Accelerated casting. The vertical marginal discrepancy produced by the Accelerated casting technique was well within the maximum clinical tolerance limits. Accelerated casting technique can be used to save lab time to fabricate clinical crowns with acceptable vertical marginal discrepancy.

Environmental Education in Brazil: Preventive Measures to Avoid Contamination with U and Th

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

Silva Pastura, Valeria Fonseca da; Wieland, Patricia

2008-08-07

Aiming at increasing awareness of radiation health effects, environmental issues and preventive measures, the Nuclear Energy National Commission (CNEN) launched in 2004 an education and public outreach programme for mine workers, students, teachers, governmental leaders, labor representatives and members of communities nearby small mining sites at the North and Northeast regions. Many Brazilian conventional mines present a significant risk of exposure to radiation due to Uranium and Thorium. CNEN inspects the mines but there are several small mining sites dedicated to open pit short term mineral extraction, called 'garimpagem', that are of difficult control. Therefore, information at large about preventivemore » measures to avoid contamination during exploration, transportation and storage is necessary. CNEN developed an educational campaign which includes a series of open seminars, talks, folders, booklets and posters. The objective of this paper is to present the Brazilian educational campaign to avoid contamination risks at those small mineral exploration sites and its results. This campaign is a joint task that receives collaboration of other organizations such as federal police, schools and universities.« less

Environmental Education in Brazil: Preventive Measures to Avoid Contamination with U and Th

NASA Astrophysics Data System (ADS)

da Silva Pastura, Valéria Fonseca; Wieland, Patricia

2008-08-01

Aiming at increasing awareness of radiation health effects, environmental issues and preventive measures, the Nuclear Energy National Commission (CNEN) launched in 2004 an education and public outreach programme for mine workers, students, teachers, governmental leaders, labor representatives and members of communities nearby small mining sites at the North and Northeast regions. Many Brazilian conventional mines present a significant risk of exposure to radiation due to Uranium and Thorium. CNEN inspects the mines but there are several small mining sites dedicated to open pit short term mineral extraction, called "garimpagem", that are of difficult control. Therefore, information at large about preventive measures to avoid contamination during exploration, transportation and storage is necessary. CNEN developed an educational campaign which includes a series of open seminars, talks, folders, booklets and posters. The objective of this paper is to present the Brazilian educational campaign to avoid contamination risks at those small mineral exploration sites and its results. This campaign is a joint task that receives collaboration of other organizations such as federal police, schools and universities.

An Expertise Recommender using Web Mining

NASA Technical Reports Server (NTRS)

Joshi, Anupam; Chandrasekaran, Purnima; ShuYang, Michelle; Ramakrishnan, Ramya

2001-01-01

This report explored techniques to mine web pages of scientists to extract information regarding their expertise, build expertise chains and referral webs, and semi automatically combine this information with directory information services to create a recommender system that permits query by expertise. The approach included experimenting with existing techniques that have been reported in research literature in recent past , and adapted them as needed. In addition, software tools were developed to capture and use this information.

Assessing the Ability of Hyperspectral Data to Detect Lyngbya SPP.: A Potential Biological Indicator for Presence of Metal Objects in the Littoral Environment

DTIC Science & Technology

2006-12-01

environment. This concept would have potential benefits and applications in mine detection and countermeasure techniques. Using a USB2000 field...be distinguished by a different phycocyanin absorption, at 615-632 nm. 15. NUMBER OF PAGES 261 14. SUBJECT TERMS Hyperspectral... applications in mine detection and countermeasure techniques. Using a USB2000 field spectroradiometer, a spectral library was developed for the

The effects of different representations on static structure analysis of computer malware signatures.

PubMed

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka.

The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures

PubMed Central

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka. PMID:23983644

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Data mining for the identification of metabolic syndrome status

PubMed Central

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS. PMID:29383020

Data mining for the identification of metabolic syndrome status.

PubMed

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS.

Cooperative organic mine avoidance path planning

NASA Astrophysics Data System (ADS)

McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David

2005-06-01

The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.

Slope stability radar for monitoring mine walls

NASA Astrophysics Data System (ADS)

Reeves, Bryan; Noon, David A.; Stickley, Glen F.; Longstaff, Dennis

2001-11-01

Determining slope stability in a mining operation is an important task. This is especially true when the mine workings are close to a potentially unstable slope. A common technique to determine slope stability is to monitor the small precursory movements, which occur prior to collapse. The slope stability radar has been developed to remotely scan a rock slope to continuously monitor the spatial deformation of the face. Using differential radar interferometry, the system can detect deformation movements of a rough wall with sub-millimeter accuracy, and with high spatial and temporal resolution. The effects of atmospheric variations and spurious signals can be reduced via signal processing means. The advantage of radar over other monitoring techniques is that it provides full area coverage without the need for mounted reflectors or equipment on the wall. In addition, the radar waves adequately penetrate through rain, dust and smoke to give reliable measurements, twenty-four hours a day. The system has been trialed at three open-cut coal mines in Australia, which demonstrated the potential for real-time monitoring of slope stability during active mining operations.

Fluid placement of fixated scrubber sludge to reduce surface subsidence and to abate acid mine drainage in abandoned underground coal mines

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

Meiers, R.J.; Golden, D.; Gray, R.

1995-12-31

Indianapolis Power and Light Company (IPL) began researching the use of fluid placement techniques of the fixated scrubber sludge (FSS) to reduce surface subsidence from underground coal mines to develop an economic alternative to low strength concrete grout. Abandoned underground coal mines surround property adjacent to IPL`s coal combustion by-product (CCBP) landfill at the Petersburg Generating Station. Landfill expansion into these areas is in question because of the high potential for sinkhole subsidence to develop. Sinkholes manifesting at the surface would put the integrity of a liner or runoff pond containment structure for a CCBP disposal facility at risk. Themore » fluid placement techniques of the FSS as a subsidence abatement technology was demonstrated during an eight week period in September, October, and November 1994 at the Petersburg Generating Station. The success of this technology will be determined by the percentage of the mine void filled, strength of the FSS placed, and the overall effects on the hydrogeologic environment. The complete report for this project will be finalized in early 1996.« less

Industrial application of semantic process mining

NASA Astrophysics Data System (ADS)

Espen Ingvaldsen, Jon; Atle Gulla, Jon

2012-05-01

Process mining relates to the extraction of non-trivial and useful information from information system event logs. It is a new research discipline that has evolved significantly since the early work on idealistic process logs. Over the last years, process mining prototypes have incorporated elements from semantics and data mining and targeted visualisation techniques that are more user-friendly to business experts and process owners. In this article, we present a framework for evaluating different aspects of enterprise process flows and address practical challenges of state-of-the-art industrial process mining. We also explore the inherent strengths of the technology for more efficient process optimisation.

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%.

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.

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.

40 CFR 434.44 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... control technology (BCT). [Reserved] 434.44 Section 434.44 Protection of Environment ENVIRONMENTAL..., BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Alkaline Mine Drainage § 434.44 Effluent... conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.44 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... control technology (BCT). [Reserved] 434.44 Section 434.44 Protection of Environment ENVIRONMENTAL..., BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Alkaline Mine Drainage § 434.44 Effluent... conventional pollutant control technology (BCT). [Reserved] ...

Blasting Rocks and Blasting Cars Applied Engineering

ScienceCinema

LBNL

2017-12-09

June 30, 2004 Berkeley Lab lecture: Deb Hopkins works with industries like automobile, mining and paper to improve their evaluation and measuring techniques. For several years, she has coordinated ... June 30, 2004 Berkeley Lab lecture: Deb Hopkins works with industries like automobile, mining and paper to improve their evaluation and measuring techniques. For several years, she has coordinated a program at Berkeley Lab funded under the Partnership for a New Generation of Vehicles, a collaboration between the federal government and the U.S. Council for Automotive Research. Nondestructive evaluation techniques to test a car's structural integrity are being developed for auto assembly lines.

Realising the knowledge spiral in healthcare: the role of data mining and knowledge management.

PubMed

Wickramasinghe, Nilmini; Bali, Rajeev K; Gibbons, M Chris; Schaffer, Jonathan

2008-01-01

Knowledge Management (KM) is an emerging business approach aimed at solving current problems such as competitiveness and the need to innovate which are faced by businesses today. The premise for the need for KM is based on a paradigm shift in the business environment where knowledge is central to organizational performance . Organizations trying to embrace KM have many tools, techniques and strategies at their disposal. A vital technique in KM is data mining which enables critical knowledge to be gained from the analysis of large amounts of data and information. The healthcare industry is a very information rich industry. The collecting of data and information permeate most, if not all areas of this industry; however, the healthcare industry has yet to fully embrace KM, let alone the new evolving techniques of data mining. In this paper, we demonstrate the ubiquitous benefits of data mining and KM to healthcare by highlighting their potential to enable and facilitate superior clinical practice and administrative management to ensue. Specifically, we show how data mining can realize the knowledge spiral by effecting the four key transformations identified by Nonaka of turning: (1) existing explicit knowledge to new explicit knowledge, (2) existing explicit knowledge to new tacit knowledge, (3) existing tacit knowledge to new explicit knowledge and (4) existing tacit knowledge to new tacit knowledge. This is done through the establishment of theoretical models that respectively identify the function of the knowledge spiral and the powers of data mining, both exploratory and predictive, in the knowledge discovery process. Our models are then applied to a healthcare data set to demonstrate the potential of this approach as well as the implications of such an approach to the clinical and administrative aspects of healthcare. Further, we demonstrate how these techniques can facilitate hospitals to address the six healthcare quality dimensions identified by the Committee for Quality Healthcare.

Mining High-Dimensional Data

NASA Astrophysics Data System (ADS)

Wang, Wei; Yang, Jiong

With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.

Redefining the Practice of Peer Review Through Intelligent Automation Part 1: Creation of a Standardized Methodology and Referenceable Database.

PubMed

Reiner, Bruce I

2017-10-01

Conventional peer review practice is compromised by a number of well-documented biases, which in turn limit standard of care analysis, which is fundamental to determination of medical malpractice. In addition to these intrinsic biases, other existing deficiencies exist in current peer review including the lack of standardization, objectivity, retrospective practice, and automation. An alternative model to address these deficiencies would be one which is completely blinded to the peer reviewer, requires independent reporting from both parties, utilizes automated data mining techniques for neutral and objective report analysis, and provides data reconciliation for resolution of finding-specific report differences. If properly implemented, this peer review model could result in creation of a standardized referenceable peer review database which could further assist in customizable education, technology refinement, and implementation of real-time context and user-specific decision support.

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

NASA Technical Reports Server (NTRS)

Karr, C. L.; Freeman, L. M.; Meredith, D. L.

1990-01-01

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Process development for elemental recovery from PGM tailings by thermochemical treatment: Preliminary major element extraction studies using ammonium sulphate as extracting agent.

PubMed

Mohamed, Sameera; van der Merwe, Elizabet M; Altermann, Wladyslaw; Doucet, Frédéric J

2016-04-01

Mine tailings can represent untapped secondary resources of non-ferrous, ferrous, precious, rare and trace metals. Continuous research is conducted to identify opportunities for the utilisation of these materials. This preliminary study investigated the possibility of extracting major elements from South African tailings associated with the mining of Platinum Group Metals (PGM) at the Two Rivers mine operations. These PGM tailings typically contain four major elements (11% Al2O3; 12% MgO; 22% Fe2O3; 34% Cr2O3), with lesser amounts of SiO2 (18%) and CaO (2%). Extraction was achieved via thermochemical treatment followed by aqueous dissolution, as an alternative to conventional hydrometallurgical processes. The thermochemical treatment step used ammonium sulphate, a widely available, low-cost, recyclable chemical agent. Quantification of the efficiency of the thermochemical process required the development and optimisation of the dissolution technique. Dissolution in water promoted the formation of secondary iron precipitates, which could be prevented by leaching thermochemically-treated tailings in 0.6M HNO3 solution. The best extraction efficiencies were achieved for aluminium (ca. 60%) and calcium (ca. 80%). 35% iron and 32% silicon were also extracted, alongside chromium (27%) and magnesium (25%). Thermochemical treatment using ammonium sulphate may therefore represent a promising technology for extracting valuable elements from PGM tailings, which could be subsequently converted to value-added products. However, it is not element-selective, and major elements were found to compete with the reagent to form water-soluble sulphate-metal species. Further development of this integrated process, which aims at achieving the full potential of utilisation of PGM tailings, is currently underway. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nanoparticulate mineral matter from basalt dust wastes.

PubMed

Dalmora, Adilson C; Ramos, Claudete G; Querol, Xavier; Kautzmann, Rubens M; Oliveira, Marcos L S; Taffarel, Silvio R; Moreno, Teresa; Silva, Luis F O

2016-02-01

Ultra-fine and nano-particles derived from basalt dust wastes (BDW) during "stonemeal" soil fertilizer application have been the subject of some concern recently around the world for their possible adverse effects on human health and environmental pollution. Samples of BDW utilized were obtained from companies in the mining district of Nova Prata in southern Brazil for chemical characterization and nano-mineralogy investigation, using an integrated application of advanced characterization techniques such as X-ray diffraction (XRD), High Resolution-Transmission Electron microscopy (HR-TEM)/(Energy Dispersive Spectroscopy) EDS/(selected-area diffraction pattern) SAED, Field Emission-Scanning Electron Microscopy (FE-SEM)/EDS and granulometric distribution analysis. The investigation has revealed that BDW materials are dominated by SiO2, Al2O3 and Fe2O3, with a complex micromineralogy including alkali feldspar, augite, barite, labradorite, hematite, heulandrite, gypsum, kaolinite, quartz, and smectite. In addition we have identified a number of trace metals such as Cd, Cu, Cr, Zn that are preferentially concentrated into the finer, inhalable, dust fraction and could so present a health hazard in the urban areas around the basalt mining zone. The implication of this observation is that use of these nanometric-sized particulates as soil fertilizer may present different health challenges to those of conventional fertilizers, inviting future work regarding the relative toxicities of these materials. Our investigation on the particle size distribution, nano-particle mineralogy and chemical composition in typical BDW samples highlights the need to develop cleaning procedures to minimise exposure to these natural fertilizing basalt dust wastes and is thus of direct relevance to both the industrial sector of basalt mining and to agriculture in the region. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Data mining of air traffic control operational errors

DOT National Transportation Integrated Search

2006-01-01

In this paper we present the results of : applying data mining techniques to identify patterns and : anomalies in air traffic control operational errors (OEs). : Reducing the OE rate is of high importance and remains a : challenge in the aviation saf...

Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring.

PubMed

Asner, Gregory P; Llactayo, William; Tupayachi, Raul; Luna, Ernesto Ráez

2013-11-12

Gold mining has rapidly increased in western Amazonia, but the rates and ecological impacts of mining remain poorly known and potentially underestimated. We combined field surveys, airborne mapping, and high-resolution satellite imaging to assess road- and river-based gold mining in the Madre de Dios region of the Peruvian Amazon from 1999 to 2012. In this period, the geographic extent of gold mining increased 400%. The average annual rate of forest loss as a result of gold mining tripled in 2008 following the global economic recession, closely associated with increased gold prices. Small clandestine operations now comprise more than half of all gold mining activities throughout the region. These rates of gold mining are far higher than previous estimates that were based on traditional satellite mapping techniques. Our results prove that gold mining is growing more rapidly than previously thought, and that high-resolution monitoring approaches are required to accurately quantify human impacts on tropical forests.

Application of a Novel Liquid Nitrogen Control Technique for Heat Stress and Fire Prevention in Underground Mines.

PubMed

Shi, Bobo; Ma, Lingjun; Dong, Wei; Zhou, Fubao

2015-01-01

With the continually increasing mining depths, heat stress and spontaneous combustion hazards in high-temperature mines are becoming increasingly severe. Mining production risks from natural hazards and exposures to hot and humid environments can cause occupational diseases and other work-related injuries. Liquid nitrogen injection, an engineering control developed to reduce heat stress and spontaneous combustion hazards in mines, was successfully utilized for environmental cooling and combustion prevention in an underground mining site named "Y120205 Working Face" (Y120205 mine) of Yangchangwan colliery. Both localized humidities and temperatures within the Y120205 mine decreased significantly with liquid nitrogen injection. The maximum percentage drop in temperature and humidity of the Y120205 mine were 21.9% and 10.8%, respectively. The liquid nitrogen injection system has the advantages of economical price, process simplicity, energy savings and emission reduction. The optimized heat exchanger used in the liquid nitrogen injection process achieved superior air-cooling results, resulting in considerable economic benefits.

Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring

PubMed Central

Asner, Gregory P.; Llactayo, William; Tupayachi, Raul; Luna, Ernesto Ráez

2013-01-01

Gold mining has rapidly increased in western Amazonia, but the rates and ecological impacts of mining remain poorly known and potentially underestimated. We combined field surveys, airborne mapping, and high-resolution satellite imaging to assess road- and river-based gold mining in the Madre de Dios region of the Peruvian Amazon from 1999 to 2012. In this period, the geographic extent of gold mining increased 400%. The average annual rate of forest loss as a result of gold mining tripled in 2008 following the global economic recession, closely associated with increased gold prices. Small clandestine operations now comprise more than half of all gold mining activities throughout the region. These rates of gold mining are far higher than previous estimates that were based on traditional satellite mapping techniques. Our results prove that gold mining is growing more rapidly than previously thought, and that high-resolution monitoring approaches are required to accurately quantify human impacts on tropical forests. PMID:24167281

Stratified sampling design based on data mining.

PubMed

Kim, Yeonkook J; Oh, Yoonhwan; Park, Sunghoon; Cho, Sungzoon; Park, Hayoung

2013-09-01

To explore classification rules based on data mining methodologies which are to be used in defining strata in stratified sampling of healthcare providers with improved sampling efficiency. We performed k-means clustering to group providers with similar characteristics, then, constructed decision trees on cluster labels to generate stratification rules. We assessed the variance explained by the stratification proposed in this study and by conventional stratification to evaluate the performance of the sampling design. We constructed a study database from health insurance claims data and providers' profile data made available to this study by the Health Insurance Review and Assessment Service of South Korea, and population data from Statistics Korea. From our database, we used the data for single specialty clinics or hospitals in two specialties, general surgery and ophthalmology, for the year 2011 in this study. Data mining resulted in five strata in general surgery with two stratification variables, the number of inpatients per specialist and population density of provider location, and five strata in ophthalmology with two stratification variables, the number of inpatients per specialist and number of beds. The percentages of variance in annual changes in the productivity of specialists explained by the stratification in general surgery and ophthalmology were 22% and 8%, respectively, whereas conventional stratification by the type of provider location and number of beds explained 2% and 0.2% of variance, respectively. This study demonstrated that data mining methods can be used in designing efficient stratified sampling with variables readily available to the insurer and government; it offers an alternative to the existing stratification method that is widely used in healthcare provider surveys in South Korea.

[Hygienic and ergonomic analysis of the technology for sinking main and subsidiary mine shafts].

PubMed

Meniaĭlo, N I; Tyshlek, E G; Gritsenko, V S; Shemiakin, G M

1989-01-01

The labour conditions in mine shafts do not correspond to the existing ergonomic and hygienic norms. Drilling and blasting techniques are most hazardous as to the gravity and duration of the factors involved. Working conditions normalization should be based on the elaboration of specifically innovative technologies which should envisage the workers' periodic staying in the mine shaft area during the work shift.

Focusing on Environmental Biofilms With Variable-Pressure Scanning Electron Microscopy

NASA Astrophysics Data System (ADS)

Joubert, L.; Wolfaardt, G. M.; Du Plessis, K.

2006-12-01

Since the term biofilm has been coined almost 30 years ago, visualization has formed an integral part of investigations on microbial attachment. Electron microscopic (EM) biofilm studies, however, have been limited by the hydrated extracellular matrix which loses structural integrity with conventional preparative techniques, and under required high-vacuum conditions, resulting in a loss of information on spatial relationships and distribution of biofilm microbes. Recent advances in EM technology enable the application of Variable Pressure Scanning Electron Microscopy (VP SEM) to biofilms, allowing low vacuum and hydrated chamber atmosphere during visualization. Environmental biofilm samples can be viewed in situ, unfixed and fully hydrated, with application of gold-sputter-coating only, to increase image resolution. As the impact of microbial biofilms can be both hazardous and beneficial to man and his environment, recognition of biofilms as a natural form of microbial existence is needed to fully assess the potential role of microbial communities on technology. The integration of multiple techniques to elucidate biofilm processes has become imperative for unraveling complex phenotypic adaptations of this microbial lifestyle. We applied VP SEM as integrative technique with traditional and novel analytical techniques to (1)localize lignocellulosic microbial consortia applied for producing alternative bio-energy sources in the mining wastewater industry, (2) characterize and visualize wetland microbial communities in the treatment of winery wastewater, and (3)determine the impact of recombinant technology on yeast biofilm behavior. Visualization of microbial attachment to a lignocellulose substrate, and degradation of exposed plant tissue, gave insight into fiber degradation and volatile fatty acid production for biological sulphate removal from mining wastewater. Also, the 3D-architecture of complex biofilms developing in constructed wetlands was correlated with molecular fingerprints of wetland communities using tRFLP (Terminal Restriction Fragment Length Polymorphism) - and gave evidence of temporal and spatial variation in a wetland system, to potentially be applied as management tool in wastewater treatment. Visualization of differences in biofilm development by wild and recombinant yeast strains furthermore supported real-time quantitative data of biofilm development by Cryptococcus laurentii and Saccharomyces yeast strains. In all cases VP SEM allowed a more holistic interpretation of biofilm processes than afforded by quantitative empirical data only.

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

Detection of buried objects by fusing dual-band infrared images

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-11-01

We have conducted experiments to demonstrate the enhanced detectability of buried land mines using sensor fusion techniques. Multiple sensors, including visible imagery, infrared imagery, and ground penetrating radar (GPR), have been used to acquire data on a number of buried mines and mine surrogates. Because the visible wavelength and GPR data are currently incomplete. This paper focuses on the fusion of two-band infrared images. We use feature-level fusion and supervised learning with the probabilistic neural network (PNN) to evaluate detection performance. The novelty of the work lies in the application of advanced target recognition algorithms, the fusion of dual-band infraredmore » images and evaluation of the techniques using two real data sets.« less

Using data mining techniques to characterize participation in observational studies.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

Data mining techniques are gaining in popularity among health researchers for an array of purposes, such as improving diagnostic accuracy, identifying high-risk patients and extracting concepts from unstructured data. In this paper, we describe how these techniques can be applied to another area in the health research domain: identifying characteristics of individuals who do and do not choose to participate in observational studies. In contrast to randomized studies where individuals have no control over their treatment assignment, participants in observational studies self-select into the treatment arm and therefore have the potential to differ in their characteristics from those who elect not to participate. These differences may explain part, or all, of the difference in the observed outcome, making it crucial to assess whether there is differential participation based on observed characteristics. As compared to traditional approaches to this assessment, data mining offers a more precise understanding of these differences. To describe and illustrate the application of data mining in this domain, we use data from a primary care-based medical home pilot programme and compare the performance of commonly used classification approaches - logistic regression, support vector machines, random forests and classification tree analysis (CTA) - in correctly classifying participants and non-participants. We find that CTA is substantially more accurate than the other models. Moreover, unlike the other models, CTA offers transparency in its computational approach, ease of interpretation via the decision rules produced and provides statistical results familiar to health researchers. Beyond their application to research, data mining techniques could help administrators to identify new candidates for participation who may most benefit from the intervention. © 2016 John Wiley & Sons, Ltd.

Comparison of data mining techniques applied to fetal heart rate parameters for the early identification of IUGR fetuses.

PubMed

Magenes, G; Bellazzi, R; Malovini, A; Signorini, M G

2016-08-01

The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying data mining techniques to FHR parameters, obtained from recordings in a population of 122 fetuses (61 healthy and 61 IUGRs), through standard CTG non-stress test. We computed N=12 indices (N=4 related to time domain FHR analysis, N=4 to frequency domain and N=4 to non-linear analysis) and normalized them with respect to the gestational week. We compared, through a 10-fold crossvalidation procedure, 15 data mining techniques in order to select the more reliable approach for identifying IUGR fetuses. The results of this comparison highlight that two techniques (Random Forest and Logistic Regression) show the best classification accuracy and that both outperform the best single parameter in terms of mean AUROC on the test sets.

Accuracy of land use change detection using support vector machine and maximum likelihood techniques for open-cast coal mining areas.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-08-01

One objective of the present study was to evaluate the performance of support vector machine (SVM)-based image classification technique with the maximum likelihood classification (MLC) technique for a rapidly changing landscape of an open-cast mine. The other objective was to assess the change in land use pattern due to coal mining from 2006 to 2016. Assessing the change in land use pattern accurately is important for the development and monitoring of coalfields in conjunction with sustainable development. For the present study, Landsat 5 Thematic Mapper (TM) data of 2006 and Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) data of 2016 of a part of Jharia Coalfield, Dhanbad, India, were used. The SVM classification technique provided greater overall classification accuracy when compared to the MLC technique in classifying heterogeneous landscape with limited training dataset. SVM exceeded MLC in handling a difficult challenge of classifying features having near similar reflectance on the mean signature plot, an improvement of over 11 % was observed in classification of built-up area, and an improvement of 24 % was observed in classification of surface water using SVM; similarly, the SVM technique improved the overall land use classification accuracy by almost 6 and 3 % for Landsat 5 and Landsat 8 images, respectively. Results indicated that land degradation increased significantly from 2006 to 2016 in the study area. This study will help in quantifying the changes and can also serve as a basis for further decision support system studies aiding a variety of purposes such as planning and management of mines and environmental impact assessment.

Sustainable rehabilitation of mining waste and acid mine drainage using geochemistry, mine type, mineralogy, texture, ore extraction and climate knowledge.

PubMed

Anawar, Hossain Md

2015-08-01

The oxidative dissolution of sulfidic minerals releases the extremely acidic leachate, sulfate and potentially toxic elements e.g., As, Ag, Cd, Cr, Cu, Hg, Ni, Pb, Sb, Th, U, Zn, etc. from different mine tailings and waste dumps. For the sustainable rehabilitation and disposal of mining waste, the sources and mechanisms of contaminant generation, fate and transport of contaminants should be clearly understood. Therefore, this study has provided a critical review on (1) recent insights in mechanisms of oxidation of sulfidic minerals, (2) environmental contamination by mining waste, and (3) remediation and rehabilitation techniques, and (4) then developed the GEMTEC conceptual model/guide [(bio)-geochemistry-mine type-mineralogy- geological texture-ore extraction process-climatic knowledge)] to provide the new scientific approach and knowledge for remediation of mining wastes and acid mine drainage. This study has suggested the pre-mining geological, geochemical, mineralogical and microtextural characterization of different mineral deposits, and post-mining studies of ore extraction processes, physical, geochemical, mineralogical and microbial reactions, natural attenuation and effect of climate change for sustainable rehabilitation of mining waste. All components of this model should be considered for effective and integrated management of mining waste and acid mine drainage. Copyright © 2015 Elsevier Ltd. All rights reserved.

75 FR 48366 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-10

...: OMB Desk Officer for the Department of Labor--Mine Safety and Health Administration (MSHA), Office of..., electronic, mechanical, or other technological collection techniques or other forms of information technology, e.g., permitting electronic submission of responses. Agency: Mine Safety and Health Administration...

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.

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J. (Principal Investigator); Russell, O. R.; Amato, R. V.; Leshendok, T.

1973-01-01

The author has identified the following significant results. The Kings Station Mine in Gibson County, Indiana has experienced considerable roof fall problems. Detailed fracture mapping of the mine area was done with ERTS-1 and aircraft imagery, and a prediction map of roof problem areas was produced in advance of a visit. The visit to the mine and discussions with the operator indicated that of four zones mapped as potential problem areas, three coincided with areas of excessive roof fall. This positive correlation of 75% lends confidence to the validity of the technique being applied in the investigation. The mine officials expressed an interest in the project and are anxious to see the final product maps which are forthcoming.

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.

Data Mining and Complex Problems: Case Study in Composite Materials

NASA Technical Reports Server (NTRS)

Rabelo, Luis; Marin, Mario

2009-01-01

Data mining is defined as the discovery of useful, possibly unexpected, patterns and relationships in data using statistical and non-statistical techniques in order to develop schemes for decision and policy making. Data mining can be used to discover the sources and causes of problems in complex systems. In addition, data mining can support simulation strategies by finding the different constants and parameters to be used in the development of simulation models. This paper introduces a framework for data mining and its application to complex problems. To further explain some of the concepts outlined in this paper, the potential application to the NASA Shuttle Reinforced Carbon-Carbon structures and genetic programming is used as an illustration.

Application of geostatistics to coal-resource characterization and mine planning. Final report

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

Kauffman, P.W.; Walton, D.R.; Martuneac, L.

1981-12-01

Geostatistics is a proven method of ore reserve estimation in many non-coal mining areas but little has been published concerning its application to coal resources. This report presents the case for using geostatistics for coal mining applications and describes how a coal mining concern can best utilize geostatistical techniques for coal resource characterization and mine planning. An overview of the theory of geostatistics is also presented. Many of the applications discussed are documented in case studies that are a part of the report. The results of an exhaustive literature search are presented and recommendations are made for needed future researchmore » and demonstration projects.« less

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

Use of a remotely piloted aircraft system for hazard assessment in a rocky mining area (Lucca, Italy)

NASA Astrophysics Data System (ADS)

Salvini, Riccardo; Mastrorocco, Giovanni; Esposito, Giuseppe; Di Bartolo, Silvia; Coggan, John; Vanneschi, Claudio

2018-01-01

The use of remote sensing techniques is now common practice in different working environments, including engineering geology. Moreover, in recent years the development of structure from motion (SfM) methods, together with rapid technological improvement, has allowed the widespread use of cost-effective remotely piloted aircraft systems (RPAS) for acquiring detailed and accurate geometrical information even in evolving environments, such as mining contexts. Indeed, the acquisition of remotely sensed data from hazardous areas provides accurate 3-D models and high-resolution orthophotos minimizing the risk for operators. The quality and quantity of the data obtainable from RPAS surveys can then be used for inspection of mining areas, audit of mining design, rock mass characterizations, stability analysis investigations and monitoring activities. Despite the widespread use of RPAS, its potential and limitations still have to be fully understood.In this paper a case study is shown where a RPAS was used for the engineering geological investigation of a closed marble mine area in Italy; direct ground-based techniques could not be applied for safety reasons. In view of the re-activation of mining operations, high-resolution images taken from different positions and heights were acquired and processed using SfM techniques to obtain an accurate and detailed 3-D model of the area. The geometrical and radiometrical information was subsequently used for a deterministic rock mass characterization, which led to the identification of two large marble blocks that pose a potential significant hazard issue for the future workforce. A preliminary stability analysis, with a focus on investigating the contribution of potential rock bridges, was then performed in order to demonstrate the potential use of RPAS information in engineering geological contexts for geohazard identification, awareness and reduction.

Knowledge-Based Reinforcement Learning for Data Mining

NASA Astrophysics Data System (ADS)

Kudenko, Daniel; Grzes, Marek

Data Mining is the process of extracting patterns from data. Two general avenues of research in the intersecting areas of agents and data mining can be distinguished. The first approach is concerned with mining an agent’s observation data in order to extract patterns, categorize environment states, and/or make predictions of future states. In this setting, data is normally available as a batch, and the agent’s actions and goals are often independent of the data mining task. The data collection is mainly considered as a side effect of the agent’s activities. Machine learning techniques applied in such situations fall into the class of supervised learning. In contrast, the second scenario occurs where an agent is actively performing the data mining, and is responsible for the data collection itself. For example, a mobile network agent is acquiring and processing data (where the acquisition may incur a certain cost), or a mobile sensor agent is moving in a (perhaps hostile) environment, collecting and processing sensor readings. In these settings, the tasks of the agent and the data mining are highly intertwined and interdependent (or even identical). Supervised learning is not a suitable technique for these cases. Reinforcement Learning (RL) enables an agent to learn from experience (in form of reward and punishment for explorative actions) and adapt to new situations, without a teacher. RL is an ideal learning technique for these data mining scenarios, because it fits the agent paradigm of continuous sensing and acting, and the RL agent is able to learn to make decisions on the sampling of the environment which provides the data. Nevertheless, RL still suffers from scalability problems, which have prevented its successful use in many complex real-world domains. The more complex the tasks, the longer it takes a reinforcement learning algorithm to converge to a good solution. For many real-world tasks, human expert knowledge is available. For example, human experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data collection behaviour in the respective domains. In future work, we intend to demonstrate and evaluate our techniques on concrete real-world data mining applications.

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

Greenwalt, R J; Magnoli, D

The purpose of this study is to determine battlefield effectiveness of the self-healing minefield (''Frogs'') concept system compared to basecases of the standard AP/AT (anti-personnel/anti-tank) mixed minefield, the AT (anti-tank) pure minefield, and no minefields. This involves tactical modeling where a basecase with and without mines is compared to the concept system. However, it is first necessary to establish system characteristics and behavior of the Frog mine and minefield in order to do the tactical modeling. This initial report provides emerging insights into various minefield parameters in order to allow better program definition early in the conceptual development. In themore » following sections of this report, we investigate the self-healing minefield's ground pattern and several concepts for movement (''jump'') of a mine. Basic enemy breaching techniques are compared for the different mine movement concepts. These results are then used in the (Joint Conflict and Tactical Simulation) JCATS tactical model to evaluate minefield effects in a combat situation. The three basecases and the Frogs concept are used against a North Korean mechanized rifle battalion and outcomes are compared. Preliminary results indicate: (1) Possible breaching techniques for the self-healing minefield were proposed and compared through simulation modeling. Of these, the best breaching counter to the self-healing minefield is the ''wide-lane'' breach technique. (2) Several methods for mine movement are tested and the optimal method from this group was selected for use in the modeling. However, continued work is needed on jump criteria; a more sophisticated model may reduce the advantage of the breach counter. (3) The battle scenario used in this study is a very difficult defense for Blue. In the three baseline cases (no mines, AT mines only, and mixed AT/AP minefield), Blue loses. Only in the Frog case does Blue win, and it is a high casualty win.« less

Digital Versus Conventional Impressions in Fixed Prosthodontics: A Review.

PubMed

Ahlholm, Pekka; Sipilä, Kirsi; Vallittu, Pekka; Jakonen, Minna; Kotiranta, Ulla

2018-01-01

To conduct a systematic review to evaluate the evidence of possible benefits and accuracy of digital impression techniques vs. conventional impression techniques. Reports of digital impression techniques versus conventional impression techniques were systematically searched for in the following databases: Cochrane Central Register of Controlled Trials, PubMed, and Web of Science. A combination of controlled vocabulary, free-text words, and well-defined inclusion and exclusion criteria guided the search. Digital impression accuracy is at the same level as conventional impression methods in fabrication of crowns and short fixed dental prostheses (FDPs). For fabrication of implant-supported crowns and FDPs, digital impression accuracy is clinically acceptable. In full-arch impressions, conventional impression methods resulted in better accuracy compared to digital impressions. Digital impression techniques are a clinically acceptable alternative to conventional impression methods in fabrication of crowns and short FDPs. For fabrication of implant-supported crowns and FDPs, digital impression systems also result in clinically acceptable fit. Digital impression techniques are faster and can shorten the operation time. Based on this study, the conventional impression technique is still recommended for full-arch impressions. © 2016 by the American College of Prosthodontists.

Updated methods for assessing the impacts of nearby gas drilling and production on neighborhood air quality and human health.

PubMed

Olaguer, Eduardo P; Erickson, Matthew; Wijesinghe, Asanga; Neish, Brad; Williams, Jeff; Colvin, John

2016-02-01

An explosive growth in natural gas production within the last decade has fueled concern over the public health impacts of air pollutant emissions from oil and gas sites in the Barnett and Eagle Ford shale regions of Texas. Commonly acknowledged sources of uncertainty are the lack of sustained monitoring of ambient concentrations of pollutants associated with gas mining, poor quantification of their emissions, and inability to correlate health symptoms with specific emission events. These uncertainties are best addressed not by conventional monitoring and modeling technology, but by increasingly available advanced techniques for real-time mobile monitoring, microscale modeling and source attribution, and real-time broadcasting of air quality and human health data over the World Wide Web. The combination of contemporary scientific and social media approaches can be used to develop a strategy to detect and quantify emission events from oil and gas facilities, alert nearby residents of these events, and collect associated human health data, all in real time or near-real time. The various technical elements of this strategy are demonstrated based on the results of past, current, and planned future monitoring studies in the Barnett and Eagle Ford shale regions. Resources should not be invested in expanding the conventional air quality monitoring network in the vicinity of oil and gas exploration and production sites. Rather, more contemporary monitoring and data analysis techniques should take the place of older methods to better protect the health of nearby residents and maintain the integrity of the surrounding environment.

Developing a stroke severity index based on administrative data was feasible using data mining techniques.

PubMed

Sung, Sheng-Feng; Hsieh, Cheng-Yang; Kao Yang, Yea-Huei; Lin, Huey-Juan; Chen, Chih-Hung; Chen, Yu-Wei; Hu, Ya-Han

2015-11-01

Case-mix adjustment is difficult for stroke outcome studies using administrative data. However, relevant prescription, laboratory, procedure, and service claims might be surrogates for stroke severity. This study proposes a method for developing a stroke severity index (SSI) by using administrative data. We identified 3,577 patients with acute ischemic stroke from a hospital-based registry and analyzed claims data with plenty of features. Stroke severity was measured using the National Institutes of Health Stroke Scale (NIHSS). We used two data mining methods and conventional multiple linear regression (MLR) to develop prediction models, comparing the model performance according to the Pearson correlation coefficient between the SSI and the NIHSS. We validated these models in four independent cohorts by using hospital-based registry data linked to a nationwide administrative database. We identified seven predictive features and developed three models. The k-nearest neighbor model (correlation coefficient, 0.743; 95% confidence interval: 0.737, 0.749) performed slightly better than the MLR model (0.742; 0.736, 0.747), followed by the regression tree model (0.737; 0.731, 0.742). In the validation cohorts, the correlation coefficients were between 0.677 and 0.725 for all three models. The claims-based SSI enables adjusting for disease severity in stroke studies using administrative data. Copyright © 2015 Elsevier Inc. All rights reserved.

The Algorithm of Development the World Ocean Mining of the Industry During the Global Crisis

NASA Astrophysics Data System (ADS)

Nyrkov, Anatoliy; Budnik, Vladislav; Sokolov, Sergei; Chernyi, Sergei

2016-08-01

In the article reviewed extraction effect of hydrocarbons on the general country's developing, under the impact of economical, demographical and technological factors, as well as it's future role in the world energy balance. Also adduced facts which designate offshore and deep water production of unconventional and conventional hydrocarbons including mining of marine mineral resources as perspective area of development in the future, despite all the difficulties of this sector. In the article considered the state and prospects of the Russian continental shelf, in consideration of its geographical location and its all existing problems.

Effect of type and transfer of conventional weapons on civilian injuries: retrospective analysis of prospective data from Red Cross hospitals

PubMed Central

Coupland, Robin M; Samnegaard, Hans O

1999-01-01

Objective To examine the link between different weapons used in modern wars and their potential to injury civilians. Design Retrospective analysis of prospectively collected data about hospital admissions. Setting Hospitals of the International Committee of the Red Cross. Subjects 18 877 people wounded by bullets, fragmentation munitions, or mines. Of these, 2012 had been admitted to the hospital in Kabul within six hours of injury. Main outcome measures Age and sex of wounded people according to cause of injury and whether they were civilians (women and girls, boys under 16 years old, or men of 50 or more). Results 18.7% of those injured by bullets, 34.1% of those injured by fragments, and 30.8% of those injured by mines were civilians. Of those admitted to the Red Cross hospital in Kabul within six hours of injury, 39.1% of those injured by bullets, 60.6% of those injured by fragments, and 55.0% of those injured by mines were civilians. Conclusions The proportion of civilians injured differs between weapon systems. The higher proportion injured by fragments and mines is explicable in terms of the military efficiency of weapons, the distance between user and victim, and the effect that the kind of weapon has on the psychology of the user. Key messagesDuring war, mines and fragmenting munitions (mortars, bombs, and shells) are more likely than bullets to injure civiliansCivilians in a city under siege are particularly at risk of being injured by weapons whose users are not able to see the victimThe inherent nature of weapons may be a factor in determining whether civilians are killed or injuredThere is a need for greater respect for the Fourth Geneva Convention and for greater controls on weapons being transferred to untrained and undisciplined forces PMID:10445921

30 CFR 582.23 - Testing Plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF THE INTERIOR OFFSHORE OPERATIONS IN THE OUTER... detailed Mining Plan than is obtainable under an approved Delineation Plan, to prepare feasibility studies, to carry out a pilot program to evaluate processing techniques or technology or mining equipment, or...

30 CFR 582.23 - Testing Plan.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF THE INTERIOR OFFSHORE OPERATIONS IN THE OUTER... detailed Mining Plan than is obtainable under an approved Delineation Plan, to prepare feasibility studies, to carry out a pilot program to evaluate processing techniques or technology or mining equipment, or...

30 CFR 582.23 - Testing Plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF THE INTERIOR OFFSHORE OPERATIONS IN THE OUTER... detailed Mining Plan than is obtainable under an approved Delineation Plan, to prepare feasibility studies, to carry out a pilot program to evaluate processing techniques or technology or mining equipment, or...

75 FR 53345 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-31

... the Department of Labor--Mine Safety and Health Administration (MSHA), Office of Management and Budget..., mechanical, or other technological collection techniques or other forms of information technology, e.g., permitting electronic submission of responses. Agency: Mine Safety and Health Administration. Type of Review...

ASSESSING AND MANAGING MERCURY FROM HISTORIC AND CURRENT MINING ACTIVITIES

EPA Science Inventory

In order for ORD to address uncertainties resulting from past or historical mining practices a technology transfer workshop was conducted in November, 2000 in San Francisco, CA. Two primary objectives for this workshop were: 1) identify state-of-the-science practices and techniqu...

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

PubMed Central

Chhadé, Hiba Haj; Abdallah, Fahed; Mougharbel, Imad; Gning, Amadou; Julier, Simon; Mihaylova, Lyudmila

2014-01-01

We consider the problem of localising an unknown number of land mines using concentration information provided by a wireless sensor network. A number of vapour sensors/detectors, deployed in the region of interest, are able to detect the concentration of the explosive vapours, emanating from buried land mines. The collected data is communicated to a fusion centre. Using a model for the transport of the explosive chemicals in the air, we determine the unknown number of sources using a Principal Component Analysis (PCA)-based technique. We also formulate the inverse problem of determining the positions and emission rates of the land mines using concentration measurements provided by the wireless sensor network. We present a solution for this problem based on a probabilistic Bayesian technique using a Markov chain Monte Carlo sampling scheme, and we compare it to the least squares optimisation approach. Experiments conducted on simulated data show the effectiveness of the proposed approach. PMID:25384008

Application of the pessimistic pruning to increase the accuracy of C4.5 algorithm in diagnosing chronic kidney disease

NASA Astrophysics Data System (ADS)

Muslim, M. A.; Herowati, A. J.; Sugiharti, E.; Prasetiyo, B.

2018-03-01

A technique to dig valuable information buried or hidden in data collection which is so big to be found an interesting patterns that was previously unknown is called data mining. Data mining has been applied in the healthcare industry. One technique used data mining is classification. The decision tree included in the classification of data mining and algorithm developed by decision tree is C4.5 algorithm. A classifier is designed using applying pessimistic pruning in C4.5 algorithm in diagnosing chronic kidney disease. Pessimistic pruning use to identify and remove branches that are not needed, this is done to avoid overfitting the decision tree generated by the C4.5 algorithm. In this paper, the result obtained using these classifiers are presented and discussed. Using pessimistic pruning shows increase accuracy of C4.5 algorithm of 1.5% from 95% to 96.5% in diagnosing of chronic kidney disease.

40 CFR 434.44 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2013 CFR

2013-07-01

... control technology (BCT). [Reserved] 434.44 Section 434.44 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Alkaline Mine Drainage § 434.44... of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.34 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2010 CFR

2010-07-01

... control technology (BCT). [Reserved] 434.34 Section 434.34 Protection of Environment ENVIRONMENTAL..., BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Acid or Ferruginous Mine Drainage § 434.34... of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.34 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2011 CFR

2011-07-01

... control technology (BCT). [Reserved] 434.34 Section 434.34 Protection of Environment ENVIRONMENTAL..., BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Acid or Ferruginous Mine Drainage § 434.34... of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.44 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2014 CFR

2014-07-01

... control technology (BCT). [Reserved] 434.44 Section 434.44 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Alkaline Mine Drainage § 434.44... of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.44 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... control technology (BCT). [Reserved] 434.44 Section 434.44 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Alkaline Mine Drainage § 434.44... of the best conventional pollutant control technology (BCT). [Reserved] ...

A framework for interval-valued information system

NASA Astrophysics Data System (ADS)

Yin, Yunfei; Gong, Guanghong; Han, Liang

2012-09-01

Interval-valued information system is used to transform the conventional dataset into the interval-valued form. To conduct the interval-valued data mining, we conduct two investigations: (1) construct the interval-valued information system, and (2) conduct the interval-valued knowledge discovery. In constructing the interval-valued information system, we first make the paired attributes in the database discovered, and then, make them stored in the neighbour locations in a common database and regard them as 'one' new field. In conducting the interval-valued knowledge discovery, we utilise some related priori knowledge and regard the priori knowledge as the control objectives; and design an approximate closed-loop control mining system. On the implemented experimental platform (prototype), we conduct the corresponding experiments and compare the proposed algorithms with several typical algorithms, such as the Apriori algorithm, the FP-growth algorithm and the CLOSE+ algorithm. The experimental results show that the interval-valued information system method is more effective than the conventional algorithms in discovering interval-valued patterns.

Using Decision Trees for Estimating Mode Choice of Trips in Buca-Izmir

NASA Astrophysics Data System (ADS)

Oral, L. O.; Tecim, V.

2013-05-01

Decision makers develop transportation plans and models for providing sustainable transport systems in urban areas. Mode Choice is one of the stages in transportation modelling. Data mining techniques can discover factors affecting the mode choice. These techniques can be applied with knowledge process approach. In this study a data mining process model is applied to determine the factors affecting the mode choice with decision trees techniques by considering individual trip behaviours from household survey data collected within Izmir Transportation Master Plan. From this perspective transport mode choice problem is solved on a case in district of Buca-Izmir, Turkey with CRISP-DM knowledge process model.

Blasting Rocks and Blasting Cars Applied Engineering

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

LBNL

2008-07-02

June 30, 2004 Berkeley Lab lecture: Deb Hopkins works with industries like automobile, mining and paper to improve their evaluation and measuring techniques. For several years, she has coordinated ... June 30, 2004 Berkeley Lab lecture: Deb Hopkins works with industries like automobile, mining and paper to improve their evaluation and measuring techniques. For several years, she has coordinated a program at Berkeley Lab funded under the Partnership for a New Generation of Vehicles, a collaboration between the federal government and the U.S. Council for Automotive Research. Nondestructive evaluation techniques to test a car's structural integrity are being developed formore » auto assembly lines.« less

Development of a tree classifier for discrimination of surface mine activity from Landsat digital data

NASA Technical Reports Server (NTRS)

Solomon, J. L.; Miller, W. F.; Quattrochi, D. A.

1979-01-01

In a cooperative project with the Geological Survey of Alabama, the Mississippi State Remote Sensing Applications Program has developed a single purpose, decision-tree classifier using band-ratioing techniques to discriminate various stages of surface mining activity. The tree classifier has four levels and employs only two channels in classification at each level. An accurate computation of the amount of disturbed land resulting from the mining activity can be made as a product of the classification output. The utilization of Landsat data provides a cost-efficient, rapid, and accurate means of monitoring surface mining activities.

Big data mining: In-database Oracle data mining over hadoop

NASA Astrophysics Data System (ADS)

Kovacheva, Zlatinka; Naydenova, Ina; Kaloyanova, Kalinka; Markov, Krasimir

2017-07-01

Big data challenges different aspects of storing, processing and managing data, as well as analyzing and using data for business purposes. Applying Data Mining methods over Big Data is another challenge because of huge data volumes, variety of information, and the dynamic of the sources. Different applications are made in this area, but their successful usage depends on understanding many specific parameters. In this paper we present several opportunities for using Data Mining techniques provided by the analytical engine of RDBMS Oracle over data stored in Hadoop Distributed File System (HDFS). Some experimental results are given and they are discussed.

Handling Dynamic Weights in Weighted Frequent Pattern Mining

NASA Astrophysics Data System (ADS)

Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

Monitoring of environmental effects of coal strip mining from satellite imagery

NASA Technical Reports Server (NTRS)

Brooks, R. L.; Parra, C. G.

1976-01-01

This paper evaluates satellite imagery as a means of monitoring coal strip mines and their environmental effects. The satellite imagery employed is Skylab EREP S-190A and S-190B from SL-2, SL-3 and SL-4 missions; a large variety of camera/film/filter combinations has been reviewed. The investigation includes determining the applicability of satellite imagery for detection of disturbed acreage in areas of coal surface mining as well as the much more detailed monitoring of specific surface-mining operations, including: active mines, inactive mines, highwalls, ramp roads, pits, water impoundments and their associated acidity, graded areas and types of grading, and reclamed areas. Techniques have been developed to enable mining personnel to utilize this imagery in a practical and economic manner, requiring no previous photo-interpretation background and no purchases of expensive viewing or data-analysis equipment. To corroborate the photo-interpretation results, on-site observations were made in the very active mining area near Madisonville, Kentucky.

An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

PubMed Central

Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

2014-01-01

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected. PMID:25051037

Evaluation of marginal gap of Ni-Cr copings made with conventional and accelerated casting techniques.

PubMed

Tannamala, Pavan Kumar; Azhagarasan, Nagarasampatti Sivaprakasam; Shankar, K Chitra

2013-01-01

Conventional casting techniques following the manufacturers' recommendations are time consuming. Accelerated casting techniques have been reported, but their accuracy with base metal alloys has not been adequately studied. We measured the vertical marginal gap of nickel-chromium copings made by conventional and accelerated casting techniques and determined the clinical acceptability of the cast copings in this study. Experimental design, in vitro study, lab settings. Ten copings each were cast by conventional and accelerated casting techniques. All copings were identical, only their mold preparation schedules differed. Microscopic measurements were recorded at ×80 magnification on the perpendicular to the axial wall at four predetermined sites. The marginal gap values were evaluated by paired t test. The mean marginal gap by conventional technique (34.02 μm) is approximately 10 μm lesser than that of accelerated casting technique (44.62 μm). As the P value is less than 0.0001, there is highly significant difference between the two techniques with regard to vertical marginal gap. The accelerated casting technique is time saving and the marginal gap measured was within the clinically acceptable limits and could be an alternative to time-consuming conventional techniques.

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

Prediction and innovative control strategies for oxygen and hazardous gases from diesel emission in underground mines.

PubMed

Kurnia, Jundika C; Sasmito, Agus P; Wong, Wai Yap; Mujumdar, Arun S

2014-05-15

Diesel engine is widely used in underground mining machines due to its efficiency, ease of maintenance, reliability and durability. However, it possesses significant danger to the miners and mining operations as it releases hazardous gases (CO, NO, CO2) and fine particles which can be easily inhaled by the miners. Moreover, the diesel engine consumes significant amount of oxygen which can lead to insufficient oxygen supply for miners. It is therefore critical to maintain sufficient oxygen supply while keeping hazardous gas concentrations from diesel emission below the maximum allowable level. The objective of this study is to propose and to examine various innovative ventilation strategies to control oxygen and hazardous gas concentrations in underground mine to ensure safety, productivity and cost related to energy consumption. Airflow distribution, oxygen and hazardous gas dispersion as well as ambient temperature within the mining area are evaluated by utilizing the well-established computational fluid dynamics (CFD) approach. The results suggest that our newly proposed ventilation design performs better as compared to the conventional design to handle hazardous gases from diesel emission. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative Analysis Between Computed and Conventional Inferior Alveolar Nerve Block Techniques.

PubMed

Araújo, Gabriela Madeira; Barbalho, Jimmy Charles Melo; Dias, Tasiana Guedes de Souza; Santos, Thiago de Santana; Vasconcellos, Ricardo José de Holanda; de Morais, Hécio Henrique Araújo

2015-11-01

The aim of this randomized, double-blind, controlled trial was to compare the computed and conventional inferior alveolar nerve block techniques in symmetrically positioned inferior third molars. Both computed and conventional anesthetic techniques were performed in 29 healthy patients (58 surgeries) aged between 18 and 40 years. The anesthetic of choice was 2% lidocaine with 1: 200,000 epinephrine. The Visual Analogue Scale assessed the pain variable after anesthetic infiltration. Patient satisfaction was evaluated using the Likert Scale. Heart and respiratory rates, mean time to perform technique, and the need for additional anesthesia were also evaluated. Pain variable means were higher for the conventional technique as compared with computed, 3.45 ± 2.73 and 2.86 ± 1.96, respectively, but no statistically significant differences were found (P > 0.05). Patient satisfaction showed no statistically significant differences. The average computed technique runtime and the conventional were 3.85 and 1.61 minutes, respectively, showing statistically significant differences (P <0.001). The computed anesthetic technique showed lower mean pain perception, but did not show statistically significant differences when contrasted to the conventional technique.

Establishment of trees and shrubs on lands disturbed by mining in the West

Treesearch

Ardell J. Bjugstad

1984-01-01

Increased research and development of cultural practices and species has assured success of establishment of trees and shrubs on lands disturbed by surface mining. Trickle irrigation and water harvesting techniques have increased survival of planted stock by 250 percent for some species.

Using Text Mining to Characterize Online Discussion Facilitation

ERIC Educational Resources Information Center

Ming, Norma; Baumer, Eric

2011-01-01

Facilitating class discussions effectively is a critical yet challenging component of instruction, particularly in online environments where student and faculty interaction is limited. Our goals in this research were to identify facilitation strategies that encourage productive discussion, and to explore text mining techniques that can help…

Revegetation for aesthetics

Treesearch

Bernard M. Slick

1980-01-01

Surface mining is changing the landscape character of forests in the East. Aesthetic visual aspects of the landscape are considered in the analysis, planning, and design of revegetation strategies. Application of landscape architectural design techniques in the revegetation of surface-mined lands, as well as knowledge of biological characteristics, will enhance the...

Untangling Topic Threads in Chat-Based Communication: A Case Study

DTIC Science & Technology

2011-08-01

learning techniques such as clustering are very popular for analyzing text for topic identification (Anjewierden,, Kollöffel and Hulshof 2007; Adams...Anjewierden, A., Kollöffel, B., and Hulshof , C. (2007). Towards educational data mining: Using data mining methods for automated chat analysis to

Applying Data Mining Principles to Library Data Collection.

ERIC Educational Resources Information Center

Guenther, Kim

2000-01-01

Explains how libraries can use data mining techniques for more effective data collection. Highlights include three phases: data selection and acquisition; data preparation and processing, including a discussion of the use of XML (extensible markup language); and data interpretation and integration, including database management systems. (LRW)

Geological evaluation and applications of ERTS-1 imagery over Georgia

NASA Technical Reports Server (NTRS)

Pickering, S. M.; Jones, R. C.

1974-01-01

ERTS-1 70mm and 9 x 9 film negatives are being used by conventional and color enhancement methods as a tool for geologic investigation. Geologic mapping and mineral exploration by conventional methods is very difficult in Georgia. Thick soil cover and heavy vegetation cause outcrops of bed rock to be small, rare and obscure. ERTS imagery, and remote sensing in general have helped delineate: (1) major tectonic boundaries; (2) lithologic contacts; (3) foliation trends; (4) topographic lineaments; and (5) faults. The ERTS-1 MSS imagery yields the greatest amount of geologic information on the Piedomont, Blue Ridge, and Valley and Ridge Provinces of Georgia where topography is strongly controlled by the bedrock geology. ERTS imagery, and general remote sensing techniques, have provided us with a powerful tool to assist geologic research; have significantly increased the mapping efficiency of our field geologists; have shown new lineaments associated with known shear and fault zones; have delineated new structural features; have provided a tool to re-evaluate our tectonic history; have helped to locate potential ground water sources and areas of aquifer recharge; have defined areas of geologic hazards; have shown areas of heavy siltation in major reservoirs; and by its close interval repetition, have aided in monitoring surface mine reclamation activities and the environmental protection of our intricate marshland system.

Arguments for the need of mining education continuity and development in Romania

NASA Astrophysics Data System (ADS)

Bud, I.; Duma, S.; Pasca, I.; Gusat, D.

2018-01-01

Mining is considered the oldest conscious man activity. In the beginning, man searched for hard rocks in the outskirts area and used it to make weapons and ornaments. Subsequently, civilizations evolved through the development of infrastructure, buildings and monuments and finally, weapons. For all these it was necessary to have mineral raw materials obtained under increasingly difficult conditions, through increasingly evolved techniques. In this way, the art of mining and metallurgy was born, which led to the formation of scientific bases. The mining activity was equally art and science. The art and the science have been learned and taught in schools since ancient times and continue today in large universities with mining engineering, metallurgy, mining topography, mining environmental protection, and geology. Lately, in Romania, the mining high school has reached a deadlock and the middle and professional school has collapsed. The development of infrastructure, construction, etc. requires the exploitation and valorisation of mineral resources based on specialists. The paper warns against the danger of losing tradition and skills in mining engineers formation and militate for the re-establishment of professional and technical schools.

Mining problems caused by tectonic stress in Illinois basin

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

Nelson, W.J.

1991-08-01

The Illinois basin coalfield is subject to a contemporary tectonic stress field in which the principal compressive stress axis ({sigma}1) is horizontal and strikes N60{degree}E to east-west. This stress is responsible for widespread development of kind zones and directional roof failures in mine headings driven perpendicular to {sigma}1. Also, small thrust faults perpendicular to {sigma}1 and joints parallel to {sigma}1 weaken the mine roof and occasionally admit water and gas to workings, depending upon geologic setting. The direction of magnitude of stress have been identified by a variety of techniques that can be applied both prior to mining and duringmore » development. Mining experience shows that the best method of minimizing stress-related problems is to drive mine headings at about 45 to {sigma}1.« less

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

Black Thunder Coal Mine and Los Alamos National Laboratory experimental study of seismic energy generated by large scale mine blasting

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

Martin, R.L.; Gross, D.; Pearson, D.C.

In an attempt to better understand the impact that large mining shots will have on verifying compliance with the international, worldwide, Comprehensive Test Ban Treaty (CTBT, no nuclear explosion tests), a series of seismic and videographic experiments has been conducted during the past two years at the Black Thunder Coal Mine. Personnel from the mine and Los Alamos National Laboratory have cooperated closely to design and perform experiments to produce results with mutual benefit to both organizations. This paper summarizes the activities, highlighting the unique results of each. Topics which were covered in these experiments include: (1) synthesis of seismic,more » videographic, acoustic, and computer modeling data to improve understanding of shot performance and phenomenology; (2) development of computer generated visualizations of observed blasting techniques; (3) documentation of azimuthal variations in radiation of seismic energy from overburden casting shots; (4) identification of, as yet unexplained, out of sequence, simultaneous detonation in some shots using seismic and videographic techniques; (5) comparison of local (0.1 to 15 kilometer range) and regional (100 to 2,000 kilometer range) seismic measurements leading to determine of the relationship between local and regional seismic amplitude to explosive yield for overburden cast, coal bulking and single fired explosions; and (6) determination of the types of mining shots triggering the prototype International Monitoring System for the CTBT.« less

Application of underground microseismic monitoring for ground failure and secure longwall coal mining operation: A case study in an Indian mine

NASA Astrophysics Data System (ADS)

Ghosh, G. K.; Sivakumar, C.

2018-03-01

Longwall mining technique has been widely used around the globe due to its safe mining process. However, mining operations are suspended when various problems arise like collapse of roof falls, cracks and fractures propagation in the roof and complexity in roof strata behaviors. To overcome these colossal problems, an underground real time microseismic monitoring technique has been implemented in the working panel-P2 in the Rajendra longwall underground coal mine at South Eastern Coalfields Limited (SECL), India. The target coal seams appears at the panel P-2 within a depth of 70 m to 76 m. In this process, 10 to 15 uniaxial geophones were placed inside a borehole at depth range of 40 m to 60 m located over the working panel-P2 with high rock quality designation value for better seismic signal. Various microseismic events were recorded with magnitude ranging from -5 to 2 in the Richter scale. The time-series processing was carried out to get various seismic parameters like activity rate, potential energy, viscosity rate, seismic moment, energy index, apparent volume and potential energy with respect to time. The used of these parameters helped tracing the events, understanding crack and fractures propagation and locating both high and low stress distribution zones prior to roof fall occurrence. In most of the cases, the events were divided into three stage processes: initial or preliminary, middle or building, and final or falling. The results of this study reveal that underground microseismic monitoring provides sufficient prior information of underground weighting events. The information gathered during the study was conveyed to the mining personnel in advance prior to roof fall event. This permits to take appropriate action for safer mining operations and risk reduction during longwall operation.

toxoMine: an integrated omics data warehouse for Toxoplasma gondii systems biology research

PubMed Central

Rhee, David B.; Croken, Matthew McKnight; Shieh, Kevin R.; Sullivan, Julie; Micklem, Gos; Kim, Kami; Golden, Aaron

2015-01-01

Toxoplasma gondii (T. gondii) is an obligate intracellular parasite that must monitor for changes in the host environment and respond accordingly; however, it is still not fully known which genetic or epigenetic factors are involved in regulating virulence traits of T. gondii. There are on-going efforts to elucidate the mechanisms regulating the stage transition process via the application of high-throughput epigenomics, genomics and proteomics techniques. Given the range of experimental conditions and the typical yield from such high-throughput techniques, a new challenge arises: how to effectively collect, organize and disseminate the generated data for subsequent data analysis. Here, we describe toxoMine, which provides a powerful interface to support sophisticated integrative exploration of high-throughput experimental data and metadata, providing researchers with a more tractable means toward understanding how genetic and/or epigenetic factors play a coordinated role in determining pathogenicity of T. gondii. As a data warehouse, toxoMine allows integration of high-throughput data sets with public T. gondii data. toxoMine is also able to execute complex queries involving multiple data sets with straightforward user interaction. Furthermore, toxoMine allows users to define their own parameters during the search process that gives users near-limitless search and query capabilities. The interoperability feature also allows users to query and examine data available in other InterMine systems, which would effectively augment the search scope beyond what is available to toxoMine. toxoMine complements the major community database ToxoDB by providing a data warehouse that enables more extensive integrative studies for T. gondii. Given all these factors, we believe it will become an indispensable resource to the greater infectious disease research community. Database URL: http://toxomine.org PMID:26130662

Exit and Voice: Organizational Loyalty and Dispute Resolution Strategies

ERIC Educational Resources Information Center

Hoffmann, Elizabeth A.

2006-01-01

This study compares workplace dispute resolution strategies (exit, voice and toleration) in matched pairs of conventional and worker-owned cooperative organizations operating in three industries--coal mining, taxicab driving and organic food distribution. Building on Hirschman's classic exit, voice and loyalty thesis, this research demonstrates…

40 CFR 434.34 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2013 CFR

2013-07-01

... control technology (BCT). [Reserved] 434.34 Section 434.34 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Acid or Ferruginous Mine Drainage § 434... application of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.34 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2014 CFR

2014-07-01

... control technology (BCT). [Reserved] 434.34 Section 434.34 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Acid or Ferruginous Mine Drainage § 434... application of the best conventional pollutant control technology (BCT). [Reserved] ...

40 CFR 434.34 - Effluent limitations guidelines representing the degree of effluent reduction attainable by the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... control technology (BCT). [Reserved] 434.34 Section 434.34 Protection of Environment ENVIRONMENTAL... BPT, BAT, BCT LIMITATIONS AND NEW SOURCE PERFORMANCE STANDARDS Acid or Ferruginous Mine Drainage § 434... application of the best conventional pollutant control technology (BCT). [Reserved] ...

Coal mine burns drainage gas to generate power for profit

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

Scholes, W.A.

A recently commissioned gas turbine power plant that uses methane gas recovered from a coal mine is described. The power plant uses the ASEA Stal GT35B series gas turbines with a base load rating on gas of 12.9 MW at 29.3% efficiency. The plant was installed at a cost of $4 million, as part of an extensive system for removing the methane from the coal mine, enabling higher ratio of coal production to be achieved in safety with modern longwall mining techniques. The plant will save the mine up to $250,000 per month on its electricity bill plus generate profitmore » from the sale of surplus power to the local activity.« 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

User Oriented Platform for Data Analytics in Medical Imaging Repositories.

PubMed

Valerio, Miguel; Godinho, Tiago Marques; Costa, Carlos

2016-01-01

The production of medical imaging studies and associated data has been growing in the last decades. Their primary use is to support medical diagnosis and treatment processes. However, the secondary use of the tremendous amount of stored data is generally more limited. Nowadays, medical imaging repositories have turned into rich databanks holding not only the images themselves, but also a wide range of metadata related to the medical practice. Exploring these repositories through data analysis and business intelligence techniques has the potential of increasing the efficiency and quality of the medical practice. Nevertheless, the continuous production of tremendous amounts of data makes their analysis difficult by conventional approaches. This article proposes a novel automated methodology to derive knowledge from medical imaging repositories that does not disrupt the regular medical practice. Our method is able to apply statistical analysis and business intelligence techniques directly on top of live institutional repositories. It is a Web-based solution that provides extensive dashboard capabilities, including complete charting and reporting options, combined with data mining components. Moreover, it enables the operator to set a wide multitude of query parameters and operators through the use of an intuitive graphical interface.

Stratified Sampling Design Based on Data Mining

PubMed Central

Kim, Yeonkook J.; Oh, Yoonhwan; Park, Sunghoon; Cho, Sungzoon

2013-01-01

Objectives To explore classification rules based on data mining methodologies which are to be used in defining strata in stratified sampling of healthcare providers with improved sampling efficiency. Methods We performed k-means clustering to group providers with similar characteristics, then, constructed decision trees on cluster labels to generate stratification rules. We assessed the variance explained by the stratification proposed in this study and by conventional stratification to evaluate the performance of the sampling design. We constructed a study database from health insurance claims data and providers' profile data made available to this study by the Health Insurance Review and Assessment Service of South Korea, and population data from Statistics Korea. From our database, we used the data for single specialty clinics or hospitals in two specialties, general surgery and ophthalmology, for the year 2011 in this study. Results Data mining resulted in five strata in general surgery with two stratification variables, the number of inpatients per specialist and population density of provider location, and five strata in ophthalmology with two stratification variables, the number of inpatients per specialist and number of beds. The percentages of variance in annual changes in the productivity of specialists explained by the stratification in general surgery and ophthalmology were 22% and 8%, respectively, whereas conventional stratification by the type of provider location and number of beds explained 2% and 0.2% of variance, respectively. Conclusions This study demonstrated that data mining methods can be used in designing efficient stratified sampling with variables readily available to the insurer and government; it offers an alternative to the existing stratification method that is widely used in healthcare provider surveys in South Korea. PMID:24175117

Mining Longitudinal Web Queries: Trends and Patterns.

ERIC Educational Resources Information Center

Wang, Peiling; Berry, Michael W.; Yang, Yiheng

2003-01-01

Analyzed user queries submitted to an academic Web site during a four-year period, using a relational database, to examine users' query behavior, to identify problems they encounter, and to develop techniques for optimizing query analysis and mining. Linguistic analyses focus on query structures, lexicon, and word associations using statistical…

Traffic Flow Management: Data Mining Update

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.

2012-01-01

This presentation provides an update on recent data mining efforts that have been designed to (1) identify like/similar days in the national airspace system, (2) cluster/aggregate national-level rerouting data and (3) apply machine learning techniques to predict when Ground Delay Programs are required at a weather-impacted airport

Restoring tropical forests on bauxite mined lands: lessons from the Brazilian Amazon

Treesearch

John A. Parrotta; Oliver H. Knowles

2001-01-01

Restoring self-sustaining tropical forest ecosystems on surface mined sites is a formidable challenge that requires the integration of proven reclamation techniques and reforestation strategies appropriate to specific site conditions, including landscape biodiversity patterns. Restorationists working in most tropical settings are usually hampered by lack of basic...

76 FR 9376 - Proposed Extension of Existing Information Collection;

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-17

... helps to assure that requested data can be provided in the desired format, reporting burden (time and...) that are removed during mining operations or separated from mined coal and deposited on the surface... collection techniques or other forms of information technology, e.g., permitting electronic submissions of...

76 FR 65180 - Proposed Information Collection; Comment Request; Deep Seabed Mining Exploration Licenses

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-20

... Collection; Comment Request; Deep Seabed Mining Exploration Licenses AGENCY: National Oceanic and Atmospheric... documentation electronically when feasible. III. Data OMB Control Number: 0648-0145. Form Number: None. Type of... information on respondents, including through the use of automated collection techniques or other forms of...

Application and Evaluation of ALOS PALSAR Data for Monitoring of Mining Induced Surface Deformations Using Interferometric Techniques

NASA Astrophysics Data System (ADS)

Walter, Diana; Wegmuller, Urs; Spreckels, Volker; Busch, Wolfgang

2008-11-01

The main objective of the projects "Determination of ground motions in mining areas by interferometric analyses of ALOS data" (ALOS ADEN 3576, ESA) and "Monitoring of mining induced surface deformation" (ALOS-RA-094, JAXA) is to evaluate PALSAR data for surface deformation monitoring, using interferometric techniques. We present monitoring results of surface movements for an active hard coal colliery of the German hard coal mining company RAG Deutsche Steinkohle (RAG). Underground mining activities lead to ground movements at the surface with maximum subsidence rates of about 10cm per month for the test site. In these projects the L-band sensor clearly demonstrates the good potential for deformation monitoring in active mining areas, especially in rural areas. In comparison to C-band sensors we clearly observe advantages in resolving the high deformation gradients that are present in this area and we achieve a more complete spatial coverage than with C-band. Extensive validation data based on levelling data and GPS measurements are available within RAǴs GIS based database "GeoMon" and thus enable an adequate analysis of the quality of the interferometric results. Previous analyses confirm the good accuracy of PALSAR data for deformation monitoring in mining areas. Furthermore, we present results of special investigations like precision geocoding of PALSAR data and corner reflector analysis. At present only DInSAR results are obtained due to the currently available number of PALSAR scenes. For the future we plan to also apply Persistent Scatterer Interferometry (PSI) using longer series of PALSAR data.

Wavelet-based higher-order neural networks for mine detection in thermal IR imagery

NASA Astrophysics Data System (ADS)

Baertlein, Brian A.; Liao, Wen-Jiao

2000-08-01

An image processing technique is described for the detection of miens in RI imagery. The proposed technique is based on a third-order neural network, which processes the output of a wavelet packet transform. The technique is inherently invariant to changes in signature position, rotation and scaling. The well-known memory limitations that arise with higher-order neural networks are addressed by (1) the data compression capabilities of wavelet packets, (2) protections of the image data into a space of similar triangles, and (3) quantization of that 'triangle space'. Using these techniques, image chips of size 28 by 28, which would require 0(109) neural net weights, are processed by a network having 0(102) weights. ROC curves are presented for mine detection in real and simulated imagery.

Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

PubMed Central

Batal, Iyad; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

Western energy related overhead monitoring project. Phase 2: Summary. [Campbell County, Wyoming and coal strip mines in Montana and New Mexico

NASA Technical Reports Server (NTRS)

Anderson, J. E. (Principal Investigator)

1979-01-01

Assistance by NASA to EPA in the establishment and maintenance of a fully operational energy-related monitoring system included: (1) regional analysis applications based on LANDSAT and auxiliary data; (2) development of techniques for using aircraft MSS data to rapidly monitor site specific surface coal mine activities; and (3) registration of aircraft MSS data to a map base. The coal strip mines used in the site specific task were in Campbell County, Wyoming; Big Horn County, Montana; and the Navajo mine in San Juan County, New Mexico. The procedures and software used to accomplish these tasks are described.

Text and Structural Data Mining of Influenza Mentions in Web and Social Media

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

Corley, Courtney D.; Cook, Diane; Mikler, Armin R.

Text and structural data mining of Web and social media (WSM) provides a novel disease surveillance resource and can identify online communities for targeted public health communications (PHC) to assure wide dissemination of pertinent information. WSM that mention influenza are harvested over a 24-week period, 5-October-2008 to 21-March-2009. Link analysis reveals communities for targeted PHC. Text mining is shown to identify trends in flu posts that correlate to real-world influenza-like-illness patient report data. We also bring to bear a graph-based data mining technique to detect anomalies among flu blogs connected by publisher type, links, and user-tags.

Biomechanical comparison of the double-push technique and the conventional skate skiing technique in cross-country sprint skiing.

PubMed

Stöggl, Thomas; Müller, Erich; Lindinger, Stefan

2008-09-01

The aims of the study were to: (1) adapt the "double-push" technique from inline skating to cross-country skiing; (2) compare this new skiing technique with the conventional skate skiing cross-country technique; and (3) test the hypothesis that the double-push technique improves skiing speed in a short sprint. 13 elite skiers performed maximum-speed sprints over 100 m using the double-push skate skiing technique and using the conventional "V2" skate skiing technique. Pole and plantar forces, knee angle, cycle characteristics, and electromyography of nine lower body muscles were analysed. We found that the double-push technique could be successfully transferred to cross-country skiing, and that this new technique is faster than the conventional skate skiing technique. The double-push technique was 2.9 +/- 2.2% faster (P < 0.001), which corresponds to a time advantage of 0.41 +/- 0.31 s over 100 m. The double-push technique had a longer cycle length and a lower cycle rate, and it was characterized by higher muscle activity, higher knee extension amplitudes and velocities, and higher peak foot forces, especially in the first phase of the push-off. Also, the foot was more loaded laterally in the double-push technique than in the conventional skate skiing technique.

Speciation and distribution of copper in a mining soil using multiple synchrotron-based bulk and microscopic techniques.

PubMed

Yang, Jianjun; Liu, Jin; Dynes, James J; Peak, Derek; Regier, Tom; Wang, Jian; Zhu, Shenhai; Shi, Jiyan; Tse, John S

2014-02-01

Molecular-level understanding of soil Cu speciation and distribution assists in management of Cu contamination in mining sites. In this study, one soil sample, collected from a mining site contaminated since 1950s, was characterized complementarily by multiple synchrotron-based bulk and spatially resolved techniques for the speciation and distribution of Cu as well as other related elements (Fe, Ca, Mn, K, Al, and Si). Bulk X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopy revealed that soil Cu was predominantly associated with Fe oxides instead of soil organic matter. This agreed with the closest association of Cu to Fe by microscopic X-ray fluorescence (U-XRF) and scanning transmission X-ray microscopy (STXM) nanoanalysis, along with the non-occurrence of photoreduction of soil Cu(II) by quick Cu L3,2-edge XANES spectroscopy (Q-XANES) which often occurs when Cu organic complexes are present. Furthermore, bulk-EXAFS and STXM-coupled Fe L3,2-edge nano-XANES analysis revealed soil Cu adsorbed primarily to Fe(III) oxides by inner-sphere complexation. Additionally, Cu K-edge μ-XANES, L3,2-edge bulk-XANES, and successive Q-XANES results identified the presence of Cu2S rather than radiation-damage artifacts dominant in certain microsites of the mining soil. This study demonstrates the great benefits in use of multiple combined synchrotron-based techniques for comprehensive understanding of Cu speciation in heterogeneous soil matrix, which facilitates our prediction of Cu reactivity and environmental fate in the mining site.

Characterization of As-polluted soils by laboratory X-ray-based techniques coupled with sequential extractions and electron microscopy: the case of Crocette gold mine in the Monte Rosa mining district (Italy).

PubMed

Allegretta, Ignazio; Porfido, Carlo; Martin, Maria; Barberis, Elisabetta; Terzano, Roberto; Spagnuolo, Matteo

2018-06-24

Arsenic concentration and distribution were studied by combining laboratory X-ray-based techniques (wavelength dispersive X-ray fluorescence (WDXRF), micro X-ray fluorescence (μXRF), and X-ray powder diffraction (XRPD)), field emission scanning electron microscopy equipped with microanalysis (FE-SEM-EDX), and sequential extraction procedure (SEP) coupled to total reflection X-ray fluorescence (TXRF) analysis. This approach was applied to three contaminated soils and one mine tailing collected near the gold extraction plant at the Crocette gold mine (Macugnaga, VB) in the Monte Rosa mining district (Piedmont, Italy). Arsenic (As) concentration, measured with WDXRF, ranged from 145 to 40,200 mg/kg. XRPD analysis evidenced the presence of jarosite and the absence of any As-bearing mineral, suggesting a high weathering grade and strong oxidative conditions. However, small domains of Fe arsenate were identified by combining μXRF with FE-SEM-EDX. SEP results revealed that As was mainly associated to amorphous Fe oxides/hydroxides or hydroxysulfates (50-80%) and the combination of XRPD and FE-SEM-EDX suggested that this phase could be attributed to schwertmannite. On the basis of the reported results, As is scarcely mobile, even if a consistent As fraction (1-3 g As/kg of soil) is still potentially mobilizable. In general, the proposed combination of laboratory X-ray techniques could be successfully employed to unravel environmental issues related to metal(loid) pollution in soil and sediments.

Roadway backfill method to prevent geohazards induced by room and pillar mining: a case study in Changxing coal mine, China

NASA Astrophysics Data System (ADS)

Zhou, Nan; Li, Meng; Zhang, Jixiong; Gao, Rui

2016-11-01

Coal mines in the western areas of China experience low mining rates and induce many geohazards when using the room and pillar mining method. In this research, we proposed a roadway backfill method during longwall mining to target these problems. We tested the mechanical properties of the backfill materials to determine a reasonable ratio of backfill materials for the driving roadway during longwall mining. We also introduced the roadway layout and the backfill mining technique required for this method. Based on the effects of the abutment stress from a single roadway driving task, we designed the distance between roadways and a driving and filling sequence for multiple-roadway driving. By doing so, we found the movement characteristics of the strata with quadratic stabilization for backfill mining during roadway driving. Based on this research, the driving and filling sequence of the 3101 working face in Changxing coal mine was optimized to avoid the superimposed influence of mining-induced stress. According to the analysis of the surface monitoring data, the accumulated maximum subsidence is 15 mm and the maximum horizontal deformation is 0.8 mm m-1, which indicated that the ground basically had no obvious deformation after the implementation of the roadway backfill method at 3101 working face.

A Simplified Technique for Implant-Abutment Level Impression after Soft Tissue Adaptation around Provisional Restoration

PubMed Central

Kutkut, Ahmad; Abu-Hammad, Osama; Frazer, Robert

2016-01-01

Impression techniques for implant restorations can be implant level or abutment level impressions with open tray or closed tray techniques. Conventional implant-abutment level impression techniques are predictable for maximizing esthetic outcomes. Restoration of the implant traditionally requires the use of the metal or plastic impression copings, analogs, and laboratory components. Simplifying the dental implant restoration by reducing armamentarium through incorporating conventional techniques used daily for crowns and bridges will allow more general dentists to restore implants in their practices. The demonstrated technique is useful when modifications to implant abutments are required to correct the angulation of malpositioned implants. This technique utilizes conventional crown and bridge impression techniques. As an added benefit, it reduces costs by utilizing techniques used daily for crowns and bridges. The aim of this report is to describe a simplified conventional impression technique for custom abutments and modified prefabricated solid abutments for definitive restorations. PMID:29563457

Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.

PubMed

Wang, Weiqi; Wang, Yanbo Justin; Bañares-Alcántara, René; Coenen, Frans; Cui, Zhanfeng

2009-12-01

In this paper, data mining is used to analyze the data on the differentiation of mammalian Mesenchymal Stem Cells (MSCs), aiming at discovering known and hidden rules governing MSC differentiation, following the establishment of a web-based public database containing experimental data on the MSC proliferation and differentiation. To this effect, a web-based public interactive database comprising the key parameters which influence the fate and destiny of mammalian MSCs has been constructed and analyzed using Classification Association Rule Mining (CARM) as a data-mining technique. The results show that the proposed approach is technically feasible and performs well with respect to the accuracy of (classification) prediction. Key rules mined from the constructed MSC database are consistent with experimental observations, indicating the validity of the method developed and the first step in the application of data mining to the study of MSCs.

The Perceived Consequences of Gold Mining in Postwar El Salvador: A Qualitative Study.

PubMed

Zakrison, Tanya L; Cabezas, Pedro; Valle, Evan; Kornfeld, Julie; Muntaner, Carles; Soklaridis, Sophie

2015-11-01

We investigated themes related to the health and environmental impacts of gold mining in El Salvador. Over a 1-month period in 2013, we conducted focus groups (n = 32 participants in total) and individual semistructured interviews (n = 11) with community leaders until we achieved thematic saturation. Data collection took place in 4 departments throughout the country. We used a combination of criterion-purposive and snowballing sampling techniques to identify participants. Multiple themes emerged: (1) the fallacy of economic development; (2) critique of mining activities; (3) the creation of mining-related violence, with parallels to El Salvador's civil war; and (4) solutions and alternatives to mining activity. Solutions involved the creation of cooperative microenterprises for sustainable economic growth, political empowerment within communities, and development of local participatory democracies. Gold mining in El Salvador is perceived as a significant environmental and public health threat. Local solutions may be applicable broadly.

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

Sequential Extraction Results and Mineralogy of Mine Waste and Stream Sediments Associated With Metal Mines in Vermont, Maine, and New Zealand

USGS Publications Warehouse

Piatak, N.M.; Seal, R.R.; Sanzolone, R.F.; Lamothe, P.J.; Brown, Z.A.; Adams, M.

2007-01-01

We report results from sequential extraction experiments and the quantitative mineralogy for samples of stream sediments and mine wastes collected from metal mines. Samples were from the Elizabeth, Ely Copper, and Pike Hill Copper mines in Vermont, the Callahan Mine in Maine, and the Martha Mine in New Zealand. The extraction technique targeted the following operationally defined fractions and solid-phase forms: (1) soluble, adsorbed, and exchangeable fractions; (2) carbonates; (3) organic material; (4) amorphous iron- and aluminum-hydroxides and crystalline manganese-oxides; (5) crystalline iron-oxides; (6) sulfides and selenides; and (7) residual material. For most elements, the sum of an element from all extractions steps correlated well with the original unleached concentration. Also, the quantitative mineralogy of the original material compared to that of the residues from two extraction steps gave insight into the effectiveness of reagents at dissolving targeted phases. The data are presented here with minimal interpretation or discussion and further analyses and interpretation will be presented elsewhere.

Exploitation of multi-temporal Earth Observation imagery for monitoring land cover change in mining sites

NASA Astrophysics Data System (ADS)

Petropoulos, G.; Partsinevelos, P.; Mitraka, Z.

2012-04-01

Surface mining has been shown to cause intensive environmental degradation in terms of landscape, vegetation and biological communities. Nowadays, the commercial availability of remote sensing imagery at high spatiotemporal scales, has improved dramatically our ability to monitor surface mining activity and evaluate its impact on the environment and society. In this study we investigate the potential use of Landsat TM imagery combined with diverse classification techniques, namely artificial neural networks and support vector machines for delineating mining exploration and assessing its effect on vegetation in various surface mining sites in the Greek island of Milos. Assessment of the mining impact in the study area is validated through the analysis of available QuickBird imagery acquired nearly concurrently to the TM overpasses. Results indicate the capability of the TM sensor combined with the image analysis applied herein as a potential economically viable solution to provide rapidly and at regular time intervals information on mining activity and its impact to the local environment. KEYWORDS: mining environmental impact, remote sensing, image classification, change detection, land reclamation, support vector machines, neural networks

The peculiarities of structurizing enclosing rock massif while developing a coal seam

NASA Astrophysics Data System (ADS)

Kozyreva, E. N.; Shinkevich, M. V.

2017-09-01

Different concepts of the development of geo-mechanical processes during longwall mining of a seam which are fundamentally different from the conventional ones are introduced in the article. Fundamental principles of the model for structurizing enclosing rock mass while longwall mining along the strike are described. The model was developed on the bases of non-linear geomechanical laws. According to the model, rock mass in the area of mining operation is organized as rock geomechanical layers with shifting arches. And the formation period of shifting arches in disintegrated rock mass is divisible by the length of the stope. Undulate characteristic of a massif as a peculiarity of man-made structurization of a massif is defined. It is shown that structuring the broken massif causes the formation of block-structured system and it can be detected while monitoring the ground pressure in powered support props. The results of the research allow decreasing the negative influence of a ground pressure and can be applied to specify parameters for controlling the roof, defining geometrical dimensions of a mining section and positioning of holing chute (face entry).

Improving the sensitivity and accuracy of gamma activation analysis for the rapid determination of gold in mineral ores.

PubMed

Tickner, James; Ganly, Brianna; Lovric, Bojan; O'Dwyer, Joel

2017-04-01

Mining companies rely on chemical analysis methods to determine concentrations of gold in mineral ore samples. As gold is often mined commercially at concentrations around 1 part-per-million, it is necessary for any analysis method to provide good sensitivity as well as high absolute accuracy. We describe work to improve both the sensitivity and accuracy of the gamma activation analysis (GAA) method for gold. We present analysis results for several suites of ore samples and discuss the design of a GAA facility designed to replace conventional chemical assay in industrial applications. Copyright © 2017. Published by Elsevier Ltd.

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

PubMed

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Mining and beneficiation of lunar ores

NASA Technical Reports Server (NTRS)

Bunch, T. E.; Williams, R. J.; Mckay, D. S.; Giles, D.

1979-01-01

The beneficiation of lunar plagioclase and ilmenite ores to feedstock grade permits a rapid growth of the space manufacturing economy by maximizing the production rate of metals and oxygen. A beneficiation scheme based on electrostatic and magnetic separation is preferred over conventional schemes, but such a scheme cannot be completely modeled because beneficiation processes are empirical and because some properties of lunar minerals have not been measured. To meet anticipated shipping and processing needs, the peak lunar mining rate will exceed 1000 tons/hr by the fifth year of operation. Such capabilities will be best obtained by automated mining vehicles and conveyor systems rather than trucks. It may be possible to extract about 40 kg of volatiles (60 percent H2O) by thermally processing the less than 20 micron ilmenite concentrate extracted from 130 tons of ilmenite ore. A thermodynamic analysis of an extraction process is presented.

Coal rib response during bench mining: A case study

PubMed Central

Sears, Morgan M.; Rusnak, John; Van Dyke, Mark; Rashed, Gamal; Mohamed, Khaled; Sloan, Michael

2018-01-01

In 2016, room-and-pillar mining provided nearly 40% of underground coal production in the United States. Over the past decade, rib falls have resulted in 12 fatalities, representing 28% of the ground fall fatalities in U.S. underground coal mines. Nine of these 12 fatalities (75%) have occurred in room-and-pillar mines. The objective of this research is to study the geomechanics of bench room-and-pillar mining and the associated response of high pillar ribs at overburden depths greater than 300 m. This paper provides a definition of the bench technique, the pillar response due to loading, observational data for a case history, a calibrated numerical model of the observed rib response, and application of this calibrated model to a second site. PMID:29862125

Charcoal from a prehistoric copper mine in the Austrian Alps: dendrochronological and dendrological data, demand for wood and forest utilisation.

PubMed

Pichler, Thomas; Nicolussi, Kurt; Goldenberg, Gert; Hanke, Klaus; Kovács, Kristóf; Thurner, Andrea

2013-02-01

During prehistory fire-setting was the most appropriate technique for exploiting ore deposits. Charcoal fragments found in the course of archaeological excavations in a small mine called Mauk E in the area of Schwaz/Brixlegg (Tyrol, Austria) are argued to be evidence for the use of this technology. Dendrochronological analyses of the charcoal samples yielded calendar dates for the mining activities showing that the exploitation of the Mauk E mine lasted approximately one decade in the late 8th century BC. Dendrological studies show that the miners utilised stem wood of spruce and fir from forests with high stand density for fire-setting and that the exploitation of the Mauk E mine had only a limited impact on the local forests.

The Application of LANDSAT Multi-Temporal Thermal Infrared Data to Identify Coal Fire in the Khanh Hoa Coal Mine, Thai Nguyen province, Vietnam

NASA Astrophysics Data System (ADS)

Trinh, Le Hung; Zablotskii, V. R.

2017-12-01

The Khanh Hoa coal mine is a surface coal mine in the Thai Nguyen province, which is one of the largest deposits of coal in the Vietnam. Numerous reasons such as improper mining techniques and policy, as well as unauthorized mining caused surface and subsurface coal fire in this area. Coal fire is a dangerous phenomenon which affects the environment seriously by releasing toxic fumes which causes forest fires, and subsidence of infrastructure surface. This article presents study on the application of LANDSAT multi-temporal thermal infrared images, which help to detect coal fire. The results obtained in this study can be used to monitor fire zones so as to give warnings and solutions to prevent coal fire.

Ultrawideband radar echoes of land mine targets measured at oblique incidence using a 250-kW impulse radar system

NASA Astrophysics Data System (ADS)

Chant, Ian J.; Staines, Geoff

1997-07-01

United Nations Peacekeeping forces around the world need to transport food, personnel and medical supplies through disputed regions were land mines are in active use as road blocks and terror weapons. A method of fast, effective land mine detection is needed to combat this threat to road transport. The technique must operate from a vehicle travelling at a reasonable velocity and give warning far enough ahead for the vehicle to stop in time to avoid the land mine. There is particular interest in detecting low- metallic content land mines. One possible solutionis the use of ultra-wide-band (UWB) radar. The Australian Defence Department is investigating the feasibility of using UWB radar for land mine detection from a vehicle. A 3 GHz UWB system has been used to collect target response from a series of inert land mines and mine-like objects placed on the ground and buried in the ground. The targets measured were a subset of those in the target set described in Wong et al. with the addition of inert land mines corresponding to some of the surrogate targets in this set. The results are encouraging for the detection of metallic land mines and the larger non-metallic land mines. Smaller low-metallic- content anti-personnel land mines are less likely to be detected.

Evaluation of the Accuracy of Conventional and Digital Impression Techniques for Implant Restorations.

PubMed

Moura, Renata Vasconcellos; Kojima, Alberto Noriyuki; Saraceni, Cintia Helena Coury; Bassolli, Lucas; Balducci, Ivan; Özcan, Mutlu; Mesquita, Alfredo Mikail Melo

2018-05-01

The increased use of CAD systems can generate doubt about the accuracy of digital impressions for angulated implants. The aim of this study was to evaluate the accuracy of different impression techniques, two conventional and one digital, for implants with and without angulation. We used a polyurethane cast that simulates the human maxilla according to ASTM F1839, and 6 tapered implants were installed with external hexagonal connections to simulate tooth positions 17, 15, 12, 23, 25, and 27. Implants 17 and 23 were placed with 15° of mesial angulation and distal angulation, respectively. Mini cone abutments were installed on these implants with a metal strap 1 mm in height. Conventional and digital impression procedures were performed on the maxillary master cast, and the implants were separated into 6 groups based on the technique used and measurement type: G1 - control, G2 - digital impression, G3 - conventional impression with an open tray, G4 - conventional impression with a closed tray, G5 - conventional impression with an open tray and a digital impression, and G6 - conventional impression with a closed tray and a digital impression. A statistical analysis was performed using two-way repeated measures ANOVA to compare the groups, and a Kruskal-Wallis test was conducted to analyze the accuracy of the techniques. No significant difference in the accuracy of the techniques was observed between the groups. Therefore, no differences were found among the conventional impression and the combination of conventional and digital impressions, and the angulation of the implants did not affect the accuracy of the techniques. All of the techniques exhibited trueness and had acceptable precision. The variation of the angle of the implants did not affect the accuracy of the techniques. © 2018 by the American College of Prosthodontists.

e-Research and Learning Theory: What Do Sequence and Process Mining Methods Contribute?

ERIC Educational Resources Information Center

Reimann, Peter; Markauskaite, Lina; Bannert, Maria

2014-01-01

This paper discusses the fundamental question of how data-intensive e-research methods could contribute to the development of learning theories. Using methodological developments in research on self-regulated learning as an example, it argues that current applications of data-driven analytical techniques, such as educational data mining and its…

Mining and Analyzing Circulation and ILL Data for Informed Collection Development

ERIC Educational Resources Information Center

Link, Forrest E.; Tosaka, Yuji; Weng, Cathy

2015-01-01

The authors investigated quantitative methods of collection use analysis employing library data that are available in ILS and ILL systems to better understand library collection use and user needs. For the purpose of the study, the authors extracted circulation and ILL records from the library's systems using data-mining techniques. By comparing…

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

Expanding the Role of Institutional Research at Small Private Universities: A Case Study in Enrollment Management Using Data Mining

ERIC Educational Resources Information Center

Antons, Christopher M.; Maltz, Elliot N.

2006-01-01

This case study documents a successful application of data-mining techniques in enrollment management through a partnership between the admissions office, a business administration master's-degree program, and the institutional research office at Willamette University (Salem, Oregon). (Contains 1 table and 3 figures.)

Binary Coded Web Access Pattern Tree in Education Domain

ERIC Educational Resources Information Center

Gomathi, C.; Moorthi, M.; Duraiswamy, K.

2008-01-01

Web Access Pattern (WAP), which is the sequence of accesses pursued by users frequently, is a kind of interesting and useful knowledge in practice. Sequential Pattern mining is the process of applying data mining techniques to a sequential database for the purposes of discovering the correlation relationships that exist among an ordered list of…

Data Mining in Earth System Science (DMESS 2011)

Treesearch

Forrest M. Hoffman; J. Walter Larson; Richard Tran Mills; Bhorn-Gustaf Brooks; Auroop R. Ganguly; William Hargrove; et al

2011-01-01

From field-scale measurements to global climate simulations and remote sensing, the growing body of very large and long time series Earth science data are increasingly difficult to analyze, visualize, and interpret. Data mining, information theoretic, and machine learning techniques—such as cluster analysis, singular value decomposition, block entropy, Fourier and...

Characterization and speciation of mercury-bearing mine wastes using X-ray absorption spectroscopy

USGS Publications Warehouse

Kim, C.S.; Brown, Gordon E.; Rytuba, J.J.

2000-01-01

Mining of mercury deposits located in the California Coast Range has resulted in the release of mercury to the local environment and water supplies. The solubility, transport, and potential bioavailability of mercury are controlled by its chemical speciation, which can be directly determined for samples with total mercury concentrations greater than 100 mg kg-1 (ppm) using X-ray absorption spectroscopy (XAS). This technique has the additional benefits of being non-destructive to the sample, element-specific, relatively sensitive at low concentrations, and requiring minimal sample preparation. In this study, Hg L(III)-edge extended X-ray absorption fine structure (EXAFS) spectra were collected for several mercury mine tailings (calcines) in the California Coast Range. Total mercury concentrations of samples analyzed ranged from 230 to 1060 ppm. Speciation data (mercury phases present and relative abundances) were obtained by comparing the spectra from heterogeneous, roasted (calcined) mine tailings samples with a spectral database of mercury minerals and sorbed mercury complexes. Speciation analyses were also conducted on known mixtures of pure mercury minerals in order to assess the quantitative accuracy of the technique. While some calcine samples were found to consist exclusively of mercuric sulfide, others contain additional, more soluble mercury phases, indicating a greater potential for the release of mercury into solution. Also, a correlation was observed between samples from hot-spring mercury deposits, in which chloride levels are elevated, and the presence of mercury-chloride species as detected by the speciation analysis. The speciation results demonstrate the ability of XAS to identify multiple mercury phases in a heterogeneous sample, with a quantitative accuracy of ??25% for the mercury-containing phases considered. Use of this technique, in conjunction with standard microanalytical techniques such as X-ray diffraction and electron probe microanalysis, is beneficial in the prioritization and remediation of mercury-contaminated mine sites. (C) 2000 Elsevier Science B.V.

Systematic Review of Data Mining Applications in Patient-Centered Mobile-Based Information Systems.

PubMed

Fallah, Mina; Niakan Kalhori, Sharareh R

2017-10-01

Smartphones represent a promising technology for patient-centered healthcare. It is claimed that data mining techniques have improved mobile apps to address patients' needs at subgroup and individual levels. This study reviewed the current literature regarding data mining applications in patient-centered mobile-based information systems. We systematically searched PubMed, Scopus, and Web of Science for original studies reported from 2014 to 2016. After screening 226 records at the title/abstract level, the full texts of 92 relevant papers were retrieved and checked against inclusion criteria. Finally, 30 papers were included in this study and reviewed. Data mining techniques have been reported in development of mobile health apps for three main purposes: data analysis for follow-up and monitoring, early diagnosis and detection for screening purpose, classification/prediction of outcomes, and risk calculation (n = 27); data collection (n = 3); and provision of recommendations (n = 2). The most accurate and frequently applied data mining method was support vector machine; however, decision tree has shown superior performance to enhance mobile apps applied for patients' self-management. Embedded data-mining-based feature in mobile apps, such as case detection, prediction/classification, risk estimation, or collection of patient data, particularly during self-management, would save, apply, and analyze patient data during and after care. More intelligent methods, such as artificial neural networks, fuzzy logic, and genetic algorithms, and even the hybrid methods may result in more patients-centered recommendations, providing education, guidance, alerts, and awareness of personalized output.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

PubMed

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other

PubMed Central

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients’ medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD. PMID:28497080

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.

Factoring uncertainty into restoration modeling of in-situ leach uranium mines

USGS Publications Warehouse

Johnson, Raymond H.; Friedel, Michael J.

2009-01-01

Postmining restoration is one of the greatest concerns for uranium in-situ leach (ISL) mining operations. The ISL-affected aquifer needs to be returned to conditions specified in the mining permit (either premining or other specified conditions). When uranium ISL operations are completed, postmining restoration is usually achieved by injecting reducing agents into the mined zone. The objective of this process is to restore the aquifer to premining conditions by reducing the solubility of uranium and other metals in the ground water. Reactive transport modeling is a potentially useful method for simulating the effectiveness of proposed restoration techniques. While reactive transport models can be useful, they are a simplification of reality that introduces uncertainty through the model conceptualization, parameterization, and calibration processes. For this reason, quantifying the uncertainty in simulated temporal and spatial hydrogeochemistry is important for postremedial risk evaluation of metal concentrations and mobility. Quantifying the range of uncertainty in key predictions (such as uranium concentrations at a specific location) can be achieved using forward Monte Carlo or other inverse modeling techniques (trial-and-error parameter sensitivity, calibration constrained Monte Carlo). These techniques provide simulated values of metal concentrations at specified locations that can be presented as nonlinear uncertainty limits or probability density functions. Decisionmakers can use these results to better evaluate environmental risk as future metal concentrations with a limited range of possibilities, based on a scientific evaluation of uncertainty.

Integrating unified medical language system and association mining techniques into relevance feedback for biomedical literature search.

PubMed

Ji, Yanqing; Ying, Hao; Tran, John; Dews, Peter; Massanari, R Michael

2016-07-19

Finding highly relevant articles from biomedical databases is challenging not only because it is often difficult to accurately express a user's underlying intention through keywords but also because a keyword-based query normally returns a long list of hits with many citations being unwanted by the user. This paper proposes a novel biomedical literature search system, called BiomedSearch, which supports complex queries and relevance feedback. The system employed association mining techniques to build a k-profile representing a user's relevance feedback. More specifically, we developed a weighted interest measure and an association mining algorithm to find the strength of association between a query and each concept in the article(s) selected by the user as feedback. The top concepts were utilized to form a k-profile used for the next-round search. BiomedSearch relies on Unified Medical Language System (UMLS) knowledge sources to map text files to standard biomedical concepts. It was designed to support queries with any levels of complexity. A prototype of BiomedSearch software was made and it was preliminarily evaluated using the Genomics data from TREC (Text Retrieval Conference) 2006 Genomics Track. Initial experiment results indicated that BiomedSearch increased the mean average precision (MAP) for a set of queries. With UMLS and association mining techniques, BiomedSearch can effectively utilize users' relevance feedback to improve the performance of biomedical literature search.

Analyzing Large Gene Expression and Methylation Data Profiles Using StatBicRM: Statistical Biclustering-Based Rule Mining

PubMed Central

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level. PMID:25830807

Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

PubMed

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level.

Application of Foam-gel Technique to Control CO Exposure Generated During Spontaneous Combustion of Coal in Coal Mines.

PubMed

Ren, Xing W; Wang, Feng Z; Guo, Qing; Zuo, Zhao B; Fang, Qi S

2015-01-01

In China, 47.3% of state-owned coal mines are located in coal seams that are prone to spontaneous combustion. The spontaneous combustion of coal is the main cause of the generation of a large amount of carbon monoxide, which can cause serious health issues to miners. A new technique using foam-gel formation was developed to effectively control the spontaneous combustion of coal. The gel can capture more than 90% of the water in the grout and at the same time the foam can cover dangerous areas in the goaf by stacking and cooling of foam in all directions. In this study, a mechanism of foam-gel formation was introduced and the optimal proportions of additives were defined based on experiments of different foaming properties, gelling time and water loss rate as the main index parameters. The results of a field application in a coal mine promise that this new technique would effectively prevent coal oxidation in the goaf and reduce the generation of carbon monoxide.

Text Classification for Organizational Researchers

PubMed Central

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

2017-01-01

Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable. Techniques from text mining facilitate the automatic assignment of text strings to categories, making classification expedient, fast, and reliable, which creates potential for its application in organizational research. The purpose of this article is to familiarize organizational researchers with text mining techniques from machine learning and statistics. We describe the text classification process in several roughly sequential steps, namely training data preparation, preprocessing, transformation, application of classification techniques, and validation, and provide concrete recommendations at each step. To help researchers develop their own text classifiers, the R code associated with each step is presented in a tutorial. The tutorial draws from our own work on job vacancy mining. We end the article by discussing how researchers can validate a text classification model and the associated output. PMID:29881249

Carbon Sequestration on Surface Mine Lands

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

Donald Graves; Christopher Barton; Richard Sweigard

2006-03-31

Since the implementation of the federal Surface Mining Control and Reclamation Act of 1977 (SMCRA) in May of 1978, many opportunities have been lost for the reforestation of surface mines in the eastern United States. Research has shown that excessive compaction of spoil material in the backfilling and grading process is the biggest impediment to the establishment of productive forests as a post-mining land use (Ashby, 1998, Burger et al., 1994, Graves et al., 2000). Stability of mine sites was a prominent concern among regulators and mine operators in the years immediately following the implementation of SMCRA. These concerns resultedmore » in the highly compacted, flatly graded, and consequently unproductive spoils of the early post-SMCRA era. However, there is nothing in the regulations that requires mine sites to be overly compacted as long as stability is achieved. It has been cultural barriers and not regulatory barriers that have contributed to the failure of reforestation efforts under the federal law over the past 27 years. Efforts to change the perception that the federal law and regulations impede effective reforestation techniques and interfere with bond release must be implemented. Demonstration of techniques that lead to the successful reforestation of surface mines is one such method that can be used to change perceptions and protect the forest ecosystems that were indigenous to these areas prior to mining. The University of Kentucky initiated a large-scale reforestation effort to address regulatory and cultural impediments to forest reclamation in 2003. During the three years of this project 383,000 trees were planted on over 556 acres in different physiographic areas of Kentucky (Table 1, Figure 1). Species used for the project were similar to those that existed on the sites before mining was initiated (Table 2). A monitoring program was undertaken to evaluate growth and survival of the planted species as a function of spoil characteristics and reclamation practice. In addition, experiments were integrated within the reforestation effort to address specific questions pertaining to sequestration of carbon (C) on these sites.« less

Preliminary report on the Black Thunder, Wyoming CTBT R and D experiment quicklook report: LLNL input from regional stations

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

Harben, P.E.; Glenn, L.A.

This report presents a preliminary summary of the data recorded at three regional seismic stations from surface blasting at the Black Thunder Coal Mine in northeast Wyoming. The regional stations are part of a larger effort that includes many more seismic stations in the immediate vicinity of the mine. The overall purpose of this effort is to characterize the source function and propagation characteristics of large typical surface mine blasts. A detailed study of source and propagation features of conventional surface blasts is a prerequisite to attempts at discriminating this type of blasting activity from other sources of seismic events.more » The Black Thunder Seismic experiment is a joint verification effort to determine seismic source and path effects that result from very large, but routine ripple-fired surface mining blasts. Studies of the data collected will be for the purpose of understanding how the near-field and regional seismic waveforms from these surface mining blasts are similar to, and different from, point shot explosions and explosions at greater depth. The Black Hills Station is a Designated Seismic Station that was constructed for temporary occupancy by the Former Soviet Union seismic verification scientists in accordance with the Threshold Test Ban Treaty protocol.« less

Occupational safety and health implications of increased coal utilization.

PubMed Central

Bridbord, K; Costello, J; Gamble, J; Groce, D; Hutchison, M; Jones, W; Merchant, J; Ortmeyer, C; Reger, R; Wagner, W L

1979-01-01

An area of major concern in considering increased coal production and utilization is the health and safety of increased numbers of workers who mine, process, or utilize coal. Hazards related to mining activities in the past have been especially serious, resulting in many mine related accidental deaths, disabling injuries, and disability and death from chronic lung disease. Underground coal mines are clearly less safe than surface mines. Over one-third of currently employed underground miners experience chronic lung disease. Other stresses include noise and extremes of heat and cold. Newly emphasized technologies of the use of diesel powered mining equipment and the use of longwall mining techniques may be associated with serious health effects. Workers at coal-fired power plants are also potentially at risk of occupational diseases. Occupational safety and health aspects of coal mining are understood well enough today to justify implementing necessary and technically feasible and available control measures to minimize potential problems associated with increased coal production and use in the future. Increased emphasis on safety and health training for inexperienced coal miners expected to enter the work force is clearly needed. The recently enacted Federal Mine Safety and Health Act of 1977 will provide impetus for increased control over hazards in coal mining. PMID:540621

A Comparative Evaluation of the Effect of Double Casting Technique Using Functionally Generated Path and Conventional Single Casting with Respect to Functional Articulation, Patient Satisfaction and Chair Side Time, in Single Unit Molar Teeth: An In Vivo Study.

PubMed

Memon, Sarfaraz

2014-12-01

A stable centric occlusal position that shows no evidence of occlusal disease should not be altered. Confirmative restorative dentistry deals with making restorations that are in harmony with existing jaw relations. Conventional techniques for construction have been unsuccessful in producing a prosthesis that can be inserted without minor intraoral occlusal adjustment. This study was conducted to evaluate the benefits of the double casting technique with FGP over the conventional casting technique. Ten patients with root canal treated maxillary molar were selected for the fabrication of metal crown. Two techniques, one involving the conventional fabrication and other using functionally generated path with double casting were used to fabricate the prosthesis. A comparison based on various parameters which was done between the two techniques. The change in the height of castings for the double casting group was less compared to the conventional group and was highly statistically significant (P < 0.001). The time taken for occlusal correction was significantly lower in double casting group than the conventional group (P < 0.001). The patient satisfaction (before occlusal correction) indicated better satisfaction for double casting group compared to conventional (P < 0.01). The functionally generated path with double casting technique resulted in castings which had better dimensional accuracy, less occlusal correction and better patient satisfaction compared to the conventional castings.

Comparison of digital and conventional impression techniques: evaluation of patients' perception, treatment comfort, effectiveness and clinical outcomes.

PubMed

Yuzbasioglu, Emir; Kurt, Hanefi; Turunc, Rana; Bilir, Halenur

2014-01-30

The purpose of this study was to compare two impression techniques from the perspective of patient preferences and treatment comfort. Twenty-four (12 male, 12 female) subjects who had no previous experience with either conventional or digital impression participated in this study. Conventional impressions of maxillary and mandibular dental arches were taken with a polyether impression material (Impregum, 3 M ESPE), and bite registrations were made with polysiloxane bite registration material (Futar D, Kettenbach). Two weeks later, digital impressions and bite scans were performed using an intra-oral scanner (CEREC Omnicam, Sirona). Immediately after the impressions were made, the subjects' attitudes, preferences and perceptions towards impression techniques were evaluated using a standardized questionnaire. The perceived source of stress was evaluated using the State-Trait Anxiety Scale. Processing steps of the impression techniques (tray selection, working time etc.) were recorded in seconds. Statistical analyses were performed with the Wilcoxon Rank test, and p < 0.05 was considered significant. There were significant differences among the groups (p < 0.05) in terms of total working time and processing steps. Patients stated that digital impressions were more comfortable than conventional techniques. Digital impressions resulted in a more time-efficient technique than conventional impressions. Patients preferred the digital impression technique rather than conventional techniques.

[Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

PubMed

Li, Na; Lü, Jian-sheng; Altemann, W

2010-09-01

Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.

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.

Visual mining geo-related data using pixel bar charts

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Keim, Daniel A.; Dayal, Umeshwar; Wright, Peter; Schneidewind, Joern

2005-03-01

A common approach to analyze geo-related data is using bar charts or x-y plots. They are intuitive and easy to use. But important information often gets lost. In this paper, we introduce a new interactive visualization technique called Geo Pixel Bar Charts, which combines the advantages of Pixel Bar Charts and interactive maps. This technique allows analysts to visualize large amounts of spatial data without aggregation and shows the geographical regions corresponding to the spatial data attribute at the same time. In this paper, we apply Geo Pixel Bar Charts to visually mining sales transactions and Internet usage from different locations. Our experimental results show the effectiveness of this technique for providing data distribution and exceptions from the map.

A proposed framework on hybrid feature selection techniques for handling high dimensional educational data

NASA Astrophysics Data System (ADS)

Shahiri, Amirah Mohamed; Husain, Wahidah; Rashid, Nur'Aini Abd

2017-10-01

Huge amounts of data in educational datasets may cause the problem in producing quality data. Recently, data mining approach are increasingly used by educational data mining researchers for analyzing the data patterns. However, many research studies have concentrated on selecting suitable learning algorithms instead of performing feature selection process. As a result, these data has problem with computational complexity and spend longer computational time for classification. The main objective of this research is to provide an overview of feature selection techniques that have been used to analyze the most significant features. Then, this research will propose a framework to improve the quality of students' dataset. The proposed framework uses filter and wrapper based technique to support prediction process in future study.

Hybrid weeds! Agent biotypes!: Montana's ever-evolving toadflax biological control soap opera

Treesearch

S. E. Sing; D. K. Weaver; S. M. Ward; J. Milan; C. L. Jorgensen; R. A. Progar; A. Gassmann; I. Tooevski

2013-01-01

An exotic toadflax stem mining weevil conventionally identified as Mecinus janthinus Germar has become widely established on Dalmatian toadflax [Linaria dalmatica (Linnaeus) Miller] in western North America, although agent density and control efficacy are highly variable across release sites (De Clerck-Floate & Miller, 2002; McClay & Hughes, 2007; Van Hezewijk...

Mining lesquerella seed transcriptome for oil and meal improvement and translational research

USDA-ARS?s Scientific Manuscript database

Lesquerella (Physaria fendleri), a member of the Brassicaceae family, is currently being developed as a new industrial oilseed. Lesquerella is valued for its unusual hydroxy fatty acid (HFA) lesquerolic acid (20:1OH). The conventional source of HFA is ricinoleic acid (18:1OH) from castor oil. Ricino...

40 CFR 440.105 - Effluent limitations representing the degree of effluent reduction attainable by the application...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Effluent limitations representing the degree of effluent reduction attainable by the application of the best conventional pollutant control... AGENCY (CONTINUED) EFFLUENT GUIDELINES AND STANDARDS ORE MINING AND DRESSING POINT SOURCE CATEGORY Copper...

29 CFR 452.80 - Bona fide candidates.

Code of Federal Regulations, 2010 CFR

2010-07-01

... nominated in order to be a bona fide candidate entitled to exercise the rights mentioned in §§ 452.67 and... able to take advantage of the distribution rights even before the convention meets and thus attempt to.... United Mine Workers, 71 LRRM 2606, 60 L.C. 10,204 (D.D.C. 1969). ...

Selecting Proper Plant Species for Mine Reclamation Using Fuzzy AHP Approach (Case Study: Chadormaloo Iron Mine of Iran)

NASA Astrophysics Data System (ADS)

Ebrahimabadi, Arash

2016-12-01

This paper describes an effective approach to select suitable plant species for reclamation of mined lands in Chadormaloo iron mine which is located in central part of Iran, near the city of Bafgh in Yazd province. After mine's total reserves are excavated, the mine requires to be permanently closed and reclaimed. Mine reclamation and post-mining land-use are the main issues in the phase of mine closure. In general, among various scenarios for mine reclamation process, i.e. planting, agriculture, forestry, residency, tourist attraction, etc., planting is the oldest and commonly-used technology for the reclamation of lands damaged by mining activities. Planting and vegetation play a major role in restoring productivity, ecosystem stability and biological diversity to degraded areas, therefore the main goal of this research work is to choose proper and suitable plants compatible with the conditions of Chadormaloo mined area, providing consistent conditions for future use. To ensure the sustainability of the reclaimed landscape, the most suitable plant species adapted to the mine conditions are selected. Plant species selection is a Multi Criteria Decision Making (MCDM) problem. In this paper, a fuzzy MCDM technique, namely Fuzzy Analytic Hierarchy Process (FAHP) is developed to assist chadormaloo iron mine managers and designers in the process of plant type selection for reclamation of the mine under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The results achieved from using FAHP approach demonstrate that the most proper plant species are ranked as Artemisia sieberi, Salsola yazdiana, Halophytes types, and Zygophyllum, respectively for reclamation of Chadormaloo iron mine.

Evaluation of the marginal fit of metal copings fabricated on three different marginal designs using conventional and accelerated casting techniques: an in vitro study.

PubMed

Vaidya, Sharad; Parkash, Hari; Bhargava, Akshay; Gupta, Sharad

2014-01-01

Abundant resources and techniques have been used for complete coverage crown fabrication. Conventional investing and casting procedures for phosphate-bonded investments require a 2- to 4-h procedure before completion. Accelerated casting techniques have been used, but may not result in castings with matching marginal accuracy. The study measured the marginal gap and determined the clinical acceptability of single cast copings invested in a phosphate-bonded investment with the use of conventional and accelerated methods. One hundred and twenty cast coping samples were fabricated using conventional and accelerated methods, with three finish lines: Chamfer, shoulder and shoulder with bevel. Sixty copings were prepared with each technique. Each coping was examined with a stereomicroscope at four predetermined sites and measurements of marginal gaps were documented for each. A master chart was prepared for all the data and was analyzed using Statistical Package for the Social Sciences version. Evidence of marginal gap was then evaluated by t-test. Analysis of variance and Post-hoc analysis were used to compare two groups as well as to make comparisons between three subgroups . Measurements recorded showed no statistically significant difference between conventional and accelerated groups. Among the three marginal designs studied, shoulder with bevel showed the best marginal fit with conventional as well as accelerated casting techniques. Accelerated casting technique could be a vital alternative to the time-consuming conventional casting technique. The marginal fit between the two casting techniques showed no statistical difference.

Discovery of Information Diffusion Process in Social Networks

NASA Astrophysics Data System (ADS)

Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

Integrating gravity and magnetic field data to delineate structurally controlled gold mineralization in the Sefwi Belt of Ghana

NASA Astrophysics Data System (ADS)

Konadu Amoah, Bernard; Dadzie, Isaac; Takyi-Kyeremeh, Kwaku

2018-08-01

Gravity and magnetic surveys were used to delineate potential gold mineralization zones in the Sefwi belt of Ghana. The study area is an intrusive dominated area that hosts pockets of small scale mining operations locally referred to as Galamsey. These Galamsey operations are not guided by a scientific approach to back the trend of gold mineralization which is conventionally mined. The study aimed at mapping lithological units, structural setting and relating Galamsey sites to delineate potential zones of gold mineralization. A Scintrex CG5 gravimeter and GEM’s Overhauser magnetometer were used for gravity and magnetic data acquisition respectively. The magnetic data were corrected and enhancing filters such as reduction to the pole (RTP), analytical signal and first vertical derivative were applied using Oasis montaj 7.1. Gravity data were also reduced to the geoid using the Oasis montaj software to produce a complete Bouguer anomaly map. The regional/residual separation technique produced a residual gravity map. The RTP and analytical signal filters from the magnetic data and residual gravity anomaly map from the gravity data helped in mapping belt type (Dixcove) Birimian granitoids and mafic intrusive unit, interpreted as gabbro. The first vertical derivative filter was useful in mapping NE/SW minor faults and crosscutting dykes largely concentrated in the belt type Birimian granitoids. All the three mapped Galamsey sites fell on a minor fault and are associated with the belt type granitoids which were used in delineating four potential zones of gold mineralization.

The association rules search of Indonesian university graduate’s data using FP-growth algorithm

NASA Astrophysics Data System (ADS)

Faza, S.; Rahmat, R. F.; Nababan, E. B.; Arisandi, D.; Effendi, S.

2018-02-01

The attribute varieties in university graduates data have caused frustrations to the institution in finding the combinations of attributes that often emerge and have high integration between attributes. Association rules mining is a data mining technique to determine the integration of the data or the way of a data set affects another set of data. By way of explanation, there are possibilities in finding the integration of data on a large scale. Frequent Pattern-Growth (FP-Growth) algorithm is one of the association rules mining technique to determine a frequent itemset in an FP-Tree data set. From the research on the search of university graduate’s association rules, it can be concluded that the most common attributes that have high integration between them are in the combination of State-owned High School outside Medan, regular university entrance exam, GPA of 3.00 to 3.49 and over 4-year-long study duration.

Assessing the effects of underground mining activities on high-voltage overhead power lines

NASA Astrophysics Data System (ADS)

Gusev, Vladimir; Zhuravlyov, Alexei; Maliukhina, Elena

2017-11-01

This paper introduces a technique for predictive assessment of changes in the position of power transmission towers and condition of overhead power lines, located in the zone of influence of displacements and deformations of the Earth's surface caused by mining activities. A special approach for monitoring the technical condition of towers and cables is proposed. It is intended to address the issue of controlling the condition of transmission lines that are under the influence of underground mining activities and to checkmate such impact.

Maps showing mines, quarries, and prospects, with analyses of samples, Gee Creek Wilderness, Polk and Monroe counties, Tennessee

USGS Publications Warehouse

Gazdik, Gertrude C.; Behum, Paul T.

1983-01-01

During the recent U.S. Bureau of Mines field investigation, 21 samples were collected (fig. 2) and were submitted to the Bureau's Reno Metallurgy Research Center, Reno, Nev., for analysis. All samples were tested for 40 elements by semiquantitative spectrographic analyses. Additional testing by atomic absorption, neutron activation, and wet chemical techniques was performed for selected elements on some samples. Two shale samples were submitted to the Bureau of Mines, Tuscaloosa Metallurgy Research Center, Tuscaloosa, Ala., for the evaluation of ceramic properties. 

Careflow Mining Techniques to Explore Type 2 Diabetes Evolution.

PubMed

Dagliati, Arianna; Tibollo, Valentina; Cogni, Giulia; Chiovato, Luca; Bellazzi, Riccardo; Sacchi, Lucia

2018-03-01

In this work we describe the application of a careflow mining algorithm to detect the most frequent patterns of care in a type 2 diabetes patients cohort. The applied method enriches the detected patterns with clinical data to define temporal phenotypes across the studied population. Novel phenotypes are discovered from heterogeneous data of 424 Italian patients, and compared in terms of metabolic control and complications. Results show that careflow mining can help to summarize the complex evolution of the disease into meaningful patterns, which are also significant from a clinical point of view.

Classical Measurement Methods and Laser Scanning Usage in Shaft Hoist Assembly Inventory

NASA Astrophysics Data System (ADS)

Jaśkowski, Wojciech; Lipecki, Tomasz; Matwij, Wojciech; Jabłoński, Mateusz

2018-03-01

The shaft hoist assembly is the base of underground mining plant. Its efficiency and correct operation is subject to restrictive legal regulations and is controlled on a daily visual assessment by shaft crew and energomechanics. In addition, in the regular interval, the shaft hoist assembly is subject to a thorough inventory, which includes the determination of the geometrical relationships between the hoisting machine, the headframe and the shaft with its housing. Inventory measurements for shaft and headframe are used for years of conventional geodetic methods including mechanical or laser plumbing and tachymetric surveys. Additional precision levelling is also used for measuring shafts of hoisting machines and rope pulleys. Continuous modernization of measuring technology makes it possible to implement the further methods to the above mentioned purposes. The comparison of the accuracy and the economics of performing measurements based on many years of experience with comprehensive inventory of shaft hoist assembly using various research techniques was made and detailed in the article.

Assimilation of cyanide and cyano-derivatives by Pseudomonas pseudoalcaligenes CECT5344: from omic approaches to biotechnological applications

PubMed Central

Cabello, Purificación; Luque-Almagro, Víctor M; Olaya-Abril, Alfonso; Sáez, Lara P; Moreno-Vivián, Conrado; Roldán, M Dolores

2018-01-01

Abstract Mining, jewellery and metal-processing industries use cyanide for extracting gold and other valuable metals, generating large amounts of highly toxic wastewater. Biological treatments may be a clean alternative under the environmental point of view to the conventional physical or chemical processes used to remove cyanide and related compounds from these industrial effluents. Pseudomonas pseudoalcaligenes CECT5344 can grow under alkaline conditions using cyanide, cyanate or different nitriles as the sole nitrogen source, and is able to remove up to 12 mM total cyanide from a jewellery industry wastewater that contains cyanide free and complexed to metals. Complete genome sequencing of this bacterium has allowed the application of transcriptomic and proteomic techniques, providing a holistic view of the cyanide biodegradation process. The complex response to cyanide by the cyanotrophic bacterium P. pseudoalcaligenes CECT5344 and the potential biotechnological applications of this model organism in the bioremediation of cyanide-containing industrial residues are reviewed. PMID:29438505

Assimilation of cyanide and cyano-derivatives by Pseudomonas pseudoalcaligenes CECT5344: from omic approaches to biotechnological applications.

PubMed

Cabello, Purificación; Luque-Almagro, Víctor M; Olaya-Abril, Alfonso; Sáez, Lara P; Moreno-Vivián, Conrado; Roldán, M Dolores

2018-03-01

Mining, jewellery and metal-processing industries use cyanide for extracting gold and other valuable metals, generating large amounts of highly toxic wastewater. Biological treatments may be a clean alternative under the environmental point of view to the conventional physical or chemical processes used to remove cyanide and related compounds from these industrial effluents. Pseudomonas pseudoalcaligenes CECT5344 can grow under alkaline conditions using cyanide, cyanate or different nitriles as the sole nitrogen source, and is able to remove up to 12 mM total cyanide from a jewellery industry wastewater that contains cyanide free and complexed to metals. Complete genome sequencing of this bacterium has allowed the application of transcriptomic and proteomic techniques, providing a holistic view of the cyanide biodegradation process. The complex response to cyanide by the cyanotrophic bacterium P. pseudoalcaligenes CECT5344 and the potential biotechnological applications of this model organism in the bioremediation of cyanide-containing industrial residues are reviewed.

Credit Risk Evaluation of Power Market Players with Random Forest

NASA Astrophysics Data System (ADS)

Umezawa, Yasushi; Mori, Hiroyuki

A new method is proposed for credit risk evaluation in a power market. The credit risk evaluation is to measure the bankruptcy risk of the company. The power system liberalization results in new environment that puts emphasis on the profit maximization and the risk minimization. There is a high probability that the electricity transaction causes a risk between companies. So, power market players are concerned with the risk minimization. As a management strategy, a risk index is requested to evaluate the worth of the business partner. This paper proposes a new method for evaluating the credit risk with Random Forest (RF) that makes ensemble learning for the decision tree. RF is one of efficient data mining technique in clustering data and extracting relationship between input and output data. In addition, the method of generating pseudo-measurements is proposed to improve the performance of RF. The proposed method is successfully applied to real financial data of energy utilities in the power market. A comparison is made between the proposed and the conventional methods.

Mining large heterogeneous data sets in drug discovery.

PubMed

Wild, David J

2009-10-01

Increasingly, effective drug discovery involves the searching and data mining of large volumes of information from many sources covering the domains of chemistry, biology and pharmacology amongst others. This has led to a proliferation of databases and data sources relevant to drug discovery. This paper provides a review of the publicly-available large-scale databases relevant to drug discovery, describes the kinds of data mining approaches that can be applied to them and discusses recent work in integrative data mining that looks for associations that pan multiple sources, including the use of Semantic Web techniques. The future of mining large data sets for drug discovery requires intelligent, semantic aggregation of information from all of the data sources described in this review, along with the application of advanced methods such as intelligent agents and inference engines in client applications.

Radon dynamics and reduction in an underground mine in Brazil. Implications for workers' exposure.

PubMed

Evangelista, H; Pereira, E B; Fernandes, H M; Sampaio, M

2002-01-01

This work was aimed at studying the behaviour of 222Rn in an experimental underground copper mine in Brazil with a single entrance. The 222Rn concentrations, meaured by using a dynamic radon measuring technique. varied between 30.5 Bq.m(-3), during ventilated conditions applied to the mine galleries, and 19.4 x 10(3) Bq.(-3) for non-ventilated conditions and when operational mining activities were conducted inside. High radon concentration surges were observed after blasting and drilling activities. In the cases of inadequate ventilation, it was estimated that workers could be subjected to exposures as high as 10 microSv.h(-1), only due to 222Rn and its short-lived progeny. The results show the importance of real-time measurements to evaluate radon dynamics during mining operations.

Chapter 4: Low compaction grading to enhance reforestation success on coal surface mines

Treesearch

R. Sweigard; J. Burger; C. Zipper; J. Skousen; C. Barton; P. Angel

2017-01-01

This Forest Reclamation Advisory describes final-grading techniques for reclaiming coal surface mines to forest postmining land uses. Final grading that leaves a loose soil and a rough surface increases survival of planted seedlings and forest productivity. Such practices are often less costly than traditional "smooth grading" while meeting the requirements...

Breaking Ground: Improving Undergraduate Engineering Projects through Flipped Teaching of Literature Search Techniques

ERIC Educational Resources Information Center

Maddison, Tasha; Beneteau, Donna; Sokoloski, Brandy

2014-01-01

This case study describes the use of flipped teaching for information literacy instruction in a new course, "Drill, Blast, and Excavate GeoE 498," within the mining option for geological engineering (GeoE) students. These students will enter the mining industry with less discipline-specific knowledge than a student that graduated with a…

Mining Interactions in Immersive Learning Environments for Real-Time Student Feedback

ERIC Educational Resources Information Center

Kennedy, Gregor; Ioannou, Ioanna; Zhou, Yun; Bailey, James; O'Leary, Stephen

2013-01-01

The analysis and use of data generated by students' interactions with learning systems or programs--learning analytics--has recently gained widespread attention in the educational technology community. Part of the reason for this interest is based on the potential of learning analytic techniques such as data mining to find hidden patterns in…

3-D Wave-Structure Interaction with Coastal Sediments - A Multi-Physics/Multi-Solution Techniques Approach

DTIC Science & Technology

2007-01-01

Stokes (RANS) and the particle finite element method ( PFEM ) will be used in the water/mine/sand domain. Sand and the geomaterials around the sand will...wave propagation over a bottom mine at various time steps (Soil and Foam model) 8 SOLID/FEM SAND/SPH GEOMATERIALS FNPF/BEM FNPF/BEM RANS/ PFEM

Trends of E-Learning Research from 2000 to 2008: Use of Text Mining and Bibliometrics

ERIC Educational Resources Information Center

Hung, Jui-long

2012-01-01

This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…

Determination of Consciousness and Awareness of the Public in Lefka about the Cyprus Mining Corporation (CMC)

ERIC Educational Resources Information Center

Gündüz, Serife; Erbulut, Can; Öznacar, Behcet; Bastas, Mert

2016-01-01

Supporting the increase of environmental consciousness with environmental education is always important in order to make healthy recommendations specific to the countries. Aim of this study is to determine the awareness and consciousness of the local community against the environmental pollution caused by the CMC mine by survey technique. 123…

The Effectiveness of Web-Based Learning Environment: A Case Study of Public Universities in Kenya

ERIC Educational Resources Information Center

Kirui, Paul A.; Mutai, Sheila J.

2010-01-01

Web mining is emerging in many aspects of e-learning, aiming at improving online learning and teaching processes and making them more transparent and effective. Researchers using Web mining tools and techniques are challenged to learn more about the online students' reshaping online courses and educational websites, and create tools for…

Identifying Engineering Students' English Sentence Reading Comprehension Errors: Applying a Data Mining Technique

ERIC Educational Resources Information Center

Tsai, Yea-Ru; Ouyang, Chen-Sen; Chang, Yukon

2016-01-01

The purpose of this study is to propose a diagnostic approach to identify engineering students' English reading comprehension errors. Student data were collected during the process of reading texts of English for science and technology on a web-based cumulative sentence analysis system. For the analysis, the association-rule, data mining technique…

Comparative Evaluation of Conventional and Accelerated Castings on Marginal Fit and Surface Roughness.

PubMed

Jadhav, Vivek Dattatray; Motwani, Bhagwan K; Shinde, Jitendra; Adhapure, Prasad

2017-01-01

The aim of this study was to evaluate the marginal fit and surface roughness of complete cast crowns made by a conventional and an accelerated casting technique. This study was divided into three parts. In Part I, the marginal fit of full metal crowns made by both casting techniques in the vertical direction was checked, in Part II, the fit of sectional metal crowns in the horizontal direction made by both casting techniques was checked, and in Part III, the surface roughness of disc-shaped metal plate specimens made by both casting techniques was checked. A conventional technique was compared with an accelerated technique. In Part I of the study, the marginal fit of the full metal crowns as well as in Part II, the horizontal fit of sectional metal crowns made by both casting techniques was determined, and in Part III, the surface roughness of castings made with the same techniques was compared. The results of the t -test and independent sample test do not indicate statistically significant differences in the marginal discrepancy detected between the two casting techniques. For the marginal discrepancy and surface roughness, crowns fabricated with the accelerated technique were significantly different from those fabricated with the conventional technique. Accelerated casting technique showed quite satisfactory results, but the conventional technique was superior in terms of marginal fit and surface roughness.

Data mining and statistical inference in selective laser melting

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

Kamath, Chandrika

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Data mining and statistical inference in selective laser melting

DOE PAGES

Kamath, Chandrika

2016-01-11

Selective laser melting (SLM) is an additive manufacturing process that builds a complex three-dimensional part, layer-by-layer, using a laser beam to fuse fine metal powder together. The design freedom afforded by SLM comes associated with complexity. As the physical phenomena occur over a broad range of length and time scales, the computational cost of modeling the process is high. At the same time, the large number of parameters that control the quality of a part make experiments expensive. In this paper, we describe ways in which we can use data mining and statistical inference techniques to intelligently combine simulations andmore » experiments to build parts with desired properties. We start with a brief summary of prior work in finding process parameters for high-density parts. We then expand on this work to show how we can improve the approach by using feature selection techniques to identify important variables, data-driven surrogate models to reduce computational costs, improved sampling techniques to cover the design space adequately, and uncertainty analysis for statistical inference. Here, our results indicate that techniques from data mining and statistics can complement those from physical modeling to provide greater insight into complex processes such as selective laser melting.« less

Microbial communities associated with uranium in-situ recovery mining process are related to acid mine drainage assemblages.

PubMed

Coral, Thomas; Descostes, Michaël; De Boissezon, Hélène; Bernier-Latmani, Rizlan; de Alencastro, Luiz Felippe; Rossi, Pierre

2018-07-01

A large fraction (47%) of the world's uranium is mined by a technique called "In Situ Recovery" (ISR). This mining technique involves the injection of a leaching fluid (acidic or alkaline) into a uranium-bearing aquifer and the pumping of the resulting solution through cation exchange columns for the recovery of dissolved uranium. The present study reports the in-depth alterations brought to autochthonous microbial communities during acidic ISR activities. Water samples were collected from a uranium roll-front deposit that is part of an ISR mine in operation (Tortkuduk, Kazakhstan). Water samples were obtained at a depth of ca 500 m below ground level from several zones of the Uyuk aquifer following the natural redox zonation inherited from the roll front deposit, including the native mineralized orebody and both upstream and downstream adjacent locations. Samples were collected equally from both the entrance and the exit of the uranium concentration plant. Next-generation sequencing data showed that the redox gradient shaped the community structures, within the anaerobic, reduced, and oligotrophic habitats of the native aquifer zones. Acid injection induced drastic changes in the structures of these communities, with a large decrease in both cell numbers and diversity. Communities present in the acidified (pH values < 2) mining areas exhibited similarities to those present in acid mine drainage, with the dominance of Sulfobacillus sp., Leptospirillum sp. and Acidithiobacillus sp., as well as the archaean Ferroplasma sp. Communities located up- and downstream of the mineralized zone under ISR and affected by acidic fluids were blended with additional facultative anaerobic and acidophilic microorganisms. These mixed biomes may be suitable communities for the natural attenuation of ISR mining-affected subsurface through the reduction of metals and sulfate. Assessing the effect of acidification on the microbial community is critical to evaluating the potential for natural attenuation or active bioremediation strategies. Copyright © 2018 Elsevier B.V. All rights reserved.

An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines

PubMed Central

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

2015-01-01

The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique) and CPM (Critical Path Method). If the delay of the critical operation (which is on a critical path) inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints. PMID:26062092

An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines.

PubMed

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

2015-01-01

The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique) and CPM (Critical Path Method). If the delay of the critical operation (which is on a critical path) inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints.

New approach for reduction of diesel consumption by comparing different mining haulage configurations.

PubMed

Rodovalho, Edmo da Cunha; Lima, Hernani Mota; de Tomi, Giorgio

2016-05-01

The mining operations of loading and haulage have an energy source that is highly dependent on fossil fuels. In mining companies that select trucks for haulage, this input is the main component of mining costs. How can the impact of the operational aspects on the diesel consumption of haulage operations in surface mines be assessed? There are many studies relating the consumption of fuel trucks to several variables, but a methodology that prioritizes higher-impact variables under each specific condition is not available. Generic models may not apply to all operational settings presented in the mining industry. This study aims to create a method of analysis, identification, and prioritization of variables related to fuel consumption of haul trucks in open pit mines. For this purpose, statistical analysis techniques and mathematical modelling tools using multiple linear regressions will be applied. The model is shown to be suitable because the results generate a good description of the fuel consumption behaviour. In the practical application of the method, the reduction of diesel consumption reached 10%. The implementation requires no large-scale investments or very long deadlines and can be applied to mining haulage operations in other settings. Copyright © 2016 Elsevier Ltd. All rights reserved.