Collaborative Data Mining Tool for Education

ERIC Educational Resources Information Center

Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; Gea, Miguel; de Castro, Carlos

2009-01-01

This paper describes a collaborative educational data mining tool based on association rule mining for the continuous improvement of e-learning courses allowing teachers with similar course's profile sharing and scoring the discovered information. This mining tool is oriented to be used by instructors non experts in data mining such that, its…

A Visualization Tool for Integrating Research Results at an Underground Mine

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A Collaborative Educational Association Rule Mining Tool

ERIC Educational Resources Information Center

Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; de Castro, Carlos

2011-01-01

This paper describes a collaborative educational data mining tool based on association rule mining for the ongoing improvement of e-learning courses and allowing teachers with similar course profiles to share and score the discovered information. The mining tool is oriented to be used by non-expert instructors in data mining so its internal…

A survey on annotation tools for the biomedical literature.

PubMed

Neves, Mariana; Leser, Ulf

2014-03-01

New approaches to biomedical text mining crucially depend on the existence of comprehensive annotated corpora. Such corpora, commonly called gold standards, are important for learning patterns or models during the training phase, for evaluating and comparing the performance of algorithms and also for better understanding the information sought for by means of examples. Gold standards depend on human understanding and manual annotation of natural language text. This process is very time-consuming and expensive because it requires high intellectual effort from domain experts. Accordingly, the lack of gold standards is considered as one of the main bottlenecks for developing novel text mining methods. This situation led the development of tools that support humans in annotating texts. Such tools should be intuitive to use, should support a range of different input formats, should include visualization of annotated texts and should generate an easy-to-parse output format. Today, a range of tools which implement some of these functionalities are available. In this survey, we present a comprehensive survey of tools for supporting annotation of biomedical texts. Altogether, we considered almost 30 tools, 13 of which were selected for an in-depth comparison. The comparison was performed using predefined criteria and was accompanied by hands-on experiences whenever possible. Our survey shows that current tools can support many of the tasks in biomedical text annotation in a satisfying manner, but also that no tool can be considered as a true comprehensive solution.

Pattern mining of user interaction logs for a post-deployment usability evaluation of a radiology PACS client.

PubMed

Jorritsma, Wiard; Cnossen, Fokie; Dierckx, Rudi A; Oudkerk, Matthijs; van Ooijen, Peter M A

2016-01-01

To perform a post-deployment usability evaluation of a radiology Picture Archiving and Communication System (PACS) client based on pattern mining of user interaction log data, and to assess the usefulness of this approach compared to a field study. All user actions performed on the PACS client were logged for four months. A data mining technique called closed sequential pattern mining was used to automatically extract frequently occurring interaction patterns from the log data. These patterns were used to identify usability issues with the PACS. The results of this evaluation were compared to the results of a field study based usability evaluation of the same PACS client. The interaction patterns revealed four usability issues: (1) the display protocols do not function properly, (2) the line measurement tool stays active until another tool is selected, rather than being deactivated after one use, (3) the PACS's built-in 3D functionality does not allow users to effectively perform certain 3D-related tasks, (4) users underuse the PACS's customization possibilities. All usability issues identified based on the log data were also found in the field study, which identified 48 issues in total. Post-deployment usability evaluation based on pattern mining of user interaction log data provides useful insights into the way users interact with the radiology PACS client. However, it reveals few usability issues compared to a field study and should therefore not be used as the sole method of usability evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

PubRunner: A light-weight framework for updating text mining results.

PubMed

Anekalla, Kishore R; Courneya, J P; Fiorini, Nicolas; Lever, Jake; Muchow, Michael; Busby, Ben

2017-01-01

Biomedical text mining promises to assist biologists in quickly navigating the combined knowledge in their domain. This would allow improved understanding of the complex interactions within biological systems and faster hypothesis generation. New biomedical research articles are published daily and text mining tools are only as good as the corpus from which they work. Many text mining tools are underused because their results are static and do not reflect the constantly expanding knowledge in the field. In order for biomedical text mining to become an indispensable tool used by researchers, this problem must be addressed. To this end, we present PubRunner, a framework for regularly running text mining tools on the latest publications. PubRunner is lightweight, simple to use, and can be integrated with an existing text mining tool. The workflow involves downloading the latest abstracts from PubMed, executing a user-defined tool, pushing the resulting data to a public FTP or Zenodo dataset, and publicizing the location of these results on the public PubRunner website. We illustrate the use of this tool by re-running the commonly used word2vec tool on the latest PubMed abstracts to generate up-to-date word vector representations for the biomedical domain. This shows a proof of concept that we hope will encourage text mining developers to build tools that truly will aid biologists in exploring the latest publications.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Hard-Rock Stability Analysis for Span Design in Entry-Type Excavations with Learning Classifiers

PubMed Central

García-Gonzalo, Esperanza; Fernández-Muñiz, Zulima; García Nieto, Paulino José; Bernardo Sánchez, Antonio; Menéndez Fernández, Marta

2016-01-01

The mining industry relies heavily on empirical analysis for design and prediction. An empirical design method, called the critical span graph, was developed specifically for rock stability analysis in entry-type excavations, based on an extensive case-history database of cut and fill mining in Canada. This empirical span design chart plots the critical span against rock mass rating for the observed case histories and has been accepted by many mining operations for the initial span design of cut and fill stopes. Different types of analysis have been used to classify the observed cases into stable, potentially unstable and unstable groups. The main purpose of this paper is to present a new method for defining rock stability areas of the critical span graph, which applies machine learning classifiers (support vector machine and extreme learning machine). The results show a reasonable correlation with previous guidelines. These machine learning methods are good tools for developing empirical methods, since they make no assumptions about the regression function. With this software, it is easy to add new field observations to a previous database, improving prediction output with the addition of data that consider the local conditions for each mine. PMID:28773653

Hard-Rock Stability Analysis for Span Design in Entry-Type Excavations with Learning Classifiers.

PubMed

García-Gonzalo, Esperanza; Fernández-Muñiz, Zulima; García Nieto, Paulino José; Bernardo Sánchez, Antonio; Menéndez Fernández, Marta

2016-06-29

The mining industry relies heavily on empirical analysis for design and prediction. An empirical design method, called the critical span graph, was developed specifically for rock stability analysis in entry-type excavations, based on an extensive case-history database of cut and fill mining in Canada. This empirical span design chart plots the critical span against rock mass rating for the observed case histories and has been accepted by many mining operations for the initial span design of cut and fill stopes. Different types of analysis have been used to classify the observed cases into stable, potentially unstable and unstable groups. The main purpose of this paper is to present a new method for defining rock stability areas of the critical span graph, which applies machine learning classifiers (support vector machine and extreme learning machine). The results show a reasonable correlation with previous guidelines. These machine learning methods are good tools for developing empirical methods, since they make no assumptions about the regression function. With this software, it is easy to add new field observations to a previous database, improving prediction output with the addition of data that consider the local conditions for each mine.

Estimating Software-Development Costs With Greater Accuracy

NASA Technical Reports Server (NTRS)

Baker, Dan; Hihn, Jairus; Lum, Karen

2008-01-01

COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.

Helmet-Cam: tool for assessing miners’ respirable dust exposure

PubMed Central

Cecala, A.B.; Reed, W.R.; Joy, G.J.; Westmoreland, S.C.; O’Brien, A.D.

2015-01-01

Video technology coupled with datalogging exposure monitors have been used to evaluate worker exposure to different types of contaminants. However, previous application of this technology used a stationary video camera to record the worker’s activity while the worker wore some type of contaminant monitor. These techniques are not applicable to mobile workers in the mining industry because of their need to move around the operation while performing their duties. The Helmet-Cam is a recently developed exposure assessment tool that integrates a person-wearable video recorder with a datalogging dust monitor. These are worn by the miner in a backpack, safety belt or safety vest to identify areas or job tasks of elevated exposure. After a miner performs his or her job while wearing the unit, the video and dust exposure data files are downloaded to a computer and then merged together through a NIOSH-developed computer software program called Enhanced Video Analysis of Dust Exposure (EVADE). By providing synchronized playback of the merged video footage and dust exposure data, the EVADE software allows for the assessment and identification of key work areas and processes, as well as work tasks that significantly impact a worker’s personal respirable dust exposure. The Helmet-Cam technology has been tested at a number of metal/nonmetal mining operations and has proven to be a valuable assessment tool. Mining companies wishing to use this technique can purchase a commercially available video camera and an instantaneous dust monitor to obtain the necessary data, and the NIOSH-developed EVADE software will be available for download at no cost on the NIOSH website. PMID:26380529

Two modelling approaches to water-quality simulation in a flooded iron-ore mine (Saizerais, Lorraine, France): a semi-distributed chemical reactor model and a physically based distributed reactive transport pipe network model.

PubMed

Hamm, V; Collon-Drouaillet, P; Fabriol, R

2008-02-19

The flooding of abandoned mines in the Lorraine Iron Basin (LIB) over the past 25 years has degraded the quality of the groundwater tapped for drinking water. High concentrations of dissolved sulphate have made the water unsuitable for human consumption. This problematic issue has led to the development of numerical tools to support water-resource management in mining contexts. Here we examine two modelling approaches using different numerical tools that we tested on the Saizerais flooded iron-ore mine (Lorraine, France). A first approach considers the Saizerais Mine as a network of two chemical reactors (NCR). The second approach is based on a physically distributed pipe network model (PNM) built with EPANET 2 software. This approach considers the mine as a network of pipes defined by their geometric and chemical parameters. Each reactor in the NCR model includes a detailed chemical model built to simulate quality evolution in the flooded mine water. However, in order to obtain a robust PNM, we simplified the detailed chemical model into a specific sulphate dissolution-precipitation model that is included as sulphate source/sink in both a NCR model and a pipe network model. Both the NCR model and the PNM, based on different numerical techniques, give good post-calibration agreement between the simulated and measured sulphate concentrations in the drinking-water well and overflow drift. The NCR model incorporating the detailed chemical model is useful when a detailed chemical behaviour at the overflow is needed. The PNM incorporating the simplified sulphate dissolution-precipitation model provides better information of the physics controlling the effect of flow and low flow zones, and the time of solid sulphate removal whereas the NCR model will underestimate clean-up time due to the complete mixing assumption. In conclusion, the detailed NCR model will give a first assessment of chemical processes at overflow, and in a second time, the PNM model will provide more detailed information on flow and chemical behaviour (dissolved sulphate concentrations, remaining mass of solid sulphate) in the network. Nevertheless, both modelling methods require hydrological and chemical parameters (recharge flow rate, outflows, volume of mine voids, mass of solids, kinetic constants of the dissolution-precipitation reactions), which are commonly not available for a mine and therefore call for calibration data.

CALL FOR ABSTRACTS FOR WORKSHOP ON MINING IMPACTED NATIVE AMERICAN LANDS 2003

EPA Science Inventory

This is a Call for Abstracts for a workshop 9/9-11/2003 in Reno, NV, to unite Tribal members and representatives, and other government officials to examine technical and policy issues related to historic, current, and future mining impacts on Native American Lands.

Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods.

PubMed

Ulaczyk, Jan; Morawiec, Krzysztof; Zabierowski, Paweł; Drobiazg, Tomasz; Barreau, Nicolas

2017-09-01

A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Matériaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Data mining for multiagent rules, strategies, and fuzzy decision tree structure

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

2002-03-01

A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

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.

Deep learning with word embeddings improves biomedical named entity recognition.

PubMed

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-07-15

Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/ . habibima@informatik.hu-berlin.de. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Deep learning with word embeddings improves biomedical named entity recognition

PubMed Central

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-01-01

Abstract Motivation: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. Results: We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. Availability and implementation: The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/. Contact: habibima@informatik.hu-berlin.de PMID:28881963

Toward edge minability for role mining in bipartite networks

NASA Astrophysics Data System (ADS)

Dong, Lijun; Wang, Yi; Liu, Ran; Pi, Benjie; Wu, Liuyi

2016-11-01

Bipartite network models have been extensively used in information security to automatically generate role-based access control (RBAC) from dataset. This process is called role mining. However, not all the topologies of bipartite networks are suitable for role mining; some edges may even reduce the quality of role mining. This causes unnecessary time consumption as role mining is NP-hard. Therefore, to promote the quality of role mining results, the capability that an edge composes roles with other edges, called the minability of edge, needs to be identified. We tackle the problem from an angle of edge importance in complex networks; that is an edge easily covered by roles is considered to be more important. Based on this idea, the k-shell decomposition of complex networks is extended to reveal the different minability of edges. By this way, a bipartite network can be quickly purified by excluding the low-minability edges from role mining, and thus the quality of role mining can be effectively improved. Extensive experiments via the real-world datasets are conducted to confirm the above claims.

Graph mining for next generation sequencing: leveraging the assembly graph for biological insights.

PubMed

Warnke-Sommer, Julia; Ali, Hesham

2016-05-06

The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are merged into longer sequences or contigs. The assembly graph is information rich and capable of capturing the genomic architecture of an input read data set. We have developed a novel hybrid graph in which nodes represent sequence regions at different levels of granularity. This model, utilized in the assembly and analysis pipeline Focus, presents a concise yet feature rich view of a given input data set, allowing for the extraction of biologically relevant graph structures for graph mining purposes. Focus was used to create hybrid graphs to model metagenomics data sets obtained from the gut microbiomes of five individuals with Crohn's disease and eight healthy individuals. Repetitive and mobile genetic elements are found to be associated with hybrid graph structure. Using graph mining techniques, a comparative study of the Crohn's disease and healthy data sets was conducted with focus on antibiotics resistance genes associated with transposase genes. Results demonstrated significant differences in the phylogenetic distribution of categories of antibiotics resistance genes in the healthy and diseased patients. Focus was also evaluated as a pure assembly tool and produced excellent results when compared against the Meta-velvet, Omega, and UD-IDBA assemblers. Mining the hybrid graph can reveal biological phenomena captured by its structure. We demonstrate the advantages of considering assembly graphs as data-mining support in addition to their role as frameworks for assembly.

Genexpi: a toolset for identifying regulons and validating gene regulatory networks using time-course expression data.

PubMed

Modrák, Martin; Vohradský, Jiří

2018-04-13

Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks. We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package. Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.

HARDROCK MINING 2002 CALL FOR ABSTRACTS

EPA Science Inventory

This flyer will announcement the Hardrock Mining 2002 Conference on May 7-9/2002 in Westminster, CO. This conference will provide participants with an opportunity to examine and discuss current and future environmental issues shaping the hardrock mining industry with emphasis on ...

Condition-Based Conveyor Belt Replacement Strategy in Lignite Mines with Random Belt Deterioration

NASA Astrophysics Data System (ADS)

Blazej, Ryszard; Jurdziak, Leszek

2017-12-01

In Polish lignite surface mines, condition-based belt replacement strategies are applied in order to assure profitable refurbishment of worn out belts performed by external firms specializing in belt maintenance. In two of three lignite mines, staff asses belt condition subjectively during visual inspections. Only one mine applies specialized diagnostic device (HRDS) allowing objective magnetic evaluation of belt core condition in order to choose the most profitable moment for the dismantling of worn out belt segments from conveyors and sending them to the maintenance firm which provides their refurbishment. This article describes the advantages of a new diagnostic device called DiagBelt. It was developed at the Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology. Economic gains from its application are calculated for the lignite mine and for the belt maintenance firm, taking into account random life (durability) of new and reconditioned belts (after the 1st and the 2nd refurbishment). Recursive calculations for following years allow the estimation of the length and costs of replaced, reconditioned and purchased belts on an annual basis, while the use of the Monte Carlo method allows the estimation of their variability caused by random deterioration of belts. Savings are obtained due to better selection of moments (times) for the replacement of belt segments and die to the possibility to qualify worn out belts for refurbishment without the need to remove their covers. In effect, increased belt durability and lowered share of waste belts (which were not qualified for reconditioning) create savings which can quickly cover expenditures on new diagnostic tools and regular belt inspections in the mine.

Igloo-Plot: a tool for visualization of multidimensional datasets.

PubMed

Kuntal, Bhusan K; Ghosh, Tarini Shankar; Mande, Sharmila S

2014-01-01

Advances in science and technology have resulted in an exponential growth of multivariate (or multi-dimensional) datasets which are being generated from various research areas especially in the domain of biological sciences. Visualization and analysis of such data (with the objective of uncovering the hidden patterns therein) is an important and challenging task. We present a tool, called Igloo-Plot, for efficient visualization of multidimensional datasets. The tool addresses some of the key limitations of contemporary multivariate visualization and analysis tools. The visualization layout, not only facilitates an easy identification of clusters of data-points having similar feature compositions, but also the 'marker features' specific to each of these clusters. The applicability of the various functionalities implemented herein is demonstrated using several well studied multi-dimensional datasets. Igloo-Plot is expected to be a valuable resource for researchers working in multivariate data mining studies. Igloo-Plot is available for download from: http://metagenomics.atc.tcs.com/IglooPlot/. Copyright © 2014 Elsevier Inc. All rights reserved.

NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data.

PubMed

Johnson, Owen A; Hall, Peter S; Hulme, Claire

2016-02-01

Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of 'big data'. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital's EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com ) suitable for visualization of both human-designed and data-mined processes which can then be used for 'what-if' analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively 'deep dive' into big data.

JEDI - an executive dashboard and decision support system for lean global military medical resource and logistics management.

PubMed

Sloane, Elliot B; Rosow, Eric; Adam, Joe; Shine, Dave

2006-01-01

Each individual U.S. Air Force, Army, and Navy Surgeon General has integrated oversight of global medical supplies and resources using the Joint Medical Asset Repository (JMAR). A Business Intelligence system called the JMAR Executive Dashboard Initiative (JEDI) was developed over a three-year period to add real-time interactive data-mining tools and executive dashboards. Medical resources can now be efficiently reallocated to military, veteran, family, or civilian purposes and inventories can be maintained at lean levels with peaks managed by interactive dashboards that reduce workload and errors.

Prehospital Emergencies in Illegal Gold Mining Sites in French Guiana.

PubMed

Egmann, Gérald; Tattevin, Pierre; Palancade, Renaud; Nacher, Matthieu

2018-03-01

Illegal gold mining is flourishing in French Guiana, existing outside the law due to both the high cost of gold mining permits and the challenges of law enforcement within the Amazon forest. We report the characteristics of, and the medical responses to, medical emergencies in illegal gold mining sites. We performed a retrospective study of all medical emergencies reported from illegal gold mining sites to the centralized call office of SAMU 973 from 1998 through 2000 and from 2008 through 2010. According to the national health care system, any medical emergency within the territory is handled by the prehospital emergency medical service (SAMU 973), irrespective of the patients' legal status. Data were extracted from the SAMU 973 notebook registry (1998-2000) or the SAMU 973 computerized database (2008-2010) and werre collected using a standardized questionnaire. Of 71,932 calls for medical emergencies in French Guiana during the study periods, 340 (0.5%) originated from illegal gold mining sites. Of these, 196 (58%) led to medical evacuation by helicopter, whereas the overall rate of evacuation by helicopter after placing a call to SAMU 973 was only 4% (3020/71,932; P<0.0001 for comparison with illegal gold mining sites). Medical emergencies were classified as illness (48%, mostly infectious), trauma (44%, mostly weapon wounds), and miscellaneous (8%). Medical emergencies at illegal gold mining sites in the Amazon forest mostly include infectious diseases, followed by trauma, and often require medical evacuation by helicopter. Our study suggests that implementation of preventive medicine within gold mining sites, irrespective of their legal status, could be cost-effective and reduce morbidity. Copyright © 2017 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

30 CFR 56.12033 - Hand-held electric tools.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Hand-held electric tools. 56.12033 Section 56.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Electricity § 56...

30 CFR 56.12033 - Hand-held electric tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Hand-held electric tools. 56.12033 Section 56.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Electricity § 56...

30 CFR 56.12033 - Hand-held electric tools.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Hand-held electric tools. 56.12033 Section 56.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Electricity § 56...

30 CFR 56.12033 - Hand-held electric tools.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Hand-held electric tools. 56.12033 Section 56.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Electricity § 56...

30 CFR 56.12033 - Hand-held electric tools.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Hand-held electric tools. 56.12033 Section 56.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Electricity § 56...

30 CFR 75.214 - Supplemental support materials, equipment and tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... tools. 75.214 Section 75.214 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75... accessible location on each working section or within four crosscuts of each working section. (b) The...

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

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

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

Mining Induced Displacement and Mental Health: A Call for Action

ERIC Educational Resources Information Center

Goessling, Kristen P.

2010-01-01

India is a country of unparalleled diversity within both the cultural and ecological spheres of life. This paper examines the author's experience exploring and inquiring into the mental health implications of mining and mining induced displacement within several Adivasi (tribal) communities in Andhra Pradesh, India. Through collaboration with…

Definition of redox and pH influence in the AMD mine system using a fuzzy qualitative tool (Iberian Pyrite Belt, SW Spain).

PubMed

de la Torre, M L; Grande, J A; Valente, T; Perez-Ostalé, E; Santisteban, M; Aroba, J; Ramos, I

2016-03-01

Poderosa Mine is an abandoned pyrite mine, located in the Iberian Pyrite Belt which pours its acid mine drainage (AMD) waters into the Odiel river (South-West Spain). This work focuses on establishing possible reasons for interdependence between the potential redox and pH, with the load of metals and sulfates, as well as a set of variables that define the physical chemistry of the water-conductivity, temperature, TDS, and dissolved oxygen-transported by a channel from Poderosa mine affected by acid mine drainage, through the use of techniques of artificial intelligence: fuzzy logic and data mining. The sampling campaign was carried out in May of 2012. There were a total of 16 sites, the first inside the tunnel and the last at the mouth of the river Odiel, with a distance of approximately 10 m between each pair of measuring stations. While the tools of classical statistics, which are widely used in this context, prove useful for defining proximity ratios between variables based on Pearson's correlations, in addition to making it easier to handle large volumes of data and producing easier-to-understand graphs, the use of fuzzy logic tools and data mining results in better definition of the variations produced by external stimuli on the set of variables. This tool is adaptable and can be extrapolated to any system polluted by acid mine drainage using simple, intuitive reasoning.

Coal and Open-pit surface mining impacts on American Lands (COAL)

NASA Astrophysics Data System (ADS)

Brown, T. A.; McGibbney, L. J.

2017-12-01

Mining is known to cause environmental degradation, but software tools to identify its impacts are lacking. However, remote sensing, spectral reflectance, and geographic data are readily available, and high-performance cloud computing resources exist for scientific research. Coal and Open-pit surface mining impacts on American Lands (COAL) provides a suite of algorithms and documentation to leverage these data and resources to identify evidence of mining and correlate it with environmental impacts over time.COAL was originally developed as a 2016 - 2017 senior capstone collaboration between scientists at the NASA Jet Propulsion Laboratory (JPL) and computer science students at Oregon State University (OSU). The COAL team implemented a free and open-source software library called "pycoal" in the Python programming language which facilitated a case study of the effects of coal mining on water resources. Evidence of acid mine drainage associated with an open-pit coal mine in New Mexico was derived by correlating imaging spectrometer data from the JPL Airborne Visible/InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG), spectral reflectance data published by the USGS Spectroscopy Laboratory in the USGS Digital Spectral Library 06, and GIS hydrography data published by the USGS National Geospatial Program in The National Map. This case study indicated that the spectral and geospatial algorithms developed by COAL can be used successfully to analyze the environmental impacts of mining activities.Continued development of COAL has been promoted by a Startup allocation award of high-performance computing resources from the Extreme Science and Engineering Discovery Environment (XSEDE). These resources allow the team to undertake further benchmarking, evaluation, and experimentation using multiple XSEDE resources. The opportunity to use computational infrastructure of this caliber will further enable the development of a science gateway to continue foundational COAL research.This work documents the original design and development of COAL and provides insight into continuing research efforts which have potential applications beyond the project to environmental data science and other fields.

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.

Application of Quality Management Tools for Evaluating the Failure Frequency of Cutter-Loader and Plough Mining Systems

NASA Astrophysics Data System (ADS)

Biały, Witold

2017-06-01

Failure frequency in the mining process, with a focus on the mining machine, has been presented and illustrated by the example of two coal-mines. Two mining systems have been subjected to analysis: a cutter-loader and a plough system. In order to reduce costs generated by failures, maintenance teams should regularly make sure that the machines are used and operated in a rational and effective way. Such activities will allow downtimes to be reduced, and, in consequence, will increase the effectiveness of a mining plant. The evaluation of mining machines' failure frequency contained in this study has been based on one of the traditional quality management tools - the Pareto chart.

Design and Testing of a New Diatom-Based Index for Heavy Metal Pollution.

PubMed

Fernández, M R; Martín, G; Corzo, J; de la Linde, A; García, E; López, M; Sousa, M

2018-01-01

The Tinto and Odiel river basins (SW Spain) are known worldwide for their unique water characteristics. Such uniqueness is a consequence of their flow through the Iberian Pyrite Belt (an area rich in metal sulphides) and the mining activities in the basins. A process of sulphide oxidation occurs in this region, which acidifies the water and increases the amount of heavy metals in it. As a result, the rivers suffer the so-called "acid mine drainage" (AMD). Traditional biotic diatom-based indexes (IPS, IBD, EPI-D, etc.) do not take into account the pollution caused by AMD. The purpose of this paper is to develop a new diatom-based index which can serve as a useful and quick monitoring tool. Such tool must reflect the level of AMD while being user friendly. We present the development and validation of the ICM (Índice de Contaminación por Metales or Metal Pollution Index). ICM demonstrated to meet successfully the above criteria and, therefore, can assess water quality in the Tinto and Odiel Rivers. In addition, ICM was applied with satisfactory results in the Guadiamar River (SW Spain), which was subjected to AMD too. Thus, we propose to make use of it in any other basin with the same type of pollution.

MINEs: Open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

DOE PAGES

Jeffryes, James G.; Colastani, Ricardo L.; Elbadawi-Sidhu, Mona; ...

2015-08-28

Metabolomics have proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likelymore » to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.« less

30 CFR 57.9261 - Transporting tools and materials on locomotives.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Transporting tools and materials on locomotives. 57.9261 Section 57.9261 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... MINES Loading, Hauling, and Dumping Transportation of Persons and Materials § 57.9261 Transporting tools...

30 CFR 57.9261 - Transporting tools and materials on locomotives.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Transporting tools and materials on locomotives. 57.9261 Section 57.9261 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... MINES Loading, Hauling, and Dumping Transportation of Persons and Materials § 57.9261 Transporting tools...

30 CFR 56.14116 - Hand-held power tools.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Hand-held power tools. 56.14116 Section 56... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14116 Hand-held power tools. (a) Power drills...

30 CFR 56.14116 - Hand-held power tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Hand-held power tools. 56.14116 Section 56... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14116 Hand-held power tools. (a) Power drills...

30 CFR 56.14116 - Hand-held power tools.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Hand-held power tools. 56.14116 Section 56... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14116 Hand-held power tools. (a) Power drills...

30 CFR 57.14116 - Hand-held power tools.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Hand-held power tools. 57.14116 Section 57... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14116 Hand-held power tools. (a) Power drills...

30 CFR 56.14116 - Hand-held power tools.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Hand-held power tools. 56.14116 Section 56... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14116 Hand-held power tools. (a) Power drills...

30 CFR 57.14116 - Hand-held power tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Hand-held power tools. 57.14116 Section 57... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14116 Hand-held power tools. (a) Power drills...

30 CFR 57.14116 - Hand-held power tools.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Hand-held power tools. 57.14116 Section 57... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14116 Hand-held power tools. (a) Power drills...

30 CFR 56.14116 - Hand-held power tools.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Hand-held power tools. 56.14116 Section 56... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14116 Hand-held power tools. (a) Power drills...

30 CFR 57.14116 - Hand-held power tools.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Hand-held power tools. 57.14116 Section 57... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14116 Hand-held power tools. (a) Power drills...

30 CFR 57.14116 - Hand-held power tools.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Hand-held power tools. 57.14116 Section 57... MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14116 Hand-held power tools. (a) Power drills...

HSA: a heuristic splice alignment tool.

PubMed

Bu, Jingde; Chi, Xuebin; Jin, Zhong

2013-01-01

RNA-Seq methodology is a revolutionary transcriptomics sequencing technology, which is the representative of Next generation Sequencing (NGS). With the high throughput sequencing of RNA-Seq, we can acquire much more information like differential expression and novel splice variants from deep sequence analysis and data mining. But the short read length brings a great challenge to alignment, especially when the reads span two or more exons. A two steps heuristic splice alignment tool is generated in this investigation. First, map raw reads to reference with unspliced aligner--BWA; second, split initial unmapped reads into three equal short reads (seeds), align each seed to the reference, filter hits, search possible split position of read and extend hits to a complete match. Compare with other splice alignment tools like SOAPsplice and Tophat2, HSA has a better performance in call rate and efficiency, but its results do not as accurate as the other software to some extent. HSA is an effective spliced aligner of RNA-Seq reads mapping, which is available at https://github.com/vlcc/HSA.

LAND REBORN: TOOLS FOR THE 21ST CENTURY/NATIONAL ASSOCIATION OF ABANDONED MINE LAND PROGRAMS

EPA Science Inventory

Mining activities in the US (not counting coal) produce 1-2 billion tons of mine waste annually. Since many of the ore mines involve sulfide minerals, the production of acid mine drainage (AMD) is a common problem from these abandoned mine sites. The combination of acidity, heavy...

Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.

PubMed

Wiegers, Thomas C; Davis, Allan Peter; Mattingly, Carolyn J

2014-01-01

The Critical Assessment of Information Extraction systems in Biology (BioCreAtIvE) challenge evaluation tasks collectively represent a community-wide effort to evaluate a variety of text-mining and information extraction systems applied to the biological domain. The BioCreative IV Workshop included five independent subject areas, including Track 3, which focused on named-entity recognition (NER) for the Comparative Toxicogenomics Database (CTD; http://ctdbase.org). Previously, CTD had organized document ranking and NER-related tasks for the BioCreative Workshop 2012; a key finding of that effort was that interoperability and integration complexity were major impediments to the direct application of the systems to CTD's text-mining pipeline. This underscored a prevailing problem with software integration efforts. Major interoperability-related issues included lack of process modularity, operating system incompatibility, tool configuration complexity and lack of standardization of high-level inter-process communications. One approach to potentially mitigate interoperability and general integration issues is the use of Web services to abstract implementation details; rather than integrating NER tools directly, HTTP-based calls from CTD's asynchronous, batch-oriented text-mining pipeline could be made to remote NER Web services for recognition of specific biological terms using BioC (an emerging family of XML formats) for inter-process communications. To test this concept, participating groups developed Representational State Transfer /BioC-compliant Web services tailored to CTD's NER requirements. Participants were provided with a comprehensive set of training materials. CTD evaluated results obtained from the remote Web service-based URLs against a test data set of 510 manually curated scientific articles. Twelve groups participated in the challenge. Recall, precision, balanced F-scores and response times were calculated. Top balanced F-scores for gene, chemical and disease NER were 61, 74 and 51%, respectively. Response times ranged from fractions-of-a-second to over a minute per article. We present a description of the challenge and summary of results, demonstrating how curation groups can effectively use interoperable NER technologies to simplify text-mining pipeline implementation. Database URL: http://ctdbase.org/ © The Author(s) 2014. Published by Oxford University Press.

Web services-based text-mining demonstrates broad impacts for interoperability and process simplification

PubMed Central

Wiegers, Thomas C.; Davis, Allan Peter; Mattingly, Carolyn J.

2014-01-01

The Critical Assessment of Information Extraction systems in Biology (BioCreAtIvE) challenge evaluation tasks collectively represent a community-wide effort to evaluate a variety of text-mining and information extraction systems applied to the biological domain. The BioCreative IV Workshop included five independent subject areas, including Track 3, which focused on named-entity recognition (NER) for the Comparative Toxicogenomics Database (CTD; http://ctdbase.org). Previously, CTD had organized document ranking and NER-related tasks for the BioCreative Workshop 2012; a key finding of that effort was that interoperability and integration complexity were major impediments to the direct application of the systems to CTD's text-mining pipeline. This underscored a prevailing problem with software integration efforts. Major interoperability-related issues included lack of process modularity, operating system incompatibility, tool configuration complexity and lack of standardization of high-level inter-process communications. One approach to potentially mitigate interoperability and general integration issues is the use of Web services to abstract implementation details; rather than integrating NER tools directly, HTTP-based calls from CTD's asynchronous, batch-oriented text-mining pipeline could be made to remote NER Web services for recognition of specific biological terms using BioC (an emerging family of XML formats) for inter-process communications. To test this concept, participating groups developed Representational State Transfer /BioC-compliant Web services tailored to CTD's NER requirements. Participants were provided with a comprehensive set of training materials. CTD evaluated results obtained from the remote Web service-based URLs against a test data set of 510 manually curated scientific articles. Twelve groups participated in the challenge. Recall, precision, balanced F-scores and response times were calculated. Top balanced F-scores for gene, chemical and disease NER were 61, 74 and 51%, respectively. Response times ranged from fractions-of-a-second to over a minute per article. We present a description of the challenge and summary of results, demonstrating how curation groups can effectively use interoperable NER technologies to simplify text-mining pipeline implementation. Database URL: http://ctdbase.org/ PMID:24919658

Data mining in radiology

PubMed Central

Kharat, Amit T; Singh, Amarjit; Kulkarni, Vilas M; Shah, Digish

2014-01-01

Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining. PMID:25024513

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…

MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.

PubMed

Jeffryes, James G; Colastani, Ricardo L; Elbadawi-Sidhu, Mona; Kind, Tobias; Niehaus, Thomas D; Broadbelt, Linda J; Hanson, Andrew D; Fiehn, Oliver; Tyo, Keith E J; Henry, Christopher S

2015-01-01

In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography-mass spectrometry (LC-MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC-MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.

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…

Understanding Teacher Users of a Digital Library Service: A Clustering Approach

ERIC Educational Resources Information Center

Xu, Beijie; Recker, Mimi

2011-01-01

This article describes the Knowledge Discovery and Data Mining (KDD) process and its application in the field of educational data mining (EDM) in the context of a digital library service called the Instructional Architect (IA.usu.edu). In particular, the study reported in this article investigated a certain type of data mining problem, clustering,…

Tools for Educational Data Mining: A Review

ERIC Educational Resources Information Center

Slater, Stefan; Joksimovic, Srecko; Kovanovic, Vitomir; Baker, Ryan S.; Gasevic, Dragan

2017-01-01

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

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.

Evaluating the Utility of Web-Based Consumer Support Tools Using Rough Sets

NASA Astrophysics Data System (ADS)

Maciag, Timothy; Hepting, Daryl H.; Slezak, Dominik; Hilderman, Robert J.

On the Web, many popular e-commerce sites provide consumers with decision support tools to assist them in their commerce-related decision-making. Many consumers will rank the utility of these tools quite highly. Data obtained from web usage mining analyses, which may provide knowledge about a user's online experiences, could help indicate the utility of these tools. This type of analysis could provide insight into whether provided tools are adequately assisting consumers in conducting their online shopping activities or if new or additional enhancements need consideration. Although some research in this regard has been described in previous literature, there is still much that can be done. The authors of this paper hypothesize that a measurement of consumer decision accuracy, i.e. a measurement preferences, could help indicate the utility of these tools. This paper describes a procedure developed towards this goal using elements of rough set theory. The authors evaluated the procedure using two support tools, one based on a tool developed by the US-EPA and the other developed by one of the authors called cogito. Results from the evaluation did provide interesting insights on the utility of both support tools. Although it was shown that the cogito tool obtained slightly higher decision accuracy, both tools could be improved from additional enhancements. Details of the procedure developed and results obtained from the evaluation will be provided. Opportunities for future work are also discussed.

Static versus dynamic sampling for data mining

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

John, G.H.; Langley, P.

1996-12-31

As data warehouses grow to the point where one hundred gigabytes is considered small, the computational efficiency of data-mining algorithms on large databases becomes increasingly important. Using a sample from the database can speed up the datamining process, but this is only acceptable if it does not reduce the quality of the mined knowledge. To this end, we introduce the {open_quotes}Probably Close Enough{close_quotes} criterion to describe the desired properties of a sample. Sampling usually refers to the use of static statistical tests to decide whether a sample is sufficiently similar to the large database, in the absence of any knowledgemore » of the tools the data miner intends to use. We discuss dynamic sampling methods, which take into account the mining tool being used and can thus give better samples. We describe dynamic schemes that observe a mining tool`s performance on training samples of increasing size and use these results to determine when a sample is sufficiently large. We evaluate these sampling methods on data from the UCI repository and conclude that dynamic sampling is preferable.« less

Bioinformatics and molecular modeling in glycobiology

PubMed Central

Schloissnig, Siegfried

2010-01-01

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed. PMID:20364395

The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

PubMed

Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas

2009-01-01

An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

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.

IT Data Mining Tool Uses in Aerospace

NASA Technical Reports Server (NTRS)

Monroe, Gilena A.; Freeman, Kenneth; Jones, Kevin L.

2012-01-01

Data mining has a broad spectrum of uses throughout the realms of aerospace and information technology. Each of these areas has useful methods for processing, distributing, and storing its corresponding data. This paper focuses on ways to leverage the data mining tools and resources used in NASA's information technology area to meet the similar data mining needs of aviation and aerospace domains. This paper details the searching, alerting, reporting, and application functionalities of the Splunk system, used by NASA's Security Operations Center (SOC), and their potential shared solutions to address aircraft and spacecraft flight and ground systems data mining requirements. This paper also touches on capacity and security requirements when addressing sizeable amounts of data across a large data infrastructure.

HC StratoMineR: A Web-Based Tool for the Rapid Analysis of High-Content Datasets.

PubMed

Omta, Wienand A; van Heesbeen, Roy G; Pagliero, Romina J; van der Velden, Lieke M; Lelieveld, Daphne; Nellen, Mehdi; Kramer, Maik; Yeong, Marley; Saeidi, Amir M; Medema, Rene H; Spruit, Marco; Brinkkemper, Sjaak; Klumperman, Judith; Egan, David A

2016-10-01

High-content screening (HCS) can generate large multidimensional datasets and when aligned with the appropriate data mining tools, it can yield valuable insights into the mechanism of action of bioactive molecules. However, easy-to-use data mining tools are not widely available, with the result that these datasets are frequently underutilized. Here, we present HC StratoMineR, a web-based tool for high-content data analysis. It is a decision-supportive platform that guides even non-expert users through a high-content data analysis workflow. HC StratoMineR is built by using My Structured Query Language for storage and querying, PHP: Hypertext Preprocessor as the main programming language, and jQuery for additional user interface functionality. R is used for statistical calculations, logic and data visualizations. Furthermore, C++ and graphical processor unit power is diffusely embedded in R by using the rcpp and rpud libraries for operations that are computationally highly intensive. We show that we can use HC StratoMineR for the analysis of multivariate data from a high-content siRNA knock-down screen and a small-molecule screen. It can be used to rapidly filter out undesirable data; to select relevant data; and to perform quality control, data reduction, data exploration, morphological hit picking, and data clustering. Our results demonstrate that HC StratoMineR can be used to functionally categorize HCS hits and, thus, provide valuable information for hit prioritization.

Mine Waste at The Kherzet Youcef Mine : Environmental Characterization

NASA Astrophysics Data System (ADS)

Issaad, Mouloud; Boutaleb, Abdelhak; Kolli, Omar

2017-04-01

Mining activity in Algeria has existed since antiquity. But it was very important since the 20th century. This activity has virtually ceased since the beginning of the 1990s, leaving many mine sites abandoned (so-called orphan mines). The abandonment of mining today poses many environmental problems (soil pollution, contamination of surface water, mining collapses...). The mining wastes often occupy large volumes that can be hazardous to the environment and human health, often neglected in the past: Faulting geotechnical implementation, acid mine drainage (AMD), alkalinity, presence of pollutants and toxic substances (heavy metals, cyanide...). The study started already six years ago and it covers all mines located in NE Algeria, almost are stopped for more than thirty years. So the most important is to have an overview of all the study area. After the inventory job of the abandoned mines, the rock drainage prediction will help us to classify sites according to their acid generating potential.

Quantification of Operational Risk Using A Data Mining

NASA Technical Reports Server (NTRS)

Perera, J. Sebastian

1999-01-01

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

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…

NASA aviation safety program aircraft engine health management data mining tools roadmap

DOT National Transportation Integrated Search

2000-04-01

Aircraft Engine Health Management Data Mining Tools is a project led by NASA Glenn Research Center in support of the NASA Aviation Safety Program's Aviation System Monitoring and Modeling Thrust. The objective of the Glenn-led effort is to develop en...

MiMiR – an integrated platform for microarray data sharing, mining and analysis

PubMed Central

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-01-01

Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies. PMID:18801157

MiMiR--an integrated platform for microarray data sharing, mining and analysis.

PubMed

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-09-18

Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Cyanide

USGS Publications Warehouse

Creekmore, Lynn H.

1999-01-01

Cyanide poisoning of birds is caused by exposure to cyanide in two forms: inorganic salts and hydrogen cyanide gas (HCN). Two sources of cyanide have been associated with bird mortalities: gold and silver mines that use cyanide in the extraction process and a predator control device called the M-44 sodium cyanide ejector, which uses cyanide as the toxic agent.Most of the cyanide mortality documented in birds is a result of exposure to cyanide used in heap leach and carbonin-pulp mill gold or silver mining processes. At these mines, the animals are exposed when they ingest water that contains cyanide salts used in mining processes or, possibly, when they inhale HCN gas. In heap leach mining operations, the ore is placed on an impermeable pad over which a cyanide solution is sprayed or dripped. The cyanide solution dissolves and attaches to or “leaches out” the gold. The cyanide and gold solution is then drained to a plastic-lined pond, which is commonly called the pregnant pond. The gold is extracted, and the remaining solution is moved into another lined pond, which is commonly called the barren pond. The cyanide concentration in this pond is increased so that the solution is again suitable for use in the leaching process, and the solution is used again on the ore heap (Fig. 46.1). Bird use of the HCN-contaminated water in the ponds (Fig. 46.2) or contaminated water on or at the base of the heap leach pads (Fig. 46.3) can result in mortality.

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…

Mining relational paths in integrated biomedical data.

PubMed

He, Bing; Tang, Jie; Ding, Ying; Wang, Huijun; Sun, Yuyin; Shin, Jae Hong; Chen, Bin; Moorthy, Ganesh; Qiu, Judy; Desai, Pankaj; Wild, David J

2011-01-01

Much life science and biology research requires an understanding of complex relationships between biological entities (genes, compounds, pathways, diseases, and so on). There is a wealth of data on such relationships in publicly available datasets and publications, but these sources are overlapped and distributed so that finding pertinent relational data is increasingly difficult. Whilst most public datasets have associated tools for searching, there is a lack of searching methods that can cross data sources and that in particular search not only based on the biological entities themselves but also on the relationships between them. In this paper, we demonstrate how graph-theoretic algorithms for mining relational paths can be used together with a previous integrative data resource we developed called Chem2Bio2RDF to extract new biological insights about the relationships between such entities. In particular, we use these methods to investigate the genetic basis of side-effects of thiazolinedione drugs, and in particular make a hypothesis for the recently discovered cardiac side-effects of Rosiglitazone (Avandia) and a prediction for Pioglitazone which is backed up by recent clinical studies.

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes

PubMed Central

Corcoran, Callan C.; Grady, Cameron R.; Pisitkun, Trairak; Parulekar, Jaya

2017-01-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. PMID:27974320

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

PubMed Central

Castañón–Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

2015-01-01

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information. PMID:26633417

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.

PubMed

Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

2015-12-02

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

Machine learning for a Toolkit for Image Mining

NASA Technical Reports Server (NTRS)

Delanoy, Richard L.

1995-01-01

A prototype user environment is described that enables a user with very limited computer skills to collaborate with a computer algorithm to develop search tools (agents) that can be used for image analysis, creating metadata for tagging images, searching for images in an image database on the basis of image content, or as a component of computer vision algorithms. Agents are learned in an ongoing, two-way dialogue between the user and the algorithm. The user points to mistakes made in classification. The algorithm, in response, attempts to discover which image attributes are discriminating between objects of interest and clutter. It then builds a candidate agent and applies it to an input image, producing an 'interest' image highlighting features that are consistent with the set of objects and clutter indicated by the user. The dialogue repeats until the user is satisfied. The prototype environment, called the Toolkit for Image Mining (TIM) is currently capable of learning spectral and textural patterns. Learning exhibits rapid convergence to reasonable levels of performance and, when thoroughly trained, Fo appears to be competitive in discrimination accuracy with other classification techniques.

Technical Challenges of the U.S. Army’s Ground Combat Vehicle Program

DTIC Science & Technology

2012-11-01

for mine protection and a distinctive armored extension on the top, called the doghouse. Those features optimize it for counterinsurgency operations...vehicles. Less complex approaches have also evolved, such as mines designed to attack the weaker bottoms of vehicles or improvised explosive devices...Improvised Explosive Devices, Suicide Bombers, Unexploded Ordnance, and Mines ,” section I-G-10, “Countermeasures.” See also Clay Wilson, Improvised

The Geogenomic Mutational Atlas of Pathogens (GoMAP) Web System

PubMed Central

Sargeant, David P.; Hedden, Michael W.; Deverasetty, Sandeep; Strong, Christy L.; Alaniz, Izua J.; Bartlett, Alexandria N.; Brandon, Nicholas R.; Brooks, Steven B.; Brown, Frederick A.; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P.; Dobritch, Karlyn M.; Guerra, Horacio P.; Levit, Kelvy S.; Mathew, Kiran R.; Matti, Ray; Maza, Dorothea Q.; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F.; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A.; Schooler, Steve G.; Songao, Sarah; Tuggle, Sean L.; Wing, Helen J.; Yousif, Sandy; Schiller, Martin R.

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/ PMID:24675726

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system.

PubMed

Sargeant, David P; Hedden, Michael W; Deverasetty, Sandeep; Strong, Christy L; Alaniz, Izua J; Bartlett, Alexandria N; Brandon, Nicholas R; Brooks, Steven B; Brown, Frederick A; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P; Dobritch, Karlyn M; Guerra, Horacio P; Levit, Kelvy S; Mathew, Kiran R; Matti, Ray; Maza, Dorothea Q; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A; Schooler, Steve G; Songao, Sarah; Tuggle, Sean L; Wing, Helen J; Yousif, Sandy; Schiller, Martin R

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Ergonomics in the arctic - a study and checklist for heavy machinery in open pit mining.

PubMed

Reiman, Arto; Sormunen, Erja; Morris, Drew

2016-11-22

Heavy mining vehicle operators at arctic mines have a high risk of discomfort, musculoskeletal disorders and occupational accidents. There is a need for tailored approaches and safety management tools that take into account the specific characteristics of arctic work environments. The aim of this study was to develop a holistic evaluation tool for heavy mining vehicles and operator well-being in arctic mine environments. Data collection was based on design science principles and included literature review, expert observations and participatory ergonomic sessions. As a result of this study, a systemic checklist was developed and tested by eight individuals in a 350-employee mining environment. The checklist includes sections for evaluating vehicle specific ergonomic and safety aspects from a technological point of view and for checking if the work has been arranged so that it can be performed safely and fluently from an employee's point of view.

Data Mining in Health and Medical Information.

ERIC Educational Resources Information Center

Bath, Peter A.

2004-01-01

Presents a literature review that covers the following topics related to data mining (DM) in health and medical information: the potential of DM in health and medicine; statistical methods; evaluation of methods; DM tools for health and medicine; inductive learning of symbolic rules; application of DM tools in diagnosis and prognosis; and…

A software communication tool for the tele-ICU.

PubMed

Pimintel, Denise M; Wei, Shang Heng; Odor, Alberto

2013-01-01

The Tele Intensive Care Unit (tele-ICU) supports a high volume, high acuity population of patients. There is a high-volume of incoming and outgoing calls, especially during the evening and night hours, through the tele-ICU hubs. The tele-ICU clinicians must be able to communicate effectively to team members in order to support the care of complex and critically ill patients while supporting and maintaining a standard to improve time to intervention. This study describes a software communication tool that will improve the time to intervention, over the paper-driven communication format presently used in the tele-ICU. The software provides a multi-relational database of message instances to mine information for evaluation and quality improvement for all entities that touch the tele-ICU. The software design incorporates years of critical care and software design experience combined with new skills acquired in an applied Health Informatics program. This software tool will function in the tele-ICU environment and perform as a front-end application that gathers, routes, and displays internal communication messages for intervention by priority and provider.

PubMedMiner: Mining and Visualizing MeSH-based Associations in PubMed.

PubMed

Zhang, Yucan; Sarkar, Indra Neil; Chen, Elizabeth S

2014-01-01

The exponential growth of biomedical literature provides the opportunity to develop approaches for facilitating the identification of possible relationships between biomedical concepts. Indexing by Medical Subject Headings (MeSH) represent high-quality summaries of much of this literature that can be used to support hypothesis generation and knowledge discovery tasks using techniques such as association rule mining. Based on a survey of literature mining tools, a tool implemented using Ruby and R - PubMedMiner - was developed in this study for mining and visualizing MeSH-based associations for a set of MEDLINE articles. To demonstrate PubMedMiner's functionality, a case study was conducted that focused on identifying and comparing comorbidities for asthma in children and adults. Relative to the tools surveyed, the initial results suggest that PubMedMiner provides complementary functionality for summarizing and comparing topics as well as identifying potentially new knowledge.

Investigating MOOCs through Blog Mining

ERIC Educational Resources Information Center

Chen, Yong

2014-01-01

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

78 FR 77024 - Telemarketing Sales Rule; Notice of Termination of Caller ID Rulemaking

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-20

..., data mining and anomaly detection, and call-blocking technology). \\19\\ AT&T Servs., Inc., No. 00040, at... technically feasible, by looking at the signaling data . . . to distinguish between a CPN [calling party...

tmBioC: improving interoperability of text-mining tools with BioC.

PubMed

Khare, Ritu; Wei, Chih-Hsuan; Mao, Yuqing; Leaman, Robert; Lu, Zhiyong

2014-01-01

The lack of interoperability among biomedical text-mining tools is a major bottleneck in creating more complex applications. Despite the availability of numerous methods and techniques for various text-mining tasks, combining different tools requires substantial efforts and time owing to heterogeneity and variety in data formats. In response, BioC is a recent proposal that offers a minimalistic approach to tool interoperability by stipulating minimal changes to existing tools and applications. BioC is a family of XML formats that define how to present text documents and annotations, and also provides easy-to-use functions to read/write documents in the BioC format. In this study, we introduce our text-mining toolkit, which is designed to perform several challenging and significant tasks in the biomedical domain, and repackage the toolkit into BioC to enhance its interoperability. Our toolkit consists of six state-of-the-art tools for named-entity recognition, normalization and annotation (PubTator) of genes (GenNorm), diseases (DNorm), mutations (tmVar), species (SR4GN) and chemicals (tmChem). Although developed within the same group, each tool is designed to process input articles and output annotations in a different format. We modify these tools and enable them to read/write data in the proposed BioC format. We find that, using the BioC family of formats and functions, only minimal changes were required to build the newer versions of the tools. The resulting BioC wrapped toolkit, which we have named tmBioC, consists of our tools in BioC, an annotated full-text corpus in BioC, and a format detection and conversion tool. Furthermore, through participation in the 2013 BioCreative IV Interoperability Track, we empirically demonstrate that the tools in tmBioC can be more efficiently integrated with each other as well as with external tools: Our experimental results show that using BioC reduces >60% in lines of code for text-mining tool integration. The tmBioC toolkit is publicly available at http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/. Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Tools of Realization of Social Responsibility of Industrial Business for Sustainable Socio-economic Development of Mining Region's Rural Territory

NASA Astrophysics Data System (ADS)

Jurzina, Tatyana; Egorova, Natalia; Zaruba, Natalia; Kosinskij, Peter

2017-11-01

Modern conditions of the Russian economy do especially relevant questions of social responsibility of industrial business of the mining region for sustainable social and economic development of rural territories that demands search of the new strategy, tools, ways for positioning and increase in competitiveness of the enterprises, which are carrying out the entrepreneurial activity in this territory. The article opens problems of an influence of the industrial enterprises on the territory of presence, reasons the theoretical base directed to the formation of practical tools (mechanism) providing realization of social responsibility of business for sustainable social and economic development of rural territories of the mining region.

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

NASA Astrophysics Data System (ADS)

Garvey, Ryan J.

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

A Data Warehouse Architecture for DoD Healthcare Performance Measurements.

DTIC Science & Technology

1999-09-01

design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse of healthcare metrics. With the DoD healthcare...framework, this thesis defines a methodology to design, develop, implement, and apply statistical analysis and data mining tools to a Data Warehouse...21 F. INABILITY TO CONDUCT HELATHCARE ANALYSIS

Discovering Knowledge from Noisy Databases Using Genetic Programming.

ERIC Educational Resources Information Center

Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.

2000-01-01

Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…

Engaging Business Students with Data Mining

ERIC Educational Resources Information Center

Brandon, Dan

2016-01-01

The Economist calls it "a golden vein", and many business experts now say it is the new science of winning. Business and technologists have many names for this new science, "business intelligence" (BI), " data analytics," and "data mining" are among the most common. The job market for people skilled in this…

Mining and Indexing Graph Databases

ERIC Educational Resources Information Center

Yuan, Dayu

2013-01-01

Graphs are widely used to model structures and relationships of objects in various scientific and commercial fields. Chemical molecules, proteins, malware system-call dependencies and three-dimensional mechanical parts are all modeled as graphs. In this dissertation, we propose to mine and index those graph data to enable fast and scalable search.…

The research of structure and mechanical properties of superhard electro-spark coatings for hardwearing mining tools

NASA Astrophysics Data System (ADS)

Bajin, P. A.; Chijikov, A. P.; Leybo, D. V.; Chuprunov, K. O.; Yudin, A. G.; Alymov, M. A.; Kuznetsov, D. V.

2016-01-01

The development of low cost and hardwearing mining tools is one of the most important areas in mining industry. It is especially important for technologies of rare and rare earth metals mining due to high hardness of related ores. Coatings for electrodes, produced by extrusion of self-propagating high temperature synthesis (SHS) products from hard-alloyed materials with nanosized structure, for further application in processes of electrospark alloying and deposition were studied in this work. The results of microstructure and properties of deposited layers, interaction of support with SHS produced electrodes, comparison of frictional properties of obtained materials as well as some industrial testing results are presented in this work.

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…

Text Mining in Cancer Gene and Pathway Prioritization

PubMed Central

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes. PMID:25392685

Text mining in cancer gene and pathway prioritization.

PubMed

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

HPVdb: a data mining system for knowledge discovery in human papillomavirus with applications in T cell immunology and vaccinology

PubMed Central

Zhang, Guang Lan; Riemer, Angelika B.; Keskin, Derin B.; Chitkushev, Lou; Reinherz, Ellis L.; Brusic, Vladimir

2014-01-01

High-risk human papillomaviruses (HPVs) are the causes of many cancers, including cervical, anal, vulvar, vaginal, penile and oropharyngeal. To facilitate diagnosis, prognosis and characterization of these cancers, it is necessary to make full use of the immunological data on HPV available through publications, technical reports and databases. These data vary in granularity, quality and complexity. The extraction of knowledge from the vast amount of immunological data using data mining techniques remains a challenging task. To support integration of data and knowledge in virology and vaccinology, we developed a framework called KB-builder to streamline the development and deployment of web-accessible immunological knowledge systems. The framework consists of seven major functional modules, each facilitating a specific aspect of the knowledgebase construction process. Using KB-builder, we constructed the Human Papillomavirus T cell Antigen Database (HPVdb). It contains 2781 curated antigen entries of antigenic proteins derived from 18 genotypes of high-risk HPV and 18 genotypes of low-risk HPV. The HPVdb also catalogs 191 verified T cell epitopes and 45 verified human leukocyte antigen (HLA) ligands. Primary amino acid sequences of HPV antigens were collected and annotated from the UniProtKB. T cell epitopes and HLA ligands were collected from data mining of scientific literature and databases. The data were subject to extensive quality control (redundancy elimination, error detection and vocabulary consolidation). A set of computational tools for an in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, classification of HPV types based on cancer risk, T cell epitope/HLA ligand visualization, T cell epitope/HLA ligand conservation analysis and sequence variability analysis, has been integrated within the HPVdb. Predicted Class I and Class II HLA binding peptides for 15 common HLA alleles are included in this database as putative targets. HPVdb is a knowledge-based system that integrates curated data and information with tailored analysis tools to facilitate data mining for HPV vaccinology and immunology. To our best knowledge, HPVdb is a unique data source providing a comprehensive list of HPV antigens and peptides. Database URL: http://cvc.dfci.harvard.edu/hpv/ PMID:24705205

HPVdb: a data mining system for knowledge discovery in human papillomavirus with applications in T cell immunology and vaccinology.

PubMed

Zhang, Guang Lan; Riemer, Angelika B; Keskin, Derin B; Chitkushev, Lou; Reinherz, Ellis L; Brusic, Vladimir

2014-01-01

High-risk human papillomaviruses (HPVs) are the causes of many cancers, including cervical, anal, vulvar, vaginal, penile and oropharyngeal. To facilitate diagnosis, prognosis and characterization of these cancers, it is necessary to make full use of the immunological data on HPV available through publications, technical reports and databases. These data vary in granularity, quality and complexity. The extraction of knowledge from the vast amount of immunological data using data mining techniques remains a challenging task. To support integration of data and knowledge in virology and vaccinology, we developed a framework called KB-builder to streamline the development and deployment of web-accessible immunological knowledge systems. The framework consists of seven major functional modules, each facilitating a specific aspect of the knowledgebase construction process. Using KB-builder, we constructed the Human Papillomavirus T cell Antigen Database (HPVdb). It contains 2781 curated antigen entries of antigenic proteins derived from 18 genotypes of high-risk HPV and 18 genotypes of low-risk HPV. The HPVdb also catalogs 191 verified T cell epitopes and 45 verified human leukocyte antigen (HLA) ligands. Primary amino acid sequences of HPV antigens were collected and annotated from the UniProtKB. T cell epitopes and HLA ligands were collected from data mining of scientific literature and databases. The data were subject to extensive quality control (redundancy elimination, error detection and vocabulary consolidation). A set of computational tools for an in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, classification of HPV types based on cancer risk, T cell epitope/HLA ligand visualization, T cell epitope/HLA ligand conservation analysis and sequence variability analysis, has been integrated within the HPVdb. Predicted Class I and Class II HLA binding peptides for 15 common HLA alleles are included in this database as putative targets. HPVdb is a knowledge-based system that integrates curated data and information with tailored analysis tools to facilitate data mining for HPV vaccinology and immunology. To our best knowledge, HPVdb is a unique data source providing a comprehensive list of HPV antigens and peptides. Database URL: http://cvc.dfci.harvard.edu/hpv/.

New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

NASA Astrophysics Data System (ADS)

Brescia, Massimo

2012-11-01

Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to produce efficient and reliable scientific results. All these considerations will be described in the detail in the chapter. Moreover, examples of modern applications offering to a wide variety of e-science communities a large spectrum of computational facilities to exploit the wealth of available massive data sets and powerful machine learning and statistical algorithms will be also introduced.

Mine Improvement and New Emergency Response Act of 2006. Public Law 109-236, S2803

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

NONE

2006-06-15

This Act may be cited as the 'Mine Improvement and New Emergency Response Act of 2006' or the 'MINER Act'. It amends the Federal Mine Safety and Health Act of 1977 to improve the safety of mines and mining. The Act requires operators of underground coal mines to improve accident preparedness. The legislation requires mining companies to develop an emergency response plan specific to each mine they operate, and requires that every mine has at least two rescue teams located within one hour. S. 2803 also limits the legal liability of rescue team members and the companies that employ them.more » The act increases both civil and criminal penalties for violations of federal mining safety standards and gives the Mine Safety and Health Administration (MSHA) the ability to temporarily close a mine that fails to pay the penalties or fines. In addition, the act calls for several studies into ways to enhance mine safety, as well as the establishment of a new office within the National Institute for Occupational Safety and Health devoted to improving mine safety. Finally, the legislation establishes new scholarship and grant programs devoted to training individuals with respect to mine safety.« less

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.

PubMed

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A V S K; Varshney, Rajeev K

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.

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

NASA Astrophysics Data System (ADS)

Wasilewski, Stanisław

2012-12-01

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

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

PubMed

Liu, Sandra S; Chen, Jie

2009-01-01

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

Data Mining Tools Make Flights Safer, More Efficient

NASA Technical Reports Server (NTRS)

2014-01-01

A small data mining team at Ames Research Center developed a set of algorithms ideal for combing through flight data to find anomalies. Dallas-based Southwest Airlines Co. signed a Space Act Agreement with Ames in 2011 to access the tools, helping the company refine its safety practices, improve its safety reviews, and increase flight efficiencies.

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…

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.

Integration of Text- and Data-Mining Technologies for Use in Banking Applications

NASA Astrophysics Data System (ADS)

Maslankowski, Jacek

Unstructured data, most of it in the form of text files, typically accounts for 85% of an organization's knowledge stores, but it's not always easy to find, access, analyze or use (Robb 2004). That is why it is important to use solutions based on text and data mining. This solution is known as duo mining. This leads to improve management based on knowledge owned in organization. The results are interesting. Data mining provides to lead with structuralized data, usually powered from data warehouses. Text mining, sometimes called web mining, looks for patterns in unstructured data — memos, document and www. Integrating text-based information with structured data enriches predictive modeling capabilities and provides new stores of insightful and valuable information for driving business and research initiatives forward.

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

Application of text mining in the biomedical domain.

PubMed

Fleuren, Wilco W M; Alkema, Wynand

2015-03-01

In recent years the amount of experimental data that is produced in biomedical research and the number of papers that are being published in this field have grown rapidly. In order to keep up to date with developments in their field of interest and to interpret the outcome of experiments in light of all available literature, researchers turn more and more to the use of automated literature mining. As a consequence, text mining tools have evolved considerably in number and quality and nowadays can be used to address a variety of research questions ranging from de novo drug target discovery to enhanced biological interpretation of the results from high throughput experiments. In this paper we introduce the most important techniques that are used for a text mining and give an overview of the text mining tools that are currently being used and the type of problems they are typically applied for. Copyright © 2015 Elsevier Inc. All rights reserved.

Empirical Models of Zones Protecting Against Coal Dust Explosion

NASA Astrophysics Data System (ADS)

Prostański, Dariusz

2017-09-01

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

Implementation of a Flexible Tool for Automated Literature-Mining and Knowledgebase Development (DevToxMine)

EPA Science Inventory

Deriving novel relationships from the scientific literature is an important adjunct to datamining activities for complex datasets in genomics and high-throughput screening activities. Automated text-mining algorithms can be used to extract relevant content from the literature and...

Finite Element Analysis of M15 and M19 Mines Under Wheeled Vehicle Load

DTIC Science & Technology

2008-03-01

the plate statically. An implicit finite element option in a code called LSDYNA was used to model the pressure generated in the explosive by the...figure 4 for the M19 mines. Maximum pressure in the explosive for each mine calculated by LSDYNA code shown for a variety of plate sizes and weights...Director U.S. Army TRADOC Analysis Center-WSMR ATTN: ATRC-WSS-R White Sands Missile Range, NM 88002 Chemical Propulsion Information Agency ATTN

DynGO: a tool for visualizing and mining of Gene Ontology and its associations

PubMed Central

Liu, Hongfang; Hu, Zhang-Zhi; Wu, Cathy H

2005-01-01

Background A large volume of data and information about genes and gene products has been stored in various molecular biology databases. A major challenge for knowledge discovery using these databases is to identify related genes and gene products in disparate databases. The development of Gene Ontology (GO) as a common vocabulary for annotation allows integrated queries across multiple databases and identification of semantically related genes and gene products (i.e., genes and gene products that have similar GO annotations). Meanwhile, dozens of tools have been developed for browsing, mining or editing GO terms, their hierarchical relationships, or their "associated" genes and gene products (i.e., genes and gene products annotated with GO terms). Tools that allow users to directly search and inspect relations among all GO terms and their associated genes and gene products from multiple databases are needed. Results We present a standalone package called DynGO, which provides several advanced functionalities in addition to the standard browsing capability of the official GO browsing tool (AmiGO). DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations. The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Conclusion We have presented a standalone package DynGO that provides functionalities to search and browse GO and its association databases as well as several additional functions such as batch retrieval and semantic retrieval. The complete documentation and software are freely available for download from the website . PMID:16091147

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

PubMed Central

Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels. PMID:28817602

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight.

PubMed

Regad, Leslie; Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.

Mining Student Data Captured from a Web-Based Tutoring Tool: Initial Exploration and Results

ERIC Educational Resources Information Center

Merceron, Agathe; Yacef, Kalina

2004-01-01

In this article we describe the initial investigations that we have conducted on student data collected from a web-based tutoring tool. We have used some data mining techniques such as association rule and symbolic data analysis, as well as traditional SQL queries to gain further insight on the students' learning and deduce information to improve…

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

DMT-TAFM: a data mining tool for technical analysis of futures market

NASA Astrophysics Data System (ADS)

Stepanov, Vladimir; Sathaye, Archana

2002-03-01

Technical analysis of financial markets describes many patterns of market behavior. For practical use, all these descriptions need to be adjusted for each particular trading session. In this paper, we develop a data mining tool for technical analysis of the futures markets (DMT-TAFM), which dynamically generates rules based on the notion of the price pattern similarity. The tool consists of three main components. The first component provides visualization of data series on a chart with different ranges, scales, and chart sizes and types. The second component constructs pattern descriptions using sets of polynomials. The third component specifies the training set for mining, defines the similarity notion, and searches for a set of similar patterns. DMT-TAFM is useful to prepare the data, and then reveal and systemize statistical information about similar patterns found in any type of historical price series. We performed experiments with our tool on three decades of trading data fro hundred types of futures. Our results for this data set shows that, we can prove or disprove many well-known patterns based on real data, as well as reveal new ones, and use the set of relatively consistent patterns found during data mining for developing better futures trading strategies.

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

PubMed

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

2017-09-01

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

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)

Applying WEPP technologies to western alkaline surface coal mines

Treesearch

J. Q. Wu; S. Dun; H. Rhee; X. Liu; W. J. Elliot; T. Golnar; J. R. Frankenberger; D. C. Flanagan; P. W. Conrad; R. L. McNearny

2011-01-01

One aspect of planning surface mining operations, regulated by the National Pollutant Discharge Elimination System (NPDES), is estimating potential environmental impacts during mining operations and the reclamation period that follows. Practical computer simulation tools are effective for evaluating site-specific sediment control and reclamation plans for the NPDES....

D Reconstruction and Modeling of Subterranean Landscapes in Collaborative Mining Archeology Projects: Techniques, Applications and Experiences

NASA Astrophysics Data System (ADS)

Arles, A.; Clerc, P.; Sarah, G.; Téreygeol, F.; Bonnamour, G.; Heckes, J.; Klein, A.

2013-07-01

Mining and underground archaeology are two domains of expertise where three-dimensional data take an important part in the associated researches. Up to now, archaeologists study mines and underground networks from line-plot surveys, cross-section of galleries, and from tool marks surveys. All this kind of information can be clearly recorded back from the field from threedimensional models with a more cautious and extensive approach. Besides, the volumes of the underground structures that are very important data to explain the mining activities are difficult to evaluate from "traditional" hand-made recordings. They can now be calculated more accurately from a 3D model. Finally, reconstructed scenes are a powerful tool as thinking aid to look back again to a structure in the office or in future times. And the recorded models, rendered photo-realistically, can also be used for cultural heritage documentation presenting inaccessible and sometimes dangerous places to the public. Nowadays, thanks to modern computer technologies and highly developed software tools paired with sophisticated digital camera equipment, complex photogrammetric processes are available for moderate costs for research teams. Recognizing these advantages the authors develop and utilize image-based workflows in order to document ancient mining monuments and underground sites as a basis for further historical and archaeological researches, performed in collaborative partnership during recent projects on medieval silver mines and preventive excavations of undergrounds in France.

An overview of the BioCreative 2012 Workshop Track III: interactive text mining task

PubMed Central

Arighi, Cecilia N.; Carterette, Ben; Cohen, K. Bretonnel; Krallinger, Martin; Wilbur, W. John; Fey, Petra; Dodson, Robert; Cooper, Laurel; Van Slyke, Ceri E.; Dahdul, Wasila; Mabee, Paula; Li, Donghui; Harris, Bethany; Gillespie, Marc; Jimenez, Silvia; Roberts, Phoebe; Matthews, Lisa; Becker, Kevin; Drabkin, Harold; Bello, Susan; Licata, Luana; Chatr-aryamontri, Andrew; Schaeffer, Mary L.; Park, Julie; Haendel, Melissa; Van Auken, Kimberly; Li, Yuling; Chan, Juancarlos; Muller, Hans-Michael; Cui, Hong; Balhoff, James P.; Chi-Yang Wu, Johnny; Lu, Zhiyong; Wei, Chih-Hsuan; Tudor, Catalina O.; Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar; Cejuela, Juan Miguel; Dubey, Pratibha; Wu, Cathy

2013-01-01

In many databases, biocuration primarily involves literature curation, which usually involves retrieving relevant articles, extracting information that will translate into annotations and identifying new incoming literature. As the volume of biological literature increases, the use of text mining to assist in biocuration becomes increasingly relevant. A number of groups have developed tools for text mining from a computer science/linguistics perspective, and there are many initiatives to curate some aspect of biology from the literature. Some biocuration efforts already make use of a text mining tool, but there have not been many broad-based systematic efforts to study which aspects of a text mining tool contribute to its usefulness for a curation task. Here, we report on an effort to bring together text mining tool developers and database biocurators to test the utility and usability of tools. Six text mining systems presenting diverse biocuration tasks participated in a formal evaluation, and appropriate biocurators were recruited for testing. The performance results from this evaluation indicate that some of the systems were able to improve efficiency of curation by speeding up the curation task significantly (∼1.7- to 2.5-fold) over manual curation. In addition, some of the systems were able to improve annotation accuracy when compared with the performance on the manually curated set. In terms of inter-annotator agreement, the factors that contributed to significant differences for some of the systems included the expertise of the biocurator on the given curation task, the inherent difficulty of the curation and attention to annotation guidelines. After the task, annotators were asked to complete a survey to help identify strengths and weaknesses of the various systems. The analysis of this survey highlights how important task completion is to the biocurators’ overall experience of a system, regardless of the system’s high score on design, learnability and usability. In addition, strategies to refine the annotation guidelines and systems documentation, to adapt the tools to the needs and query types the end user might have and to evaluate performance in terms of efficiency, user interface, result export and traditional evaluation metrics have been analyzed during this task. This analysis will help to plan for a more intense study in BioCreative IV. PMID:23327936

An overview of the BioCreative 2012 Workshop Track III: interactive text mining task.

PubMed

Arighi, Cecilia N; Carterette, Ben; Cohen, K Bretonnel; Krallinger, Martin; Wilbur, W John; Fey, Petra; Dodson, Robert; Cooper, Laurel; Van Slyke, Ceri E; Dahdul, Wasila; Mabee, Paula; Li, Donghui; Harris, Bethany; Gillespie, Marc; Jimenez, Silvia; Roberts, Phoebe; Matthews, Lisa; Becker, Kevin; Drabkin, Harold; Bello, Susan; Licata, Luana; Chatr-aryamontri, Andrew; Schaeffer, Mary L; Park, Julie; Haendel, Melissa; Van Auken, Kimberly; Li, Yuling; Chan, Juancarlos; Muller, Hans-Michael; Cui, Hong; Balhoff, James P; Chi-Yang Wu, Johnny; Lu, Zhiyong; Wei, Chih-Hsuan; Tudor, Catalina O; Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar; Cejuela, Juan Miguel; Dubey, Pratibha; Wu, Cathy

2013-01-01

In many databases, biocuration primarily involves literature curation, which usually involves retrieving relevant articles, extracting information that will translate into annotations and identifying new incoming literature. As the volume of biological literature increases, the use of text mining to assist in biocuration becomes increasingly relevant. A number of groups have developed tools for text mining from a computer science/linguistics perspective, and there are many initiatives to curate some aspect of biology from the literature. Some biocuration efforts already make use of a text mining tool, but there have not been many broad-based systematic efforts to study which aspects of a text mining tool contribute to its usefulness for a curation task. Here, we report on an effort to bring together text mining tool developers and database biocurators to test the utility and usability of tools. Six text mining systems presenting diverse biocuration tasks participated in a formal evaluation, and appropriate biocurators were recruited for testing. The performance results from this evaluation indicate that some of the systems were able to improve efficiency of curation by speeding up the curation task significantly (∼1.7- to 2.5-fold) over manual curation. In addition, some of the systems were able to improve annotation accuracy when compared with the performance on the manually curated set. In terms of inter-annotator agreement, the factors that contributed to significant differences for some of the systems included the expertise of the biocurator on the given curation task, the inherent difficulty of the curation and attention to annotation guidelines. After the task, annotators were asked to complete a survey to help identify strengths and weaknesses of the various systems. The analysis of this survey highlights how important task completion is to the biocurators' overall experience of a system, regardless of the system's high score on design, learnability and usability. In addition, strategies to refine the annotation guidelines and systems documentation, to adapt the tools to the needs and query types the end user might have and to evaluate performance in terms of efficiency, user interface, result export and traditional evaluation metrics have been analyzed during this task. This analysis will help to plan for a more intense study in BioCreative IV.

Bats, mines, and citizen science in the Rockies: Volunteers make a difference in Colorado

USGS Publications Warehouse

Hayes, Mark A.

2012-01-01

Biologists at the Colorado Division of Wildlife faced a big problem back in 1990. They wanted to protect important bat roosts in the state’s abandoned mines, but first they had to find the bats. Colorado’s rich mining history had left more than 23,000 old mines scattered across the landscape, few of which had ever been surveyed for bat roosts. The magnitude of the task was overwhelming. So the agency put out a call for volunteers, “citizen scientists” willing to donate their time for bat conservation. Two decades later, the results have surpassed their wildest expectations.

A Feature Mining Based Approach for the Classification of Text Documents into Disjoint Classes.

ERIC Educational Resources Information Center

Nieto Sanchez, Salvador; Triantaphyllou, Evangelos; Kraft, Donald

2002-01-01

Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)

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…

Supervised learning of tools for content-based search of image databases

NASA Astrophysics Data System (ADS)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Research on Customer Value Based on Extension Data Mining

NASA Astrophysics Data System (ADS)

Chun-Yan, Yang; Wei-Hua, Li

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

Management of the water balance and quality in mining areas

NASA Astrophysics Data System (ADS)

Pasanen, Antti; Krogerus, Kirsti; Mroueh, Ulla-Maija; Turunen, Kaisa; Backnäs, Soile; Vento, Tiia; Veijalainen, Noora; Hentinen, Kimmo; Korkealaakso, Juhani

2015-04-01

Although mining companies have long been conscious of water related risks they still face environmental management problems. These problems mainly emerge because mine sites' water balances have not been adequately assessed in the stage of the planning of mines. More consistent approach is required to help mining companies identify risks and opportunities related to the management of water resources in all stages of mining. This approach requires that the water cycle of a mine site is interconnected with the general hydrologic water cycle. In addition to knowledge on hydrological conditions, the control of the water balance in the mining processes require knowledge of mining processes, the ability to adjust process parameters to variable hydrological conditions, adaptation of suitable water management tools and systems, systematic monitoring of amounts and quality of water, adequate capacity in water management infrastructure to handle the variable water flows, best practices to assess the dispersion, mixing and dilution of mine water and pollutant loading to receiving water bodies, and dewatering and separation of water from tailing and precipitates. WaterSmart project aims to improve the awareness of actual quantities of water, and water balances in mine areas to improve the forecasting and the management of the water volumes. The study is executed through hydrogeological and hydrological surveys and online monitoring procedures. One of the aims is to exploit on-line water quantity and quality monitoring for the better management of the water balances. The target is to develop a practical and end-user-specific on-line input and output procedures. The second objective is to develop mathematical models to calculate combined water balances including the surface, ground and process waters. WSFS, the Hydrological Modeling and Forecasting System of SYKE is being modified for mining areas. New modelling tools are developed on spreadsheet and system dynamics platforms to systematically integrate all water balance components (groundwater, surface water, infiltration, precipitation, mine water facilities and operations etc.) into overall dynamic mine site considerations. After coupling the surface and ground water models (e.g. Feflow and WSFS) with each other, they are compared with Goldsim. The third objective is to integrate the monitoring and modelling tools into the mine management system and process control. The modelling and predictive process control can prevent flood situations, ensure water adequacy, and enable the controlled mine water treatment. The project will develop a constantly updated management system for water balance including both natural waters and process waters.

From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes.

PubMed

Corcoran, Callan C; Grady, Cameron R; Pisitkun, Trairak; Parulekar, Jaya; Knepper, Mark A

2017-03-01

The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database ( https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database ( Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. Copyright © 2017 the American Physiological Society.

Underground coal mine instrumentation and test

NASA Technical Reports Server (NTRS)

Burchill, R. F.; Waldron, W. D.

1976-01-01

The need to evaluate mechanical performance of mine tools and to obtain test performance data from candidate systems dictate that an engineering data recording system be built. Because of the wide range of test parameters which would be evaluated, a general purpose data gathering system was designed and assembled to permit maximum versatility. A primary objective of this program was to provide a specific operating evaluation of a longwall mining machine vibration response under normal operating conditions. A number of mines were visited and a candidate for test evaluation was selected, based upon management cooperation, machine suitability, and mine conditions. Actual mine testing took place in a West Virginia mine.

Big data analytics in immunology: a knowledge-based approach.

PubMed

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

Empirical study using network of semantically related associations in bridging the knowledge gap.

PubMed

Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

2014-11-27

The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

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.

An overview of the biocreative 2012 workshop track III: Interactive text mining task

USDA-ARS?s Scientific Manuscript database

An important question is how to make use of text mining to enhance the biocuration workflow. A number of groups have developed tools for text mining from a computer science/linguistics perspective and there are many initiatives to curate some aspect of biology from the literature. In some cases the ...

PRO-Elicere: A Study for Create a New Process of Dependability Analysis of Space Computer Systems

NASA Astrophysics Data System (ADS)

da Silva, Glauco; Netto Lahoz, Carlos Henrique

2013-09-01

This paper presents the new approach to the computer system dependability analysis, called PRO-ELICERE, which introduces data mining concepts and intelligent mechanisms to decision support to analyze the potential hazards and failures of a critical computer system. Also, are presented some techniques and tools that support the traditional dependability analysis and briefly discusses the concept of knowledge discovery and intelligent databases for critical computer systems. After that, introduces the PRO-ELICERE process, an intelligent approach to automate the ELICERE, a process created to extract non-functional requirements for critical computer systems. The PRO-ELICERE can be used in the V&V activities in the projects of Institute of Aeronautics and Space, such as the Brazilian Satellite Launcher (VLS-1).

"A gold mine and a tool for democracy": George Gallup, Elmo Roper, and the business of scientific polling, 1935-1955.

PubMed

Igo, Sarah E

2006-01-01

"Scientific" public opinion polls arrived on the American scene in 1936. Examining the work of opinion surveyors George Gallup and Elmo Roper, this essay tracks the early career of a new social scientific technology, one that powerfully shaped conceptions of "the public." Pollsters described their craft as a democratic one that could accurately represent the U.S. populace. Yet, their assumptions about that same public-and the techniques they employed to measure it-undermined such claims, and even risked calling the polling profession into question. To understand why Gallup and Roper fell short of their stated ambitions, one must turn not only to the state of midcentury sampling methods but also to the corporate sponsors and commercial pressures underlying their enterprise.

Mining Software Usage with the Automatic Library Tracking Database (ALTD)

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

Hadri, Bilel; Fahey, Mark R

2013-01-01

Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batchmore » job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.« less

Development, installation, and testing services for an automatic, point type thermal sensor, fire protection system on a mining dozer. Final report

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

Lease, W.D.

1976-08-01

Lease AFEX, Inc., modified its standard design of an automatic fire protection system used in the past on logging equipment, and long-term, in-mine tested system on a Fiat-Alli's HD-41B dozer at the Lemmons and Company coal mine, Boonville, Ind. The modification of the standard AFEX system involved improving the actuation device. The AFEX system is called a point-type thermal sensor, automatic fire protection system. The in-mine test took place in late 1975, and early 1976. The system was then tested by simulating a fire on the dozer. The system operated successfully after the 4 months of in-mine endurance testing. (Colormore » illustrations reproduced in black and white.)« less

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.

KSC-2011-4145

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida, university students maneuver their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4157

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida, university students maneuver their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4161

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida, university students give their "thumbs up" after maneuvering their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4150

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students monitor their team's remote controlled or autonomous excavator, called a lunabot, as it is maneuvered in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4018

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor in Florida, university students maneuver their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-4149

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students monitor their team's remote controlled or autonomous excavator, called a lunabot, as it is maneuvered in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4162

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students monitor their team's remote controlled or autonomous excavator, called a lunabot, as it is maneuvered in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4019

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- University students monitor their team's remote controlled or autonomous excavator, called a lunabot, as it is maneuvered in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-4144

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida, university students maneuver their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4002

NASA Image and Video Library

2011-05-25

CAPE CANAVERAL, Fla. -- This tent called a "Lunarena" is a giant "sandbox," with about 60 tons of ultra-fine simulated lunar soil spread on the floor for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Frankie Martin

KSC-2011-4017

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- Inside the "Lunarena" at the Kennedy Space Center Visitor in Florida, university students maneuver their remote controlled or autonomous excavators, called lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

Field monitoring versus individual miner dosimetry of radon daughter products in mines.

PubMed

Domański, T; Kluszczyński, D; Olszewski, J; Chruscielewski, W

1989-01-01

The paper presents the results realised simultaneously by two different and independent systems of measurement of an assessment of miners' exposure to radon daughter products which naturally occur in the air of mines. The first one, called the Air Sampling System (ASS), was based on the field monitoring of radon progeny in air, the second one, called the Individual Dosimetry System (IDS), was based on the individual dosimeters worn by miners. Experimental comparison of these two systems has been conducted for six years in eleven Polish underground metal-ore mines. This study reveals that no correlation exists between the concentration and annual miners' exposures evaluated by the ASS and IDS. The ratio ASS/IDS for mine population varies from 11.0 to 0.14 in respect of annual concentration means, and in respect to annual exposures, this ratio varies from 4.5 to 0.14. The conclusion to be drawn from six years' observation and comparison of both systems is that correct and true evaluation of miners' exposure to radon progeny can be made only by the use of the Individual Dosimetry System, since the Air Sampling System is too sensitive and too dependent on the Strategy of sampling and its radiation.

Application of the Biosonar Measurement Tool (BMT) and Instrumented Mine Simulators (IMS) to Exploration of Dolphin Echolocation During Free-Swimming, Bottom-Object Searches

DTIC Science & Technology

2003-09-01

0-933957-31-9 311 Application of the Biosonar Measurement Tool (BMT) and Instrumented...dolphin biosonar (echolocation). Research work conducted by the Navy has addressed the characteristics of echolocation clicks, mechanisms of...information on dolphin echolocation that can be data mined for biosonar search strategies under real-world conditions. Results can be applied to the

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

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

Anderson, W.S.

1962-01-01

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

Stress monitoring versus microseismic ruptures in an active deep mine

NASA Astrophysics Data System (ADS)

Tonnellier, Alice; Bouffier, Christian; Bigarré, Pascal; Nyström, Anders; Österberg, Anders; Fjellström, Peter

2015-04-01

Nowadays, underground mining industry has developed high-technology mass mining methods to optimise the productivity at deep levels. Such massive extraction induces high-level stress redistribution generating seismic events around the mining works, threatening safety and economics. For this reason mining irregular deep ore bodies calls for steadily enhanced scientific practises and technologies to guarantee the mine environment to be safer and stable for the miners and the infrastructures. INERIS, within the framework of the FP7 European project I2Mine and in partnership with the Swedish mining company Boliden, has developed new methodologies in order to monitor both quasi-static stress changes and ruptures in a seismic prone area. To this purpose, a unique local permanent microseismic and stress monitoring network has been installed into the deep-working Garpenberg mine situated to the north of Uppsala (Sweden). In this mine, ore is extracted using sublevel stoping with paste fill production/distribution system and long-hole drilling method. This monitoring network has been deployed between about 1100 and 1250 meter depth. It consists in six 1-component and five 3-component microseismic probes (14-Hz geophones) deployed in the Lappberget area, in addition to three 3D stress monitoring cells that focus on a very local exploited area. Objective is three-fold: to quantify accurately quasi-static stress changes and freshly-induced stress gradients with drift development in the orebody, to study quantitatively those stress changes versus induced detected and located microseismic ruptures, and possibly to identify quasi-static stress transfer from those seismic ruptures. Geophysical and geotechnical data are acquired continuously and automatically transferred to INERIS datacenter through the web. They are made available on a secured web cloud monitoring infrastructure called e.cenaris and completed with mine data. Such interface enables the visualisation of the monitoring data coming from the mine in quasi-real time and facilitates information exchanges and decision making for experts and stakeholders. On the basis of these data acquisition and sharing, preliminary analysis has been started to highlight whether stress variations and seismic sources behaviour might be directly bound with mine working evolution and could improve the knowledge on the equilibrium states inside the mine. Knowing such parameters indeed will be a potential solution to understand better the response of deep mining activities to the exploitation solicitations and to develop, if possible, methods to prevent from major hazards such as rock bursts and other ground failure phenomena.

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

Closedure - Mine Closure Technologies Resource

NASA Astrophysics Data System (ADS)

Kauppila, Päivi; Kauppila, Tommi; Pasanen, Antti; Backnäs, Soile; Liisa Räisänen, Marja; Turunen, Kaisa; Karlsson, Teemu; Solismaa, Lauri; Hentinen, Kimmo

2015-04-01

Closure of mining operations is an essential part of the development of eco-efficient mining and the Green Mining concept in Finland to reduce the environmental footprint of mining. Closedure is a 2-year joint research project between Geological Survey of Finland and Technical Research Centre of Finland that aims at developing accessible tools and resources for planning, executing and monitoring mine closure. The main outcome of the Closedure project is an updatable wiki technology-based internet platform (http://mineclosure.gtk.fi) in which comprehensive guidance on the mine closure is provided and main methods and technologies related to mine closure are evaluated. Closedure also provides new data on the key issues of mine closure, such as performance of passive water treatment in Finland, applicability of test methods for evaluating cover structures for mining wastes, prediction of water effluents from mine wastes, and isotopic and geophysical methods to recognize contaminant transport paths in crystalline bedrock.

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

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.

PubMedPortable: A Framework for Supporting the Development of Text Mining Applications.

PubMed

Döring, Kersten; Grüning, Björn A; Telukunta, Kiran K; Thomas, Philippe; Günther, Stefan

2016-01-01

Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds a relational database and a full text index on PubMed citations. It can be applied either to the complete PubMed data set or an arbitrary subset of downloaded PubMed XML files. The software provides the infrastructure to combine stand-alone applications by exporting different data formats, e.g. BioC. The presented workflows show how to use PubMedPortable to retrieve, store, and analyse a disease-specific data set. The provided use cases are well documented in the PubMedPortable wiki. The open-source software library is small, easy to use, and scalable to the user's system requirements. It is freely available for Linux on the web at https://github.com/KerstenDoering/PubMedPortable and for other operating systems as a virtual container. The approach was tested extensively and applied successfully in several projects.

PubMedPortable: A Framework for Supporting the Development of Text Mining Applications

PubMed Central

Döring, Kersten; Grüning, Björn A.; Telukunta, Kiran K.; Thomas, Philippe; Günther, Stefan

2016-01-01

Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds a relational database and a full text index on PubMed citations. It can be applied either to the complete PubMed data set or an arbitrary subset of downloaded PubMed XML files. The software provides the infrastructure to combine stand-alone applications by exporting different data formats, e.g. BioC. The presented workflows show how to use PubMedPortable to retrieve, store, and analyse a disease-specific data set. The provided use cases are well documented in the PubMedPortable wiki. The open-source software library is small, easy to use, and scalable to the user’s system requirements. It is freely available for Linux on the web at https://github.com/KerstenDoering/PubMedPortable and for other operating systems as a virtual container. The approach was tested extensively and applied successfully in several projects. PMID:27706202

Financing Renewable Energy Projects on Contaminated Lands, Landfills, and Mine Sites

EPA Pesticide Factsheets

Provides information concerning financing tools and structures, as well as federal financial incentives that may be available for redeveloping potentially contaminated sites, landfills, or mine sites for renewable energy for site owners.

Text mining resources for the life sciences.

PubMed

Przybyła, Piotr; Shardlow, Matthew; Aubin, Sophie; Bossy, Robert; Eckart de Castilho, Richard; Piperidis, Stelios; McNaught, John; Ananiadou, Sophia

2016-01-01

Text mining is a powerful technology for quickly distilling key information from vast quantities of biomedical literature. However, to harness this power the researcher must be well versed in the availability, suitability, adaptability, interoperability and comparative accuracy of current text mining resources. In this survey, we give an overview of the text mining resources that exist in the life sciences to help researchers, especially those employed in biocuration, to engage with text mining in their own work. We categorize the various resources under three sections: Content Discovery looks at where and how to find biomedical publications for text mining; Knowledge Encoding describes the formats used to represent the different levels of information associated with content that enable text mining, including those formats used to carry such information between processes; Tools and Services gives an overview of workflow management systems that can be used to rapidly configure and compare domain- and task-specific processes, via access to a wide range of pre-built tools. We also provide links to relevant repositories in each section to enable the reader to find resources relevant to their own area of interest. Throughout this work we give a special focus to resources that are interoperable-those that have the crucial ability to share information, enabling smooth integration and reusability. © The Author(s) 2016. Published by Oxford University Press.

Text mining resources for the life sciences

PubMed Central

Shardlow, Matthew; Aubin, Sophie; Bossy, Robert; Eckart de Castilho, Richard; Piperidis, Stelios; McNaught, John; Ananiadou, Sophia

2016-01-01

Text mining is a powerful technology for quickly distilling key information from vast quantities of biomedical literature. However, to harness this power the researcher must be well versed in the availability, suitability, adaptability, interoperability and comparative accuracy of current text mining resources. In this survey, we give an overview of the text mining resources that exist in the life sciences to help researchers, especially those employed in biocuration, to engage with text mining in their own work. We categorize the various resources under three sections: Content Discovery looks at where and how to find biomedical publications for text mining; Knowledge Encoding describes the formats used to represent the different levels of information associated with content that enable text mining, including those formats used to carry such information between processes; Tools and Services gives an overview of workflow management systems that can be used to rapidly configure and compare domain- and task-specific processes, via access to a wide range of pre-built tools. We also provide links to relevant repositories in each section to enable the reader to find resources relevant to their own area of interest. Throughout this work we give a special focus to resources that are interoperable—those that have the crucial ability to share information, enabling smooth integration and reusability. PMID:27888231

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Development of a multilevel health and safety climate survey tool within a mining setting.

PubMed

Parker, Anthony W; Tones, Megan J; Ritchie, Gabrielle E

2017-09-01

This study aimed to design, implement and evaluate the reliability and validity of a multifactorial and multilevel health and safety climate survey (HSCS) tool with utility in the Australian mining setting. An 84-item questionnaire was developed and pilot tested on a sample of 302 Australian miners across two open cut sites. A 67-item, 10 factor solution was obtained via exploratory factor analysis (EFA) representing prioritization and attitudes to health and safety across multiple domains and organizational levels. Each factor demonstrated a high level of internal reliability, and a series of ANOVAs determined a high level of consistency in responses across the workforce, and generally irrespective of age, experience or job category. Participants tended to hold favorable views of occupational health and safety (OH&S) climate at the management, supervisor, workgroup and individual level. The survey tool demonstrated reliability and validity for use within an open cut Australian mining setting and supports a multilevel, industry specific approach to OH&S climate. Findings suggested a need for mining companies to maintain high OH&S standards to minimize risks to employee health and safety. Future research is required to determine the ability of this measure to predict OH&S outcomes and its utility within other mine settings. As this tool integrates health and safety, it may have benefits for assessment, monitoring and evaluation in the industry, and improving the understanding of how health and safety climate interact at multiple levels to influence OH&S outcomes. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

SPMBR: a scalable algorithm for mining sequential patterns based on bitmaps

NASA Astrophysics Data System (ADS)

Xu, Xiwei; Zhang, Changhai

2013-12-01

Now some sequential patterns mining algorithms generate too many candidate sequences, and increase the processing cost of support counting. Therefore, we present an effective and scalable algorithm called SPMBR (Sequential Patterns Mining based on Bitmap Representation) to solve the problem of mining the sequential patterns for large databases. Our method differs from previous related works of mining sequential patterns. The main difference is that the database of sequential patterns is represented by bitmaps, and a simplified bitmap structure is presented firstly. In this paper, First the algorithm generate candidate sequences by SE(Sequence Extension) and IE(Item Extension), and then obtain all frequent sequences by comparing the original bitmap and the extended item bitmap .This method could simplify the problem of mining the sequential patterns and avoid the high processing cost of support counting. Both theories and experiments indicate that the performance of SPMBR is predominant for large transaction databases, the required memory size for storing temporal data is much less during mining process, and all sequential patterns can be mined with feasibility.

An Integrated Suite of Text and Data Mining Tools - Phase II

DTIC Science & Technology

2005-08-30

Riverside, CA, USA Mazda Motor Corp, Jpn Univ of Darmstadt, Darmstadt, Ger Navy Center for Applied Research in Artificial Intelligence Univ of...with Georgia Tech Research Corporation developed a desktop text-mining software tool named TechOASIS (known commercially as VantagePoint). By the...of this dataset and groups the Corporate Source items that co-occur with the found items. He decides he is only interested in the institutions

SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.

PubMed

Merelli, Ivan; Calabria, Andrea; Cozzi, Paolo; Viti, Federica; Mosca, Ettore; Milanesi, Luciano

2013-01-01

The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects. We propose a new bioinformatics approach to support biological data mining in the analysis and interpretation of SNPs associated to pathologies. This system can be employed to design custom genotyping chips for disease-oriented studies and to re-score GWAS results. The proposed method relies (1) on the data integration of public resources using a gene-centric database design, (2) on the evaluation of a set of static biomolecular annotations, defined as features, and (3) on the SNP scoring function, which computes SNP scores using parameters and weights set by users. We employed a machine learning classifier to set default feature weights and an ontological annotation layer to enable the enrichment of the input gene set. We implemented our method as a web tool called SNPranker 2.0 (http://www.itb.cnr.it/snpranker), improving our first published release of this system. A user-friendly interface allows the input of a list of genes, SNPs or a biological process, and to customize the features set with relative weights. As result, SNPranker 2.0 returns a list of SNPs, localized within input and ontologically enriched genes, combined with their prioritization scores. Different databases and resources are already available for SNPs annotation, but they do not prioritize or re-score SNPs relying on a-priori biomolecular knowledge. SNPranker 2.0 attempts to fill this gap through a user-friendly integrated web resource. End users, such as researchers in medical genetics and epidemiology, may find in SNPranker 2.0 a new tool for data mining and interpretation able to support SNPs analysis. Possible scenarios are GWAS data re-scoring, SNPs selection for custom genotyping arrays and SNPs/diseases association studies.

China and Proliferation of Weapons of Mass Destruction and Missiles: Policy Issues

DTIC Science & Technology

2010-08-16

nuclear weapons facilities, while experts from China worked at a uranium mine at Saghand and a centrifuge facility (for uranium enrichment) near...brief interruptions.”85 84 Barbara Opall -Rome and Vago Muradian, “Bush Privately Lauds...confiscated a rare metal used to produce alloy steel (called vanadium) being smuggled to North Korea. In the same month, China’s NHI Shenyang Mining

A Tools-Based Approach to Teaching Data Mining Methods

ERIC Educational Resources Information Center

Jafar, Musa J.

2010-01-01

Data mining is an emerging field of study in Information Systems programs. Although the course content has been streamlined, the underlying technology is still in a state of flux. The purpose of this paper is to describe how we utilized Microsoft Excel's data mining add-ins as a front-end to Microsoft's Cloud Computing and SQL Server 2008 Business…

A simplified economic filter for open-pit mining and heap-leach recovery of copper in the United States

USGS Publications Warehouse

Long, Keith R.; Singer, Donald A.

2001-01-01

Determining the economic viability of mineral deposits of various sizes and grades is a critical task in all phases of mineral supply, from land-use management to mine development. This study evaluates two simple tools for estimating the economic viability of porphyry copper deposits mined by open-pit, heap-leach methods when only limited information on these deposits is available. These two methods are useful for evaluating deposits that either (1) are undiscovered deposits predicted by a mineral resource assessment, or (2) have been discovered but for which little data has been collected or released. The first tool uses ordinary least-squared regression analysis of cost and operating data from selected deposits to estimate a predictive relationship between mining rate, itself estimated from deposit size, and capital and operating costs. The second method uses cost models developed by the U.S. Bureau of Mines (Camm, 1991) updated using appropriate cost indices. We find that the cost model method works best for estimating capital costs and the empirical model works best for estimating operating costs for mines to be developed in the United States.

Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov.

PubMed

Su, Eric Wen; Sanger, Todd M

2017-01-01

Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).

Information Mining Technologies to Enable Discovery of Actionable Intelligence to Facilitate Maritime Situational Awareness: I-MINE

DTIC Science & Technology

2013-01-01

website). Data mining tools are in-house code developed in Python, C++ and Java . • NGA The National Geospatial-Intelligence Agency (NGA) performs data...as PostgreSQL (with PostGIS), MySQL , Microsoft SQL Server, SQLite, etc. using the appropriate JDBC driver. 14 The documentation and ease to learn are...written in Java that is able to perform various types of regressions, classi- fications, and other data mining tasks. There is also a commercial version

Metal mining and the environment

USGS Publications Warehouse

Hudson, Travis L.; Fox, Frederick D.; Plumlee, Geoffrey S.

1999-01-01

The booklet, Metal Mining and the Environment, and the colorful companion poster offer new tools for raising awareness and understanding of the impact and issues surrounding metal mining and the environment. The 64-page full-color booklet contains a copy of the poster which includes a student activity on the back. This booklet and poster can help you: illustrate the importance of our natural and environmental resources; provide a geoscience perspective on metal mining and the environment; improve Earth science literacy; and increase student understandings of Earth resources and systems.

U-Compare: share and compare text mining tools with UIMA.

PubMed

Kano, Yoshinobu; Baumgartner, William A; McCrohon, Luke; Ananiadou, Sophia; Cohen, K Bretonnel; Hunter, Lawrence; Tsujii, Jun'ichi

2009-08-01

Due to the increasing number of text mining resources (tools and corpora) available to biologists, interoperability issues between these resources are becoming significant obstacles to using them effectively. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources. These resources, originally developed by different groups for a variety of domains, include many famous tools and corpora. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources. http://u-compare.org/

Disk Rock Cutting Tool for the Implementation of Resource-Saving Technologies of Mining of Solid Minerals

NASA Astrophysics Data System (ADS)

Manietyev, Leonid; Khoreshok, Aleksey; Tsekhin, Alexander; Borisov, Andrey

2017-11-01

The directions of a resource and energy saving when creating a boom-type effectors of roadheaders of selective action with disc rock cutting tools on a multi-faceted prisms for the destruction of formation of minerals and rocks pricemax are presented. Justified reversing the modes of the crowns and booms to improve the efficiency of mining works. Parameters of destruction of coal and rock faces by the disk tool of a biconical design with the unified fastening knots to many-sided prisms on effectors of extraction mining machines are determined. Parameters of tension of the interfaced elements of knots of fastening of the disk tool at static interaction with the destroyed face of rocks are set. The technical solutions containing the constructive and kinematic communications realizing counter and reverse mode of rotation of two radial crowns with the disk tool on trihedral prisms and cases of booms with the disk tool on tetrahedral prisms in internal space between two axial crowns with the cutter are proposed. Reserves of expansion of the front of loading outside a table of a feeder of the roadheader of selective action, including side zones in which loading corridors by blades of trihedral prisms in internal space between two radial crowns are created are revealed.

Surface Mining and Reclamation Effects on Flood Response of Watersheds in the Central Appalachian Plateau Region

NASA Technical Reports Server (NTRS)

Ferrari, J. R.; Lookingbill, T. R.; McCormick, B.; Townsend, P. A.; Eshleman, K. N.

2009-01-01

Surface mining of coal and subsequent reclamation represent the dominant land use change in the central Appalachian Plateau (CAP) region of the United States. Hydrologic impacts of surface mining have been studied at the plot scale, but effects at broader scales have not been explored adequately. Broad-scale classification of reclaimed sites is difficult because standing vegetation makes them nearly indistinguishable from alternate land uses. We used a land cover data set that accurately maps surface mines for a 187-km2 watershed within the CAP. These land cover data, as well as plot-level data from within the watershed, are used with HSPF (Hydrologic Simulation Program-Fortran) to estimate changes in flood response as a function of increased mining. Results show that the rate at which flood magnitude increases due to increased mining is linear, with greater rates observed for less frequent return intervals. These findings indicate that mine reclamation leaves the landscape in a condition more similar to urban areas rather than does simple deforestation, and call into question the effectiveness of reclamation in terms of returning mined areas to the hydrological state that existed before mining.

Data Processing System (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research.

PubMed

Tang, Qi-Yi; Zhang, Chuan-Xi

2013-04-01

A comprehensive but simple-to-use software package called DPS (Data Processing System) has been developed to execute a range of standard numerical analyses and operations used in experimental design, statistics and data mining. This program runs on standard Windows computers. Many of the functions are specific to entomological and other biological research and are not found in standard statistical software. This paper presents applications of DPS to experimental design, statistical analysis and data mining in entomology. © 2012 The Authors Insect Science © 2012 Institute of Zoology, Chinese Academy of Sciences.

Accessing Cloud Properties and Satellite Imagery: A tool for visualization and data mining

NASA Astrophysics Data System (ADS)

Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.

2016-12-01

Providing public access to imagery of cloud macro and microphysical properties and the underlying satellite imagery is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and system that allows end users to easily browse cloud information and satellite imagery that is otherwise difficult to acquire and manipulate. The tool has two uses, one to visualize the data and the other to access the data directly. It uses a widely used access protocol, the Open Geospatial Consortium's Web Map and Processing Services, to encourage user to access the data we produce. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud. One goal of the tool is to provide a demonstration of the back end capability to end users so that they can use the dynamically generated imagery and data as an input to their own work flows or to set up data mining constraints. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information and satellite imagery accessible and easily searchable. Increasingly, information is used in a "mash-up" form where multiple sources of information are combined to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much cutting edge scientific knowledge, observations and products available to the citizen science, research and interested communities for these kinds of "mash-ups" as well as provide a means for automated systems to data mine our information. This tool and access method provides a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

Constraint-based Data Mining

NASA Astrophysics Data System (ADS)

Boulicaut, Jean-Francois; Jeudy, Baptiste

Knowledge Discovery in Databases (KDD) is a complex interactive process. The promising theoretical framework of inductive databases considers this is essentially a querying process. It is enabled by a query language which can deal either with raw data or patterns which hold in the data. Mining patterns turns to be the so-called inductive query evaluation process for which constraint-based Data Mining techniques have to be designed. An inductive query specifies declaratively the desired constraints and algorithms are used to compute the patterns satisfying the constraints in the data. We survey important results of this active research domain. This chapter emphasizes a real breakthrough for hard problems concerning local pattern mining under various constraints and it points out the current directions of research as well.

KSC-2011-3939

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3941

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3946

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3944

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3940

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3947

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3943

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3945

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3942

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

KSC-2011-3948

NASA Image and Video Library

2011-05-23

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Cory Huston

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

Leaf-Mining and Gall-Forming Insects: Tools for Teaching Population Ecology.

ERIC Educational Resources Information Center

Brown, Valerie K.

1984-01-01

Discusses the use of leaf mines (formed by larvae of small moths or flies) and galls (wasps' larvae) in various insect population studies. Also considers the advantages of using these structures for instructional purposes. (DH)

Alkemio: association of chemicals with biomedical topics by text and data mining

PubMed Central

Gijón-Correas, José A.; Andrade-Navarro, Miguel A.; Fontaine, Jean F.

2014-01-01

The PubMed® database of biomedical citations allows the retrieval of scientific articles studying the function of chemicals in biology and medicine. Mining millions of available citations to search reported associations between chemicals and topics of interest would require substantial human time. We have implemented the Alkemio text mining web tool and SOAP web service to help in this task. The tool uses biomedical articles discussing chemicals (including drugs), predicts their relatedness to the query topic with a naïve Bayesian classifier and ranks all chemicals by P-values computed from random simulations. Benchmarks on seven human pathways showed good retrieval performance (areas under the receiver operating characteristic curves ranged from 73.6 to 94.5%). Comparison with existing tools to retrieve chemicals associated to eight diseases showed the higher precision and recall of Alkemio when considering the top 10 candidate chemicals. Alkemio is a high performing web tool ranking chemicals for any biomedical topics and it is free to non-commercial users. Availability: http://cbdm.mdc-berlin.de/∼medlineranker/cms/alkemio. PMID:24838570

Human factors model concerning the man-machine interface of mining crewstations

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

Analysis of the current rib support practices and techniques in U.S. coal mines

PubMed Central

Mohamed, Khaled M.; Murphy, Michael M.; Lawson, Heather E.; Klemetti, Ted

2016-01-01

Design of rib support systems in U.S. coal mines is based primarily on local practices and experience. A better understanding of current rib support practices in U.S. coal mines is crucial for developing a sound engineering rib support design tool. The objective of this paper is to analyze the current practices of rib control in U.S. coal mines. Twenty underground coal mines were studied representing various coal basins, coal seams, geology, loading conditions, and rib control strategies. The key findings are: (1) any rib design guideline or tool should take into account external rib support as well as internal bolting; (2) rib bolts on their own cannot contain rib spall, especially in soft ribs subjected to significant load—external rib control devices such as mesh are required in such cases to contain rib sloughing; (3) the majority of the studied mines follow the overburden depth and entry height thresholds recommended by the Program Information Bulletin 11-29 issued by the Mine Safety and Health Administration; (4) potential rib instability occurred when certain geological features prevailed—these include draw slate and/or bone coal near the rib/roof line, claystone partings, and soft coal bench overlain by rock strata; (5) 47% of the studied rib spall was classified as blocky—this could indicate a high potential of rib hazards; and (6) rib injury rates of the studied mines for the last three years emphasize the need for more rib control management for mines operating at overburden depths between 152.4 m and 304.8 m. PMID:27648341

Data Mining and Homeland Security: An Overview

DTIC Science & Technology

2006-01-27

which government agencies should use and mix commercial data with government data, whether data sources are being used for purposes other than those...example, a hardware store may compare their customers’ tool purchases with home ownership, type of CRS-2 3 John Makulowich, “ Government Data Mining...cleaning, data integration, data selection, data transformation , (data mining), pattern evaluation, and knowledge presentation.4 A number of advances in

Biomedical text mining and its applications in cancer research.

PubMed

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

2013-04-01

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

An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest

PubMed Central

Kim, Sung-Min; Yi, Huiuk; Choi, Yosoon

2017-01-01

In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further. PMID:29186922

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

PubMed

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

2002-01-01

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

An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest.

PubMed

Suh, Jangwon; Kim, Sung-Min; Yi, Huiuk; Choi, Yosoon

2017-11-27

In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further.

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.

The impact of the structural features of the rock mass on seismicity in Polish coal mines

NASA Astrophysics Data System (ADS)

Patyńska, Renata

2017-11-01

The article presents seismic activity induced in the coal mines of the Upper Silesian Coal Basin (GZW) in relation to the locations of the occurrence of rockbursts. The comparison of these measurements with the structural features of the rock mass of coal mines indicates the possibility of estimating the so-called Unitary Energy Expenditure (UEE) in a specific time. The obtained values of UEE were compared with the distribution of seismic activity in GZW mines. The level of seismic activity in the analysed period changed and depended on the intensity of mining works and diverse mining and geological conditions. Five regions, where tremors occurred (Bytom Trough, Main Saddle, Main Trough, Kazimierz Trough, and Jejkowice and Chwałowice Trough) which belong to various structural units of the Upper Silesia were analyzed. It was found out that rock bursts were recorded only in three regions: Main Saddle, Bytom Trough, and Jejkowice and Chwałowice Trough.

Assessing human rights impacts in corporate development projects

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

Salcito, Kendyl, E-mail: kendyl.salcito@unibas.ch; University of Basel, P.O. Box, CH-4003 Basel; NomoGaia, 1900 Wazee Street, Suite 303, Denver, CO 80202

Human rights impact assessment (HRIA) is a process for systematically identifying, predicting and responding to the potential impact on human rights of a business operation, capital project, government policy or trade agreement. Traditionally, it has been conducted as a desktop exercise to predict the effects of trade agreements and government policies on individuals and communities. In line with a growing call for multinational corporations to ensure they do not violate human rights in their activities, HRIA is increasingly incorporated into the standard suite of corporate development project impact assessments. In this context, the policy world's non-structured, desk-based approaches to HRIAmore » are insufficient. Although a number of corporations have commissioned and conducted HRIA, no broadly accepted and validated assessment tool is currently available. The lack of standardisation has complicated efforts to evaluate the effectiveness of HRIA as a risk mitigation tool, and has caused confusion in the corporate world regarding company duties. Hence, clarification is needed. The objectives of this paper are (i) to describe an HRIA methodology, (ii) to provide a rationale for its components and design, and (iii) to illustrate implementation of HRIA using the methodology in two selected corporate development projects—a uranium mine in Malawi and a tree farm in Tanzania. We found that as a prognostic tool, HRIA could examine potential positive and negative human rights impacts and provide effective recommendations for mitigation. However, longer-term monitoring revealed that recommendations were unevenly implemented, dependent on market conditions and personnel movements. This instability in the approach to human rights suggests a need for on-going monitoring and surveillance. -- Highlights: • We developed a novel methodology for corporate human rights impact assessment. • We piloted the methodology on two corporate projects—a mine and a plantation. • Human rights impact assessment exposed impacts not foreseen in ESIA. • Corporations adopted the majority of findings, but not necessarily immediately. • Methodological advancements are expected for monitoring processes.« less

An Integrated SNP Mining and Utilization (ISMU) Pipeline for Next Generation Sequencing Data

PubMed Central

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M.; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A. V. S. K.; Varshney, Rajeev K.

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software. PMID:25003610

LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs

PubMed Central

Chang, Hsueh-Wei; Chuang, Li-Yeh; Chang, Yan-Jhu; Cheng, Yu-Huei; Hung, Yu-Chen; Chen, Hsiang-Chi; Yang, Cheng-Hong

2009-01-01

Background Linkage disequilibrium (LD) mapping is commonly used to evaluate markers for genome-wide association studies. Most types of LD software focus strictly on LD analysis and visualization, but lack supporting services for genotyping. Results We developed a freeware called LD2SNPing, which provides a complete package of mining tools for genotyping and LD analysis environments. The software provides SNP ID- and gene-centric online retrievals for SNP information and tag SNP selection from dbSNP/NCBI and HapMap, respectively. Restriction fragment length polymorphism (RFLP) enzyme information for SNP genotype is available to all SNP IDs and tag SNPs. Single and multiple SNP inputs are possible in order to perform LD analysis by online retrieval from HapMap and NCBI. An LD statistics section provides D, D', r2, δQ, ρ, and the P values of the Hardy-Weinberg Equilibrium for each SNP marker, and Chi-square and likelihood-ratio tests for the pair-wise association of two SNPs in LD calculation. Finally, 2D and 3D plots, as well as plain-text output of the results, can be selected. Conclusion LD2SNPing thus provides a novel visualization environment for multiple SNP input, which facilitates SNP association studies. The software, user manual, and tutorial are freely available at . PMID:19500380

pGenN, a gene normalization tool for plant genes and proteins in scientific literature.

PubMed

Ding, Ruoyao; Arighi, Cecilia N; Lee, Jung-Youn; Wu, Cathy H; Vijay-Shanker, K

2015-01-01

Automatically detecting gene/protein names in the literature and connecting them to databases records, also known as gene normalization, provides a means to structure the information buried in free-text literature. Gene normalization is critical for improving the coverage of annotation in the databases, and is an essential component of many text mining systems and database curation pipelines. In this manuscript, we describe a gene normalization system specifically tailored for plant species, called pGenN (pivot-based Gene Normalization). The system consists of three steps: dictionary-based gene mention detection, species assignment, and intra species normalization. We have developed new heuristics to improve each of these phases. We evaluated the performance of pGenN on an in-house expertly annotated corpus consisting of 104 plant relevant abstracts. Our system achieved an F-value of 88.9% (Precision 90.9% and Recall 87.2%) on this corpus, outperforming state-of-art systems presented in BioCreative III. We have processed over 440,000 plant-related Medline abstracts using pGenN. The gene normalization results are stored in a local database for direct query from the pGenN web interface (proteininformationresource.org/pgenn/). The annotated literature corpus is also publicly available through the PIR text mining portal (proteininformationresource.org/iprolink/).

Framing Psychology as a Discipline (1950-1999): A Large-Scale Term Co-Occurrence Analysis of Scientific Literature in Psychology.

PubMed

Flis, Ivan; van Eck, Nees Jan

2017-07-20

This study investigated the structure of psychological literature as represented by a corpus of 676,393 articles in the period from 1950 to 1999. The corpus was extracted from 1,269 journals indexed by PsycINFO. The data in our analysis consisted of the relevant terms mined from the titles and abstracts of all of the articles in the corpus. Based on the co-occurrences of these terms, we developed a series of chronological visualizations using a bibliometric software tool called VOSviewer. These visualizations produced a stable structure through the 5 decades under analysis, and this structure was analyzed as a data-mined proxy for the disciplinary formation of scientific psychology in the second part of the 20th century. Considering the stable structure uncovered by our term co-occurrence analysis and its visualization, we discuss it in the context of Lee Cronbach's "Two Disciplines of Scientific Psychology" (1957) and conventional history of 20th-century psychology's disciplinary formation and history of methods. Our aim was to provide a comprehensive digital humanities perspective on the large-scale structural development of research in English-language psychology from 1950 to 1999. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Hypersalinity reduces the risk of cyanide toxicosis to insectivorous bats interacting with wastewater impoundments at gold mines.

PubMed

Griffiths, Stephen R; Donato, David B; Lumsden, Linda F; Coulson, Graeme

2014-01-01

Wildlife and livestock that ingest bioavailable cyanide compounds in gold mining tailings dams are known to experience cyanide toxicosis. Elevated levels of salinity in open impoundments have been shown to prevent wildlife cyanide toxicosis by reducing drinking and foraging. This finding appears to be consistent for diurnal wildlife interacting with open impoundments, however the risks to nocturnal wildlife of cyanide exposure are unknown. We investigated the activity of insectivorous bats in the airspace above both fresh (potable to wildlife) and saline water bodies at two gold mines in the goldfields of Western Australian. During this study, cyanide-bearing solutions stored in open impoundments at both mine sites were hypersaline (range=57,000-295,000 mg/L total dissolved solids (TDS)), well above known physiological tolerance of any terrestrial vertebrate. Bats used the airspace above each water body monitored, but were more active at fresh than saline water bodies. In addition, considerably more terminal echolocation buzz calls were recorded in the airspace above fresh than saline water bodies at both mine sites. However, it was not possible to determine whether these buzz calls corresponded to foraging or drinking bouts. No drinking bouts were observed in 33 h of thermal video footage recorded at one hypersaline tailings dam, suggesting that this water is not used for drinking. There is no information on salinity tolerances of bats, but it could be assumed that bats would not tolerate salinity in drinking water at concentrations greater than those documented as toxic for saline-adapted terrestrial wildlife. Therefore, when managing wastewater impoundments at gold mines to avoid wildlife mortalities, adopting a precautionary principle, bats are unlikely to drink solutions at salinity levels ≥50,000 mg/L TDS. © 2013 Published by Elsevier Inc.

Mind the seafloor

NASA Astrophysics Data System (ADS)

Boetius, Antje; Haeckel, Matthias

2018-01-01

As human use of rare metals has diversified and risen with global development, metal ore deposits from the deep ocean floor are increasingly seen as an attractive future resource. Japan recently completed the first successful test for zinc extraction from the deep seabed, and the number of seafloor exploration licenses filed at the International Seabed Authority (ISA) has tripled in the past 5 years. Seafloor-mining equipment is being tested, and industrial-scale production in national waters could start in a few years. We call for integrated scientific studies of global metal resources, the fluxes and fates of metal uses, and the ecological footprints of mining on land and in the sea, to critically assess the risks of deep-sea mining and the chances for alternative technologies. Given the increasing scientific evidence for long-lasting impacts of mining on the abyssal environment, precautionary regulations for commercial deep-sea mining are essential to protect marine ecosystems and their biodiversity.

Multivariate Spatial Condition Mapping Using Subtractive Fuzzy Cluster Means

PubMed Central

Sabit, Hakilo; Al-Anbuky, Adnan

2014-01-01

Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining. PMID:25313495

KSC-2011-4154

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- A remote controlled or autonomous excavator, called a lunabot, is on display outside of the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida where university students maneuver their remote controlled lunabots, in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4148

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- While an event judge looks on, university students monitor their team's remote controlled or autonomous excavator, called a lunabot, as it is maneuvered in a "sand box" of ultra-fine simulated lunar soil during NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

Complex Feeding Tracks of the Sessile Herbivorous Insect Ophiomyia maura as a Function of the Defense against Insect Parasitoids

PubMed Central

Ayabe, Yoshiko; Ueno, Takatoshi

2012-01-01

Because insect herbivores generally suffer from high mortality due to their natural enemies, reducing the risk of being located by natural enemies is of critical importance for them, forcing them to develop a variety of defensive measures. Larvae of leaf-mining insects lead a sedentary life inside a leaf and make conspicuous feeding tracks called mines, exposing themselves to the potential risk of parasitism. We investigated the defense strategy of the linear leafminer Ophiomyia maura Meigen (Diptera: Agromyzidae), by focusing on its mining patterns. We examined whether the leafminer could reduce the risk of being parasitized (1) by making cross structures in the inner area of a leaf to deter parasitoids from tracking the mines due to complex pathways, and (2) by mining along the edge of a leaf to hinder visually searching parasitoids from finding mined leaves due to effective background matching of the mined leaves among intact leaves. We quantified fractal dimension as mine complexity and area of mine in the inner area of the leaf as interior mine density for each sample mine, and analyzed whether these mine traits affected the susceptibility of O. maura to parasitism. Our results have shown that an increase in mine complexity with the development of occupying larvae decreases the probability of being parasitized, while interior mine density has no influence on parasitism. These results suggest that the larval development increases the host defense ability through increasing mine complexity. Thus the feeding pattern of these sessile insects has a defensive function by reducing the risk of parasitism. PMID:22393419

Mining of high utility-probability sequential patterns from uncertain databases

PubMed Central

Zhang, Binbin; Fournier-Viger, Philippe; Li, Ting

2017-01-01

High-utility sequential pattern mining (HUSPM) has become an important issue in the field of data mining. Several HUSPM algorithms have been designed to mine high-utility sequential patterns (HUPSPs). They have been applied in several real-life situations such as for consumer behavior analysis and event detection in sensor networks. Nonetheless, most studies on HUSPM have focused on mining HUPSPs in precise data. But in real-life, uncertainty is an important factor as data is collected using various types of sensors that are more or less accurate. Hence, data collected in a real-life database can be annotated with existing probabilities. This paper presents a novel pattern mining framework called high utility-probability sequential pattern mining (HUPSPM) for mining high utility-probability sequential patterns (HUPSPs) in uncertain sequence databases. A baseline algorithm with three optional pruning strategies is presented to mine HUPSPs. Moroever, to speed up the mining process, a projection mechanism is designed to create a database projection for each processed sequence, which is smaller than the original database. Thus, the number of unpromising candidates can be greatly reduced, as well as the execution time for mining HUPSPs. Substantial experiments both on real-life and synthetic datasets show that the designed algorithm performs well in terms of runtime, number of candidates, memory usage, and scalability for different minimum utility and minimum probability thresholds. PMID:28742847

Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

NASA Astrophysics Data System (ADS)

Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

2015-12-01

We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction process. We will describe our experience and implementation of our system and share lessons learned from our development. We will also discuss ways in which this could be adapted to other science fields. [1] Funk et al., 2014. [2] Kang et al., 2014. [3] Utopia Documents, http://utopiadocs.com [4] Apache cTAKES, http://ctakes.apache.org

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Detection and Monitoring of Small-Scale Mining Operations in the Eastern Democratic Republic of the Congo (DRC) Using Multi-Temporal, Multi-Sensor Remote Sensing Data

NASA Astrophysics Data System (ADS)

Walther, Christian; Frei, Michaela

2017-04-01

Mining of so-called "conflict minerals" is often related with small-scale mining activities. The here discussed activities are located in forested areas in the eastern DRC, which are often remote, difficult to access and insecure for traditional geological field inspection. In order to accelerate their CTC (Certified Trading Chain)-certification process, remote sensing data are used for detection and monitoring of these small-scale mining operations. This requires a high image acquisition frequency due to mining site relocations and for compensation of year-round high cloud coverage, especially for optical data evaluation. Freely available medium resolution optical data of Sentinel-2 and Landsat-8 as well as SAR data of Sentinel-1 are used for detecting small mining targets with a minimum size of approximately 0.5 km2. The developed method enables a robust multi-temporal detection of mining sites, monitoring of mining site spatio-temporal relocations and environmental changes. Since qualitative and quantitative comparable results are generated, the followed change detection approach is objective and transparent and may push the certification process forward.

Biocuration workflows and text mining: overview of the BioCreative 2012 Workshop Track II.

PubMed

Lu, Zhiyong; Hirschman, Lynette

2012-01-01

Manual curation of data from the biomedical literature is a rate-limiting factor for many expert curated databases. Despite the continuing advances in biomedical text mining and the pressing needs of biocurators for better tools, few existing text-mining tools have been successfully integrated into production literature curation systems such as those used by the expert curated databases. To close this gap and better understand all aspects of literature curation, we invited submissions of written descriptions of curation workflows from expert curated databases for the BioCreative 2012 Workshop Track II. We received seven qualified contributions, primarily from model organism databases. Based on these descriptions, we identified commonalities and differences across the workflows, the common ontologies and controlled vocabularies used and the current and desired uses of text mining for biocuration. Compared to a survey done in 2009, our 2012 results show that many more databases are now using text mining in parts of their curation workflows. In addition, the workshop participants identified text-mining aids for finding gene names and symbols (gene indexing), prioritization of documents for curation (document triage) and ontology concept assignment as those most desired by the biocurators. DATABASE URL: http://www.biocreative.org/tasks/bc-workshop-2012/workflow/.

Understanding social collaboration between actors and technology in an automated and digitised deep mining environment.

PubMed

Sanda, M-A; Johansson, J; Johansson, B; Abrahamsson, L

2011-10-01

The purpose of this article is to develop knowledge and learning on the best way to automate organisational activities in deep mines that could lead to the creation of harmony between the human, technical and the social system, towards increased productivity. The findings showed that though the introduction of high-level technological tools in the work environment disrupted the social relations developed over time amongst the employees in most situations, the technological tools themselves became substitute social collaborative partners to the employees. It is concluded that, in developing a digitised mining production system, knowledge of the social collaboration between the humans (miners) and the technology they use for their work must be developed. By implication, knowledge of the human's subject-oriented and object-oriented activities should be considered as an important integral resource for developing a better technological, organisational and human interactive subsystem when designing the intelligent automation and digitisation systems for deep mines. STATEMENT OF RELEVANCE: This study focused on understanding the social collaboration between humans and the technologies they use to work in underground mines. The learning provides an added knowledge in designing technologies and work organisations that could better enhance the human-technology interactive and collaborative system in the automation and digitisation of underground mines.

Realizing modeling and mapping tools to study the upsurge of noise pollution as a result of open-cast mining and transportation activities.

PubMed

Lokhande, Satish K; Jain, Mohindra C; Dhawale, Satyajeet A; Gautam, Rakesh; Bodhe, Ghanshyam L

2018-01-01

In open-cast mines, noise pollution has become a serious concern due to the extreme use of heavy earth moving machinery (HEMM). This study is focused to measure and assess the effects of the existing noise levels of major operational mines in the Keonjhar, Sundergadh, and Mayurbhanj districts of Odisha, India. The transportation noise levels were also considered in this study, which was predicted using the modified Federal Highway Administration (FHWA) model. It was observed that noise induced by HEMM such as rock breakers, jackhammers, dumpers, and excavators, blasting noise in the mining terrain, as well as associated transportation noise became a major source of annoyance to the habitants living in proximity to the mines. The noise produced by mechanized mining operations was observed between 74.3 and 115.2 dB(A), and its impact on residential areas was observed between 49.4 and 58.9 dB(A). In addition, the noise contour maps of sound level dispersion were demonstrated with the utilization of advanced noise prediction software tools for better understanding. Finally, the predicted values at residential zone and traffic noise are correlated with observed values, and the coefficient of determination, R 2 , was calculated to be 0.6891 and 0.5967, respectively.

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

Ecological effects of lead mining on Ozark streams: In-situ toxicity to woodland crayfish (Orconectes hylas)

USGS Publications Warehouse

Allert, A.L.; Fairchild, J.F.; DiStefano, R.J.; Schmitt, C.J.; Brumbaugh, W.G.; Besser, J.M.

2009-01-01

The Viburnum Trend mining district in southeast Missouri, USA is one of the largest producers of lead-zinc ore in the world. Previous stream surveys found evidence of increased metal exposure and reduced population densities of crayfish immediately downstream of mining sites. We conducted an in-situ 28-d exposure to assess toxicity of mining-derived metals to the woodland crayfish (Orconectes hylas). Crayfish survival and biomass were significantly lower at mining sites than at reference and downstream sites. Metal concentrations in water, detritus, macroinvertebrates, fish, and crayfish were significantly higher at mining sites, and were negatively correlated with caged crayfish survival. These results support previous field and laboratory studies that showed mining-derived metals negatively affect O. hylas populations in streams draining the Viburnum Trend, and that in-situ toxicity testing was a valuable tool for assessing the impacts of mining on crayfish populations.

Israel and Iran: A Dangerous Rivalry

DTIC Science & Technology

2011-01-01

and Knesset view the Islamic Republic as “a bitter ideological enemy that is deter- mined to bring about the physical annihilation of Israel”; only...entirely different set of values. . . . Iran sends children into mine fields. Iran denies the Holocaust. Iran openly calls for Israel’s destruction...compromise on sovereignty by having U.S. troops deployed here.” Quoted in Barbara Opall -Rome, “U.S. to Deploy Radar, Troops In Israel,” Defense News

a New Generation Mining Head with Disc Tool of Complex Trajectory / GŁOWICA URABIAJĄCA Nowej Generacji Z NARZĘDZIAMI Dyskowymi O ZŁOŻONEJ Trajektorii

NASA Astrophysics Data System (ADS)

Gospodarczyk, Piotr; Kotwica, Krzysztof; Stopka, Grzegorz

2013-12-01

In Polish underground mining plenty of dog headings are drilled with mechanical methods with the use of arm roadheaders equipped with milling units. Cutting tools applied on the units - rotary tangent bits in unfavourable mining and geological conditions or improper work conditions are affected by an accelerated wear process. It influences the speed and costs of drilling such excavations. The article presents a new and innovative solution of a mining head with asymmetric disc tools of complex trajectory elaborated at the Department of Mining, Dressing and Transport Machines, AGH University of Science and Technology, Krakow as an alternative for standard milling units. Advantages of the applied mining method using so called back incision were described as well as principles of construction and work of the suggested solution of the head. In order to work out a construction of the head prototype it was necessary to determine principles and guidelines based on laboratory tests. A construction of a specially prepared laboratory stand for examination of disc tools of complex trajectory, planned research methodology, course of tests and obtained results were presented. An analysis of the results allowed determining the above listed principles and guidelines for a construction of a prototype head. They were the base to work out, with cooperation of the REMAG Ltd Company in Katowice, a technical project of a new head solution, adapted for mounting on the arm of a medium arm roadheader KR 150. A constructed head underwent tests on a research stand on the REMAG testing area and received positive preliminary tests results. W polskim górnictwie podziemnym bardzo duża liczba wyrobisk korytarzowych drążona jest metodami mechanicznymi z wykorzystaniem ramionowych kombajnów chodnikowych, wyposażonych w organy frezujące. Stosowane na tych organach narzędzia skrawające - noże styczno-obrotowe, w niekorzystnych warunkach górniczo-geologicznych lub przy nieprawidłowych warunkach pracy, ulegają przyspieszonemu zużyciu. Wpływa to na prędkość i koszty drążenia tych wyrobisk. W artykule przedstawiono opracowane w Katedrze MGPiT AGH Kraków nowe i innowacyjne rozwiązanie głowicy urabiającej, z narzędziami dyskowymi niesymetrycznymi o złożonej trajektorii, jako alternatywę dla standardowych organów frezujących. Opisano zalety zastosowanej metody urabiania z wykorzystaniem tzw. tylnego podcinaniaoraz zasadę budowy i pracy zaproponowanego rozwiązania przedmiotowej głowicy. Dla opracowania konstrukcji prototypowego egzemplarza tej głowicy koniecznym było określenie, na podstawie badań laboratoryjnych, założeń i wytycznych. Przedstawiono konstrukcję opracowanego specjalnego stanowiska laboratoryjnego do badania narzędzi dyskowych o złożonej trajektorii, założoną metodykę badawczą, przebieg badań oraz uzyskane wyniki. Analiza tych wyników umożliwiła określenie wyżej wymienionych założeń i wytycznych dla konstrukcji głowicy prototypowej. Na ich podstawie opracowano, we współpracy z Zakładami REMAG S.A. w Katowicach, projekt techniczny nowego rozwiązania głowicy, dostosowanej do zabudowy na ramieniu średniego kombajnu chodnikowego KR 150. Wykonany egzemplarz głowicy został poddany próbom na stanowisku badawczym na poligonie Zakładów REMAG i uzyskał pozytywne wyniki badań wstępnych.

Poly(vinyl alcohol)/hydroxyapatite Monolithic In-Needle Extraction (MINE) device: Preparation and examination of drug affinity.

PubMed

Pietrzyńska, Monika; Czerwiński, Michał; Voelkel, Adam

2017-07-15

Polymer-ceramic materials based on poly(vinyl alcohol) (PVA) and hydroxyapatite were applied as sorption material in Monolithic In-Needle Extraction (MINE) device. The presented device provides new possibilities for the examination of bisphosphonates affinity for bone and will be a helpful tool in evaluation of potential antiresorptive drugs suitability. A ceramic part of monoliths was prepared by incorporation of hydroxyapatite (HA) into the reaction mixture or by using a soaking method (mineralization of HA on the PVA). The parameters of synthesis conditions were optimized to achieve a monolithic material having the appropriate dimensions after the soaking process enabling placing of the monolithic material inside the needle. Furthermore, the material must have had optimal dimensions after the re-soaking process to fit perfectly to the needle. Among the sixteen monolithic materials, eight of them were selected for further study, and then four of them were selected as a sorbent material for the MINE device. The material properties were examined on the basis of several parameters: swelling ratio, initial mass reversion and initial diameter reversion, mass growth due to the HA formation, and antiresorptive drug sorption. The MINE device might be then used as a tool for examination of interactions between bisphosphonate and bone. The simulated body fluid containing sodium risedronate (RSD) as a standard compound was passed through the MINE device. The obtained device allowed for sorption about 0.38mg of RSD. The desorption process was carried out in five steps allowing insightful analysis. The MINE device turned out to be a helpful tool for determination of the bisphosphonates affinity to the ceramic part of sorbent (hydroxyapatite) and to assess the usefulness of them as antiresorptive drugs in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

NASA Astrophysics Data System (ADS)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

U-Compare: share and compare text mining tools with UIMA

PubMed Central

Kano, Yoshinobu; Baumgartner, William A.; McCrohon, Luke; Ananiadou, Sophia; Cohen, K. Bretonnel; Hunter, Lawrence; Tsujii, Jun'ichi

2009-01-01

Summary: Due to the increasing number of text mining resources (tools and corpora) available to biologists, interoperability issues between these resources are becoming significant obstacles to using them effectively. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources. These resources, originally developed by different groups for a variety of domains, include many famous tools and corpora. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources. Availability: http://u-compare.org/ Contact: kano@is.s.u-tokyo.ac.jp PMID:19414535

KSC-2011-4005

NASA Image and Video Library

2011-05-25

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Frankie Martin

KSC-2011-3956

NASA Image and Video Library

2011-05-24

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-3955

NASA Image and Video Library

2011-05-24

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4151

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-3954

NASA Image and Video Library

2011-05-24

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4006

NASA Image and Video Library

2011-05-25

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Frankie Martin

KSC-2011-4003

NASA Image and Video Library

2011-05-25

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Frankie Martin

KSC-2011-4016

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-3957

NASA Image and Video Library

2011-05-24

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

Automatic target validation based on neuroscientific literature mining for tractography

PubMed Central

Vasques, Xavier; Richardet, Renaud; Hill, Sean L.; Slater, David; Chappelier, Jean-Cedric; Pralong, Etienne; Bloch, Jocelyne; Draganski, Bogdan; Cif, Laura

2015-01-01

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/. PMID:26074781

30 CFR 57.12033 - Hand-held electric tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Hand-held electric tools. 57.12033 Section 57.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Surface and Underground § 57.12033 Hand-held electric tools. Hand-held electric tools shall not be...

30 CFR 57.12033 - Hand-held electric tools.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Hand-held electric tools. 57.12033 Section 57.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Surface and Underground § 57.12033 Hand-held electric tools. Hand-held electric tools shall not be...

30 CFR 57.12033 - Hand-held electric tools.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Hand-held electric tools. 57.12033 Section 57.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Surface and Underground § 57.12033 Hand-held electric tools. Hand-held electric tools shall not be...

30 CFR 57.12033 - Hand-held electric tools.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Hand-held electric tools. 57.12033 Section 57.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Surface and Underground § 57.12033 Hand-held electric tools. Hand-held electric tools shall not be...

30 CFR 57.12033 - Hand-held electric tools.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Hand-held electric tools. 57.12033 Section 57.12033 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Surface and Underground § 57.12033 Hand-held electric tools. Hand-held electric tools shall not be...

Assimilating Text-Mining & Bio-Informatics Tools to Analyze Cellulase structures

NASA Astrophysics Data System (ADS)

Satyasree, K. P. N. V., Dr; Lalitha Kumari, B., Dr; Jyotsna Devi, K. S. N. V.; Choudri, S. M. Roy; Pratap Joshi, K.

2017-08-01

Text-mining is one of the best potential way of automatically extracting information from the huge biological literature. To exploit its prospective, the knowledge encrypted in the text should be converted to some semantic representation such as entities and relations, which could be analyzed by machines. But large-scale practical systems for this purpose are rare. But text mining could be helpful for generating or validating predictions. Cellulases have abundant applications in various industries. Cellulose degrading enzymes are cellulases and the same producing bacteria - Bacillus subtilis & fungus Pseudomonas putida were isolated from top soil of Guntur Dt. A.P. India. Absolute cultures were conserved on potato dextrose agar medium for molecular studies. In this paper, we presented how well the text mining concepts can be used to analyze cellulase producing bacteria and fungi, their comparative structures are also studied with the aid of well-establised, high quality standard bioinformatic tools such as Bioedit, Swissport, Protparam, EMBOSSwin with which a complete data on Cellulases like structure, constituents of the enzyme has been obtained.

Using software to predict occupational hearing loss in the mining industry.

PubMed

Azman, A S; Li, M; Thompson, J K

2016-01-01

Powerful mining systems typically generate high-level noise that can damage the hearing ability of miners. Engineering noise controls are the most desirable and effective control for overexposure to noise. However, the effects of these noise controls on the actual hearing status of workers are not easily measured. A tool that can provide guidance in assigning workers to jobs based on the noise levels to which they will be exposed is highly desirable. Therefore, the Pittsburgh Mining Research Division (PMRD) of the U.S. National Institute for Occupational Safety and Health (NIOSH) developed a tool to estimate in a systematic way the hearing loss due to occupational noise exposure and to evaluate the effectiveness of developed engineering controls. This computer program is based on the ISO 1999 standard and can be used to estimate the loss of hearing ability caused by occupational noise exposures. In this paper, the functionalities of this software are discussed and several case studies related to mining machinery are presented to demonstrate the functionalities of this software.

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

Arrangement for controlled engagement of the tools of a mining machine with a mine face

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

Blumenthal, G.; Bollmann, A.

1981-07-28

An arrangement for controlled engagement of the tools of a coal planer, with a mine face comprises a scraper conveyor, provided on its front face directed toward the mine face with a guide rail guiding the coal planer for reciprocation along the mine face and a mechanism for tilting the conveyor and the coal planer about a substantially horizontal axis. The tilting mechanism is connected to the rear face of the conveyor and extends in its entirety rearwardly of the rear face of the latter. The tilting mechanism comprises a guide linkage pivotally connected at its front end to themore » rear face of the scraper conveyor while its rear end portion forms a housing for a fluid operated cylinder and piston unit, the piston rod of which is connected to a connecting rod guided by the guide linkage for movement in longitudinal direction and having an upwardly extending front section pivotally connected at its upper free end to the rear face of the scraper conveyor. The fluid operated cylinder-and-piston unit is thus considerably spaced from the scraper conveyor and the material transported thereby and especially coal dust raised during transport of the mined coal by the conveyor, whereby maintenance of the tilting unit is reduced. The guide linkage, the connecting rod and the tilting unit are all in close vicinity to the sole of the mine gallery to leave a considerable free space between the arrangement and the roof of the mine gallery.« less

Transforming data into usable knowledge: the CIRC experience

NASA Astrophysics Data System (ADS)

Mote, P.; Lach, D.; Hartmann, H.; Abatzoglou, J. T.; Stevenson, J.

2017-12-01

NOAA's northwest RISA, the Climate Impacts Research Consortium, emphasizes the transformation of data into usable knowledge. This effort involves physical scientists (e.g., Abatzoglou) building web-based tools with climate and hydrologic data and model output, a team performing data mining to link crop loss claims to droughts, social scientists (eg., Lach, Hartmann) evaluating the effectiveness of such tools at communicating with end users, and two-way engagement with a wide variety of audiences who are interested in using and improving the tools. Unusual in this effort is the seamless integration across timescales past, present, and future; data mining; and the level of effort in evaluating the tools. We provide examples of agriculturally relevant climate variables (e.g. growing degree days, day of first fall freeze) and describe the iterative process of incorporating user feedback.

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.

Method to Select Technical Terms for Glossaries in Support of Joint Task Force Operations

DTIC Science & Technology

2012-01-01

have been prohibitively time-consuming. Instead, we identified two publicly available terminology extractor tools: TerMine (NaCTEM, 2011) and Alchemy ...and that from the latter, by high recall. The Alchemy approach contrasts with that used in TerMine in that Alchemy will process the text with...information categories, such as person, location, and organization, in addition to returning topic keywords. Output from both TerMine and Alchemy

LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes

PubMed Central

Cañada, Andres; Rabal, Obdulia; Oyarzabal, Julen; Valencia, Alfonso

2017-01-01

Abstract A considerable effort has been devoted to retrieve systematically information for genes and proteins as well as relationships between them. Despite the importance of chemical compounds and drugs as a central bio-entity in pharmacological and biological research, only a limited number of freely available chemical text-mining/search engine technologies are currently accessible. Here we present LimTox (Literature Mining for Toxicology), a web-based online biomedical search tool with special focus on adverse hepatobiliary reactions. It integrates a range of text mining, named entity recognition and information extraction components. LimTox relies on machine-learning, rule-based, pattern-based and term lookup strategies. This system processes scientific abstracts, a set of full text articles and medical agency assessment reports. Although the main focus of LimTox is on adverse liver events, it enables also basic searches for other organ level toxicity associations (nephrotoxicity, cardiotoxicity, thyrotoxicity and phospholipidosis). This tool supports specialized search queries for: chemical compounds/drugs, genes (with additional emphasis on key enzymes in drug metabolism, namely P450 cytochromes—CYPs) and biochemical liver markers. The LimTox website is free and open to all users and there is no login requirement. LimTox can be accessed at: http://limtox.bioinfo.cnio.es PMID:28531339

Development of Test Rig for Robotization of Mining Technological Processes - Oversized Rock Breaking Process Case

NASA Astrophysics Data System (ADS)

Pawel, Stefaniak; Jacek, Wodecki; Jakubiak, Janusz; Zimroz, Radoslaw

2017-12-01

Production chain (PCh) in underground copper ore mine consists of several subprocesses. From our perspective implementation of so called ZEPA approach (Zero Entry Production Area) might be very interesting [16]. In practice, it leads to automation/robotization of subprocesses in production area. In this paper was investigated a specific part of PCh i.e. a place when cyclic transport by LHDs is replaced with continuous transport by conveying system. Such place is called dumping point. The objective of dumping points with screen is primary classification of the material (into coarse and fine material) and breaking oversized rocks with hydraulic hammer. Current challenges for the underground mining include e.g. safety improvement as well as production optimization related to bottlenecks, stoppages and operational efficiency of the machines. As a first step, remote control of the hydraulic hammer has been introduced, which not only transferred the operator to safe workplace, but also allowed for more comfortable work environment and control over multiple technical objects by a single person. Today literature analysis shows that current mining industry around the world is oriented to automation and robotization of mining processes and reveals technological readiness for 4th industrial revolution. The paper is focused on preliminary analysis of possibilities for the use of the robotic system to rock-breaking process. Prototype test rig has been proposed and experimental works have been carried out. Automatic algorithms for detection of oversized rocks, crushing them as well as sweeping and loosening of material have been formulated. Obviously many simplifications have been assumed. Some near future works have been proposed.

Developing a Web-Based Ppgis, as AN Environmental Reporting Service

NASA Astrophysics Data System (ADS)

Ranjbar Nooshery, N.; Taleai, M.; Kazemi, R.; Ebadi, K.

2017-09-01

Today municipalities are searching for new tools to empower locals for changing the future of their own areas by increasing their participation in different levels of urban planning. These tools should involve the community in planning process using participatory approaches instead of long traditional top-down planning models and help municipalities to obtain proper insight about major problems of urban neighborhoods from the residents' point of view. In this matter, public participation GIS (PPGIS) which enables citizens to record and following up their feeling and spatial knowledge regarding problems of the city in the form of maps have been introduced. In this research, a tool entitled CAER (Collecting & Analyzing of Environmental Reports) is developed. In the first step, a software framework based on Web-GIS tool, called EPGIS (Environmental Participatory GIS) has been designed to support public participation in reporting urban environmental problems and to facilitate data flow between citizens and municipality. A web-based cartography tool was employed for geo-visualization and dissemination of map-based reports. In the second step of CAER, a subsystem is developed based on SOLAP (Spatial On-Line Analytical Processing), as a data mining tools to elicit the local knowledge facilitating bottom-up urban planning practices and to help urban managers to find hidden relations among the recorded reports. This system is implemented in a case study area in Boston, Massachusetts and its usability was evaluated. The CAER should be considered as bottom-up planning tools to collect people's problems and views about their neighborhood and transmits them to the city officials. It also helps urban planners to find solutions for better management from citizen's viewpoint and gives them this chance to develop good plans to the neighborhoods that should be satisfied the citizens.

Alkemio: association of chemicals with biomedical topics by text and data mining.

PubMed

Gijón-Correas, José A; Andrade-Navarro, Miguel A; Fontaine, Jean F

2014-07-01

The PubMed® database of biomedical citations allows the retrieval of scientific articles studying the function of chemicals in biology and medicine. Mining millions of available citations to search reported associations between chemicals and topics of interest would require substantial human time. We have implemented the Alkemio text mining web tool and SOAP web service to help in this task. The tool uses biomedical articles discussing chemicals (including drugs), predicts their relatedness to the query topic with a naïve Bayesian classifier and ranks all chemicals by P-values computed from random simulations. Benchmarks on seven human pathways showed good retrieval performance (areas under the receiver operating characteristic curves ranged from 73.6 to 94.5%). Comparison with existing tools to retrieve chemicals associated to eight diseases showed the higher precision and recall of Alkemio when considering the top 10 candidate chemicals. Alkemio is a high performing web tool ranking chemicals for any biomedical topics and it is free to non-commercial users. http://cbdm.mdc-berlin.de/∼medlineranker/cms/alkemio. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Process mining is an underutilized clinical research tool in transfusion medicine.

PubMed

Quinn, Jason G; Conrad, David M; Cheng, Calvino K

2017-03-01

To understand inventory performance, transfusion services commonly use key performance indicators (KPIs) as summary descriptors of inventory efficiency that are graphed, trended, and used to benchmark institutions. Here, we summarize current limitations in KPI-based evaluation of blood bank inventory efficiency and propose process mining as an ideal methodology for application to inventory management research to improve inventory flows and performance. The transit of a blood product from inventory receipt to final disposition is complex and relates to many internal and external influences, and KPIs may be inadequate to fully understand the complexity of the blood supply chain and how units interact with its processes. Process mining lends itself well to analysis of blood bank inventories, and modern laboratory information systems can track nearly all of the complex processes that occur in the blood bank. Process mining is an analytical tool already used in other industries and can be applied to blood bank inventory management and research through laboratory information systems data using commercial applications. Although the current understanding of real blood bank inventories is value-centric through KPIs, it potentially can be understood from a process-centric lens using process mining. © 2017 AABB.

RESPIROMETRY AS A TOOL TO DETERMINE METAL TOXICITY IN A SULFATE REDUCING BACTERIAL CULTURE

EPA Science Inventory

A novel method under development for treatment of acid mine drainage waste uses biologically- generated hydrogen sulfide (H2S) to precipitate the metals in acid mine drainage (principally zinc, copper, aluminum, nickel, cadmium, arsenic, manganese, iron, and cobalt). The insolub...

Numerical Modeling Tools for the Prediction of Solution Migration Applicable to Mining Site

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

Martell, M.; Vaughn, P.

1999-01-06

Mining has always had an important influence on cultures and traditions of communities around the globe and throughout history. Today, because mining legislation places heavy emphasis on environmental protection, there is great interest in having a comprehensive understanding of ancient mining and mining sites. Multi-disciplinary approaches (i.e., Pb isotopes as tracers) are being used to explore the distribution of metals in natural environments. Another successful approach is to model solution migration numerically. A proven method to simulate solution migration in natural rock salt has been applied to project through time for 10,000 years the system performance and solution concentrations surroundingmore » a proposed nuclear waste repository. This capability is readily adaptable to simulate solution migration around mining.« less

Mining Deployment Optimization

NASA Astrophysics Data System (ADS)

Čech, Jozef

2016-09-01

The deployment problem, researched primarily in the military sector, is emerging in some other industries, mining included. The principal decision is how to deploy some activities in space and time to achieve desired outcome while complying with certain requirements or limits. Requirements and limits are on the side constraints, while minimizing costs or maximizing some benefits are on the side of objectives. A model with application to mining of polymetallic deposit is presented. To obtain quick and immediate decision solutions for a mining engineer with experimental possibilities is the main intention of a computer-based tool. The task is to determine strategic deployment of mining activities on a deposit, meeting planned output from the mine and at the same time complying with limited reserves and haulage capacities. Priorities and benefits can be formulated by the planner.

Bats, cyanide, and gold mining

USGS Publications Warehouse

Clark, Donald R.

1991-01-01

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

Solutions Network Formulation Report. Landsat Data Continuity Mission Simulated Data Products for Bureau of Land Management and Environmental Protection Agency Abandoned Mine Lands Decision Support

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

Presently, the BLM (Bureau of Land Management) has identified a multitude of abandoned mine sites in primarily Western states for cleanup. These sites are prioritized and appropriate cleanup has been called in to reclaim the sites. The task is great in needing considerable amounts of agency resources. For instance, in Colorado alone there exists an estimated 23,000 abandoned mines. The problem is not limited to Colorado or to the United States. Cooperation for reclamation is sought at local, state, and federal agency level to aid in identification, inventory, and cleanup efforts. Dangers posed by abandoned mines are recognized widely and will tend to increase with time because some of these areas are increasingly used for recreation and, in some cases, have been or are in the process of development. In some cases, mines are often vandalized once they are closed. The perpetrators leave them open, so others can then access the mines without realizing the danger posed. Abandoned mine workings often fill with water or oxygen-deficient air and dangerous gases following mining. If the workings are accidentally entered into, water or bad air can prove fatal to those underground. Moreover, mine residue drainage negatively impacts the local watershed ecology. Some of the major hazards that might be monitored by higher-resolution satellites include acid mine drainage, clogged streams, impoundments, slides, piles, embankments, hazardous equipment or facilities, surface burning, smoke from underground fires, and mine openings.

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.

Australia unlocks her uranium reserves. [Will develop deposits in Northern Territories

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

Scott, W.E.

1977-11-01

The economic implications of Australia's move to permit the development of uranium mining and to resume exporting uranium have led to forecasts that range from pessimism over unseen factors to an optimistic estimate of $A20 billion and 500,000 jobs. Direct benefits will go to those involved in road construction, mining equipment, and construction camps. The goverment plan calls for mining operations and yellowcake exports from four major uranium mines by 1985. An overview is given of the development plan, which emphasizes an orderly procedure rather than exploitation and excessive competition. The uranium industry is viewed as a stable long-term suppliermore » for international trade. Customers will be required to submit to international Atomic Energy Agency inspection and must guarantee to limit their uranium use to peaceful projects. (DCK)« less

Coal companies hope to receive carbon credits for methane reductions

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

NONE

2007-09-30

Each year, underground coal mining in the USA liberates 2.4 million tonnes of coal mine methane (CMM), of which less than 30% is recovered and used. One barrier to CMM recovery is cost. Drainage, collection, and utilization systems are complex and expensive to install. Two coal mines have improved the cost equation, however, by signing on to earn money for CMM emissions they are keeping out of the atmosphere. Jim Walter Resources and PinnOak Resources have joined a voluntary greenhouse gas reduction trading program called the Chicago Climate Exchange (CCX) to turn their avoided emissions into carbon credits. The examplemore » they set may encourage other coal mining companies to follow suit, and may bring new projects on the line that would otherwise have not gone forward. 2 refs., 1 fig.« less

Text Mining for Adverse Drug Events: the Promise, Challenges, and State of the Art

PubMed Central

Harpaz, Rave; Callahan, Alison; Tamang, Suzanne; Low, Yen; Odgers, David; Finlayson, Sam; Jung, Kenneth; LePendu, Paea; Shah, Nigam H.

2014-01-01

Text mining is the computational process of extracting meaningful information from large amounts of unstructured text. Text mining is emerging as a tool to leverage underutilized data sources that can improve pharmacovigilance, including the objective of adverse drug event detection and assessment. This article provides an overview of recent advances in pharmacovigilance driven by the application of text mining, and discusses several data sources—such as biomedical literature, clinical narratives, product labeling, social media, and Web search logs—that are amenable to text-mining for pharmacovigilance. Given the state of the art, it appears text mining can be applied to extract useful ADE-related information from multiple textual sources. Nonetheless, further research is required to address remaining technical challenges associated with the text mining methodologies, and to conclusively determine the relative contribution of each textual source to improving pharmacovigilance. PMID:25151493

Development of ergonomics audits for bagging, haul truck and maintenance and repair operations in mining.

PubMed

Dempsey, Patrick G; Pollard, Jonisha; Porter, William L; Mayton, Alan; Heberger, John R; Gallagher, Sean; Reardon, Leanna; Drury, Colin G

2017-12-01

The development and testing of ergonomics and safety audits for small and bulk bag filling, haul truck and maintenance and repair operations in coal preparation and mineral processing plants found at surface mine sites is described. The content for the audits was derived from diverse sources of information on ergonomics and safety deficiencies including: analysis of injury, illness and fatality data and reports; task analysis; empirical laboratory studies of particular tasks; field studies and observations at mine sites; and maintenance records. These diverse sources of information were utilised to establish construct validity of the modular audits that were developed for use by mine safety personnel. User and interrater reliability testing was carried out prior to finalising the audits. The audits can be implemented using downloadable paper versions or with a free mobile NIOSH-developed Android application called ErgoMine. Practitioner Summary: The methodology used to develop ergonomics audits for three types of mining operations is described. Various sources of audit content are compared and contrasted to serve as a guide for developing ergonomics audits for other occupational contexts.

Monitoring Metal Pollution Levels in Mine Wastes around a Coal Mine Site Using GIS

NASA Astrophysics Data System (ADS)

Sanliyuksel Yucel, D.; Yucel, M. A.; Ileri, B.

2017-11-01

In this case study, metal pollution levels in mine wastes at a coal mine site in Etili coal mine (Can coal basin, NW Turkey) are evaluated using geographical information system (GIS) tools. Etili coal mine was operated since the 1980s as an open pit. Acid mine drainage is the main environmental problem around the coal mine. The main environmental contamination source is mine wastes stored around the mine site. Mine wastes were dumped over an extensive area along the riverbeds, and are now abandoned. Mine waste samples were homogenously taken at 10 locations within the sampling area of 102.33 ha. The paste pH and electrical conductivity values of mine wastes ranged from 2.87 to 4.17 and 432 to 2430 μS/cm, respectively. Maximum Al, Fe, Mn, Pb, Zn and Ni concentrations of wastes were measured as 109300, 70600, 309.86, 115.2, 38 and 5.3 mg/kg, respectively. The Al, Fe and Pb concentrations of mine wastes are higher than world surface rock average values. The geochemical analysis results from the study area were presented in the form of maps. The GIS based environmental database will serve as a reference study for our future work.

Data mining for health executive decision support: an imperative with a daunting future!

PubMed Central

Glover, Saundra; Rivers, Patrick A; Asoh, Derek A; Piper, Crystal N; Murph, Keva

2010-01-01

Summary Data mining is highly profiled. It has the potential to enhance executive information systems. Such enhancement would mean better decision-making by management, which in turn would mean better services for customers. While the future of data mining as technology should be exciting, some are worried about privacy concerns, which make the future of data mining daunting. This paper examines why data mining is highly profiled – the imperative toward data mining, data mining models and processes. Additionally, the paper examines some of the benefits and challenges of using data mining processes within the health-care arena. We cast the future of data mining by highlighting two of the many data mining tools available – one commercial and one freely available. Subsequently, we discuss a number of social and technical factors that may thwart the extensive deployment of data mining, especially when the intent is to know more about the people that organizations have to serve and cast a view of what the future holds for data mining. This component is especially important when attempting to determine the longevity of data mining within health-care organizations. It is hoped that our discussions would be useful to organizations as they engage data mining, strategies for executive information systems and information policy issues. PMID:20150610

Realizing Modeling and Mapping tools to Study the Upsurge of Noise Pollution as a Result of Open-Cast Mining and Transportation Activities

PubMed Central

Lokhande, Satish K.; Jain, Mohindra C.; Dhawale, Satyajeet A.; Gautam, Rakesh; Bodhe, Ghanshyam L.

2018-01-01

Introduction: In open-cast mines, noise pollution has become a serious concern due to the extreme use of heavy earth moving machinery (HEMM). Materials and Methods: This study is focused to measure and assess the effects of the existing noise levels of major operational mines in the Keonjhar, Sundergadh, and Mayurbhanj districts of Odisha, India. The transportation noise levels were also considered in this study, which was predicted using the modified Federal Highway Administration (FHWA) model. Result and Discussion: It was observed that noise induced by HEMM such as rock breakers, jackhammers, dumpers, and excavators, blasting noise in the mining terrain, as well as associated transportation noise became a major source of annoyance to the habitants living in proximity to the mines. The noise produced by mechanized mining operations was observed between 74.3 and 115.2 dB(A), and its impact on residential areas was observed between 49.4 and 58.9 dB(A). In addition, the noise contour maps of sound level dispersion were demonstrated with the utilization of advanced noise prediction software tools for better understanding. Conclusion: Finally, the predicted values at residential zone and traffic noise are correlated with observed values, and the coefficient of determination, R2, was calculated to be 0.6891 and 0.5967, respectively. PMID:29676297

The Process of People Gold Mining in Paningkaban Village Banyumas Indonesia

NASA Astrophysics Data System (ADS)

Muslihudin; Bambang, Azis Nur; Hendarto, Eko; Putranto, Thomas Triadi

2018-02-01

Gold mining in Paningkaban Banyumas conducted by the community is called the People gold mining. At the beginning, many miners from outside the region have involved and transferred of method, technic and knowledge about gold mining to local people. The aim of the study is to identify the existing process of public gold mining. The method of the study is qualitative by using observation and interview. The result showed that the mining process are: 1. Determining the location of mining well; in this determination there are two references; rational and intuition 2. Mining; at this stage, a deep well is drawn about 50-100 meters that leads vertically and horizontally. It is the most high-risk stage because of work accidents that occurred and potentially environment destruction. 3. Pulverization; this stage is classified as the lowest level of difficulty and risk, therefore in this work many woman included. 4. Rolling; in this stage involves enough technology, electrical mechanic and energy with the dynamo and using mercury that potentially contaminate environment. 5. Filtering; this stage is a quite risky because the workers contact directly with mercury. 6. Burning; is the shortest process to separate mercury with gold grains. 7. Sales to local buyer guided by the international gold market in every Thursday.

Microbial stratification in low pH oxic and suboxic macroscopic growths along an acid mine drainage

PubMed Central

Méndez-García, Celia; Mesa, Victoria; Sprenger, Richard R; Richter, Michael; Diez, María Suárez; Solano, Jennifer; Bargiela, Rafael; Golyshina, Olga V; Manteca, Ángel; Ramos, Juan Luis; Gallego, José R; Llorente, Irene; Martins dos Santos, Vitor AP; Jensen, Ole N; Peláez, Ana I; Sánchez, Jesús; Ferrer, Manuel

2014-01-01

Macroscopic growths at geographically separated acid mine drainages (AMDs) exhibit distinct populations. Yet, local heterogeneities are poorly understood. To gain novel mechanistic insights into this, we used OMICs tools to profile microbial populations coexisting in a single pyrite gallery AMD (pH ∼2) in three distinct compartments: two from a stratified streamer (uppermost oxic and lowermost anoxic sediment-attached strata) and one from a submerged anoxic non-stratified mat biofilm. The communities colonising pyrite and those in the mature formations appear to be populated by the greatest diversity of bacteria and archaea (including ‘ARMAN' (archaeal Richmond Mine acidophilic nano-organisms)-related), as compared with the known AMD, with ∼44.9% unclassified sequences. We propose that the thick polymeric matrix may provide a safety shield against the prevailing extreme condition and also a massive carbon source, enabling non-typical acidophiles to develop more easily. Only 1 of 39 species were shared, suggesting a high metabolic heterogeneity in local microenvironments, defined by the O2 concentration, spatial location and biofilm architecture. The suboxic mats, compositionally most similar to each other, are more diverse and active for S, CO2, CH4, fatty acid and lipopolysaccharide metabolism. The oxic stratum of the streamer, displaying a higher diversity of the so-called ‘ARMAN'-related Euryarchaeota, shows a higher expression level of proteins involved in signal transduction, cell growth and N, H2, Fe, aromatic amino acids, sphingolipid and peptidoglycan metabolism. Our study is the first to highlight profound taxonomic and functional shifts in single AMD formations, as well as new microbial species and the importance of H2 in acidic suboxic macroscopic growths. PMID:24430486

Characterizing Ground-Water Flow Paths in High-Altitude Fractured Rock Settings Impacted by Mining Activities

NASA Astrophysics Data System (ADS)

Wireman, M.; Williams, D.

2003-12-01

The Rocky Mountains of the western USA have tens of thousands of abandoned, inactive and active precious-metal(gold,silver,copper)mine sites. Most of these sites occur in fractured rock hydrogeologic settings. Mining activities often resulted in mobilization and transport of associated heavy metals (zinc,cadmium,lead) which pose a significant threat to aquatic communities in mountain streams.Transport of heavy metals from mine related sources (waste rock piles,tailings impoudments,underground workings, mine pits)can occur along numerous hydrological pathways including complex fracture controlled ground-water pathways. Since 1991, the United States Environmental Protection Agency, the Colorado Division of Minerals and Geology and the University of Colorado (INSTAAR)have been conducting applied hydrologic research at the Mary Murphy underground mine. The mine is in the Chalk Creek mining district which is located on the southwestern flanks of the Mount Princeton Batholith, a Tertiary age intrusive comprised primarily of quartz monzonite.The Mount Princeton batholith comprises a large portion of the southern part of the Collegiate Range west of Buena Vista in Chaffee County, CO. Chalk Creek and its 14 tributaries drain about 24,900 hectares of the eastern slopes of the Range including the mining district. Within the mining district, ground-water flow is controlled by the distribution, orientation and permeability of discontinuities within the bedrock. Important discontinuities include faults, joints and weathered zones. Local and intermediate flow systems are perturbed by extensive underground excavations associated with mining (adits, shafts, stopes, drifts,, etc.). During the past 12 years numerous hydrological investigations have been completed. The investigations have been focused on developing tools for characterizing ground-water flow and contaminant transport in the vicinity of hard-rock mines in fractured-rock settings. In addition, the results from these investigations have been used to develop a sound conceptual model of ground-water flow and transport of heavy metals from the mine workings to Chalk Creek. Ground-water tracing techniques (using organic, fluorescent dyes) have been successfully used to delineate ground-water flow paths. Surface-water tracing techniques have been used to acquire very accurate stream flow measuements and to identify ground-water inflow zones to streams. Stable (O18/D)and radioactive (tritium,sulphur 35) isotope anlysis of waters flowing into and out of underground workings have proved useful for conducting end member mixing analysis to determine which inflows and outflows are most significant with respect to metals loading. Hydrogeologic mapping, inverse geochemical modeling (using MINTEQAK code)and helium 3 analysis of ground water have also proven to useful tools. These tools, used in combination have provided multiple lines of evidence regarding the nature, timing and magnitude of ground-water inflow into underground mine workings and the distribution and types of hydrologic pathways that transport metals from the underground workings to Chalk Creek. This paper presents the results of some of the more important hydrologic investigations completed at the site and a conceptual model of ground-water flow in fractured rock settings that have been impacted by underground mining activites.

Naica Mine, Chihuahua, Mexico

NASA Image and Video Library

2007-10-02

The Naica mine in Chihuahua, Mexico, with its enormous gypsum crystals, may well be called the "Queen of the Giant Crystals localities." Though the Naica mine is no show mine, but still a working lead-zinc mine hosted in layered limestones, the first of several crystal caves was discovered in 1910. This "Cave of the Swords" contained extraordinary large sword-like selenite (gypsum) crystals up to 2 m long. In 2000 another crystal cave system was discovered at 300 m depth, even more spectacular than the original cave. Inside were free growing gypsum crystals up to 12 m long and 2 m in diameter. The ASTER image uses SWIR bands 4, 6, and 8 in RGB. Limestone is displayed in yellow-green colors, vegetation is red. The image was acquired February 16, 2004, covers an area of 26 x 23.5 km, and is located near 27.8 degrees north latitude, 105.5 degrees west longitude. The photo of crystals was taken from: http://www.thatcrystalsite.com/. http://photojournal.jpl.nasa.gov/catalog/PIA10615

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

PubMed Central

Collier, Nigel

2012-01-01

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

Student Evaluation of CALL Tools during the Design Process

ERIC Educational Resources Information Center

Nesbitt, Dallas

2013-01-01

This article discusses the comparative effectiveness of student input at different times during the design of CALL tools for learning kanji, the Japanese characters of Chinese origin. The CALL software "package" consisted of tools to facilitate the writing, reading and practising of kanji characters in context. A pre-design questionnaire…

KSC-2011-4155

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4152

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. hirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4141

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition held at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4160

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4004

NASA Image and Video Library

2011-05-25

CAPE CANAVERAL, Fla. -- University students prepare for NASA's second annual Lunabotics Mining Competition inside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Frankie Martin

KSC-2011-4158

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4159

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4153

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4171

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, participants applaud the winning team of the competition during the NASA's second annual Lunabotics Mining Competition award ceremony. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4164

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, university students take part in an award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4142

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition held at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4013

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- University students gather for the opening ceremony of NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-4169

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, Kennedy Center Director Bob Cabana speaks to university students at the award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4146

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition held at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4143

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition held at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4163

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, university students take part in an award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4140

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- University students make final preparations for NASA's second annual Lunabotics Mining Competition held at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

PubMed

Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

2007-03-15

Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

MetalS(3), a database-mining tool for the identification of structurally similar metal sites.

PubMed

Valasatava, Yana; Rosato, Antonio; Cavallaro, Gabriele; Andreini, Claudia

2014-08-01

We have developed a database search tool to identify metal sites having structural similarity to a query metal site structure within the MetalPDB database of minimal functional sites (MFSs) contained in metal-binding biological macromolecules. MFSs describe the local environment around the metal(s) independently of the larger context of the macromolecular structure. Such a local environment has a determinant role in tuning the chemical reactivity of the metal, ultimately contributing to the functional properties of the whole system. The database search tool, which we called MetalS(3) (Metal Sites Similarity Search), can be accessed through a Web interface at http://metalweb.cerm.unifi.it/tools/metals3/ . MetalS(3) uses a suitably adapted version of an algorithm that we previously developed to systematically compare the structure of the query metal site with each MFS in MetalPDB. For each MFS, the best superposition is kept. All these superpositions are then ranked according to the MetalS(3) scoring function and are presented to the user in tabular form. The user can interact with the output Web page to visualize the structural alignment or the sequence alignment derived from it. Options to filter the results are available. Test calculations show that the MetalS(3) output correlates well with expectations from protein homology considerations. Furthermore, we describe some usage scenarios that highlight the usefulness of MetalS(3) to obtain mechanistic and functional hints regardless of homology.

Treatment of iron(II)-rich acid mine water with limestone and oxygen.

PubMed

Mohajane, G B; Maree, J P; Panichev, N

2014-01-01

The main components of acid mine water are free acid, sulphate, and Fe²⁺. Limestone is the most cost-effective alkali that can be used for neutralization. The purpose of this investigation was to identify conditions where Fe²⁺ is removed with limestone and simultaneously oxidized with oxygen to Fe³⁺, in a polyvinyl chloride pipe under pressure. Gypsum scaling is prevented by passing rubber balls through the pipe of the so-called Oxygen-Pipe-Neutralization (OPeN) process pilot plant. Two synthetic waters were treated: (A) acid mine water containing 123 mg L⁻¹ Fe²⁺ representing gold mine water, and (B) acid mine water containing 6,032 mg L⁻¹ Fe²⁺ representing coal mine water. Batch studies were carried out in a pipe reactor and showed that the rate of Fe²⁺ oxidation depended on the Fe²⁺ concentration, oxygen pressure, amount of recycled sludge, limestone dosage and the mixing rate. Continuous studies in an OPeN process pilot plant resulted in 100% removal of total acidity from synthetic coal mine water and a 98% removal from synthetic gold mine water. Fe²⁺ was removed completely as precipitated Fe(OH)₃ from both synthetic coal and gold mine water at around pH 7 at 200 and 100 kPa oxygen pressure, respectively.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

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

NASA Astrophysics Data System (ADS)

Jordan, Gyozo

2009-07-01

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

Landscape management in an area affected by surface brown coal mining

NASA Astrophysics Data System (ADS)

Vráblíková, J.; Wildová, E.; Vráblík, P.; Blažková, M.

2017-10-01

The contribution summarizes results of a project concentrated on landscape management of an area affected by brown coal mining located in northern Bohemia (The Most basin) focusing on restoration and reclamation processes. It describes in particular the shares of individual types of reclamations in the area of interest. A strategic document that also supports landscape restoration in anthropogenically burdened regions was written within the project called “Restart” and the second part of the contribution is focused on its chapters which address this issue.

Mutation extraction tools can be combined for robust recognition of genetic variants in the literature

PubMed Central

Jimeno Yepes, Antonio; Verspoor, Karin

2014-01-01

As the cost of genomic sequencing continues to fall, the amount of data being collected and studied for the purpose of understanding the genetic basis of disease is increasing dramatically. Much of the source information relevant to such efforts is available only from unstructured sources such as the scientific literature, and significant resources are expended in manually curating and structuring the information in the literature. As such, there have been a number of systems developed to target automatic extraction of mutations and other genetic variation from the literature using text mining tools. We have performed a broad survey of the existing publicly available tools for extraction of genetic variants from the scientific literature. We consider not just one tool but a number of different tools, individually and in combination, and apply the tools in two scenarios. First, they are compared in an intrinsic evaluation context, where the tools are tested for their ability to identify specific mentions of genetic variants in a corpus of manually annotated papers, the Variome corpus. Second, they are compared in an extrinsic evaluation context based on our previous study of text mining support for curation of the COSMIC and InSiGHT databases. Our results demonstrate that no single tool covers the full range of genetic variants mentioned in the literature. Rather, several tools have complementary coverage and can be used together effectively. In the intrinsic evaluation on the Variome corpus, the combined performance is above 0.95 in F-measure, while in the extrinsic evaluation the combined recall performance is above 0.71 for COSMIC and above 0.62 for InSiGHT, a substantial improvement over the performance of any individual tool. Based on the analysis of these results, we suggest several directions for the improvement of text mining tools for genetic variant extraction from the literature. PMID:25285203

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.

From data mining rules to medical logical modules and medical advices.

PubMed

Gomoi, Valentin; Vida, Mihaela; Robu, Raul; Stoicu-Tivadar, Vasile; Bernad, Elena; Lupşe, Oana

2013-01-01

Using data mining in collaboration with Clinical Decision Support Systems adds new knowledge as support for medical diagnosis. The current work presents a tool which translates data mining rules supporting generation of medical advices to Arden Syntax formalism. The developed system was tested with data related to 2326 births that took place in 2010 at the Bega Obstetrics - Gynaecology Hospital, Timişoara. Based on processing these data, 14 medical rules regarding the Apgar score were generated and then translated in Arden Syntax language.

Enhanced Product Generation at NASA Data Centers Through Grid Technology

NASA Technical Reports Server (NTRS)

Barkstrom, Bruce R.; Hinke, Thomas H.; Gavali, Shradha; Seufzer, William J.

2003-01-01

This paper describes how grid technology can support the ability of NASA data centers to provide customized data products. A combination of grid technology and commodity processors are proposed to provide the bandwidth necessary to perform customized processing of data, with customized data subsetting providing the initial example. This customized subsetting engine can be used to support a new type of subsetting, called phenomena-based subsetting, where data is subsetted based on its association with some phenomena, such as mesoscale convective systems or hurricanes. This concept is expanded to allow the phenomena to be detected in one type of data, with the subsetting requirements transmitted to the subsetting engine to subset a different type of data. The subsetting requirements are generated by a data mining system and transmitted to the subsetter in the form of an XML feature index that describes the spatial and temporal extent of the phenomena. For this work, a grid-based mining system called the Grid Miner is used to identify the phenomena and generate the feature index. This paper discusses the value of grid technology in facilitating the development of a high performance customized product processing and the coupling of a grid mining system to support phenomena-based subsetting.

LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes.

PubMed

Cañada, Andres; Capella-Gutierrez, Salvador; Rabal, Obdulia; Oyarzabal, Julen; Valencia, Alfonso; Krallinger, Martin

2017-07-03

A considerable effort has been devoted to retrieve systematically information for genes and proteins as well as relationships between them. Despite the importance of chemical compounds and drugs as a central bio-entity in pharmacological and biological research, only a limited number of freely available chemical text-mining/search engine technologies are currently accessible. Here we present LimTox (Literature Mining for Toxicology), a web-based online biomedical search tool with special focus on adverse hepatobiliary reactions. It integrates a range of text mining, named entity recognition and information extraction components. LimTox relies on machine-learning, rule-based, pattern-based and term lookup strategies. This system processes scientific abstracts, a set of full text articles and medical agency assessment reports. Although the main focus of LimTox is on adverse liver events, it enables also basic searches for other organ level toxicity associations (nephrotoxicity, cardiotoxicity, thyrotoxicity and phospholipidosis). This tool supports specialized search queries for: chemical compounds/drugs, genes (with additional emphasis on key enzymes in drug metabolism, namely P450 cytochromes-CYPs) and biochemical liver markers. The LimTox website is free and open to all users and there is no login requirement. LimTox can be accessed at: http://limtox.bioinfo.cnio.es. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multimedia Exploratory Data Analysis for Geospatial Data Mining: The Case for Augmented Seriation.

ERIC Educational Resources Information Center

Gluck, Myke

2001-01-01

Reviews the role of exploratory data analysis (EDA) for spatial data mining and presents a case study addressing environmental risk assessments in New York State to illustrate the feasibility and usability of augmenting seriation for spatial data analysis. Describes augmentation with multimedia tools to understand relationships among spatial,…

High levels of activity of bats at gold mining water bodies: implications for compliance with the International Cyanide Management Code.

PubMed

Griffiths, Stephen R; Donato, David B; Coulson, Graeme; Lumsden, Linda F

2014-06-01

Wildlife and livestock are known to visit and interact with tailings dam and other wastewater impoundments at gold mines. When cyanide concentrations within these water bodies exceed a critical toxicity threshold, significant cyanide-related mortality events can occur in wildlife. Highly mobile taxa such as birds are particularly susceptible to cyanide toxicosis. Nocturnally active bats have similar access to uncovered wastewater impoundments as birds; however, cyanide toxicosis risks to bats remain ambiguous. This study investigated activity of bats in the airspace above two water bodies at an Australian gold mine, to assess the extent to which bats use these water bodies and hence are at potential risk of exposure to cyanide. Bat activity was present on most nights sampled during the 16-month survey period, although it was highly variable across nights and months. Therefore, despite the artificial nature of wastewater impoundments at gold mines, these structures present attractive habitats to bats. As tailings slurry and supernatant pooling within the tailings dam were consistently well below the industry protective concentration limit of 50 mg/L weak acid dissociable (WAD) cyanide, wastewater solutions stored within the tailings dam posed a minimal risk of cyanide toxicosis for wildlife, including bats. This study showed that passively recorded bat echolocation call data provides evidence of the presence and relative activity of bats above water bodies at mine sites. Furthermore, echolocation buzz calls recorded in the airspace directly above water provide indirect evidence of foraging and/or drinking. Both echolocation monitoring and systematic sampling of cyanide concentration in open wastewater impoundments can be incorporated into a gold mine risk-assessment model in order to evaluate the risk of bat exposure to cyanide. In relation to risk minimisation management practices, the most effective mechanism for preventing cyanide toxicosis to wildlife, including bats, is capping the concentration of cyanide in tailings discharged to open impoundments at 50 mg/L WAD.

Using software to predict occupational hearing loss in the mining industry

PubMed Central

Azman, A.S.; Li, M.; Thompson, J.K.

2017-01-01

Powerful mining systems typically generate high-level noise that can damage the hearing ability of miners. Engineering noise controls are the most desirable and effective control for overexposure to noise. However, the effects of these noise controls on the actual hearing status of workers are not easily measured. A tool that can provide guidance in assigning workers to jobs based on the noise levels to which they will be exposed is highly desirable. Therefore, the Pittsburgh Mining Research Division (PMRD) of the U.S. National Institute for Occupational Safety and Health (NIOSH) developed a tool to estimate in a systematic way the hearing loss due to occupational noise exposure and to evaluate the effectiveness of developed engineering controls. This computer program is based on the ISO 1999 standard and can be used to estimate the loss of hearing ability caused by occupational noise exposures. In this paper, the functionalities of this software are discussed and several case studies related to mining machinery are presented to demonstrate the functionalities of this software. PMID:28596700

Can abstract screening workload be reduced using text mining? User experiences of the tool Rayyan.

PubMed

Olofsson, Hanna; Brolund, Agneta; Hellberg, Christel; Silverstein, Rebecca; Stenström, Karin; Österberg, Marie; Dagerhamn, Jessica

2017-09-01

One time-consuming aspect of conducting systematic reviews is the task of sifting through abstracts to identify relevant studies. One promising approach for reducing this burden uses text mining technology to identify those abstracts that are potentially most relevant for a project, allowing those abstracts to be screened first. To examine the effectiveness of the text mining functionality of the abstract screening tool Rayyan. User experiences were collected. Rayyan was used to screen abstracts for 6 reviews in 2015. After screening 25%, 50%, and 75% of the abstracts, the screeners logged the relevant references identified. A survey was sent to users. After screening half of the search result with Rayyan, 86% to 99% of the references deemed relevant to the study were identified. Of those studies included in the final reports, 96% to 100% were already identified in the first half of the screening process. Users rated Rayyan 4.5 out of 5. The text mining function in Rayyan successfully helped reviewers identify relevant studies early in the screening process. Copyright © 2017 John Wiley & Sons, Ltd.

PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.

PubMed

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/

PPInterFinder—a mining tool for extracting causal relations on human proteins from literature

PubMed Central

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein–protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder—a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. Database URL: http://www.biomining-bu.in/ppinterfinder/ PMID:23325628

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

pGenN, a Gene Normalization Tool for Plant Genes and Proteins in Scientific Literature

PubMed Central

Ding, Ruoyao; Arighi, Cecilia N.; Lee, Jung-Youn; Wu, Cathy H.; Vijay-Shanker, K.

2015-01-01

Background Automatically detecting gene/protein names in the literature and connecting them to databases records, also known as gene normalization, provides a means to structure the information buried in free-text literature. Gene normalization is critical for improving the coverage of annotation in the databases, and is an essential component of many text mining systems and database curation pipelines. Methods In this manuscript, we describe a gene normalization system specifically tailored for plant species, called pGenN (pivot-based Gene Normalization). The system consists of three steps: dictionary-based gene mention detection, species assignment, and intra species normalization. We have developed new heuristics to improve each of these phases. Results We evaluated the performance of pGenN on an in-house expertly annotated corpus consisting of 104 plant relevant abstracts. Our system achieved an F-value of 88.9% (Precision 90.9% and Recall 87.2%) on this corpus, outperforming state-of-art systems presented in BioCreative III. We have processed over 440,000 plant-related Medline abstracts using pGenN. The gene normalization results are stored in a local database for direct query from the pGenN web interface (proteininformationresource.org/pgenn/). The annotated literature corpus is also publicly available through the PIR text mining portal (proteininformationresource.org/iprolink/). PMID:26258475

Soil eco-physiological indicators from a coal mining area in El Bierzo District (Spain).

NASA Astrophysics Data System (ADS)

Díaz Puente, Fco. Javier; Mejuto Mendieta, Marcos; Cardona García, Ana Isabel; Rodríguez Gallego, Vergelina; García Álvarez, Avelino

2010-05-01

CIEMAT. Avda. Complutense, 22. 28040 Madrid. Spain. The El Bierzo carboniferous basin (León, N.W. of Spain) is placed in a tenth of the surface of this district, in the area called "Bierzo Alto". Coal has been mined in El Bierzo from the late XVIII century, having been intensely exploited during the XX century. The mining activity has left a heritage of withdrawed mining structures. Nowadays some mining activity remains in the area, and new exploitations based on open pit processes, cause the burial of natural soil with overlaying mine tailings. Characterization and study of the edaphic landscapes in the area is a necessary activity within the framework of its overall restoration planning, also providing fundamental information for the design and monitoring of waste coal recovery activities. For this work eight zones were chosen, representing the spatial variability within the upper basin of the Rodrigatos river, into the Bierzo Alto, including reference areas not affected by mining activities. In addition three mine tailings outside the area are included in this work to cover the variability of restoration processes. After a first study, based on physical, physico-chemical and chemical characteristics of soils, we have continued the study including some eco-physiological parameters. The objective of this work is to identify potential soil disruption, its extent and causes. Soil microbial activity is influenced by a wide set of soil characteristics. Eco-physiological parameters analysed in this work are: • Microbial Biomass carbon • Basal Respirometry • Maximum respiratory rate Microbial biomass carbon was analysed according the Substrate Induced Respirometry (SIR) method. Relational parameters such as metabolic quotient (CO2-C/Cmic) and the Cmic/Corg ratio have been obtained from these variables. Our results shown that soil microbial biomass carbon is strongly influenced by the water holding capacity (WHC) of the samples (R=0,895) as well as by organic matter (O.M.) content (R=0,801), in addition, WHC and O.M. are also strongly related (R=0,794), so O.M. seems to be the key variable in the soils studied. Recovery stage of the studied plots may be stablished with each of the mentioned parameters. All the correlations mentioned were significant at P<0.001 level. Maximum respiratory rate as well as Metabolic quotient data also allow to identify most stressed soils, corresponding with coal mine tailings in the Rodrigatos river basin. Results obtained for Cmic/Corg ratio show difficulties to be interpreted in the case of mine tailings. The practice of burying soils with coal mining debris has provided this new surface with relatively high inputs of organic carbon, in excess of this provided from fresh organic matter. In our study eco-physiological parameters are usefull tools in order to clasify the restoration level of mine tailings, specially those parameters having a high correlation with the organic matter content, Nevertheless some of those parameters then present some added difficulties to be interpreted that will be discussed in this work. Acknowledgement: We appreciate technical support in the field from Mr. Luis del Riego Celada, as well as the financial support from the Fundación Ciudad de la Energía.

Preference Mining Using Neighborhood Rough Set Model on Two Universes.

PubMed

Zeng, Kai

2016-01-01

Preference mining plays an important role in e-commerce and video websites for enhancing user satisfaction and loyalty. Some classical methods are not available for the cold-start problem when the user or the item is new. In this paper, we propose a new model, called parametric neighborhood rough set on two universes (NRSTU), to describe the user and item data structures. Furthermore, the neighborhood lower approximation operator is used for defining the preference rules. Then, we provide the means for recommending items to users by using these rules. Finally, we give an experimental example to show the details of NRSTU-based preference mining for cold-start problem. The parameters of the model are also discussed. The experimental results show that the proposed method presents an effective solution for preference mining. In particular, NRSTU improves the recommendation accuracy by about 19% compared to the traditional method.

Abundance of arbuscular mychorrizal fungi in rehabilitation area of nickel post-mining land of Sorowako, South Sulawesi

NASA Astrophysics Data System (ADS)

Akib, M. A.; Mustari, K.; Kuswinanti, T.; Syaiful, S. A.

2018-05-01

Acceleration management of land rehabilitation in nickel post-mining in Sorowako has been main attention of Vale Indonesia. This acceleration can be done by utilizing of natural resources, especially indigenous endomycorrhiza. Endomycorrhiza also called arbuscular mycorrhizal has got a lot of attention for its ability to form a mutualistic symbiosis with 80% - 96% of plant species. This study aims to determine the dominance of indigenous endomycorrhiza spores and its potential to accelerate the management of land rehabilitation post-mining of nickel, which is carried out in three stages; sampling rhizosphere, trapping spores, isolation and identification of the arbuscular mycorrhizal spores types. The results showed that the dominance of indigenous endomycorrhiza were Acalauspora sp (75.1%), Gigaspora sp (19.4%) and Glomus sp (5.6%). Research on the effectiveness of indigenous endomycorrhiza using Acalauspora sp in land rehabilitation of nickel post-mining is still ongoing.

A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

NASA Astrophysics Data System (ADS)

Uswatun Khasanah, Annisa; Harwati

2017-06-01

Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

Mining Large Scale Tandem Mass Spectrometry Data for Protein Modifications Using Spectral Libraries.

PubMed

Horlacher, Oliver; Lisacek, Frederique; Müller, Markus

2016-03-04

Experimental improvements in post-translational modification (PTM) detection by tandem mass spectrometry (MS/MS) has allowed the identification of vast numbers of PTMs. Open modification searches (OMSs) of MS/MS data, which do not require prior knowledge of the modifications present in the sample, further increased the diversity of detected PTMs. Despite much effort, there is still a lack of functional annotation of PTMs. One possibility to narrow the annotation gap is to mine MS/MS data deposited in public repositories and to correlate the PTM presence with biological meta-information attached to the data. Since the data volume can be quite substantial and contain tens of millions of MS/MS spectra, the data mining tools must be able to cope with big data. Here, we present two tools, Liberator and MzMod, which are built using the MzJava class library and the Apache Spark large scale computing framework. Liberator builds large MS/MS spectrum libraries, and MzMod searches them in an OMS mode. We applied these tools to a recently published set of 25 million spectra from 30 human tissues and present tissue specific PTMs. We also compared the results to the ones obtained with the OMS tool MODa and the search engine X!Tandem.

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

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Text mining for adverse drug events: the promise, challenges, and state of the art.

PubMed

Harpaz, Rave; Callahan, Alison; Tamang, Suzanne; Low, Yen; Odgers, David; Finlayson, Sam; Jung, Kenneth; LePendu, Paea; Shah, Nigam H

2014-10-01

Text mining is the computational process of extracting meaningful information from large amounts of unstructured text. It is emerging as a tool to leverage underutilized data sources that can improve pharmacovigilance, including the objective of adverse drug event (ADE) detection and assessment. This article provides an overview of recent advances in pharmacovigilance driven by the application of text mining, and discusses several data sources-such as biomedical literature, clinical narratives, product labeling, social media, and Web search logs-that are amenable to text mining for pharmacovigilance. Given the state of the art, it appears text mining can be applied to extract useful ADE-related information from multiple textual sources. Nonetheless, further research is required to address remaining technical challenges associated with the text mining methodologies, and to conclusively determine the relative contribution of each textual source to improving pharmacovigilance.

A Recommendation Algorithm for Automating Corollary Order Generation

PubMed Central

Klann, Jeffrey; Schadow, Gunther; McCoy, JM

2009-01-01

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards. PMID:20351875

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.

A recommendation algorithm for automating corollary order generation.

PubMed

Klann, Jeffrey; Schadow, Gunther; McCoy, J M

2009-11-14

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards.

Interpreter of maladies: redescription mining applied to biomedical data analysis.

PubMed

Waltman, Peter; Pearlman, Alex; Mishra, Bud

2006-04-01

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Pongamia pinnata inoculated with Bradyrhizobium liaoningense PZHK1 shows potential for phytoremediation of mine tailings.

PubMed

Yu, Xiumei; Li, Yangxin; Li, Yanmei; Xu, Chaohua; Cui, Yongliang; Xiang, Quanju; Gu, Yunfu; Zhao, Ke; Zhang, Xiaoping; Penttinen, Petri; Chen, Qiang

2017-02-01

Mine tailings contain high concentrations of metal contaminants and only little nutrients, making the tailings barren for decades after the mining has been terminated. Effective phytoremediation of mine tailings calls for deep-rooted, metal accumulating, and soil fertility increasing plants with tolerance against harsh environmental conditions. We assessed the potential of the biofuel leguminous tree Pongamia pinnata inoculated with plant growth promoting rhizobia to remediate iron-vanadium-titanium oxide (V-Ti magnetite) mine tailing soil by pot experiment and in situ remediation test. A metal tolerant rhizobia strain PZHK1 was isolated from the tailing soil and identified as Bradyrhizobium liaoningense by phylogenetic analysis. Inoculation with PZHK1 increased the growth of P. pinnata both in V-Ti magnetite mine tailings and in Ni-contaminated soil. Furthermore, inoculation increased the metal accumulation capacity and superoxide dismutase activity of P. pinnata. The concentrations of Ni accumulated by inoculated plants were higher than the hyperaccumulator threshold. Inoculated P. pinnata accumulated high concentration of Fe, far exceeding the upper limit (1000 mg kg -1 ) of Fe in plant tissue. In summary, P. pinnata-B. liaoningense PZHK1 symbiosis showed potential to be applied as an effective phytoremediation technology for mine tailings and to produce biofuel feedstock on the marginal land.

Reducing Mercury Pollution from Artisanal and Small-Scale Gold Mining

EPA Pesticide Factsheets

To reduce airborne mercury emissions from these Gold Shops, EPA and the Argonne National Laboratory (ANL) have partnered to design a low cost, easily constructible technology called the Gold Shop Mercury Capture System (MCS).

Occupational accidents in artisanal mining in Katanga, D.R.C.

PubMed

Elenge, Myriam; Leveque, Alain; De Brouwer, Christophe

2013-04-01

This study focuses on accidents in artisanal mining, to support policies improving miners' employability. Based on a questionnaire administered in November 2009 to a sample of 180 miners from the artisanal mining of LUPOTO, in the Province of Katanga, we explored significant trends between the accidents and their consequences and behavioral or sociological variables. During the 12 months preceding the study, 392 accidents occurred, affecting 72.2% of miners. Tools handling represents 51.5%, of the accidents' causes, followed by handling heavy loads (32.9%). Factors such as age, seniority or apprenticeship did not generate significant differences. Contusions were the most common injuries (50.2%), followed by wounds (44.4%). These injuries were located in upper limbs (50.5%) and in lower limbs (29.3%). 80.5% of miners were cared for by their colleagues and 50% of them could not work for more than 3 days. Physical sequelae were reported by 19% of the injured miners. Many surveys related to accidents in the area of artisanal mining report such high frequency. The unsuitability of tools to jobs to be done is usually raised as one of the major causes of accidents. The lack of differentiation of the tasks carried out in relation to age is another factor explaining the lack of protective effect of seniority as it minimizes the contribution of experience in the worker's safety. The apprenticeship reported is inadequate; it is rather a learning by doing than anything else. That is why it lacks protective effect. Low income combined with precariousness of artisanal mining are likely to explain the low level of work stoppages. Tools improvement associated with adequate training seem to be the basis of accident prevention. Availability of suitable medical care should improve artisanal miners' recovery after accidents.

KSC-2011-4166

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, Eric Reiners, manager with the Product Development and Global Technology Division of Caterpillar Inc., speaks to university students at the award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4156

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- University students wait their turn to compete in NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida taking place near the complex's Rocket Garden. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4014

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- Pat Simpkins, Kennedy Space Center engineering director talks to university students gathered for the opening ceremony of NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-4147

NASA Image and Video Library

2011-05-27

CAPE CANAVERAL, Fla. -- Outside the "Lunarena" at the Kennedy Space Center Visitor Complex in Florida, NASA astronaut John McBride (center) discusses the day's events with event leaders during NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4170

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, the Laurentian University Team from Ontario, accepts a check for its "lunabot," which came in first place at NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4015

NASA Image and Video Library

2011-05-26

CAPE CANAVERAL, Fla. -- Tana Utley, Caterpillar Company vice president and chief technology officer talks to university students gathered for the opening ceremony of NASA's second annual Lunabotics Mining Competition at the Kennedy Space Center Visitor Complex in Florida. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India will participate in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jim Grossmann

KSC-2011-4168

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, Bill Moore, Visitor Complex chief operating officer speaks to university students at the award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

KSC-2011-4165

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, Rob Mueller Kennedy's chief of the Surface Systems Office speaks to university students at the award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

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.

The status of the Callio Lab Underground Laboratory in the Pyhäsalmi mine

NASA Astrophysics Data System (ADS)

Joutsenvaara, Jari; Enqvist, Timo; Isoherranen, Ville; Jalas, Panu; Kutuniva, Johanna; Kuusiniemi, Pasi

2017-04-01

We present the structure and the latest technical characteristics of the Callio Lab, the new underground laboratory managing the scientific and other non-mining related operations in the Pyhäsalmi mine in Pyhäjärvi, Finland. The very deep laboratory hall space, called Lab 2 of Callio Lab, was finished in spring 2016 at the depth of 1 430 metres (4 100 m.w.e.). Callio Lab has also other easily accessible (by car or truck) halls for laboratory use, for example at the depths of 440 m, 600 m and 990 m. We also review the current and planned activities related to particle physics, applied sciences, industrial R&D and production.

Applications of multi-season hyperspectral remote sensing for acid mine water characterization and mapping of secondary iron minerals associated with acid mine drainage

NASA Astrophysics Data System (ADS)

Davies, Gwendolyn E.

Acid mine drainage (AMD) resulting from the oxidation of sulfides in mine waste is a major environmental issue facing the mining industry today. Open pit mines, tailings ponds, ore stockpiles, and waste rock dumps can all be significant sources of pollution, primarily heavy metals. These large mining-induced footprints are often located across vast geographic expanses and are difficult to access. With the continuing advancement of imaging satellites, remote sensing may provide a useful monitoring tool for pit lake water quality and the rapid assessment of abandoned mine sites. This study explored the applications of laboratory spectroscopy and multi-season hyperspectral remote sensing for environmental monitoring of mine waste environments. Laboratory spectral experiments were first performed on acid mine waters and synthetic ferric iron solutions to identify and isolate the unique spectral properties of mine waters. These spectral characterizations were then applied to airborne hyperspectral imagery for identification of poor water quality in AMD ponds at the Leviathan Mine Superfund site, CA. Finally, imagery varying in temporal and spatial resolutions were used to identify changes in mineralogy over weathering overburden piles and on dry AMD pond liner surfaces at the Leviathan Mine. Results show the utility of hyperspectral remote sensing for monitoring a diverse range of surfaces associated with AMD.

The risk of collapse in abandoned mine sites: the issue of data uncertainty

NASA Astrophysics Data System (ADS)

Longoni, Laura; Papini, Monica; Brambilla, Davide; Arosio, Diego; Zanzi, Luigi

2016-04-01

Ground collapses over abandoned underground mines constitute a new environmental risk in the world. The high risk associated with subsurface voids, together with lack of knowledge of the geometric and geomechanical features of mining areas, makes abandoned underground mines one of the current challenges for countries with a long mining history. In this study, a stability analysis of Montevecchia marl mine is performed in order to validate a general approach that takes into account the poor local information and the variability of the input data. The collapse risk was evaluated through a numerical approach that, starting with some simplifying assumptions, is able to provide an overview of the collapse probability. The final results is an easy-accessible-transparent summary graph that shows the collapse probability. This approach may be useful for public administrators called upon to manage this environmental risk. The approach tries to simplify this complex problem in order to achieve a roughly risk assessment, but, since it relies on just a small amount of information, any final user should be aware that a comprehensive and detailed risk scenario can be generated only through more exhaustive investigations.

Screening and prioritisation of chemical risks from metal mining operations, identifying exposure media of concern.

PubMed

Pan, Jilang; Oates, Christopher J; Ihlenfeld, Christian; Plant, Jane A; Voulvoulis, Nikolaos

2010-04-01

Metals have been central to the development of human civilisation from the Bronze Age to modern times, although in the past, metal mining and smelting have been the cause of serious environmental pollution with the potential to harm human health. Despite problems from artisanal mining in some developing countries, modern mining to Western standards now uses the best available mining technology combined with environmental monitoring, mitigation and remediation measures to limit emissions to the environment. This paper develops risk screening and prioritisation methods previously used for contaminated land on military and civilian sites and engineering systems for the analysis and prioritisation of chemical risks from modern metal mining operations. It uses hierarchical holographic modelling and multi-criteria decision making to analyse and prioritise the risks from potentially hazardous inorganic chemical substances released by mining operations. A case study of an active platinum group metals mine in South Africa is used to demonstrate the potential of the method. This risk-based methodology for identifying, filtering and ranking mining-related environmental and human health risks can be used to identify exposure media of greatest concern to inform risk management. It also provides a practical decision-making tool for mine acquisition and helps to communicate risk to all members of mining operation teams.

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing

EPA Science Inventory

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically a...

Using Data Mining for Predicting Relationships between Online Question Theme and Final Grade

ERIC Educational Resources Information Center

Abdous, M'hammed; He, Wu; Yen, Cherng-Jyh

2012-01-01

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students' learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped…

Application of Learning Analytics Using Clustering Data Mining for Students' Disposition Analysis

ERIC Educational Resources Information Center

Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay

2018-01-01

Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…

Myth Busting: Using Data Mining to Refute Link between Transfer Students and Retention Risk

ERIC Educational Resources Information Center

McAleer, Brenda; Szakas, Joseph S.

2010-01-01

In the past few years, universities have become much more involved in outcomes assessment. Outside of the classroom analysis of learning outcomes, an investigation is performed into the use of current data mining tools to assess the issue of student retention within the Computer Information Systems (CIS) department. Utilizing both a historical…

Use of amendments to restore ecosystem function to metal mining impacted sites; Tools to evaluate efficacy

USDA-ARS?s Scientific Manuscript database

There is a long history of using residuals based soil amendments for restoration of disturbed sites. More recently, this approach has been tested for use on metal contaminated mining sites. For these sites, amendment mixtures are targeted to reduce metal availability in situ as well as restore eco...

Mining Mathematics in Textbook Lessons

ERIC Educational Resources Information Center

Ronda, Erlina; Adler, Jill

2017-01-01

In this paper, we propose an analytic tool for describing the mathematics made available to learn in a "textbook lesson". The tool is an adaptation of the Mathematics Discourse in Instruction (MDI) analytic tool that we developed to analyze what is made available to learn in teachers' lessons. Our motivation to adapt the use of the MDI…

Web Usage Mining Analysis of Federated Search Tools for Egyptian Scholars

ERIC Educational Resources Information Center

Mohamed, Khaled A.; Hassan, Ahmed

2008-01-01

Purpose: This paper aims to examine the behaviour of the Egyptian scholars while accessing electronic resources through two federated search tools. The main purpose of this article is to provide guidance for federated search tool technicians and support teams about user issues, including the need for training. Design/methodology/approach: Log…

30 CFR 56.7050 - Tool and drill steel racks.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Tool and drill steel racks. 56.7050 Section 56.7050 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL... Jet Piercing Drilling § 56.7050 Tool and drill steel racks. Receptacles or racks shall be provided for...

New perspectives on a 140-year legacy of mining and abandoned mine cleanup in the San Juan Mountains, Colorado

USGS Publications Warehouse

Yager, Douglas B.; Fey, David L.; Chapin, Thomas; Johnson, Raymond H.

2016-01-01

The Gold King mine water release that occurred on 5 August 2015 near the historical mining community of Silverton, Colorado, highlights the environmental legacy that abandoned mines have on the environment. During reclamation efforts, a breach of collapsed workings at the Gold King mine sent 3 million gallons of acidic and metal-rich mine water into the upper Animas River, a tributary to the Colorado River basin. The Gold King mine is located in the scenic, western San Juan Mountains, a region renowned for its volcano-tectonic and gold-silver-base metal mineralization history. Prior to mining, acidic drainage from hydrothermally altered areas was a major source of metals and acidity to streams, and it continues to be so. In addition to abandoned hard rock metal mines, uranium mine waste poses a long-term storage and immobilization challenge in this area. Uranium resources are mined in the Colorado Plateau, which borders the San Juan Mountains on the west. Uranium processing and repository sites along the Animas River near Durango, Colorado, are a prime example of how the legacy of mining must be managed for the health and well-being of future generations. The San Juan Mountains are part of a geoenvironmental nexus where geology, mining, agriculture, recreation, and community issues converge. This trip will explore the geology, mining, and mine cleanup history in which a community-driven, watershed-based stakeholder process is an integral part. Research tools and historical data useful for understanding complex watersheds impacted by natural sources of metals and acidity overprinted by mining will also be discussed.

Horizontal hydraulic conductivity estimates for intact coal barriers between closed underground mines

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

Mccoy, K.J.; Donovan, J.J.; Leavitt, B.R.

2006-08-15

Unmined blocks of coal, called barriers, separate and restrict horizontal leakage between adjacent bituminous coal mines. Understanding the leakage rate across such barriers is important in planning mine closure and strongly affects recharge calculations for postmining flooding. This study presents upper-limit estimates for hydraulic conductivity (K) of intact barriers in two closed mines at moderate depth (75-300 m) in the Pittsburgh coal basin. The estimates are based on pumping rates from these mines for the years ranging from 1992 to 2000. The two mines do not approach the outcrop and are sufficiently deep that vertical infiltration is thought to bemore » negligible. Similarly, there are no saturated zones on the pumped mines' side of shared barriers with other mines, and therefore pumping is the only outflow. Virtually all of the pumping is attributed to leakage across or over the top of barriers shared with upgradient flooded mines. The length of shared barriers totals 24 km for the two mines, and the barriers range in thickness from 15 to 50 m. K values calculated independently for each of the 9 years of the pumping record ranged from 0.037 m/d to 0.18 m/d using an isotropic model of barrier flow. Using an anisotropic model for differential K in the face cleat (K{sub f}) and butt cleat (K{sub b}) directions, results range from 0.074 to 0.34 m/d for K{sub f} and from 0.022 to 0.099 m/d for K{sub b}.« less

The application of high-resolution mass spectrometry-based data-mining tools in tandem to metabolite profiling of a triple drug combination in humans.

PubMed

Xing, Jie; Zang, Meitong; Zhang, Haiying; Zhu, Mingshe

2015-10-15

Patients are usually exposed to multiple drugs, and metabolite profiling of each drug in complex biological matrices is a big challenge. This study presented a new application of an improved high resolution mass spectrometry (HRMS)-based data-mining tools in tandem to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was metronidazole-pantoprazole-clarithromycin (MET-PAN-CLAR), which is widely used in clinic to treat ulcers caused by Helicobacter pylori. First, mass defect filter (MDF), as a targeted data processing tool, was able to recover all relevant metabolites of MET-PAN-CLAR in human plasma and urine from the full-scan MS dataset when appropriate MDF templates for each drug were defined. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, worked effectively except for several trace metabolites, which were buried in the remaining background signals. Third, an integrated strategy, i.e., untargeted BS followed by improved MDF, was effective for metabolite identification of MET-PAN-CLAR. Most metabolites except for trace ones were found in the first step of BS-processed datasets, and the results led to the setup of appropriate metabolite MDF template for the subsequent MDF data processing. Trace metabolites were further recovered by MDF, which used both common MDF templates and the novel metabolite-based MDF templates. As a result, a total of 44 metabolites or related components were found for MET-PAN-CLAR in human plasma and urine using the integrated strategy. New metabolic pathways such as N-glucuronidation of PAN and dehydrogenation of CLAR were found. This study demonstrated that the combination of accurate mass-based multiple data-mining techniques in tandem, i.e., untargeted background subtraction followed by targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drugs in vivo. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Data mining for signals in spontaneous reporting databases: proceed with caution.

PubMed

Stephenson, Wendy P; Hauben, Manfred

2007-04-01

To provide commentary and points of caution to consider before incorporating data mining as a routine component of any Pharmacovigilance program, and to stimulate further research aimed at better defining the predictive value of these new tools as well as their incremental value as an adjunct to traditional methods of post-marketing surveillance. Commentary includes review of current data mining methodologies employed and their limitations, caveats to consider in the use of spontaneous reporting databases and caution against over-confidence in the results of data mining. Future research should focus on more clearly delineating the limitations of the various quantitative approaches as well as the incremental value that they bring to traditional methods of pharmacovigilance.

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.

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

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

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

Astroinformatics, data mining and the future of astronomical research

NASA Astrophysics Data System (ADS)

Brescia, Massimo; Longo, Giuseppe

2013-08-01

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

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

NASA Astrophysics Data System (ADS)

Kinilakodi, Harisha

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

Back analysis of fault-slip in burst prone environment

NASA Astrophysics Data System (ADS)

Sainoki, Atsushi; Mitri, Hani S.

2016-11-01

In deep underground mines, stress re-distribution induced by mining activities could cause fault-slip. Seismic waves arising from fault-slip occasionally induce rock ejection when hitting the boundary of mine openings, and as a result, severe damage could be inflicted. In general, it is difficult to estimate fault-slip-induced ground motion in the vicinity of mine openings because of the complexity of the dynamic response of faults and the presence of geological structures. In this paper, a case study is conducted for a Canadian underground mine, herein called "Mine-A", which is known for its seismic activities. Using a microseismic database collected from the mine, a back analysis of fault-slip is carried out with mine-wide 3-dimensional numerical modeling. A back analysis is conducted to estimate the physical and mechanical properties of the causative fracture or shear zones. One large seismic event has been selected for the back analysis to detect a fault-slip related seismic event. In the back analysis, the shear zone properties are estimated with respect to moment magnitude of the seismic event and peak particle velocity (PPV) recorded by a strong ground motion sensor. The estimated properties are then validated through comparison with peak ground acceleration recorded by accelerometers. Lastly, ground motion in active mining areas is estimated by conducting dynamic analysis with the estimated values. The present study implies that it would be possible to estimate the magnitude of seismic events that might occur in the near future by applying the estimated properties to the numerical model. Although the case study is conducted for a specific mine, the developed methodology can be equally applied to other mines suffering from fault-slip related seismic events.

ANDSystem: an Associative Network Discovery System for automated literature mining in the field of biology

PubMed Central

2015-01-01

Background Sufficient knowledge of molecular and genetic interactions, which comprise the entire basis of the functioning of living systems, is one of the necessary requirements for successfully answering almost any research question in the field of biology and medicine. To date, more than 24 million scientific papers can be found in PubMed, with many of them containing descriptions of a wide range of biological processes. The analysis of such tremendous amounts of data requires the use of automated text-mining approaches. Although a handful of tools have recently been developed to meet this need, none of them provide error-free extraction of highly detailed information. Results The ANDSystem package was developed for the reconstruction and analysis of molecular genetic networks based on an automated text-mining technique. It provides a detailed description of the various types of interactions between genes, proteins, microRNA's, metabolites, cellular components, pathways and diseases, taking into account the specificity of cell lines and organisms. Although the accuracy of ANDSystem is comparable to other well known text-mining tools, such as Pathway Studio and STRING, it outperforms them in having the ability to identify an increased number of interaction types. Conclusion The use of ANDSystem, in combination with Pathway Studio and STRING, can improve the quality of the automated reconstruction of molecular and genetic networks. ANDSystem should provide a useful tool for researchers working in a number of different fields, including biology, biotechnology, pharmacology and medicine. PMID:25881313

PubstractHelper: A Web-based Text-Mining Tool for Marking Sentences in Abstracts from PubMed Using Multiple User-Defined Keywords.

PubMed

Chen, Chou-Cheng; Ho, Chung-Liang

2014-01-01

While a huge amount of information about biological literature can be obtained by searching the PubMed database, reading through all the titles and abstracts resulting from such a search for useful information is inefficient. Text mining makes it possible to increase this efficiency. Some websites use text mining to gather information from the PubMed database; however, they are database-oriented, using pre-defined search keywords while lacking a query interface for user-defined search inputs. We present the PubMed Abstract Reading Helper (PubstractHelper) website which combines text mining and reading assistance for an efficient PubMed search. PubstractHelper can accept a maximum of ten groups of keywords, within each group containing up to ten keywords. The principle behind the text-mining function of PubstractHelper is that keywords contained in the same sentence are likely to be related. PubstractHelper highlights sentences with co-occurring keywords in different colors. The user can download the PMID and the abstracts with color markings to be reviewed later. The PubstractHelper website can help users to identify relevant publications based on the presence of related keywords, which should be a handy tool for their research. http://bio.yungyun.com.tw/ATM/PubstractHelper.aspx and http://holab.med.ncku.edu.tw/ATM/PubstractHelper.aspx.

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

Analysis of Nature of Science Included in Recent Popular Writing Using Text Mining Techniques

ERIC Educational Resources Information Center

Jiang, Feng; McComas, William F.

2014-01-01

This study examined the inclusion of nature of science (NOS) in popular science writing to determine whether it could serve supplementary resource for teaching NOS and to evaluate the accuracy of text mining and classification as a viable research tool in science education research. Four groups of documents published from 2001 to 2010 were…

75 FR 60694 - Taking and Importing Marine Mammals; Naval Explosive Ordnance Disposal School Training Operations...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-01

... Countermeasures (MCM) detonations is one function of the U.S. Navy EOD force, which involves mine-hunting and mine... of SRI for a portion of the NEODS class. The NEODS would utilize areas approximately one to three nmi... the training is to give NEODS students the tools and techniques to implement MCM through real...

Use of Data Mining to Reveal Body Mass Index (BMI): Patterns among Pennsylvania Schoolchildren, Pre-K to Grade 12

ERIC Educational Resources Information Center

YoussefAgha, Ahmed H.; Lohrmann, David K.; Jayawardene, Wasantha P.

2013-01-01

Background: Health eTools for Schools was developed to assist school nurses with routine entries, including height and weight, on student health records, thus providing a readily accessible data base. Data-mining techniques were applied to this database to determine if clinically signi?cant results could be generated. Methods: Body mass index…

Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

2008-01-01

Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

Beyond accuracy: creating interoperable and scalable text-mining web services.

PubMed

Wei, Chih-Hsuan; Leaman, Robert; Lu, Zhiyong

2016-06-15

The biomedical literature is a knowledge-rich resource and an important foundation for future research. With over 24 million articles in PubMed and an increasing growth rate, research in automated text processing is becoming increasingly important. We report here our recently developed web-based text mining services for biomedical concept recognition and normalization. Unlike most text-mining software tools, our web services integrate several state-of-the-art entity tagging systems (DNorm, GNormPlus, SR4GN, tmChem and tmVar) and offer a batch-processing mode able to process arbitrary text input (e.g. scholarly publications, patents and medical records) in multiple formats (e.g. BioC). We support multiple standards to make our service interoperable and allow simpler integration with other text-processing pipelines. To maximize scalability, we have preprocessed all PubMed articles, and use a computer cluster for processing large requests of arbitrary text. Our text-mining web service is freely available at http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/#curl : Zhiyong.Lu@nih.gov. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Visual information mining in remote sensing image archives

NASA Astrophysics Data System (ADS)

Pelizzari, Andrea; Descargues, Vincent; Datcu, Mihai P.

2002-01-01

The present article focuses on the development of interactive exploratory tools for visually mining the image content in large remote sensing archives. Two aspects are treated: the iconic visualization of the global information in the archive and the progressive visualization of the image details. The proposed methods are integrated in the Image Information Mining (I2M) system. The images and image structure in the I2M system are indexed based on a probabilistic approach. The resulting links are managed by a relational data base. Both the intrinsic complexity of the observed images and the diversity of user requests result in a great number of associations in the data base. Thus new tools have been designed to visualize, in iconic representation the relationships created during a query or information mining operation: the visualization of the query results positioned on the geographical map, quick-looks gallery, visualization of the measure of goodness of the query, visualization of the image space for statistical evaluation purposes. Additionally the I2M system is enhanced with progressive detail visualization in order to allow better access for operator inspection. I2M is a three-tier Java architecture and is optimized for the Internet.

How we use online broadcasting - Web TV - for community engagement

NASA Astrophysics Data System (ADS)

Allison, M. L.; Conway, F. M.; Matti, J.; Palmer, R.

2013-12-01

The Arizona Geological Survey uses online broadcasting (Webcast or 'Web TV') to help fulfill our statutory mission to 'Inform, advise and assist the public in matters concerning the geological processes, materials and landscapes and the development and use of the mineral resources of this state.' We launched a monthly online broadcast called 'Arizona Mining Review' via Livestream, a low-cost or free video streaming service. The show provides news, interviews, and discussions about mining and mineral resources topics of interest in Arizona, the nation's second largest non-fuel mining state. The costs to set up and broadcast are minor. Interviews with local guests are held in a corner of the AZGS conference room with easy chairs and a couch; long-distance interviews are held via Skype. The broadcast originates from a desktop computer with a webcam, a $60 microphone, three sets of earbud headphones and a powered amplifier. During broadcasts, we supplement interview footage with slides, photos, or video clips that we have or are provided by guests. Initial broadcasts were live; recordings of these were later uploaded to our YouTube channel. Because scheduling and executing a live Internet broadcast is stressful and demanding for both the production team and guests, we recently elected to record and produce episodes prior to broadcasting them. This allows us more control over supplementary materials used during the broadcast; it also permits us to record the broadcast using a high-definition digital video camera that cannot be used for streaming video. In addition to the Arizona Mining Review, we record conferences and workshops and special presentations on topical issues. A video on the recently discovered Little Chino fault has drawn over 3,000 views. Our latest presentations are short 1-2 minute 'video abstracts' delivered by authors of new publications released by the Survey. These include maps and graphics from the reports to help illustrate the topics and their importance. We envision online broadcasts as a viable emergent tool that offers a wide range of opportunities at low cost to aid in distributing our message.

Mineral resource of the month: barite

USGS Publications Warehouse

Miller, M. Michael

2006-01-01

Also called barytes, barite forms in various geologic environments and is frequently found with both metallic and nonmetallic minerals. Most barite is produced by open-pit mining techniques, and most crude barite requires some upgrading to meet minimum purity or specific gravity levels.

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

PubMed

Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

Biomedical hypothesis generation by text mining and gene prioritization.

PubMed

Petric, Ingrid; Ligeti, Balazs; Gyorffy, Balazs; Pongor, Sandor

2014-01-01

Text mining methods can facilitate the generation of biomedical hypotheses by suggesting novel associations between diseases and genes. Previously, we developed a rare-term model called RaJoLink (Petric et al, J. Biomed. Inform. 42(2): 219-227, 2009) in which hypotheses are formulated on the basis of terms rarely associated with a target domain. Since many current medical hypotheses are formulated in terms of molecular entities and molecular mechanisms, here we extend the methodology to proteins and genes, using a standardized vocabulary as well as a gene/protein network model. The proposed enhanced RaJoLink rare-term model combines text mining and gene prioritization approaches. Its utility is illustrated by finding known as well as potential gene-disease associations in ovarian cancer using MEDLINE abstracts and the STRING database.

Social Web mining and exploitation for serious applications: Technosocial Predictive Analytics and related technologies for public health, environmental and national security surveillance.

PubMed

Kamel Boulos, Maged N; Sanfilippo, Antonio P; Corley, Courtney D; Wheeler, Steve

2010-10-01

This paper explores Technosocial Predictive Analytics (TPA) and related methods for Web "data mining" where users' posts and queries are garnered from Social Web ("Web 2.0") tools such as blogs, micro-blogging and social networking sites to form coherent representations of real-time health events. The paper includes a brief introduction to commonly used Social Web tools such as mashups and aggregators, and maps their exponential growth as an open architecture of participation for the masses and an emerging way to gain insight about people's collective health status of whole populations. Several health related tool examples are described and demonstrated as practical means through which health professionals might create clear location specific pictures of epidemiological data such as flu outbreaks. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana.

PubMed

Obiri, Samuel; Mattah, Precious A D; Mattah, Memuna M; Armah, Frederick A; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O

2016-01-26

Gold mining has played an important role in Ghana's economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants' perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities.

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana

PubMed Central

Obiri, Samuel; Mattah, Precious A. D.; Mattah, Memuna M.; Armah, Frederick A.; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O.

2016-01-01

Gold mining has played an important role in Ghana’s economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants’ perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities. PMID:26821039

77 FR 72830 - Request for Comments on Request for Continued Examination (RCE) Practice

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-06

... the submission of written comments using a Web-based collaboration tool called IdeaScale[supreg]; and... collaboration tool called IdeaScale[supreg]. The tool allows users to post comments on a topic, and view and...

Conflict minerals in the compute sector: estimating extent of tin, tantalum, tungsten, and gold use in ICT products.

PubMed

Fitzpatrick, Colin; Olivetti, Elsa; Miller, Reed; Roth, Richard; Kirchain, Randolph

2015-01-20

Recent legislation has focused attention on the supply chains of tin, tungsten, tantalum, and gold (3TG), specifically those originating from the eastern part of the Democratic Republic of Congo. The unique properties of these so-called “conflict minerals” lead to their use in many products, ranging from medical devices to industrial cutting tools. This paper calculates per product use of 3TG in several information, communication, and technology (ICT) products such as desktops, servers, laptops, smart phones, and tablets. By scaling up individual product estimates to global shipment figures, this work estimates the influence of the ICT sector on 3TG mining in covered countries. The model estimates the upper bound of tin, tungsten, tantalum, and gold use within ICT products to be 2%, 0.1%, 15%, and 3% of the 2013 market share, respectively. This result is projected into the future (2018) based on the anticipated increase in ICT device production.

Wavefront cellular learning automata.

PubMed

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Mining Adverse Drug Reactions in Social Media with Named Entity Recognition and Semantic Methods.

PubMed

Chen, Xiaoyi; Deldossi, Myrtille; Aboukhamis, Rim; Faviez, Carole; Dahamna, Badisse; Karapetiantz, Pierre; Guenegou-Arnoux, Armelle; Girardeau, Yannick; Guillemin-Lanne, Sylvie; Lillo-Le-Louët, Agnès; Texier, Nathalie; Burgun, Anita; Katsahian, Sandrine

2017-01-01

Suspected adverse drug reactions (ADR) reported by patients through social media can be a complementary source to current pharmacovigilance systems. However, the performance of text mining tools applied to social media text data to discover ADRs needs to be evaluated. In this paper, we introduce the approach developed to mine ADR from French social media. A protocol of evaluation is highlighted, which includes a detailed sample size determination and evaluation corpus constitution. Our text mining approach provided very encouraging preliminary results with F-measures of 0.94 and 0.81 for recognition of drugs and symptoms respectively, and with F-measure of 0.70 for ADR detection. Therefore, this approach is promising for downstream pharmacovigilance analysis.

Biota dose assessment of small mammals sampled near uranium mines in northern Arizona

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

Jannik, T.; Minter, K.; Kuhne, W.

In 2015, the U. S. Geological Survey (USGS) collected approximately 50 small mammal carcasses from Northern Arizona uranium mines and other background locations. Based on the highest gross alpha results, 11 small mammal samples were selected for radioisotopic analyses. None of the background samples had significant gross alpha results. The 11 small mammals were identified relative to the three ‘indicator’ mines located south of Fredonia, AZ on the Kanab Plateau (Kanab North Mine, Pinenut Mine, and Arizona 1 Mine) (Figure 1-1) and are operated by Energy Fuels Resources Inc. (EFRI). EFRI annually reports soil analysis for uranium and radium-226 usingmore » Arizona Department of Environmental Quality (ADEQ)-approved Standard Operating Procedures for Soil Sampling (EFRI 2016a, 2016b, 2017). In combination with the USGS small mammal radioiosotopic tissue analyses, a biota dose assessment was completed by Savannah River National Laboratory (SRNL) using the RESidual RADioactivity-BIOTA (RESRAD-BIOTA, V. 1.8) dose assessment tool provided by the Argonne National Laboratory (ANL 2017).« less

Tracking acid mine-drainage in Southeast Arizona using GIS and sediment delivery models

USGS Publications Warehouse

Norman, L.M.; Gray, F.; Guertin, D.P.; Wissler, C.; Bliss, J.D.

2008-01-01

This study investigates the application of models traditionally used to estimate erosion and sediment deposition to assess the potential risk of water quality impairment resulting from metal-bearing materials related to mining and mineralization. An integrated watershed analysis using Geographic Information Systems (GIS) based tools was undertaken to examine erosion and sediment transport characteristics within the watersheds. Estimates of stream deposits of sediment from mine tailings were related to the chemistry of surface water to assess the effectiveness of the methodology to assess the risk of acid mine-drainage being dispersed downstream of abandoned tailings and waste rock piles. A watershed analysis was preformed in the Patagonia Mountains in southeastern Arizona which has seen substantial mining and where recent water quality samples have reported acidic surface waters. This research demonstrates an improvement of the ability to predict streams that are likely to have severely degraded water quality as a result of past mining activities. ?? Springer Science+Business Media B.V. 2007.

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.

Inferring transposons activity chronology by TRANScendence - TEs database and de-novo mining tool.

PubMed

Startek, Michał Piotr; Nogły, Jakub; Gromadka, Agnieszka; Grzebelus, Dariusz; Gambin, Anna

2017-10-16

The constant progress in sequencing technology leads to ever increasing amounts of genomic data. In the light of current evidence transposable elements (TEs for short) are becoming useful tools for learning about the evolution of host genome. Therefore the software for genome-wide detection and analysis of TEs is of great interest. Here we describe the computational tool for mining, classifying and storing TEs from newly sequenced genomes. This is an online, web-based, user-friendly service, enabling users to upload their own genomic data, and perform de-novo searches for TEs. The detected TEs are automatically analyzed, compared to reference databases, annotated, clustered into families, and stored in TEs repository. Also, the genome-wide nesting structure of found elements are detected and analyzed by new method for inferring evolutionary history of TEs. We illustrate the functionality of our tool by performing a full-scale analyses of TE landscape in Medicago truncatula genome. TRANScendence is an effective tool for the de-novo annotation and classification of transposable elements in newly-acquired genomes. Its streamlined interface makes it well-suited for evolutionary studies.

Make Mine a Metasearcher, Please!

ERIC Educational Resources Information Center

Repman, Judi; Carlson, Randal D.

2000-01-01

Describes metasearch tools and explains their value in helping library media centers improve students' Web searches. Discusses Boolean queries and the emphasis on speed at the expense of comprehensiveness; and compares four metasearch tools, including the number of search engines consulted, user control, and databases included. (LRW)

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.

An Evaluation of Fractal Surface Measurement Methods for Characterizing Landscape Complexity from Remote-Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina Siu-Ngan; Qiu, Hong-Lie; Quattrochi, Dale A.; Emerson, Charles W.; Arnold, James E. (Technical Monitor)

2001-01-01

The rapid increase in digital data volumes from new and existing sensors necessitates the need for efficient analytical tools for extracting information. We developed an integrated software package called ICAMS (Image Characterization and Modeling System) to provide specialized spatial analytical functions for interpreting remote sensing data. This paper evaluates the three fractal dimension measurement methods: isarithm, variogram, and triangular prism, along with the spatial autocorrelation measurement methods Moran's I and Geary's C, that have been implemented in ICAMS. A modified triangular prism method was proposed and implemented. Results from analyzing 25 simulated surfaces having known fractal dimensions show that both the isarithm and triangular prism methods can accurately measure a range of fractal surfaces. The triangular prism method is most accurate at estimating the fractal dimension of higher spatial complexity, but it is sensitive to contrast stretching. The variogram method is a comparatively poor estimator for all of the surfaces, particularly those with higher fractal dimensions. Similar to the fractal techniques, the spatial autocorrelation techniques are found to be useful to measure complex images but not images with low dimensionality. These fractal measurement methods can be applied directly to unclassified images and could serve as a tool for change detection and data mining.

Guasom Analysis Of The Alhambra Survey

NASA Astrophysics Data System (ADS)

Garabato, Daniel; Manteiga, Minia; Dafonte, Carlos; Álvarez, Marco A.

2017-10-01

GUASOM is a data mining tool designed for knowledge discovery in large astronomical spectrophotometric archives developed in the framework of Gaia DPAC (Data Processing and Analysis Consortium). Our tool is based on a type of unsupervised learning Artificial Neural Networks named Self-organizing maps (SOMs). SOMs permit the grouping and visualization of big amount of data for which there is no a priori knowledge and hence they are very useful for analyzing the huge amount of information present in modern spectrophotometric surveys. SOMs are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Each cluster has a representative, called prototype which is a virtual pattern that better represents or resembles the set of input patterns belonging to such a cluster. Prototypes make easier the task of determining the physical nature and properties of the objects populating each cluster. Our algorithm has been tested on the ALHAMBRA survey spectrophotometric observations, here we present our results concerning the survey segmentation, visualization of the data structure, separation between types of objects (stars and galaxies), data homogeneity of neurons, cluster prototypes, redshift distribution and crossmatch with other databases (Simbad).

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

NASA Astrophysics Data System (ADS)

Górniak-Zimroz, Justyna; Pactwa, Katarzyna

2016-10-01

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

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

An open data mining framework for the analysis of medical images: application on obstructive nephropathy microscopy images.

PubMed

Doukas, Charalampos; Goudas, Theodosis; Fischer, Simon; Mierswa, Ingo; Chatziioannou, Aristotle; Maglogiannis, Ilias

2010-01-01

This paper presents an open image-mining framework that provides access to tools and methods for the characterization of medical images. Several image processing and feature extraction operators have been implemented and exposed through Web Services. Rapid-Miner, an open source data mining system has been utilized for applying classification operators and creating the essential processing workflows. The proposed framework has been applied for the detection of salient objects in Obstructive Nephropathy microscopy images. Initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64.

PubMed

Winkler, Robert

2015-01-01

In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models displayed a higher robustness and accuracy for classifying sample groups in targeted Metabolomics than cluster analyses. Random Forest models do not only provide predictive models, which can be deployed for new data sets, but also the variable importance. We demonstrate that the later is especially useful for tracking down significant signals and affected pathways in untargeted Metabolomics. Thus, Random Forest modeling supports the unbiased search for relevant biological features in Metabolomics. Our results clearly manifest the importance of Data Mining methods to disclose non-obvious information in biological mass spectrometry . The application of a Workflow Management System and the integration of all required programs and data in a consistent platform makes the presented data analyses strategies reproducible for non-expert users. The simple remastering process and the Open Source licenses of MASSyPup64 (http://www.bioprocess.org/massypup/) enable the continuous improvement of the system.

Visual Analysis as a design and decision-making tool in the development of a quarry

Treesearch

Randall Boyd Fitzgerald

1979-01-01

In order to obtain local and state government approvals, an environmental impact analysis of the mining and reclamation of a proposed hard rock quarry was required. High visibility of the proposed mining area from the adjacent community required a visual impact analysis in the planning and design of the project. The Visual Analysis defined design criteria for the...

Data Mining in Institutional Economics Tasks

NASA Astrophysics Data System (ADS)

Kirilyuk, Igor; Kuznetsova, Anna; Senko, Oleg

2018-02-01

The paper discusses problems associated with the use of data mining tools to study discrepancies between countries with different types of institutional matrices by variety of potential explanatory variables: climate, economic or infrastructure indicators. An approach is presented which is based on the search of statistically valid regularities describing the dependence of the institutional type on a single variable or a pair of variables. Examples of regularities are given.

Accounts receivable reports: underutilized mining tools.

PubMed

Wallace, R

1999-01-01

There is gold to be found in accounts receivable reports for those willing to mine the data. The key is to know how to interpret the information buried within the numbers and use it to recover monies owed. This article identifies seven reports that should be staples in every organization committed to improving its overall collection performance. Also included are tips on understanding reports and implementing changes.

Performance Support Tools: Delivering Value when and where It Is Needed

ERIC Educational Resources Information Center

McManus, Paul; Rossett, Allison

2006-01-01

Some call them Electronic Performance Support Systems (EPSSs). Others prefer Performance Support Tools (PSTs) or decision support tools. One might call EPSSs or PSTs job aids on steroids, technological tools that provide critical information or advice needed to move forward at a particular moment in time. Characteristic advantages of an EPSS or a…

Resources for Functional Genomics Studies in Drosophila melanogaster

PubMed Central

Mohr, Stephanie E.; Hu, Yanhui; Kim, Kevin; Housden, Benjamin E.; Perrimon, Norbert

2014-01-01

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, “meta” information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally. PMID:24653003

Data Mining and Machine Learning Tools for Combinatorial Material Science of All-Oxide Photovoltaic Cells.

PubMed

Yosipof, Abraham; Nahum, Oren E; Anderson, Assaf Y; Barad, Hannah-Noa; Zaban, Arie; Senderowitz, Hanoch

2015-06-01

Growth in energy demands, coupled with the need for clean energy, are likely to make solar cells an important part of future energy resources. In particular, cells entirely made of metal oxides (MOs) have the potential to provide clean and affordable energy if their power conversion efficiencies are improved. Such improvements require the development of new MOs which could benefit from combining combinatorial material sciences for producing solar cells libraries with data mining tools to direct synthesis efforts. In this work we developed a data mining workflow and applied it to the analysis of two recently reported solar cell libraries based on Titanium and Copper oxides. Our results demonstrate that QSAR models with good prediction statistics for multiple solar cells properties could be developed and that these models highlight important factors affecting these properties in accord with experimental findings. The resulting models are therefore suitable for designing better solar cells. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MyWEST: my Web Extraction Software Tool for effective mining of annotations from web-based databanks.

PubMed

Masseroli, Marco; Stella, Andrea; Meani, Natalia; Alcalay, Myriam; Pinciroli, Francesco

2004-12-12

High-throughput technologies create the necessity to mine large amounts of gene annotations from diverse databanks, and to integrate the resulting data. Most databanks can be interrogated only via Web, for a single gene at a time, and query results are generally available only in the HTML format. Although some databanks provide batch retrieval of data via FTP, this requires expertise and resources for locally reimplementing the databank. We developed MyWEST, a tool aimed at researchers without extensive informatics skills or resources, which exploits user-defined templates to easily mine selected annotations from different Web-interfaced databanks, and aggregates and structures results in an automatically updated database. Using microarray results from a model system of retinoic acid-induced differentiation, MyWEST effectively gathered relevant annotations from various biomolecular databanks, highlighted significant biological characteristics and supported a global approach to the understanding of complex cellular mechanisms. MyWEST is freely available for non-profit use at http://www.medinfopoli.polimi.it/MyWEST/

The application of data mining techniques to oral cancer prognosis.

PubMed

Tseng, Wan-Ting; Chiang, Wei-Fan; Liu, Shyun-Yeu; Roan, Jinsheng; Lin, Chun-Nan

2015-05-01

This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two data mining tools, namely decision tree and artificial neural network, were used to analyze the historical cases of oral cancer, and their performance was compared with that of logistic regression, the popular statistical analysis tool. Both decision tree and artificial neural network models showed superiority to the traditional statistical model. However, as to clinician, the trees created by the decision tree models are relatively easier to interpret compared to that of the artificial neural network models. Cluster analysis also discovers that those stage 4 patients whose also possess the following four characteristics are having an extremely low survival rate: pN is N2b, level of RLNM is level I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.

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.

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

The Profile Interface Generator (PIG) is a tool for loosely coupling applications and performance tools. It enables applications to write code that looks like standard C and Fortran functions calls, without requiring that applications link to specific implementations of those function calls. Performance tools can register with PIG in order to listen to only the calls that give information they care about. This interface reduces the build and configuration burden on application developers and allows semantic instrumentation to live in production codes without interfering with production runs.

78 FR 39012 - Public Land Order No. 7816; Partial Revocation of the Executive Order dated April 17, 1926; Idaho

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-28

... for non-metaliferous minerals under the United States mining laws, for protection of springs and... device for the deaf (TDD) may call the Federal Information Relay Service (FIRS) at 1-800- 877-8339 to...

KSC-2011-4167

NASA Image and Video Library

2011-05-28

CAPE CANAVERAL, Fla. -- At NASA Kennedy Space Center's Apollo/Saturn V Center, Jerry Hartman, Education Lead with the Exploration Systems Mission Directorate at NASA Headquarters and Susan Sawyer, Lunabotics Project Coordinator with ReDe/Critique, display the trophy the winning team will receive at the award ceremony for NASA's second annual Lunabotics Mining Competition. Thirty-six teams of undergraduate and graduate students from the United States, Bangladesh, Canada, Colombia and India participated in NASA's Lunabotics Mining Competition May 26 - 28 at the agency's Kennedy Space Center in Florida. The competition is designed to engage and retain students in science, technology, engineering and mathematics (STEM). Teams will maneuver their remote controlled or autonomous excavators, called lunabots, in about 60 tons of ultra-fine simulated lunar soil, called BP-1. The competition is an Exploration Systems Mission Directorate project managed by Kennedy's Education Division. The event also provides a competitive environment that could result in innovative ideas and solutions for NASA's future excavation of the moon. Photo credit: NASA/Jack Pfaller

Forecasting the ocean optical environment in support of Navy mine warfare operations

NASA Astrophysics Data System (ADS)

Ladner, S. D.; Arnone, R.; Jolliff, J.; Casey, B.; Matulewski, K.

2012-06-01

A 3D ocean optical forecast system called TODS (Tactical Ocean Data System) has been developed to determine the performance of underwater LIDAR detection/identification systems. TODS fuses optical measurements from gliders, surface satellite optical properties, and 3D ocean forecast circulation models to extend the 2-dimensional surface satellite optics into a 3-dimensional optical volume including subsurface optical layers of beam attenuation coefficient (c) and diver visibility. Optical 3D nowcast and forecasts are combined with electro-optical identification (EOID) models to determine the underwater LIDAR imaging performance field used to identify subsurface mine threats in rapidly changing coastal regions. TODS was validated during a recent mine warfare exercise with Helicopter Mine Countermeasures Squadron (HM-14). Results include the uncertainties in the optical forecast and lidar performance and sensor tow height predictions that are based on visual detection and identification metrics using actual mine target images from the EOID system. TODS is a new capability of coupling the 3D optical environment and EOID system performance and is proving important for the MIW community as both a tactical decision aid and for use in operational planning, improving timeliness and efficiency in clearance operations.

Knowledge discovery through games and game theory

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D.

2001-03-01

A fuzzy logic based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. The initial version of the algorithm was optimized using a genetic algorithm employing fitness functions constructed based on expertise. A new approach is being explored that involves embedding the resource manager in a electronic game environment. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the database as required. The game allows easy evaluation of the information mined in the second step. The measure of effectiveness (MOE) for re-optimization is discussed. The mined information is extremely valuable as shown through demanding scenarios.

A novel approach for acid mine drainage pollution biomonitoring using rare earth elements bioaccumulated in the freshwater clam Corbicula fluminea.

PubMed

Bonnail, Estefanía; Pérez-López, Rafael; Sarmiento, Aguasanta M; Nieto, José Miguel; DelValls, T Ángel

2017-09-15

Lanthanide series have been used as a record of the water-rock interaction and work as a tool for identifying impacts of acid mine drainage (lixiviate residue derived from sulphide oxidation). The application of North-American Shale Composite-normalized rare earth elements patterns to these minority elements allows determining the origin of the contamination. In the current study, geochemical patterns were applied to rare earth elements bioaccumulated in the soft tissue of the freshwater clam Corbicula fluminea after exposure to different acid mine drainage contaminated environments. Results show significant bioaccumulation of rare earth elements in soft tissue of the clam after 14 days of exposure to acid mine drainage contaminated sediment (ΣREE=1.3-8μg/gdw). Furthermore, it was possible to biomonitor different degrees of contamination based on rare earth elements in tissue. The pattern of this type of contamination describes a particular curve characterized by an enrichment in the middle rare earth elements; a homologous pattern (E MREE =0.90) has also been observed when applied NASC normalization in clam tissues. Results of lanthanides found in clams were contrasted with the paucity of toxicity studies, determining risk caused by light rare earth elements in the Odiel River close to the Estuary. The current study purposes the use of clam as an innovative "bio-tool" for the biogeochemical monitoring of pollution inputs that determines the acid mine drainage networks affection. Copyright © 2017 Elsevier B.V. All rights reserved.

User Guidelines for the Brassica Database: BRAD.

PubMed

Wang, Xiaobo; Cheng, Feng; Wang, Xiaowu

2016-01-01

The genome sequence of Brassica rapa was first released in 2011. Since then, further Brassica genomes have been sequenced or are undergoing sequencing. It is therefore necessary to develop tools that help users to mine information from genomic data efficiently. This will greatly aid scientific exploration and breeding application, especially for those with low levels of bioinformatic training. Therefore, the Brassica database (BRAD) was built to collect, integrate, illustrate, and visualize Brassica genomic datasets. BRAD provides useful searching and data mining tools, and facilitates the search of gene annotation datasets, syntenic or non-syntenic orthologs, and flanking regions of functional genomic elements. It also includes genome-analysis tools such as BLAST and GBrowse. One of the important aims of BRAD is to build a bridge between Brassica crop genomes with the genome of the model species Arabidopsis thaliana, thus transferring the bulk of A. thaliana gene study information for use with newly sequenced Brassica crops.

Supporting the annotation of chronic obstructive pulmonary disease (COPD) phenotypes with text mining workflows.

PubMed

Fu, Xiao; Batista-Navarro, Riza; Rak, Rafal; Ananiadou, Sophia

2015-01-01

Chronic obstructive pulmonary disease (COPD) is a life-threatening lung disorder whose recent prevalence has led to an increasing burden on public healthcare. Phenotypic information in electronic clinical records is essential in providing suitable personalised treatment to patients with COPD. However, as phenotypes are often "hidden" within free text in clinical records, clinicians could benefit from text mining systems that facilitate their prompt recognition. This paper reports on a semi-automatic methodology for producing a corpus that can ultimately support the development of text mining tools that, in turn, will expedite the process of identifying groups of COPD patients. A corpus of 30 full-text papers was formed based on selection criteria informed by the expertise of COPD specialists. We developed an annotation scheme that is aimed at producing fine-grained, expressive and computable COPD annotations without burdening our curators with a highly complicated task. This was implemented in the Argo platform by means of a semi-automatic annotation workflow that integrates several text mining tools, including a graphical user interface for marking up documents. When evaluated using gold standard (i.e., manually validated) annotations, the semi-automatic workflow was shown to obtain a micro-averaged F-score of 45.70% (with relaxed matching). Utilising the gold standard data to train new concept recognisers, we demonstrated that our corpus, although still a work in progress, can foster the development of significantly better performing COPD phenotype extractors. We describe in this work the means by which we aim to eventually support the process of COPD phenotype curation, i.e., by the application of various text mining tools integrated into an annotation workflow. Although the corpus being described is still under development, our results thus far are encouraging and show great potential in stimulating the development of further automatic COPD phenotype extractors.

Seismic tomography as a tool for measuring stress in mines

USGS Publications Warehouse

Scott, Douglas F.; Williams, T.J.; Denton, D.K.; Friedel, M.J.

1999-01-01

Spokane Research Center personnel have been investigating the use of seismic tomography to monitor the behavior of a rock mass, detect hazardous ground conditions and assess the mechanical integrity of a rock mass affected by mining. Seismic tomography can be a valuable tool for determining relative stress in deep, >1,220-m (>4,000-ft), underground pillars. If high-stress areas are detected, they can be destressed prior to development or they can be avoided. High-stress areas can be monitored with successive seismic surveys to determine if stress decreases to a level where development can be initiated safely. There are several benefits to using seismic tomography to identify high stress in deep underground pillars. The technique is reliable, cost-effective, efficient and noninvasive. Also, investigators can monitor large rock masses, as well as monitor pillars during the mining cycle. By identifying areas of high stress, engineers will be able to assure that miners are working in a safer environment.Spokane Research Center personnel have been investigating the use of seismic tomography to monitor the behavior of a rock mass, detect hazardous ground conditions and assess the mechanical integrity of a rock mass affected by mining. Seismic tomography can be a valuable tool for determining relative stress in deep, >1,200-m (>4,000-ft), underground pillars. If high-stress areas are detected, they can be destressed prior to development or they can be avoided. High-stress areas can be monitored with successive seismic surveys to determine if stress decreases to a level where development can be initiated safely. There are several benefits to using seismic tomography to identify high stress in deep underground pillars. The technique is reliable, cost-effective, efficient and noninvasive. Also, investigators can monitor large rock masses, as well as monitor pillars during the mining cycle. By identifying areas of high stress. engineers will be able to assure that miners are working in a safer environment.

What the papers say: Text mining for genomics and systems biology

PubMed Central

2010-01-01

Keeping up with the rapidly growing literature has become virtually impossible for most scientists. This can have dire consequences. First, we may waste research time and resources on reinventing the wheel simply because we can no longer maintain a reliable grasp on the published literature. Second, and perhaps more detrimental, judicious (or serendipitous) combination of knowledge from different scientific disciplines, which would require following disparate and distinct research literatures, is rapidly becoming impossible for even the most ardent readers of research publications. Text mining -- the automated extraction of information from (electronically) published sources -- could potentially fulfil an important role -- but only if we know how to harness its strengths and overcome its weaknesses. As we do not expect that the rate at which scientific results are published will decrease, text mining tools are now becoming essential in order to cope with, and derive maximum benefit from, this information explosion. In genomics, this is particularly pressing as more and more rare disease-causing variants are found and need to be understood. Not being conversant with this technology may put scientists and biomedical regulators at a severe disadvantage. In this review, we introduce the basic concepts underlying modern text mining and its applications in genomics and systems biology. We hope that this review will serve three purposes: (i) to provide a timely and useful overview of the current status of this field, including a survey of present challenges; (ii) to enable researchers to decide how and when to apply text mining tools in their own research; and (iii) to highlight how the research communities in genomics and systems biology can help to make text mining from biomedical abstracts and texts more straightforward. PMID:21106487

Moment tensor clustering: a tool to monitor mining induced seismicity

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Text mining and medicine: usefulness in respiratory diseases.

PubMed

Piedra, David; Ferrer, Antoni; Gea, Joaquim

2014-03-01

It is increasingly common to have medical information in electronic format. This includes scientific articles as well as clinical management reviews, and even records from health institutions with patient data. However, traditional instruments, both individual and institutional, are of little use for selecting the most appropriate information in each case, either in the clinical or research field. So-called text or data «mining» enables this huge amount of information to be managed, extracting it from various sources using processing systems (filtration and curation), integrating it and permitting the generation of new knowledge. This review aims to provide an overview of text and data mining, and of the potential usefulness of this bioinformatic technique in the exercise of care in respiratory medicine and in research in the same field. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

The MINE project: Minority Involvement in NASA Engineering

NASA Technical Reports Server (NTRS)

Allen, H., Jr.

1977-01-01

The Mine Project developed by Lewis Research Center (LRC) along with Tennessee State University and Tuskegee Institute, is described. The project calls for LRC to assemble on-going NASA university affairs programs aimed at benefiting the school, its faculty, and its student body. The schools receive grants to pursue research and technology projects that are relevant to NASA's missions. Upon request from the universities, LRC furnishes instructors and lecturers. The schools have use of surplus government equipment and access to NASA research facilities for certain projects. Both the faculty and students of the universities are eligible for summer employment at LRC through special programs. The MINE Project is designed to establish a continuing active relationship of 3 to 5 years between NASA and the universities, and will afford LRC with an opportunity to increase its recruitment of minority and women employees.

Monitoring food safety violation reports from internet forums.

PubMed

Kate, Kiran; Negi, Sumit; Kalagnanam, Jayant

2014-01-01

Food-borne illness is a growing public health concern in the world. Government bodies, which regulate and monitor the state of food safety, solicit citizen feedback about food hygiene practices followed by food establishments. They use traditional channels like call center, e-mail for such feedback collection. With the growing popularity of Web 2.0 and social media, citizens often post such feedback on internet forums, message boards etc. The system proposed in this paper applies text mining techniques to identify and mine such food safety complaints posted by citizens on web data sources thereby enabling the government agencies to gather more information about the state of food safety. In this paper, we discuss the architecture of our system and the text mining methods used. We also present results which demonstrate the effectiveness of this system in a real-world deployment.

Rare disease diagnosis: A review of web search, social media and large-scale data-mining approaches.

PubMed

Svenstrup, Dan; Jørgensen, Henrik L; Winther, Ole

2015-01-01

Physicians and the general public are increasingly using web-based tools to find answers to medical questions. The field of rare diseases is especially challenging and important as shown by the long delay and many mistakes associated with diagnoses. In this paper we review recent initiatives on the use of web search, social media and data mining in data repositories for medical diagnosis. We compare the retrieval accuracy on 56 rare disease cases with known diagnosis for the web search tools google.com, pubmed.gov, omim.org and our own search tool findzebra.com. We give a detailed description of IBM's Watson system and make a rough comparison between findzebra.com and Watson on subsets of the Doctor's dilemma dataset. The recall@10 and recall@20 (fraction of cases where the correct result appears in top 10 and top 20) for the 56 cases are found to be be 29%, 16%, 27% and 59% and 32%, 18%, 34% and 64%, respectively. Thus, FindZebra has a significantly (p < 0.01) higher recall than the other 3 search engines. When tested under the same conditions, Watson and FindZebra showed similar recall@10 accuracy. However, the tests were performed on different subsets of Doctors dilemma questions. Advances in technology and access to high quality data have opened new possibilities for aiding the diagnostic process. Specialized search engines, data mining tools and social media are some of the areas that hold promise.

Rare disease diagnosis: A review of web search, social media and large-scale data-mining approaches

PubMed Central

Svenstrup, Dan; Jørgensen, Henrik L; Winther, Ole

2015-01-01

Physicians and the general public are increasingly using web-based tools to find answers to medical questions. The field of rare diseases is especially challenging and important as shown by the long delay and many mistakes associated with diagnoses. In this paper we review recent initiatives on the use of web search, social media and data mining in data repositories for medical diagnosis. We compare the retrieval accuracy on 56 rare disease cases with known diagnosis for the web search tools google.com, pubmed.gov, omim.org and our own search tool findzebra.com. We give a detailed description of IBM's Watson system and make a rough comparison between findzebra.com and Watson on subsets of the Doctor's dilemma dataset. The recall@10 and recall@20 (fraction of cases where the correct result appears in top 10 and top 20) for the 56 cases are found to be be 29%, 16%, 27% and 59% and 32%, 18%, 34% and 64%, respectively. Thus, FindZebra has a significantly (p < 0.01) higher recall than the other 3 search engines. When tested under the same conditions, Watson and FindZebra showed similar recall@10 accuracy. However, the tests were performed on different subsets of Doctors dilemma questions. Advances in technology and access to high quality data have opened new possibilities for aiding the diagnostic process. Specialized search engines, data mining tools and social media are some of the areas that hold promise. PMID:26442199

CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities.

PubMed

Manem, Venkata; Adam, George Alexandru; Gruosso, Tina; Gigoux, Mathieu; Bertos, Nicholas; Park, Morag; Haibe-Kains, Benjamin

2018-04-15

Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments. Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140-3. ©2018 AACR . ©2018 American Association for Cancer Research.

Spatial database of mining-related features in 2001 at selected phosphate mines, Bannock, Bear Lake, Bingham, and Caribou Counties, Idaho

USGS Publications Warehouse

Moyle, Phillip R.; Kayser, Helen Z.

2006-01-01

This report describes the spatial database, PHOSMINE01, and the processes used to delineate mining-related features (active and inactive/historical) in the core of the southeastern Idaho phosphate resource area. The spatial data have varying degrees of accuracy and attribution detail. Classification of areas by type of mining-related activity at active mines is generally detailed; however, for many of the closed or inactive mines the spatial coverage does not differentiate mining-related surface disturbance features. Nineteen phosphate mine sites are included in the study, three active phosphate mines - Enoch Valley (nearing closure), Rasmussen Ridge, and Smoky Canyon - and 16 inactive (or historical) phosphate mines - Ballard, Champ, Conda, Diamond Gulch, Dry Valley, Gay, Georgetown Canyon, Henry, Home Canyon, Lanes Creek, Maybe Canyon, Mountain Fuel, Trail Canyon, Rattlesnake, Waterloo, and Wooley Valley. Approximately 6,000 hc (15,000 ac), or 60 km2 (23 mi2) of phosphate mining-related surface disturbance are documented in the spatial coverage. Spatial data for the inactive mines is current because no major changes have occurred; however, the spatial data for active mines were derived from digital maps prepared in early 2001 and therefore recent activity is not included. The inactive Gay Mine has the largest total area of disturbance, 1,900 hc (4,700 ac) or about 19 km2 (7.4 mi2). It encompasses over three times the disturbance area of the next largest mine, the Conda Mine with 610 hc (1,500 ac), and it is nearly four times the area of the Smoky Canyon Mine, the largest of the active mines with about 550 hc (1,400 ac). The wide range of phosphate mining-related surface disturbance features (141) from various industry maps were reduced to 15 types or features based on a generic classification system used for this study: mine pit; backfilled mine pit; waste rock dump; adit and waste rock dump; ore stockpile; topsoil stockpile; tailings or tailings pond; sediment catchment; facilities; road; railroad; water reservoir; disturbed land, undifferentiated; and undisturbed land. In summary, the spatial coverage includes polygons totaling about 1,100 hc (2,800 ac) of mine pits, 440 hc (1100 ac) of backfilled mine pits, 1,600 hc (3,800 ac) of waste rock dumps, 31 hc (75 ac) of ore stockpiles, and 44 hc (110 ac) of tailings or tailings ponds. Areas of undifferentiated phosphate mining-related land disturbances, called 'disturbed land, undifferentiated,' total about 2,200 hc (5,500 ac) or nearly 22 km2 (8.6 mi2). No determination has been made as to status of reclamation on any of the lands. Subsequent site-specific studies to delineate distinct mine features will allow additional revisions to this spatial database.

Network-Centric Data Mining for Medical Applications

ERIC Educational Resources Information Center

Davis, Darcy A.

2012-01-01

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

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

NASA Astrophysics Data System (ADS)

Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

2017-11-01

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

Mining collections of compounds with Screening Assistant 2

PubMed Central

2012-01-01

Background High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. Results We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Conclusions Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/. PMID:23327565

Mining collections of compounds with Screening Assistant 2.

PubMed

Guilloux, Vincent Le; Arrault, Alban; Colliandre, Lionel; Bourg, Stéphane; Vayer, Philippe; Morin-Allory, Luc

2012-08-31

High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/.

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

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

Relevance of ERTS-1 to the state of Ohio

NASA Technical Reports Server (NTRS)

Sweet, D. C. (Principal Investigator); Wells, T. L.; Wukelic, G. E.

1973-01-01

The author has identified the following significant results. To date, only one significant result has been reported for the Ohio ERTS program. This result relates to the proven usefulness of ERTS-1 imagery for mapping and inventorying strip-mined areas in southeastern Ohio. ERTS provides a tool for rapidly and economically acquiring an up-to-date inventory of strip-mined lands for state planning purposes which was not previously possible.

2012 Alabama Lunabotics Systems Engineering Paper

NASA Technical Reports Server (NTRS)

Baker, Justin; Ricks, Kenneth; Hull, Bethanne J.

2012-01-01

Excavation will hold a key role for future lunar missions. NASA has stated that "advances in lunar regolith mining have the potential to significantly contribute to our nation's space vision and NASA space exploration operations." [1]. The Lunabotics Mining Competition is an event hosted by NASA that is meant to encourage "the development of innovative lunar excavation concepts from universities which may result in clever ideas and solutions which could be applied to an actual lunar excavation device or payload." [2]. Teams entering the competition must "design and build a remote controlled or autonomous excavator, called a lunabot, that can collect and deposit a minimum of 10 kilograms of lunar simulant within 10 minutes." [2]. While excavation will play an important part in lunar missions, there will still be many other tasks that would benefit from robotic assistance. An excavator might not be as well suited for these tasks as other types of robots might be. For example a lightweight rover would do well with reconnaissance, and a mobile gripper arm would be fit for manipulation, while an excavator would be comparatively clumsy and slow in both cases. Even within the realm of excavation it would be beneficial to have different types of excavators for different tasks, as there are on Earth. The Alabama Lunabotics Team at the University of Alabama has made it their goal to not only design and build a robot that could compete in the Lunabotics Mining Competition, but would also be a multipurpose tool for future NASA missions. The 2010-2011 resulting robot was named the Modular Omnidirectional Lunar Excavator (MOLE). Using the Systems Engineering process and building off of two years of Lunabotics experience, the 20ll-2012 Alabama Lunabotics team (Team NASACAR) has improved the MOLE 1.0 design and optimized it for the 2012 Lunabotics Competition rules [I]. A CAD model of MOLE 2.0 can be seen below in Fig. 1.

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Solutions for Mining Distributed Scientific Data

NASA Astrophysics Data System (ADS)

Lynnes, C.; Pham, L.; Graves, S.; Ramachandran, R.; Maskey, M.; Keiser, K.

2007-12-01

Researchers at the University of Alabama in Huntsville (UAH) and the Goddard Earth Sciences Data and Information Services Center (GES DISC) are working on approaches and methodologies facilitating the analysis of large amounts of distributed scientific data. Despite the existence of full-featured analysis tools, such as the Algorithm Development and Mining (ADaM) toolkit from UAH, and data repositories, such as the GES DISC, that provide online access to large amounts of data, there remain obstacles to getting the analysis tools and the data together in a workable environment. Does one bring the data to the tools or deploy the tools close to the data? The large size of many current Earth science datasets incurs significant overhead in network transfer for analysis workflows, even with the advanced networking capabilities that are available between many educational and government facilities. The UAH and GES DISC team are developing a capability to define analysis workflows using distributed services and online data resources. We are developing two solutions for this problem that address different analysis scenarios. The first is a Data Center Deployment of the analysis services for large data selections, orchestrated by a remotely defined analysis workflow. The second is a Data Mining Center approach of providing a cohesive analysis solution for smaller subsets of data. The two approaches can be complementary and thus provide flexibility for researchers to exploit the best solution for their data requirements. The Data Center Deployment of the analysis services has been implemented by deploying ADaM web services at the GES DISC so they can access the data directly, without the need of network transfers. Using the Mining Workflow Composer, a user can define an analysis workflow that is then submitted through a Web Services interface to the GES DISC for execution by a processing engine. The workflow definition is composed, maintained and executed at a distributed location, but most of the actual services comprising the workflow are available local to the GES DISC data repository. Additional refinements will ultimately provide a package that is easily implemented and configured at additional data centers for analysis of additional science data sets. Enhancements to the ADaM toolkit allow the staging of distributed data wherever the services are deployed, to support a Data Mining Center that can provide additional computational resources, large storage of output, easier addition and updates to available services, and access to data from multiple repositories. The Data Mining Center case provides researchers more flexibility to quickly try different workflow configurations and refine the process, using smaller amounts of data that may likely be transferred from distributed online repositories. This environment is sufficient for some analyses, but can also be used as an initial sandbox to test and refine a solution before staging the execution at a Data Center Deployment. Detection of airborne dust both over water and land in MODIS imagery using mining services for both solutions will be presented. The dust detection is just one possible example of the mining and analysis capabilities the proposed mining services solutions will provide to the science community. More information about the available services and the current status of this project is available at http://www.itsc.uah.edu/mws/

Digital database of mining-related features at selected historic and active phosphate mines, Bannock, Bear Lake, Bingham, and Caribou counties, Idaho

USGS Publications Warehouse

Causey, J. Douglas; Moyle, Phillip R.

2001-01-01

This report provides a description of data and processes used to produce a spatial database that delineates mining-related features in areas of historic and active phosphate mining in the core of the southeastern Idaho phosphate resource area. The data have varying degrees of accuracy and attribution detail. Classification of areas by type of mining-related activity at active mines is generally detailed; however, the spatial coverage does not differentiate mining-related surface disturbance features at many of the closed or inactive mines. Nineteen phosphate mine sites are included in the study. A total of 5,728 hc (14,154 ac), or more than 57 km2 (22 mi2), of phosphate mining-related surface disturbance are documented in the spatial coverage of the core of the southeast Idaho phosphate resource area. The study includes 4 active phosphate mines—Dry Valley, Enoch Valley, Rasmussen Ridge, and Smoky Canyon—and 15 historic phosphate mines—Ballard, Champ, Conda, Diamond Gulch, Gay, Georgetown Canyon, Henry, Home Canyon, Lanes Creek, Maybe Canyon, Mountain Fuel, Trail Canyon, Rattlesnake Canyon, Waterloo, and Wooley Valley. Spatial data on the inactive historic mines is relatively up-to-date; however, spatially described areas for active mines are based on digital maps prepared in early 1999. The inactive Gay mine has the largest total area of disturbance: 1,917 hc (4,736 ac) or about 19 km2 (7.4 mi2). It encompasses over three times the disturbance area of the next largest mine, the Conda mine with 607 hc (1,504 ac), and it is nearly four times the area of the Smoky Canyon mine, the largest of the active mines with 497 hc (1,228 ac). The wide range of phosphate mining-related surface disturbance features (approximately 80) were reduced to 13 types or features used in this study—adit and pit, backfilled mine pit, facilities, mine pit, ore stockpile, railroad, road, sediment catchment, tailings or tailings pond, topsoil stockpile, water reservoir, and disturbed land (undifferentiated). In summary, the spatial coverage includes polygons totaling 1,114 hc (2,753 ac) of mine pits, 272 hc (671 ac) of backfilled mine pits, 1,570 hc (3,880 ac) of waste dumps, 26 hc (64 ac) of ore stockpiles, and 44 hc (110 ac) of tailings or tailings ponds. Areas of undifferentiated phosphate mining-related land disturbances, called “disturbed land,” total 2,176 (5,377 ac) or nearly 21.8 km2 (8.4 mi2). No determination has been made as to status of reclamation on these lands. Subsequent site-specific studies to delineate distinct mine features will allow modification of this preliminary spatial database.

Use of geospatial data to predict downstream influence of coal mining in Appalachia

EPA Science Inventory

A 2001 Supreme Court decision first called into question whether some headwater streams could be considered jurisdictional under the Clean Water Act. A subsequent decision then required that non-navigable waters must be "relatively permanent" or "possess a significant nexus" to ...

Measurement and Instrumentation

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

Kirkham, Harold

This is a chapter for a book called the Standard Handbook for Electrical Engineering. Though it is not obvious from the title, the book deals mainly with power engineering. The first chapter (not mine) is about the fundamental quantities used in measurement. This chapter is about the process and the instrumentation.

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.

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.

Radioecological impacts of tin mining.

PubMed

Aliyu, Abubakar Sadiq; Mousseau, Timothy Alexander; Ramli, Ahmad Termizi; Bununu, Yakubu Aliyu

2015-12-01

The tin mining activities in the suburbs of Jos, Plateau State, Nigeria, have resulted in technical enhancement of the natural background radiation as well as higher activity concentrations of primordial radionuclides in the topsoil of mining sites and their environs. Several studies have considered the radiological human health risks of the mining activity; however, to our knowledge no documented study has investigated the radiological impacts on biota. Hence, an attempt is made to assess potential hazards using published data from the literature and the ERICA Tool. This paper considers the effects of mining and milling on terrestrial organisms like shrubs, large mammals, small burrowing mammals, birds (duck), arthropods (earth worm), grasses, and herbs. The dose rates and risk quotients to these organisms are computed using conservative values for activity concentrations of natural radionuclides reported in Bitsichi and Bukuru mining areas. The results suggest that grasses, herbs, lichens, bryophytes and shrubs receive total dose rates that are of potential concern. The effects of dose rates to specific indicator species of interest are highlighted and discussed. We conclude that further investigation and proper regulations should be set in place in order to reduce the risk posed by the tin mining activity on biota. This paper also presents a brief overview of the impact of mineral mining on biota based on documented literature for other countries.

Environmental management in North American mining sector.

PubMed

Asif, Zunaira; Chen, Zhi

2016-01-01

This paper reviews the environmental issues and management practices in the mining sector in the North America. The sustainable measures on waste management are recognized as one of the most serious environmental concerns in the mining industry. For mining activities, it will be no surprise that the metal recovery reagents and acid effluents are a threat to the ecosystem as well as hazards to human health. In addition, poor air quality and ventilation in underground mines can lead to occupational illness and death of workers. Electricity usage and fuel consumption are major factors that contribute to greenhouse gases. On the other hand, many sustainability challenges are faced in the management of tailings and disposal of waste rock. This paper aims to highlight the problems that arise due to poor air quality and acid mine drainage. The paper also addresses some of the advantages and limitations of tailing and waste rock management that still have to be studied in context of the mining sector. This paper suggests that implementation of suitable environmental management tools like life cycle assessment (LCA), cleaner production technologies (CPTs), and multicriteria decision analysis (MCD) are important as it ultimately lead to improve environmental performance and enabling a mine to focus on the next stage of sustainability.

Breast Imaging in the Era of Big Data: Structured Reporting and Data Mining.

PubMed

Margolies, Laurie R; Pandey, Gaurav; Horowitz, Eliot R; Mendelson, David S

2016-02-01

The purpose of this article is to describe structured reporting and the development of large databases for use in data mining in breast imaging. The results of millions of breast imaging examinations are reported with structured tools based on the BI-RADS lexicon. Much of these data are stored in accessible media. Robust computing power creates great opportunity for data scientists and breast imagers to collaborate to improve breast cancer detection and optimize screening algorithms. Data mining can create knowledge, but the questions asked and their complexity require extremely powerful and agile databases. New data technologies can facilitate outcomes research and precision medicine.

QTLTableMiner++: semantic mining of QTL tables in scientific articles.

PubMed

Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M; Gavai, Anand; Bachem, Christian W; Visser, Richard G F; Finkers, Richard

2018-05-25

A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner ++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.

Trace metal depositional patterns from an open pit mining activity as revealed by archived avian gizzard contents.

PubMed

Bendell, L I

2011-02-15

Archived samples of blue grouse (Dendragapus obscurus) gizzard contents, inclusive of grit, collected yearly between 1959 and 1970 were analyzed for cadmium, lead, zinc, and copper content. Approximately halfway through the 12-year sampling period, an open-pit copper mine began activities, then ceased operations 2 years later. Thus the archived samples provided a unique opportunity to determine if avian gizzard contents, inclusive of grit, could reveal patterns in the anthropogenic deposition of trace metals associated with mining activities. Gizzard concentrations of cadmium and copper strongly coincided with the onset of opening and the closing of the pit mining activity. Gizzard zinc and lead demonstrated significant among year variation; however, maximum concentrations did not correlate to mining activity. The archived gizzard contents did provide a useful tool for documenting trends in metal depositional patterns related to an anthropogenic activity. Further, blue grouse ingesting grit particles during the time of active mining activity would have been exposed to toxicologically significant levels of cadmium. Gizzard lead concentrations were also of toxicological significance but not related to mining activity. This type of "pulse" toxic metal exposure as a consequence of open-pit mining activity would not necessarily have been revealed through a "snap-shot" of soil, plant or avian tissue trace metal analysis post-mining activity. Copyright © 2010 Elsevier B.V. All rights reserved.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

PubMed Central

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers’ exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes. PMID:27832067

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

PubMed

Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-11-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the unique characteristic to color regulatory relations between genes and reveal their phenotype inclination. This unique characteristic makes MinePath a valuable tool for in silico molecular biology experimentation as it serves the biomedical researchers' exploratory needs to reveal and interpret the regulatory mechanisms that underlie and putatively govern the expression of target phenotypes.

The use of data mining by private health insurance companies and customers' privacy.

PubMed

Al-Saggaf, Yeslam

2015-07-01

This article examines privacy threats arising from the use of data mining by private Australian health insurance companies. Qualitative interviews were conducted with key experts, and Australian governmental and nongovernmental websites relevant to private health insurance were searched. Using Rationale, a critical thinking tool, the themes and considerations elicited through this empirical approach were developed into an argument about the use of data mining by private health insurance companies. The argument is followed by an ethical analysis guided by classical philosophical theories-utilitarianism, Mill's harm principle, Kant's deontological theory, and Helen Nissenbaum's contextual integrity framework. Both the argument and the ethical analysis find the use of data mining by private health insurance companies in Australia to be unethical. Although private health insurance companies in Australia cannot use data mining for risk rating to cherry-pick customers and cannot use customers' personal information for unintended purposes, this article nonetheless concludes that the secondary use of customers' personal information and the absence of customers' consent still suggest that the use of data mining by private health insurance companies is wrong.

Statistical methods of estimating mining costs

USGS Publications Warehouse

Long, K.R.

2011-01-01

Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.

MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms.

PubMed

Theodosiou, T; Vizirianakis, I S; Angelis, L; Tsaftaris, A; Darzentas, N

2011-12-01

PubMed is the most widely used database of biomedical literature. To the detriment of the user though, the ranking of the documents retrieved for a query is not content-based, and important semantic information in the form of assigned Medical Subject Headings (MeSH) terms is not readily presented or productively utilized. The motivation behind this work was the discovery of unanticipated information through the appropriate ranking of MeSH term pairs and, indirectly, documents. Such information can be useful in guiding novel research and following promising trends. A web-based tool, called MeSHy, was developed implementing a mainly statistical algorithm. The algorithm takes into account the frequencies of occurrences, concurrences, and the semantic similarities of MeSH terms in retrieved PubMed documents to create MeSH term pairs. These are then scored and ranked, focusing on their unexpectedly frequent or infrequent occurrences. MeSHy presents results through an online interactive interface facilitating further manipulation through filtering and sorting. The results themselves include the MeSH term pairs, along with MeSH categories, the score, and document IDs, all of which are hyperlinked for convenience. To highlight the applicability of the tool, we report the findings of an expert in the pharmacology field on querying the molecularly-targeted drug imatinib and nutrition-related flavonoids. To the best of our knowledge, MeSHy is the first publicly available tool able to directly provide such a different perspective on the complex nature of published work. Implemented in Perl and served by Apache2 at http://bat.ina.certh.gr/tools/meshy/ with all major browsers supported. Copyright © 2011 Elsevier Inc. All rights reserved.

Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research.

PubMed

Eppig, Janan T; Smith, Cynthia L; Blake, Judith A; Ringwald, Martin; Kadin, James A; Richardson, Joel E; Bult, Carol J

2017-01-01

The Mouse Genome Informatics (MGI), resource ( www.informatics.jax.org ) has existed for over 25 years, and over this time its data content, informatics infrastructure, and user interfaces and tools have undergone dramatic changes (Eppig et al., Mamm Genome 26:272-284, 2015). Change has been driven by scientific methodological advances, rapid improvements in computational software, growth in computer hardware capacity, and the ongoing collaborative nature of the mouse genomics community in building resources and sharing data. Here we present an overview of the current data content of MGI, describe its general organization, and provide examples using simple and complex searches, and tools for mining and retrieving sets of data.

Building Searchable Collections of Enterprise Speech Data.

ERIC Educational Resources Information Center

Cooper, James W.; Viswanathan, Mahesh; Byron, Donna; Chan, Margaret

The study has applied speech recognition and text-mining technologies to a set of recorded outbound marketing calls and analyzed the results. Since speaker-independent speech recognition technology results in a significantly lower recognition rate than that found when the recognizer is trained for a particular speaker, a number of post-processing…

Ball clay

USGS Publications Warehouse

Virta, Robert L.

2010-01-01

The article reports on the global market performance of ball clay in 2009 and presents an outlook for its 2010 performance. Several companies mined ball call in the country including Old Hickey Clay Co., Kentucky-Tennessee Clay Co., and H.C. Spinks Clay Co. Information on the decline in ball clay imports and exports is also presented.

Visual data mining for quantized spatial data

NASA Technical Reports Server (NTRS)

Braverman, Amy; Kahn, Brian

2004-01-01

In previous papers we've shown how a well known data compression algorithm called Entropy-constrained Vector Quantization ( can be modified to reduce the size and complexity of very large, satellite data sets. In this paper, we descuss how to visualize and understand the content of such reduced data sets.

Work Restructuring in Post-Apartheid South Africa.

ERIC Educational Resources Information Center

Webster, Edward; Omar, Rahmat

2003-01-01

Case studies of South African companies (mining, manufacturing, and telephone call centers) reveal a mix of management strategies that converge with and diverge from past practices. South Africa is attempting to balance the demands of efficiency, employee rights, and racial equity, a challenge that requires overcoming the legacy of the apartheid…

Huge Databases Offer a Research Gold Mine and Privacy Worries

ERIC Educational Resources Information Center

Glenn, David

2008-01-01

Last month several news organizations reported on the emergence of "fusion centers"--vast data clearinghouses, operated by state law-enforcement agencies, that can instantly call up key personal information on anyone: telephone numbers, insurance records, family ties, and much more. Architects of the fusion centers say they are a…

Application of Image Intensifier Technology to the Military, Scientific, Industrial, Educational, and Medical Communities.

DTIC Science & Technology

1980-05-30

afflicted with Retinitis Pigmentosa , commonly called night blindness. People who suffer from this are virtually blind in absence of normal room light...image intensification 5. Low light ophthalmological surgery 6. Retinitis Pigmentosa patients 7. Mine rescue and first aid 8. TV microscopy 9

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.

Translations on North Korea No. 622

DTIC Science & Technology

1978-10-13

Pyongyang Power Station 5 July Electric Factory Hamhung Machine Tool Factory Kosan Plastic Pipe Factory Sog’wangea Plastic Pipe Factory 8...August Factory Double Chollima Hamhung Disabled Veterans’ Plastic Goods Factory Mangyongdae Machine Tool Factory Kangso Coal Mine Tongdaewon Garment...21 Jul 78 p 4) innovating in machine tool production (NC 21 Jul 78 p 2) in 40 days of the 蔴 days of combat" raised coal production 10 percent

Biblio-MetReS for user-friendly mining of genes and biological processes in scientific documents.

PubMed

Usie, Anabel; Karathia, Hiren; Teixidó, Ivan; Alves, Rui; Solsona, Francesc

2014-01-01

One way to initiate the reconstruction of molecular circuits is by using automated text-mining techniques. Developing more efficient methods for such reconstruction is a topic of active research, and those methods are typically included by bioinformaticians in pipelines used to mine and curate large literature datasets. Nevertheless, experimental biologists have a limited number of available user-friendly tools that use text-mining for network reconstruction and require no programming skills to use. One of these tools is Biblio-MetReS. Originally, this tool permitted an on-the-fly analysis of documents contained in a number of web-based literature databases to identify co-occurrence of proteins/genes. This approach ensured results that were always up-to-date with the latest live version of the databases. However, this 'up-to-dateness' came at the cost of large execution times. Here we report an evolution of the application Biblio-MetReS that permits constructing co-occurrence networks for genes, GO processes, Pathways, or any combination of the three types of entities and graphically represent those entities. We show that the performance of Biblio-MetReS in identifying gene co-occurrence is as least as good as that of other comparable applications (STRING and iHOP). In addition, we also show that the identification of GO processes is on par to that reported in the latest BioCreAtIvE challenge. Finally, we also report the implementation of a new strategy that combines on-the-fly analysis of new documents with preprocessed information from documents that were encountered in previous analyses. This combination simultaneously decreases program run time and maintains 'up-to-dateness' of the results. http://metres.udl.cat/index.php/downloads, metres.cmb@gmail.com.

A web-based genomic sequence database for the Streptomycetaceae: a tool for systematics and genome mining

USDA-ARS?s Scientific Manuscript database

The ARS Microbial Genome Sequence Database (http://199.133.98.43), a web-based database server, was established utilizing the BIGSdb (Bacterial Isolate Genomics Sequence Database) software package, developed at Oxford University, as a tool to manage multi-locus sequence data for the family Streptomy...

Harnessing scientific literature reports for pharmacovigilance. Prototype software analytical tool development and usability testing.

PubMed

Sorbello, Alfred; Ripple, Anna; Tonning, Joseph; Munoz, Monica; Hasan, Rashedul; Ly, Thomas; Francis, Henry; Bodenreider, Olivier

2017-03-22

We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers' capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. All usability test participants cited the tool's ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool's automated literature search relative to a manual 'all fields' PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction.

A planetary nervous system for social mining and collective awareness

NASA Astrophysics Data System (ADS)

Giannotti, F.; Pedreschi, D.; Pentland, A.; Lukowicz, P.; Kossmann, D.; Crowley, J.; Helbing, D.

2012-11-01

We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.

RE-Powering America's Land

EPA Pesticide Factsheets

Describes how contaminated lands, landfills, and mine sites can be reused as renewable energy installations. Also supplies best practices, tools and resources for screening properties for renewable energy potential.

Improved mine blast algorithm for optimal cost design of water distribution systems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Guen Yoo, Do; Kim, Joong Hoon

2015-12-01

The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.

Partners in Physics with Colorado School of Mines' Society of Physics Students

NASA Astrophysics Data System (ADS)

Moore, Shirley; Stilwell, Matthew; Boerner, Zach

2011-04-01

The Colorado School of Mines (CSM) Society of Physics Students (SPS) revitalized in 2008 and has since blown up with outreach activity, incorporating all age levels into our programs. In Spring 2010, CSM SPS launched a new program called Partners in Physics. Students from Golden High School came to CSM where they had a college-level lesson on standing waves and their applications. These students then joined volunteers from CSM in teaching local elementary school students about standing waves beginning with a science show. The CSM and high school students then helped the children to build make-and-take demonstrations incorporating waves. This year, rockets are the theme for Partners in Physics and we began with demonstrations with local middle school students. In Spring 2011, CSM SPS will be teaching elementary school students about projectile motion and model rockets along with these middle school students. Colorado School of Mines Department of Physics

Automated Assessment of Patients' Self-Narratives for Posttraumatic Stress Disorder Screening Using Natural Language Processing and Text Mining.

PubMed

He, Qiwei; Veldkamp, Bernard P; Glas, Cees A W; de Vries, Theo

2017-03-01

Patients' narratives about traumatic experiences and symptoms are useful in clinical screening and diagnostic procedures. In this study, we presented an automated assessment system to screen patients for posttraumatic stress disorder via a natural language processing and text-mining approach. Four machine-learning algorithms-including decision tree, naive Bayes, support vector machine, and an alternative classification approach called the product score model-were used in combination with n-gram representation models to identify patterns between verbal features in self-narratives and psychiatric diagnoses. With our sample, the product score model with unigrams attained the highest prediction accuracy when compared with practitioners' diagnoses. The addition of multigrams contributed most to balancing the metrics of sensitivity and specificity. This article also demonstrates that text mining is a promising approach for analyzing patients' self-expression behavior, thus helping clinicians identify potential patients from an early stage.

Application of data mining approaches to drug delivery.

PubMed

Ekins, Sean; Shimada, Jun; Chang, Cheng

2006-11-30

Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.

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.

Underwater magnetic gradiometer for magnetic anomaly detection, localization, and tracking

NASA Astrophysics Data System (ADS)

Kumar, S.; Sulzberger, G.; Bono, J.; Skvoretz, D.; Allen, G. I.; Clem, T. R.; Ebbert, M.; Bennett, S. L.; Ostrom, R. K.; Tzouris, A.

2007-04-01

GE Security and the Naval Surface Warfare Center, Panama City (NSWC-PC) have collaborated to develop a magnetic gradiometer, called the Real-time Tracking Gradiometer or RTG that is mounted inside an unmanned underwater vehicle (UUV). The RTG is part of a buried mine hunting platform being developed by the United States Navy. The RTG has been successfully used to make test runs on mine-like targets buried off the coast of Florida. We will present a general description of the system and latest results describing system performance. This system can be also potentially used for other applications including those in the area of Homeland Security.

Evaluation of Documentation Patterns of Trainees and Supervising Physicians Using Data Mining.

PubMed

Madhavan, Ramesh; Tang, Chi; Bhattacharya, Pratik; Delly, Fadi; Basha, Maysaa M

2014-09-01

The electronic health record (EHR) includes a rich data set that may offer opportunities for data mining and natural language processing to answer questions about quality of care, key aspects of resident education, or attributes of the residents' learning environment. We used data obtained from the EHR to report on inpatient documentation practices of residents and attending physicians at a large academic medical center. We conducted a retrospective observational study of deidentified patient notes entered over 7 consecutive months by a multispecialty university physician group at an urban hospital. A novel automated data mining technology was used to extract patient note-related variables. A sample of 26 802 consecutive patient notes was analyzed using the data mining and modeling tool Healthcare Smartgrid. Residents entered most of the notes (33%, 8178 of 24 787) between noon and 4 pm and 31% (7718 of 24 787) of notes between 8 am and noon. Attending physicians placed notes about teaching attestations within 24 hours in only 73% (17 843 of 24 443) of the records. Surgical residents were more likely to place notes before noon (P < .001). Nonsurgical faculty were more likely to provide attestation of resident notes within 24 hours (P < .001). Data related to patient note entry was successfully used to objectively measure current work flow of resident physicians and their supervising faculty, and the findings have implications for physician oversight of residents' clinical work. We were able to demonstrate the utility of a data mining model as an assessment tool in graduate medical education.

Short-term scheduling of an open-pit mine with multiple objectives

NASA Astrophysics Data System (ADS)

Blom, Michelle; Pearce, Adrian R.; Stuckey, Peter J.

2017-05-01

This article presents a novel algorithm for the generation of multiple short-term production schedules for an open-pit mine, in which several objectives, of varying priority, characterize the quality of each solution. A short-term schedule selects regions of a mine site, known as 'blocks', to be extracted in each week of a planning horizon (typically spanning 13 weeks). Existing tools for constructing these schedules use greedy heuristics, with little optimization. To construct a single schedule in which infrastructure is sufficiently utilized, with production grades consistently close to a desired target, a planner must often run these heuristics many times, adjusting parameters after each iteration. A planner's intuition and experience can evaluate the relative quality and mineability of different schedules in a way that is difficult to automate. Of interest to a short-term planner is the generation of multiple schedules, extracting available ore and waste in varying sequences, which can then be manually compared. This article presents a tool in which multiple, diverse, short-term schedules are constructed, meeting a range of common objectives without the need for iterative parameter adjustment.

A GIS-based approach: Influence of the ventilation layout to the environmental conditions in an underground mine.

PubMed

Bascompta, Marc; Castañón, Ana María; Sanmiquel, Lluís; Oliva, Josep

2016-11-01

Gases such as CO, CO2 or NOx are constantly generated by the equipment in any underground mine and the ventilation layout can play an important role in keeping low concentrations in the working faces. Hence, a method able to control the workplace environment is crucial. This paper proposes a geographical information system (GIS) for such goal. The system created provides the necessary tools to manage and analyse an underground environment, connecting pollutants and temperatures with the ventilation characteristics over time. Data concerning the ventilation system, in a case study, has been taken every month since 2009 and integrated into the management system, which has quantified the gasses concentration throughout the mine due to the characteristics and evolution of the ventilation layout. Three different zones concerning CO, CO2, NOx and effective temperature have been found as well as some variations among workplaces within the same zone that suggest local airflow recirculations. The system proposed could be a useful tool to improve the workplace conditions and efficiency levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Data-driven decision support for radiologists: re-using the National Lung Screening Trial dataset for pulmonary nodule management.

PubMed

Morrison, James J; Hostetter, Jason; Wang, Kenneth; Siegel, Eliot L

2015-02-01

Real-time mining of large research trial datasets enables development of case-based clinical decision support tools. Several applicable research datasets exist including the National Lung Screening Trial (NLST), a dataset unparalleled in size and scope for studying population-based lung cancer screening. Using these data, a clinical decision support tool was developed which matches patient demographics and lung nodule characteristics to a cohort of similar patients. The NLST dataset was converted into Structured Query Language (SQL) tables hosted on a web server, and a web-based JavaScript application was developed which performs real-time queries. JavaScript is used for both the server-side and client-side language, allowing for rapid development of a robust client interface and server-side data layer. Real-time data mining of user-specified patient cohorts achieved a rapid return of cohort cancer statistics and lung nodule distribution information. This system demonstrates the potential of individualized real-time data mining using large high-quality clinical trial datasets to drive evidence-based clinical decision-making.